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April 4, 2026

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Based on โ€œThe bizarre phenomena that medicine struggles to explain | David Linden: Full Interviewโ€ from Big Think Watch the original video

Decoding the Mind-Body Mystery: A Neuroscientistโ€™s Journey into the Unexplained

For centuries, the intricate dance between our thoughts, emotions, and physical well-being has been relegated to the realms of philosophy, spirituality, or even the supernatural. Science, in its quest for empirical truth, often viewed the profound influence of the mind on the body with skepticism. But what if the โ€œuntestable and etherealโ€ is, in fact, rooted in measurable biology?

David Linden, a distinguished professor of neuroscience at Johns Hopkins University School of Medicine, has dedicated his career to studying neuroplasticity โ€“ how the brain and nervous system are reshaped by experience. In a recent interview, Linden shared his journey from a biologist resistant to the mind-body connection to a fervent advocate, revealing how cutting-edge neuroscience is finally unraveling these long-held mysteries, even touching upon his own battle with terminal cancer.

Linden admits that, like many biologists, he initially resisted the idea that mental life profoundly affects the body. The concept seemed too intangible, too far removed from the hard science of biology. Yet, his father, a psychiatrist, offered a pivotal insight: โ€œPsychiatry works not in some magical psychological realm divorced from biology, it works because it changes your brain.โ€ This principle, Linden emphasizes, applies to all behavioral practicesโ€”meditation, psychotherapy, controlled breathingโ€”they all exert their effects through biological mechanisms that we are only now beginning to understand.

A key to this understanding lies in distinguishing between how we sense the world and how we sense ourselves. We are familiar with โ€œexteroceptiveโ€ senses like sight, smell, and hearing, which provide information about our external environment. But equally crucial are our โ€œinteroceptiveโ€ senses, the inward-pointing signals that tell us if our bladder is full, our bowel is distended, or how our head relates to gravity. These interoceptive signals are the bedrock of the ongoing conversation between mind and body.

This conversation happens through various biological channels:

  • Rapid Electrical Signals: Neurons transmit fast information from the body to the brain via the spinal cord.
  • Slower Hormonal Signals: The body secretes hormones into the bloodstream, which then travel to the brain and bind to receptors on neurons, producing slower, more sustained effects.
  • Rhythmic Cues: The brain continuously monitors and responds to our breathing rhythm and heartbeat, with each pulse subtly dilating arteries in the brain, providing a rapid sensory input.

The mind, instantiated in the brain, also talks back to the body:

  • Volitional Motor System: Conscious commands, like deciding to raise an arm.
  • Autonomic Nervous System (ANS): This subconscious system governs involuntary bodily functions. Divided into the โ€œfight or flightโ€ sympathetic nervous system and the โ€œrest and digestโ€ parasympathetic nervous system, these two branches act as a yin and yang, controlling the body below our conscious awareness.
  • Hormonal Release: The brain influences glands like the pituitary and adrenal glands to secrete hormones, which broadcast general effects throughout the body via the circulatory system.
  • Immune System Modulation: Specialized immune hormones called cytokines serve as another communication pathway.

Hacking Hunger: The GLP-1 Revolution

The complexity of eating and hunger provides a vivid illustration of this intricate mind-body dialogue. From smelling pizza on the street to deciding to swallow a bite, a series of conscious and subconscious decisions are made, integrating exteroceptive (smell, sight, taste) and interoceptive (stomach fullness, nutrient content) information, alongside memory and association.

Crucially, our gut is remarkably sophisticated. Cells in the stomach lining can rapidly assess the nutrient content of food, distinguishing water from protein, fat, or carbohydrates. Later, sensors in the small intestine detect passing nutrients, triggering the slow hormonal signal of Glucagon-Like Peptide 1 (GLP-1). This hormone slows gastric emptying and, more importantly, suppresses appetite in the brain for hours.

Linden highlights a fascinating disconnect: while artificial sweeteners trick the sweet sensors in our mouths, they fail to fool the molecularly different sugar sensors in our stomachs and intestines. This mismatchโ€”mouth saying โ€œsugar,โ€ gut saying โ€œnoโ€โ€”sends conflicting signals to the brain, likely explaining why artificial sweeteners are often ineffective for weight loss.

This understanding of GLP-1 has led to a revolution in weight management. Natural GLP-1 is quickly degraded, but clever chemists found a way to modify the molecule with fatty acids, allowing it to bind to albumin in the blood. This modification makes drugs like semaglutide (Ozempic, Wegovy) and tirzepatide (Zepbound, Mounjaro) resistant to degradation, enabling once-weekly injections that profoundly suppress appetite, leading to significant weight loss (12-17% of body weight).

Beyond weight loss, GLP-1 drugs show even greater promise. Receptors for GLP-1 are found in numerous organsโ€”heart, kidneys, liverโ€”suggesting beneficial effects beyond mere weight reduction, possibly through anti-inflammatory actions. Intriguingly, early research also indicates these drugs may help control other compulsive reward-seeking behaviors, such as alcohol consumption, drug abuse, and even compulsive shopping or gambling, hinting at a shared underlying reward circuitry in the brain.

Even exercise, long known for its health benefits, plays a role in appetite regulation. Intensive exercise produces a metabolite (lactate conjugated with phenylalanine) that travels to the brain to suppress appetite. While not a complete antidote to overeating, it provides a net benefit.

Linden also points to a darker side of our evolved hunger mechanisms. Our ancestors, facing intermittent famines, were wired to โ€œsnarf downโ€ high-calorie foods. Today, the processed food industry exploits this ancient circuit, using sophisticated engineering to override our natural satiety signals, contributing to the significant weight gain observed in populations like the United States since 1960.

The Power of Belief: Voodoo Death, Broken Hearts, and Placebos

The mindโ€™s influence extends to life and death itself. Linden discusses Walter Cannonโ€™s 1942 report on โ€œvoodoo death,โ€ where individuals who believed they were cursed actually died. Cannon theorized sympathetic nervous system hyperarousal. Modern understanding refines this: a โ€œone-two punchโ€ of sympathetic overdrive followed by sustained parasympathetic activation shuts down the body. Crucially, this only works if the belief in the curse is present.

This isnโ€™t just a phenomenon of distant cultures. Linden cites cases of โ€œfatal misdiagnosesโ€โ€”like a man who died shortly after Christmas, believing he had terminal liver cancer, only for an autopsy to reveal he was largely healthy. His belief, not the disease, killed him, likely through the same biological mechanisms as voodoo death.

The romantic notion of dying from a โ€œbroken heartโ€ also finds scientific validation. Epidemiological studies confirm that people are statistically more likely to die soon after losing a long-term partner, from cardiovascular events, cancer, or autoimmune diseases. This grief-induced decline is biologically explained by phenomena like Takotsubo cardiomyopathy (or โ€œoctopus trap heartโ€), first identified in Japan, where severe emotional stress causes a dramatic, temporary impairment of heart function, linked to sympathetic nervous system overactivation.

Fortunately, the mindโ€™s power can also be harnessed for good. Positive beliefs and mental states can relieve pain and improve health outcomes. While behavioral interventions like meditation and psychotherapy are vital, understanding mind-body signaling also informs conventional therapies. GLP-1 drugs, as discussed, leverage body-to-mind signals. Vagus nerve stimulators, used for depression and epilepsy, activate the parasympathetic nervous system, exploiting mind-to-body pathways.

The placebo effect is perhaps the most striking demonstration of the mindโ€™s healing power. Sugar pills or sham treatments can significantly alleviate pain, clear infections, and improve cardiovascular function. For pain, we now know that placebos activate the brainโ€™s natural opioid system, releasing endorphins and enkephalinsโ€”an effect that can be blocked by naloxone. Placebos also appear to involve a form of associative learning, akin to Pavlovian conditioning, where a neutral stimulus (like a lemon-lime flavor) paired with a drug can eventually elicit some of the drugโ€™s effects on its own.

Curiously, the placebo effect for pain has grown stronger over recent decades, but primarily in the United States. Linden speculates this might be linked to direct-to-consumer drug advertising, which is allowed in only two countries worldwide (the US and New Zealand), potentially cultivating a stronger belief in drug efficacy. Even more counterintuitively, open-label placebosโ€”where patients are explicitly told they are receiving a sugar pillโ€”still produce beneficial effects, a phenomenon that continues to fascinate neuroscientists.

The Brainโ€™s Fight Against Cancer: A Personal Revelation

Lindenโ€™s journey into the mind-body connection took a profoundly personal turn nearly five years ago when he was diagnosed with synovial sarcoma, an aggressive cancer, and given 6 to 18 months to live. For Linden, a neuroscientist, battling a terminal illness meant embracing โ€œthe way of the nerdโ€โ€”understanding his disease through the lens of neuroscience.

He explains cancer not just as uncontrolled cell growth, but as an โ€œopportunistic bastardโ€ that co-opts other bodily systems. Tumors manipulate the immune system to avoid detection, secrete signals to attract blood vessels for nourishment, and, as increasingly understood, engage in a complex dialogue with nerves. Tumors secrete neurotrophins (like nerve growth factor, NGF) that cause nerves to grow into them, while pain-conveying sensory neurons within the tumor secrete CGRP, which suppresses immune cells (CD8+ T lymphocytes) that would otherwise fight the cancer. This tumor-nerve interaction worsens prognosis, opening a new frontier in cancer therapy: preventing nerve innervation.

The idea that psychosocial support, love, and mental state can influence cancer outcomes has long been a hopeful thought. Linden confirms that epidemiological evidence now strongly suggests a beneficial effect on cancer progression, though itโ€™s not a miracle cure for chemotherapy or surgery. Understanding the biology behind thisโ€”such as stress hormones promoting tumor growth and psychotherapy reducing stress hormone signalingโ€”opens avenues for new drug therapies. For instance, beta-blockers, drugs commonly used for anxiety and heart conditions, can slow cancer progression in certain types of tumors that possess beta-adrenergic receptors.

Recent randomized controlled studies offer compelling evidence for exercise in cancer outcomes. A 2025 study on colon cancer patients, for example, found that those randomly assigned to an exercise group had a remarkable 30% improvement in mortality over eight years. This is an effect size comparable to powerful anti-cancer drugs, robustly demonstrating exerciseโ€™s direct benefit, independent of confounding factors. โ€œIf youโ€™re battling cancer and you can bring yourself to do it,โ€ Linden asserts, โ€œexercise is one of the very, very best things that you can do.โ€

Lindenโ€™s own continued survival, far beyond his initial prognosis, serves as a poignant testament to these insights. When asked why he believes he is still alive, he speaks of the โ€œdeep loveโ€ he feels from his wife, Dina. He clarifies that this isnโ€™t a sentimental remark but a scientific observation. For Linden, love and social connection are not merely emotional comforts; they are powerful biological forces that profoundly influence our physiology, our resilience, and ultimately, our ability to heal and survive.

The revolution in understanding the mind-body connection is transforming medicine. Itโ€™s moving beyond the ethereal, providing biological explanations for phenomena once thought inexplicable. This deeper insight promises a future where behavioral interventions, targeted drugs, and sophisticated neural devices will converge, exploiting the profound and often surprising power of our own minds to foster health and combat disease.


Based on โ€œ669. Why Is 95 Percent of the Worldโ€™s Bourbon Made in Kentucky? | Freakonomics Radioโ€ from Freakonomics Radio Network Watch the original video

Kentuckyโ€™s Golden Spirit: The Barrel Tax, Bourbon Glut, and the Battle for Tomorrowโ€™s Drinkers

For most businesses, time is money in the most direct sense: products are made, sold, and investments recouped. But in the world of fine spirits, time isnโ€™t just money; itโ€™s a crucial ingredient, an investment that matures over years, even decades, before yielding its full value. This unique economic reality is nowhere more evident than in the American bourbon industry, a sector currently grappling with a paradox of its own making: an unparalleled concentration of production, a rich history, and a looming glut that could redefine its future.

Freakonomics Radio recently delved into this fascinating industry, exploring why an astounding 95% of the worldโ€™s bourbon is made within a 45-minute drive of Lexington, Kentucky, and what happens when an industry built on patience suddenly finds itself with too much product and not enough demand.

The Allure of Age: Time as an Investment

Consider products like fine cheeses or certain wines; their value appreciates with age. But for spirits, particularly Scotch whiskey and its American cousin, bourbon, the older the barrel, the dearer the bottle. This means distillers pour significant capital into production, only to have their inventory sit in warehouses for years, sometimes decades, before it can be sold.

Ken Troske, a labor economist and chair of the economics department at the University of Kentucky, observes this phenomenon firsthand. Having moved to Kentucky two decades ago, he witnessed bourbonโ€™s resurgence. โ€œWhen I got there, bourbon was just starting to recover from a long period of time of when it was in decline,โ€ Troske recounts. Today, the state holds a staggering 16 million barrels of bourbon aging in its rickhouses, a fourfold increase from the 4 million barrels when Troske arrived.

The dramatic shift in value is exemplified by Pappy Van Winkleโ€™s 20-year-old bourbon. Troskeโ€™s wife once bought a bottle for $120. Today, that same bottle could fetch $2,500 to $3,000 on the secondary market. This isnโ€™t just a testament to quality; itโ€™s a stark illustration of how time, scarcity, and brand prestige can inflate value. The allure of such high-end products even spawned a black market during the bourbon boom, with 65 cases of 20-year Pappy Van Winkle stolen from a warehouse, valued at an estimated $100,000.

Kentuckyโ€™s Claim to Fame: More Than Just Limestone?

The concentration of bourbon production in Kentucky is a striking economic anomaly. The stateโ€™s proponents often cite the unique limestone-filtered water, which purportedly lends itself perfectly to the bourbon-making process, as a primary reason. This same geological feature is also credited with contributing to the success of Kentuckyโ€™s thoroughbred horse industry, another sector highly concentrated in the Bluegrass region.

However, some economists, like Andrew Muhammad, an agricultural economist at the University of Tennessee, suggest there might be an element of โ€œsoft protectionismโ€ at play. โ€œYou do have to admit itโ€™s a bit convenient, right?โ€ Muhammad muses, highlighting that some of the finest Scotch and Japanese whiskies use barrels from Kentucky and Tennessee. This raises questions about whether the โ€œquality distinctionโ€ argument might also serve as clever marketing for the incumbent industry.

The regulatory framework for bourbon is indeed unique. As Ken Troske explains, according to the Code of Federal Regulations (CFR Chapter 27, Section 5.143), to be called โ€œstraight bourbon whiskey,โ€ it must be:

  • Fermented mash of not less than 51% corn.
  • Distilled to no more than 160 proof.
  • Stored in new American charred oak barrels at no more than 125 proof for at least two years.
  • Made in the United States.

These regulations, dating back to a 1964 US Congressional resolution, declare bourbon a distinctive product of the United States, much like Scotch whiskey is exclusive to Scotland or Champagne to Franceโ€™s Champagne region. While Master Distiller Danny Kahn of Sazerac (which owns brands like Buffalo Trace and Pappy Van Winkle) staunchly defends each component of the law as beneficial for flavor, the historical context also suggests a confluence of interests, particularly from the corn, barrel-making, and copper industries.

The Art and Science of the Brown Spirit

Danny Kahn, who transitioned from brewing beer at Anheuser-Busch to master distiller, provides a fascinating glimpse into the meticulous process behind bourbon. โ€œIf you think about whiskey, we make beer first, then we distill it, and then we age it,โ€ he explains.

Kahn elaborates on the five key requirements:

  1. 51% or more corn: Beyond historical availability, corn provides abundant starch for sugar and alcohol production, contributing significant flavor from its oils.
  2. Made in the USA: This allows for legal control and consistent application of standards.
  3. Distilled to no more than 160 proof: Kahn notes that distillers typically aim for 135-140 proof. Distilling at a lower proof retains more flavors, which are crucial for how the whiskey ages, slowly oxidizing and reacting with wood components.
  4. Put into a barrel at no more than 125 proof: This proof level is critical because different flavor components in the wood are soluble in varying alcohol-to-water ratios, allowing distillers to manipulate the final taste profile.
  5. New charred oak containers (barrels): This is perhaps the most iconic and impactful rule. The process begins with white oak staves, which are seasoned outdoors for about a year. Rainwater rinses tannins, and microbiological activity breaks down wood components. Once assembled, the inside of the barrel is subjected to intense direct flame for about 30 seconds, creating a char layer. This char acts like a filter, while the cooked wood beneath it provides the โ€œextractablesโ€ โ€“ the hemicellulose (caramel, butterscotch notes), lignins (baking spices, vanilla), and tannins (mouthfeel, astringency, color) that define bourbonโ€™s complex flavor.

Over time, a significant portion of the whiskey evaporates through the wood, famously known as the โ€œangelโ€™s share.โ€ For some 23-year-old bourbons, Kahn notes, โ€œthereโ€™s just a little bit left at the bottom.โ€ The used barrels, no longer suitable for bourbon, are often sold to producers of Scotch, Irish, or Indian whiskies, though Kahn admits the market for them โ€œis not so greatโ€ currently, leading to a proliferation of โ€œroadside plantersโ€ made from old bourbon barrels in Kentucky.

The Boomโ€™s Hangover: A โ€œQuantity Problemโ€

From 2012 to 2022, the bourbon industry experienced a robust boom, attracting numerous new distilleries. However, as Brad Patrick, an executive in residence at the University of Kentuckyโ€™s Gatton College of Business and Economics, observes, โ€œnow weโ€™ve bumped into a wall.โ€ Demand for bourbon has been falling since 2022, exacerbated by new tariffs, leaving the industry with its 16 million aging barrels and a serious โ€œquantity problem.โ€

This isnโ€™t a new phenomenon. Patrick draws parallels to the Scotch industryโ€™s overproduction in the 1980s and bourbonโ€™s own struggles from Prohibition to the 1970s. The current downturn is multifaceted:

  • Changing Consumer Tastes: Younger consumers (Gen Z) are less interested in โ€œdaddyโ€™s old brown spirit,โ€ gravitating towards โ€œwhite spiritsโ€ and ready-to-drink (RTD) cocktails.
  • Competition: The rise of cannabis (THC) products and other alcoholic beverages in cans.
  • Health & Wellness: Increased awareness and trends like GLP-1 medications may contribute to reduced alcohol consumption.
  • Market Saturation: โ€œThereโ€™s probably too much variety,โ€ Patrick states, with between 800 and 1,000 different bourbon SKUs on the market, leading to โ€œprice fatigueโ€ and overwhelming choice.

The industryโ€™s largest player, Jim Beam (owned by Suntory), has already paused production at its flagship distillery for a year, and consolidation and layoffs are affecting other producers.

The Inefficient Web of Regulation and Trade

Beyond shifting consumer preferences, the bourbon industry faces structural challenges, particularly in distribution and international trade.

The Three-Tier System: Economist Ken Troske criticizes the USโ€™s โ€œoddโ€ three-tier distribution system for alcohol, a historical artifact from post-Prohibition efforts to curb organized crime. This system mandates separate entities for production, distribution, and retail, with no financial relationships between them. While it may have served its original purpose, today itโ€™s โ€œfull of inefficiency and middlemen,โ€ leading to price discrepancies. Troske cites the example of a bottle of Blantonโ€™s bourbon: $74 at Buffalo Traceโ€™s gift shop in Kentucky, $130 at a local Kentucky liquor store, and a staggering $400 in La Jolla, California. Distributors also leverage popular brands, forcing retailers to sell less desirable products (like Fireball) to get allocations of sought-after bourbons.

Tariffs: The Trump administrationโ€™s trade policies further complicated matters. Retaliatory tariffs from the European Union, specifically a 25% tariff on American whiskey, significantly impacted exports. Andrew Muhammad explains that some companies chose to absorb the cost rather than raise prices, fearing the permanent loss of market share. โ€œOnce you lose market share in the distilled spirits sector, itโ€™s very hard to get it back,โ€ he notes. Canada took an even more drastic step, simply removing American products from shelves.

Barrel Taxes: The state of Kentucky also levies an annual โ€œbarrel taxโ€ on aging bourbon, a legacy โ€œsin taxโ€ that in 2025 amounted to $75 million. While this tax is being phased out by 2043, it represents yet another cost burden on distillers already investing for years without immediate returns.

The Road Ahead: Creative Destruction or Just a Hangover?

The bourbon industry is at a crossroads. Brad Patrick predicts a โ€œweeding out of businesses,โ€ similar to the Scotch industryโ€™s consolidation to five major players after its 1980s bust. Distilleries with strong brands are likely to survive, while contract distillers heavily reliant on borrowed money face the most significant trouble.

The question remains: where is the โ€œcreativeโ€ coming out of this โ€œdestructionโ€?

  • Global Markets: Hopes persist for emerging markets like India and China, should tariffs ease.
  • Tourism: The Kentucky Bourbon Trail continues to be a major draw, with distilleries investing in โ€œlifestyle, and luxury, and eventsโ€ to connect with consumers.
  • Ready-to-Drinks (RTDs): Sazerac, for instance, acquired BuzzBallz, a brand of colorful canned cocktails experiencing rapid growth. Danny Kahn sees this as a strategic move to tap into different market segments, acknowledging that โ€œthe alcohol pie is not growing aggressively. So, where are we not represented, and where can we get involved?โ€

While the image of a bourbon connoisseur savoring a meticulously aged spirit endures, the industry is clearly adapting to a new era. The current glut of high-quality bourbon signals a challenging period, but also potentially an opportunity for innovation. Whether itโ€™s through diversifying product lines, strengthening global presence, or enhancing the consumer experience, Kentuckyโ€™s golden spirit is once again proving that patience is not just a virtue, but a necessity, in the ever-evolving world of alcohol.


Based on โ€œAI for Atoms: How Periodic Labs is Revolutionizing Materials Engineering with Co-Founder Liam Fedusโ€ from No Priors: AI, Machine Learning, Tech, & Startups Watch the original video

The Atomic Leap: How ChatGPTโ€™s Co-Creator is Forging AI for the Physical World

Liam Fedus is a name synonymous with the AI revolution. As one of the co-creators of ChatGPT and a former VP of post-training at OpenAI, his work has indelibly shaped how millions interact with artificial intelligence. Yet, after helping to unleash the power of language models on the digital realm, Fedus has turned his formidable intellect towards a new, perhaps even more profound frontier: the physical world. Through his new company, Periodic Labs, he is building an โ€œAI foundation lab for atoms,โ€ aiming to revolutionize material sciences, chemistry, and engineering.

This isnโ€™t just about writing smarter software; itโ€™s about fundamentally changing how we discover, design, and produce the very matter that constitutes our world.

From Dark Matter to Digital Minds

Fedusโ€™s journey to the forefront of AI began, perhaps surprisingly, in the depths of physics. An undergraduate physics major, he spent time researching dark matter, working with an apparatus โ€œdirectionally sensitive to dark matterโ€™s direction.โ€ This background is not uncommon among todayโ€™s AI luminaries, prompting the host to ask why so many physicists, like Anthropicโ€™s Dario Amodei or Googleโ€™s Adam Brown, gravitate towards AI.

Fedus attributes this trend to physics instilling a โ€œvery principled,โ€ โ€œhard-nosed scientistโ€ approach to thinking about the world. โ€œItโ€™s such an incredible field,โ€ he explains, โ€œyou have such high leverage in computer science in AI.โ€ Many high-energy physicists, particularly after the discovery of the Higgs boson, found themselves looking for โ€œwhatโ€™s next,โ€ realizing their skill sets could be โ€œa huge contributor elsewhere.โ€ Itโ€™s a migration that, as the host muses, โ€œalmost feels like weโ€™re recreating the Manhattan projectโ€ฆ except now what weโ€™re seeking is different forms of intelligence.โ€

Fedusโ€™s own transition began in grad school, where he found himself โ€œalways gravitating towards the machine learning problems,โ€ particularly in particle reconstruction. Recognizing that pushing the frontier of machine learning required a shift to computer science, he landed at Google Brain in 2016-2017. This period, he recalls, was a โ€œremarkable period for Google Brainโ€ โ€“ a โ€œCambrian eraโ€ marked by the creation of distributed training strategies, Mixture of Experts, and the Transformer architecture. โ€œThe field was much, much earlier,โ€ he says, โ€œand I think there was a lot of diversity and entropy in the research, and it was very fun.โ€

His work at Google focused on architecture, specifically pushing โ€œsparsity that allows for more efficient serving of models at scaleโ€ and expanding the capabilities of what AI could achieve. By late 2022, the technology was becoming โ€œvery compelling,โ€ and Fedus, along with other Google colleagues, moved to OpenAI.

The Birth of ChatGPT and the Call of the Physical

At OpenAI, Fedusโ€™s primary goal was the โ€œproductionization of GPT-4.โ€ The powerful model had been pre-trained, but the question remained: how to turn it into a product? Initial ideas ranged from writing bots to coding bots, even a โ€œmeeting botโ€ that would take notes and assign to-dos. However, John Schulman, a key researcher, was โ€œvery opinionatedโ€ in favor of a general chatbot. โ€œAnd that became a large part of the effort,โ€ Fedus explains, culminating in the launch of ChatGPT.

The impact was instantaneous and profound. โ€œThat was kind of the starting gun of this whole AI revolution,โ€ the host notes, acknowledging how ChatGPT suddenly brought AIโ€™s power into public awareness.

But for Fedus, language models, while revolutionary, were just the beginning. The โ€œinevitability of connecting these systems to the physical worldโ€ became his driving conviction. โ€œYouโ€™re not going to see the same kind of acceleration in science and technology unless you start connecting these things to the physical world,โ€ he asserts. โ€œScience ultimately isnโ€™t sitting in a room thinking really hard. You have to conduct experiments, you have to learn from them, you have to interface with reality.โ€

The technology available in 2022, he admits, was โ€œfar too weakโ€ for Periodic Labsโ€™ ambitions. It required further advancements in reasoning, test-time inference, reliable error correction, and sophisticated tool use โ€“ capabilities that have since emerged in more advanced models and coding agents. These foundational technologies were โ€œnecessary to then connect these systems to the physical world.โ€

Bridging the Data Divide: The Challenge of Atoms

One of the biggest hurdles in applying AI to the physical world is data. Unlike language models, which feast on the internetโ€™s vast textual corpus, materials science lacks such a readily available, clean, and comprehensive dataset. Fedus explains that ML systems excel on the data theyโ€™re trained on, and while thereโ€™s a โ€œmythology of AGIโ€ sometimes, powerful systems are โ€œlimited if they donโ€™t have access to the raw data to actually make informed decisions.โ€

Periodic Labs tackles this by leveraging existing foundation models, benefiting from the โ€œorder tens of trillions of tokensโ€ they were trained on. This provides a โ€œstrong prior on the world,โ€ meaning their systems donโ€™t start from scratch, but already possess a foundational understanding of language and code.

However, this is โ€œinsufficientโ€ for the specifics of material discovery. Fedus recounts an anecdote where an engineer found reported material properties in literature spanning โ€œmany orders of magnitude.โ€ Training an ML system on such inconsistent data merely models the distribution, offering no closer path to โ€œground truth.โ€ This highlights the critical role of experimental data, which provides โ€œa grounding.โ€

Crucially, itโ€™s not just about a โ€œpool of data.โ€ Periodic Labs emphasizes an โ€œinteractive closed-loop systemโ€ where experimental data informs the models, which then identify patterns, flag aberrations, and drive the next set of experiments. This active feedback loop is what makes the system truly powerful.

Regarding data diversity, Fedus notes that the โ€œgreatest advancesโ€ internally occur where thereโ€™s โ€œan abundance of data in some space.โ€ While thereโ€™s some generalization for systems โ€œstrongly governed by quantum mechanical effects,โ€ creating a model for quantum objects wonโ€™t directly help with fluid dynamics. The generalization exists, but often within specific โ€œfirst principlesโ€ domains, allowing them to model fundamental interactions like chemical synthesis or van der Waals forces.

Orchestrating Intelligence for Material Discovery

Periodic Labsโ€™ AI architecture leverages the power of language models as an โ€œorchestration layer.โ€ Fedus describes them as โ€œa co-pilot assistant but also like a system that can direct experiments.โ€ This layer orchestrates other, more specialized models. These include neural networks โ€œspecially designed for atomic systems where thereโ€™s like some symmetry awareness,โ€ which boast lower latency and are fine-tuned for specific tasks.

The overall system acts as a sophisticated conductor, capable of ingesting vast amounts of literature, analyzing experimental data, processing different modalities, and utilizing specialized neural nets as โ€œtoolsโ€ or โ€œreward functions.โ€ This modular approach allows the AI to tackle complex material engineering challenges with both broad understanding and targeted precision.

The Vision: Generating Matter and Accelerating Progress

Periodic Labs began by treating itself as โ€œcustomer zero,โ€ transforming its own scientific processes. The commercial opportunities, however, are vast, spanning โ€œall of these industries, all these enterprises that are interfacing with the physical worldโ€ โ€“ from semiconductors and aerospace to energy. These are fields โ€œbottlenecked by materials engineering, process engineering,โ€ where engineers constantly ask questions about data, debug machinery, and seek better formulations. Fedus believes this is โ€œactually a quite universal thing as well.โ€

While starting as a โ€œsoftware business,โ€ providing an โ€œintelligence layerโ€ and โ€œcontrol planeโ€ for companies, Fedus acknowledges the โ€œvery interesting aspect of some breakthroughs here could have really high value,โ€ potentially leading to a โ€œdiscovery modelโ€ akin to biotech.

The conversation naturally drifts to the futuristic implications, evoking Neil Stephensonโ€™s novel The Diamond Age, where AI enables matter-generating 3D printers in every home. Fedusโ€™s vision for a world in 10 years, if Periodic Labs succeeds, is equally transformative: โ€œYouโ€™re going from systems that arenโ€™t just writing essays, not just writing software, but to literally generating matter.โ€ This has โ€œprofound implications to semiconductors, aerospace, energy.โ€

His core belief is that AI for atoms can โ€œincrease like the pace of just like the physical development of the world.โ€ While โ€œatoms are hard,โ€ implying physical limits, he sees โ€œan order of magnitude or two to speed upโ€ by making sense of data and reaching solutions faster. โ€œWhat weโ€™re trying to do is give humanity this agency for atomic rearrangement, synthesis, and we think itโ€™s going to just be a huge accelerator.โ€ He likens it to the โ€œmaterials equivalent of the agricultural revolution,โ€ promising a dramatic shift in human capabilities.

The Power of Multidisciplinary Scale

What excites Fedus most is the โ€œiteration between these groups of people.โ€ Periodic Labs is โ€œirreducibly a multidisciplinary problem,โ€ bringing together physicists, chemists, top AI researchers, and engineers in โ€œabsolutely incredibleโ€ close collaboration. He sees โ€œa field fundamentally changeโ€ as people who have spent decades in their domains witness the power of intelligent systems.

He draws an analogy to the industrialization of AI research itself: from a โ€œfew GPUs and a few peopleโ€ pushing the frontier in early Google Brain days, to an era โ€œindustrializedโ€ by โ€œhundreds of researchers working together with hundreds of thousands, millions of GPUs dictated and driven by scaling laws.โ€ This predictability allowed for massive capital investment. Fedus believes physical sciences and engineering โ€œwill have a very similar property where we establish these scaling properties and bring that mindset.โ€ Periodic Labs aims to bring โ€œmuch larger scale sets of experimentsโ€ to bear, enabled by intelligence and automation, addressing the challenge of scientists being overwhelmed by unprecedented data throughput.

This ambition is capital-intensive, primarily due to โ€œextraordinarily expensiveโ€ GPUs. Surprisingly, Fedus notes that โ€œthe compute cost relative to physical infrastructure is actually surprising,โ€ with compute often being the larger expense, despite the long lead times and intrinsic difficulties of physical systems. He also highlights the societal value of bringing academic scientists into a setting where they can operate at โ€œreal scaleโ€ and make a different kind of impact, acknowledging the undercompensation of many academic researchers.

The Future of Intelligence and Robotics

Periodic Labs is actively hiring across both โ€œbitsโ€ (AI infrastructure, pre-training/mid-training roles) and โ€œatomsโ€ (control engineering, system engineering, project engineering).

When discussing AGI, Fedus offers a nuanced perspective. He believes thinking of โ€œintelligence as a scalerโ€ is a fallacy, as systems often exhibit โ€œodd spikinessโ€ โ€“ being โ€œworld-class on some math domainโ€ yet degrading substantially with minor perturbations, akin to โ€œa bad high school student.โ€ Generalization can be โ€œnon-intuitive.โ€

For โ€œrecursive self-improvement,โ€ Fedus sees a โ€œvery clear path for software engineering,โ€ where systems can write repositories, identify bugs, and refactor code. This is happening โ€œnowish,โ€ driven by โ€œhuge amounts of data, really cheap verifiable environmentsโ€ (like unit tests). AI research self-improvement is a โ€œslower outer loop,โ€ requiring more GPUs and longer experiments, but also inevitable. The key, he reiterates, is the โ€œclosed loops of actually doing science, of actually doing engineering,โ€ connecting these systems to the physical world.

Robotics, while not strictly necessary for Periodicโ€™s โ€œescape velocity,โ€ is a โ€œhuge accelerator.โ€ The goal is โ€œto generate high quantity, high-quality data, diverse data,โ€ and automation assists this. While currently using โ€œoff-the-shelf robotics,โ€ improvements in โ€œmore general robotic systemsโ€ โ€“ like a โ€œdexterous humanoid who could wander into an unstructured labโ€ โ€“ will be a โ€œmassive accelerator for spinning up new labs.โ€

Beyond Periodic Labs, Fedus remains most excited about robotics and the โ€œinterface of AI systems with the physical world.โ€ He envisions โ€œagency and control of the physical world via roboticsโ€ as transformative, especially given the vast numbers of people who build the physical world compared to software engineers, and the widespread labor shortages.

As the digital realm accelerates at an unprecedented pace, Liam Fedus and Periodic Labs are pioneering the path for the physical world to catch up. By infusing AI into the very fabric of matter, they are not just building a company; they are laying the groundwork for a future where humanityโ€™s ability to create, discover, and build is profoundly amplified, ushering in an era of atomic abundance and engineered possibilities.


Based on โ€œWhat Do You Do When a Family Member Commits a Terrible Crime? | โ€˜The Opinionsโ€™ Podcastโ€ from New York Times Podcasts Watch the original video

Beyond the Bars: Why Children Need Their Incarcerated Parents, Even After Unspeakable Crimes

When a family member commits a terrible crime, the instinct for many is to sever ties, to erase the problematic individual from the family narrative. But what if this seemingly protective act, driven by understandable outrage and a desire for justice, actually inflicts deeper harm, especially on the children caught in the crossfire? This profound and challenging question lies at the heart of a recent conversation on The New York Timesโ€™ โ€˜The Opinionsโ€™ podcast, featuring host M. Gessen and author Harriet Clark. Their discussion delves into the complex, often counterintuitive, necessity of maintaining connection with incarcerated parents, even those who have committed truly heinous acts.

M. Gessen, an opinion columnist and host of โ€˜The Idiotโ€™ podcast, found himself grappling with this dilemma firsthand. His first cousin, Alan, was arrested in 2022 for orchestrating a hit on his ex-wife, the mother of his two children, and is now serving a 10-year federal prison sentence. Gessen, initially consumed by a sense of vengeance and a lack of empathy for Alan, sought to understand how children could possibly build relationships with a parent in the prison system. His search led him to Harriet Clark, a friend whose life story offers a rare and powerful perspective.

Harrietโ€™s mother, Judy Clark, spent 37 years in prison for her role as the getaway driver in a Brinks robbery that resulted in three deaths. Despite the enormity of her motherโ€™s crime, Harriet grew up maintaining a close relationship with her, a bond she credits to a confluence of โ€œluckโ€ within a deeply unlucky situation.

The Unseen Gift of Connection

Harrietโ€™s childhood visits to her motherโ€™s correctional facility were a stark contrast to the typical image of prison. Her mother was incarcerated in a facility that actively sought to facilitate parent-child relationships, offering a โ€œchildrenโ€™s centerโ€ in the visiting room where kids could play, make crafts, and engage with their mothers. โ€œIt tried as much as possible to have the prison still fit inside the childโ€™s reality,โ€ Harriet recounts. Beyond the institutionโ€™s efforts, her own family, though fractured by the crime, rallied to ensure the connection. Special dolls by the phone helped a young Harriet stay on calls, her motherโ€™s letters describing birds were read aloud, and her grandfather would help her look up the species. โ€œMany people made many efforts to really enable my mother to remain my mother,โ€ she emphasizes, calling it โ€œa great form of good fortune in a system that is very often trying to take peopleโ€™s parents away from them.โ€

This experience directly challenges the common sentiment Gessen articulated regarding his cousin: โ€œWhy would you want to have a relationship with a parent who did something so horrible?โ€ Harriet explains that research and lived experience repeatedly show that children are aided by staying in relationship with an incarcerated parent. When a parent goes to prison, a child inherits โ€œa very painful piece of knowledge, which is that you are leavable.โ€ This terrifying realization needs to be counterpointed by consistent efforts from the parent to connect, to show they still think of the child, still try to support them.

Without this connection, the absent parent becomes โ€œthis black hole,โ€ taking on a โ€œmythic dimensionโ€ that children struggle to comprehend. Kids need a real person to direct their โ€œconfusion and their upset and their needs and their rage to.โ€ The absence, Harriet argues, is โ€œas present as the presence is,โ€ and attempting to remove the parent entirely often replicates a โ€œcarceral logic of removal and disappearance,โ€ falsely believing the child is then safe.

The Vengeance Trap and Collective Responsibility

Gessen confessed to a personal struggle with vengeance, admitting that while reporting on his cousinโ€™s case, he found himself โ€œrooting for the prosecutorโ€ and โ€œwanting this guy to go to prison for as long as possible.โ€ He was shocked to find his own sense of vengeance channeled by the very system he once believed was meant to curb such primal impulses. Harriet, nodding in recognition, confirms this observation, citing the New York State prison system where parole is often denied due to โ€œa certain kind of sense of vengeance within the parole boardโ€ influenced by survivor communities.

Harrietโ€™s experience with her fatherโ€™s incarceration further underscores the damage of absence. Her grandparents, furious at her father, minimized her relationship with him, believing the harsh prison environments (visits through plastic walls, shackled to beds in repulsive prison hospitals) would be โ€œtoo much upset for a child.โ€ But for Harriet, this absence was worse. She โ€œdidnโ€™t understand what had happenedโ€ with her father and โ€œdid feel more abandoned.โ€

This โ€œtoo much upset for a childโ€ logic, while seemingly intuitive, can be misguided. Gessen ponders how his 12-year-old nephew, O, could ever wrap his mind around his father wanting his mother killed. Harrietโ€™s response is powerful: O โ€œcanโ€™t be protected from that reality. What he can be is companioned and loved within that reality.โ€ The goal isnโ€™t to shield children from the truth of their parentโ€™s incarceration, but to ensure that the parent can still be โ€œa source of delight and support and affirmation.โ€

The issue is a profoundly collective reality: โ€œWe have five million children in this country who will have a parent incarcerated at some point in their childhood.โ€ When visiting prisons, Harriet witnessed โ€œincredible people who are making heroic efforts to not let the state tear their families apart.โ€ These are the grandmothers who wake at 4 AM for a seven-hour bus ride, sending a clear message: โ€œIโ€™m not letting them throw you away. Iโ€™m not acting like you donโ€™t exist. You are still my son, my grandson, my father, my brother, my husband. You are still these childrenโ€™s father.โ€ Such efforts, Harriet believes, are inspiring and help to โ€œstate vengeance.โ€

Accountability as a Journey, Not an Ultimatum

Gessenโ€™s podcast concludes with an ultimatum to his cousin Alan: confess to your crime, take accountability, or youโ€™re out of the family. Harriet challenges this, not by saying itโ€™s wrong, but by framing it as โ€œa moment in the process.โ€ She explains that prison conditions make telling the truth incredibly difficult. โ€œNo one whoโ€™s in an active appeal is going to confess their crime to you.โ€ The demand for truth, while sounding โ€œreasonableโ€ and โ€œethical,โ€ might not be the โ€œbe all and end all of our relationship with people.โ€

Instead, Harriet advocates for a โ€œvery long road to accountability,โ€ where families collectively figure out โ€œhow connections can be rebuilt.โ€ This includes helping the incarcerated individual be the best possible parent they can be while inside, and ensuring the safety and well-being of victims like Priscilla (Alanโ€™s ex-wife) after release. โ€œViolence is the aid people turn to when they donโ€™t feel like there are other places to turn for help,โ€ Harriet notes, suggesting that the โ€œstepping in of the collectiveโ€ is crucial for healing after violence and rupture.

Gessen struggles with his cousinโ€™s habitual lying and manipulation, expressing deep frustration and a lack of trust. Harriet acknowledges the infuriating nature of manipulation, having grown up around it herself. However, she argues that this doesnโ€™t justify total disconnection. โ€œIf you donโ€™t trust him, great. Donโ€™t trust him. Donโ€™t leave him alone with his children. Offer to be the presence when he gets out that helps to kind of ease that dynamic.โ€ Itโ€™s about being โ€œclearsighted,โ€ not blindly trusting, but finding โ€œa collective solution for the fact that you have an untrustworthy member of your family.โ€

This perspective directly counters โ€œcarceral logic,โ€ which suggests that problematic individuals are simply removed, and that is the solution. Harriet points out the hypocrisy in this: โ€œHave you ever told a lie? Yes. Have you ever manipulated people? Yes. Of course. Right. And so this too is part of the problem of carceral logics. They try to take sinful behavior and say it belongs just to this population. Watch this population.โ€ The truth, she asserts, is that โ€œweโ€™re all capable of harm.โ€

The Imaginary Sixth Episode: A Path Forward

Harriet offers a vision for Gessenโ€™s โ€œimaginary sixth episode,โ€ a future where the family collectively works to create โ€œas good a future as possible for Alan and Priscilla and their children and for all of you.โ€ This involves ensuring Priscillaโ€™s safety, helping Alan be the best parent he can be, and even assisting him in finding work his children can be proud of after his release, given he will be disbarred.

For Harriet, her own parents, despite their past, were people she could be proud of. Her father, who suffered medical mistreatment in prison, became an advocate for healthcare in correctional facilities after his release. Her mother, too, was always presented as worthy of respect by her family, which in turn fostered Harrietโ€™s own โ€œstrong sense of self-respect.โ€

Ultimately, the message is one of profound human connection and collective responsibility. When a parent is incarcerated, children face a cultural narrative that labels their parent as โ€œbad.โ€ The family, then, plays a crucial role as a โ€œcountering voice,โ€ creating conditions โ€œwhereby a child can feel respect towards their parent.โ€ Itโ€™s about finding ways for meaningful connection, even amidst profound disconnection, recognizing the โ€œmultiplicity and contradictions of how people are.โ€

Harriet Clarkโ€™s insights offer a radical, yet deeply humane, challenge to our conventional understanding of justice, punishment, and family. They invite us to look beyond vengeance and simplistic solutions, urging us to embrace the messy, difficult, but ultimately more dignifying journey of maintaining human connection, for the sake of the children and the collective healing of families and communities. Itโ€™s a truth that may make us think harder than weโ€™d like, but itโ€™s a truth that might just be the most important thing for those impacted by the long shadow of incarceration.


ํ•œ๊ตญ์–ด

โ€œThe bizarre phenomena that medicine struggles to explain | David Linden: Full Interviewโ€ โ€” Big Think ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

๋งˆ์Œ์ด ๋ชธ์„ ์ง€๋ฐฐํ•˜๋Š”๊ฐ€? ๋‡Œ๊ณผํ•™์ž๊ฐ€ ํŒŒํ—ค์นœ ์˜ํ•™ ๋ฏธ์Šคํ„ฐ๋ฆฌ

์กด์Šค ํ™‰ํ‚จ์Šค ์˜๊ณผ๋Œ€ํ•™์˜ ์‹ ๊ฒฝ๊ณผํ•™ ๊ต์ˆ˜์ธ ๋ฐ์ด๋น„๋“œ ๋ฆฐ๋“  ๋ฐ•์‚ฌ๋Š” ์ˆ˜์‹ญ ๋…„๊ฐ„ ๋‡Œ์™€ ์‹ ๊ฒฝ๊ณ„๊ฐ€ ๊ฒฝํ—˜์„ ํ†ตํ•ด ์–ด๋–ป๊ฒŒ ๋ณ€ํ™”ํ•˜๋Š”์ง€, ์ฆ‰ โ€˜์‹ ๊ฒฝ๊ฐ€์†Œ์„ฑ(Neuroplasticity)โ€˜์„ ์—ฐ๊ตฌํ•ด์™”์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์˜ค๋žซ๋™์•ˆ ๋งˆ์Œ์˜ ์ž‘์šฉ์ด ์‹ ์ฒด์— ๊นŠ์€ ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค๋Š” ์ƒ๊ฐ์— ํšŒ์˜์ ์ด์—ˆ๋˜ ์—ฌ๋А ์ƒ๋ฌผํ•™์ž๋“ค๊ณผ ๋‹ค๋ฅด์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ์ธก์ • ๋ถˆ๊ฐ€๋Šฅํ•˜๊ณ  ๋น„๋ฌผ์งˆ์ ์ด๋ฉฐ ์ƒ๋ฌผํ•™์  ๊ณผํ•™๊ณผ๋Š” ๋‹ค๋ฅธ ์˜์—ญ์— ์†ํ•œ๋‹ค๊ณ  ์—ฌ๊ฒจ์กŒ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ •์‹ ๊ณผ ์˜์‚ฌ์˜€๋˜ ๊ทธ์˜ ์•„๋ฒ„์ง€๋Š” โ€œ์ •์‹  ์˜ํ•™์€ ๋งˆ๋ฒ• ๊ฐ™์€ ์‹ฌ๋ฆฌ์  ์˜์—ญ์—์„œ ์ž‘๋™ํ•˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ๋‡Œ๋ฅผ ๋ณ€ํ™”์‹œํ‚ค๊ธฐ ๋•Œ๋ฌธ์— ์ž‘๋™ํ•˜๋Š” ๊ฒƒโ€์ด๋ผ๊ณ  ๊ฐ€๋ฅด์ณค์Šต๋‹ˆ๋‹ค. ๋ช…์ƒ, ์‹ฌ๋ฆฌ ์น˜๋ฃŒ, ์กฐ์ ˆ๋œ ํ˜ธํก ๋“ฑ ๋ชจ๋“  ํ–‰๋™ ๊ณผ์ •์ด ์ƒ๋ฌผํ•™์  ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ํ†ตํ•ด ์ž‘๋™ํ•˜๋ฉฐ, ์ง€๋‚œ 10๋…„๊ฐ„ ์ด ์ƒ๋ฌผํ•™์  ์ดํ•ด๋Š” ๋น„์•ฝ์ ์œผ๋กœ ๋ฐœ์ „ํ–ˆ์Šต๋‹ˆ๋‹ค.

๋ฆฐ๋“  ๋ฐ•์‚ฌ๋Š” ์—ญ์‚ฌ์ ์œผ๋กœ ์ œ๊ธฐ๋œ โ€˜์‹ฌ์‹  ์˜ํ•™(Mind-Body Medicine)โ€˜์— ๋Œ€ํ•œ ๋ชจ๋“  ์ฃผ์žฅ์ด ์‚ฌ์‹ค๋กœ ๋ฐํ˜€์ง€์ง€๋Š” ์•Š๊ฒ ์ง€๋งŒ, ํ•œ๋•Œ ์ดˆ์ž์—ฐ์ ์œผ๋กœ ๋ณด์˜€๋˜ ์ฃผ์žฅ๋“ค ์ค‘ ์ƒ๋‹น์ˆ˜๊ฐ€ ๊ฒฐ๊ตญ ์‹ค์ œ ์ƒ๋ฌผํ•™์  ์„ค๋ช…์„ ๊ฐ–๊ฒŒ ๋  ๊ฒƒ์ด๋ผ๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ํ˜„์žฌ ์งˆ๋ณ‘๊ณผ ์ผ์ƒ ๊ธฐ๋Šฅ์— ๋Œ€ํ•œ ๋งŽ์€ ์ดํ•ด๊ฐ€ ์‹ ์ฒด ์ž์ฒด์—๋งŒ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์ง€๋งŒ, ์ด์ œ๋Š” ์•”, ์ž๊ฐ€๋ฉด์—ญ ์งˆํ™˜ ๊ฐ™์€ ๋งŽ์€ ์งˆ๋ณ‘ ๊ณผ์ •๊ณผ ์ˆ˜๋ฉด, ์‹์‚ฌ, ํ—ˆ๊ธฐ์™€ ๊ฐ™์€ ์ผ์ƒ ํ™œ๋™๋“ค์ด ๋‡Œ์˜ ๊ฐ•๋ ฅํ•œ ํ†ต์ œํ•˜์— ์žˆ๋‹ค๋Š” ํ˜๋ช…์ ์ธ ์ธ์‹์ด ํ™•์‚ฐ๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋‡Œ์˜ ํ†ต์ œํ•˜์— ์žˆ๋‹ค๋Š” ๊ฒƒ์€ ๋ฌด์˜์‹์ ์œผ๋กœ ์ผ์–ด๋‚˜๋Š” ํ˜„์ƒ์ผ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ํ˜ธํก ์—ฐ์Šต, ๋ช…์ƒ, ์‹ฌ๋ฆฌ ์น˜๋ฃŒ, ์šด๋™ ๋“ฑ ์šฐ๋ฆฌ์˜ ํ–‰๋™์„ ํ†ตํ•ด ์ด๋ฅผ ์กฐ์ ˆํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ€๋Šฅ์„ฑ์„ ์—ด์–ด์ค๋‹ˆ๋‹ค. ์ด๋Š” ์งˆ๋ณ‘์— ๋Œ€ํ•œ ์‚ฌ๊ณ ๋ฐฉ์‹์„ ์™„์ „ํžˆ ์ƒˆ๋กœ์šด ๋ฐฉ์‹์œผ๋กœ ์ „ํ™˜์‹œํ‚ต๋‹ˆ๋‹ค.

1. ๋‡Œ์™€ ๋ชธ์˜ ๋น„๋ฐ€์Šค๋Ÿฌ์šด ๋Œ€ํ™”: ๋‚ด์ˆ˜์šฉ ๊ฐ๊ฐ๊ณผ ์ž์œจ์‹ ๊ฒฝ๊ณ„

์šฐ๋ฆฌ๋Š” ๋ณดํ†ต ๋ƒ„์ƒˆ, ๋ง›, ์‹œ๊ฐ, ์ด‰๊ฐ, ์ฒญ๊ฐ์ฒ˜๋Ÿผ ์™ธ๋ถ€ ์„ธ๊ณ„์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•˜๋Š” ๊ฐ๊ฐ๋“ค์„ ๋– ์˜ฌ๋ฆฝ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์šฐ๋ฆฌ์—๊ฒŒ๋Š” โ€˜๋‚ด์ˆ˜์šฉ ๊ฐ๊ฐ(Interoceptive Senses)โ€˜์ด๋ผ๋Š” ๋‚ด๋ถ€ ์ง€ํ–ฅ์ ์ธ ๊ฐ๊ฐ๋„ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ฐฉ๊ด‘์ด๋‚˜ ์žฅ์ด ๊ฐ€๋“ ์ฐผ๋Š”์ง€, ์ค‘๋ ฅ์— ๋Œ€ํ•œ ๋จธ๋ฆฌ์˜ ์œ„์น˜๋Š” ์–ด๋–ค์ง€ ๋“ฑ ์šฐ๋ฆฌ ๋ชธ์˜ ์ƒํƒœ๋ฅผ ์•Œ๋ ค์ฃผ๋Š” ๊ฐ๊ฐ๋“ค์ž…๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋‚ด์ˆ˜์šฉ ๊ฐ๊ฐ์€ ๋งˆ์Œ๊ณผ ๋ชธ ์‚ฌ์ด์˜ ์ง€์†์ ์ธ ๋Œ€ํ™”์— ํ•„์ˆ˜์ ์ž…๋‹ˆ๋‹ค.

๋ชธ์—์„œ ๋‡Œ๋กœ ์ „๋‹ฌ๋˜๋Š” ์‹ ํ˜ธ๋Š” ํฌ๊ฒŒ ์„ธ ๊ฐ€์ง€ ๋ฐฉ์‹์œผ๋กœ ์ž‘๋™ํ•ฉ๋‹ˆ๋‹ค.

  • ๋น ๋ฅธ ์ „๊ธฐ ์‹ ํ˜ธ: ๋งค์šฐ ๋น ๋ฅด๊ฒŒ ์ „๋‹ฌ๋˜์–ด์•ผ ํ•˜๋Š” ์‹ ํ˜ธ๋Š” ๋ชธ์—์„œ ์ฒ™์ˆ˜๋ฅผ ๊ฑฐ์ณ ๋‡Œ๋กœ ์ด์–ด์ง€๋Š” ๋‰ด๋Ÿฐ(์‹ ๊ฒฝ ์„ธํฌ)์„ ํ†ตํ•ด ์ „๊ธฐ์ ์œผ๋กœ ์ „๋‹ฌ๋ฉ๋‹ˆ๋‹ค.
  • ๋А๋ฆฐ ํ˜ธ๋ฅด๋ชฌ ์‹ ํ˜ธ: ๋” ์ฒœ์ฒœํžˆ ์ž‘๋™ํ•ด๋„ ๋˜๋Š” ์‹ ํ˜ธ๋Š” ๋ชธ์—์„œ ํ˜ธ๋ฅด๋ชฌ์„ ๋ถ„๋น„ํ•˜๊ณ , ์ด ํ˜ธ๋ฅด๋ชฌ์ด ํ˜ˆ์•ก์„ ํƒ€๊ณ  ๋‡Œ์— ๋„๋‹ฌํ•˜์—ฌ ๋‰ด๋Ÿฐ์ด๋‚˜ ๋‹ค๋ฅธ ์„ธํฌ์˜ ์ˆ˜์šฉ์ฒด์— ๊ฒฐํ•ฉํ•จ์œผ๋กœ์จ ๋А๋ฆฐ ํšจ๊ณผ๋ฅผ ์œ ๋ฐœํ•ฉ๋‹ˆ๋‹ค.
  • ์ง€์†์ ์ธ ๋ฆฌ๋“ฌ ๋ฐ˜์‘: ๋‡Œ๋Š” ์šฐ๋ฆฌ์˜ ํ˜ธํก ๋ฆฌ๋“ฌ๊ณผ ์‹ฌ์žฅ ๋ฐ•๋™์— ์ง€์†์ ์œผ๋กœ ๋ฐ˜์‘ํ•ฉ๋‹ˆ๋‹ค. ์‹ฌ์žฅ์ด ํ•œ ๋ฒˆ ๋ฐ•๋™ํ•  ๋•Œ๋งˆ๋‹ค ๋‡Œ์˜ ๋™๋งฅ์ด ๋ฏธ์„ธํ•˜๊ฒŒ ํ™•์žฅ๋˜๋Š”๋ฐ, ๋‡Œ๋Š” ์ด๋ฅผ ๊ฐ์ง€ํ•˜๊ณ  ๋ฐ˜์‘ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋งค์šฐ ๋น ๋ฅธ ์‹ ํ˜ธ์ž…๋‹ˆ๋‹ค.

๋ฐ˜๋Œ€๋กœ ๋‡Œ์— ์˜ํ•ด ๊ตฌํ˜„๋˜๋Š” ๋งˆ์Œ์ด ๋ชธ์— ๋ฐ˜์‘ํ•˜๋Š” ๋ฐฉ์‹ ๋˜ํ•œ ๋‹ค์–‘ํ•ฉ๋‹ˆ๋‹ค.

  • ์˜์‹์ ์ธ ์ž๋ฐœ์  ์šด๋™ ์‹œ์Šคํ…œ: โ€œํŒ”์„ ๋“ค์–ด ์˜ฌ๋ฆฌ๊ณ  ์‹ถ๋‹คโ€๋Š” ์ƒ๊ฐ์œผ๋กœ ์‹ค์ œ๋กœ ํŒ”์„ ๋“ค์–ด ์˜ฌ๋ฆฌ๋Š” ๊ฒƒ๊ณผ ๊ฐ™์ด, ์šฐ๋ฆฌ๊ฐ€ ์˜์‹์ ์œผ๋กœ ๋ชธ์„ ์ œ์–ดํ•˜๋Š” ๋ฐฉ์‹์ž…๋‹ˆ๋‹ค.
  • ๋ฌด์˜์‹์ ์ธ ์ž์œจ์‹ ๊ฒฝ๊ณ„(Autonomic Nervous System): ๋งˆ์Œ์ด ์šฐ๋ฆฌ์˜ ์˜์‹ ์ˆ˜์ค€ ์ดํ•˜์—์„œ ๋ชธ์„ ์ œ์–ดํ•˜๋Š” ํ˜„์ƒ์ž…๋‹ˆ๋‹ค. ์ž์œจ์‹ ๊ฒฝ๊ณ„๋Š” โ€˜๊ต๊ฐ์‹ ๊ฒฝ๊ณ„(Sympathetic Nervous System)โ€˜์™€ โ€˜๋ถ€๊ต๊ฐ์‹ ๊ฒฝ๊ณ„(Parasympathetic Nervous System)โ€˜๋กœ ๋‚˜๋‰ฉ๋‹ˆ๋‹ค. ๊ต๊ฐ์‹ ๊ฒฝ๊ณ„๋Š” โ€˜ํˆฌ์Ÿ ๋˜๋Š” ๋„ํ”ผ(fight or flight)โ€™ ๋ฐ˜์‘์„ ์ค€๋น„์‹œํ‚ค๊ณ , ๋ถ€๊ต๊ฐ์‹ ๊ฒฝ๊ณ„๋Š” โ€˜ํœด์‹ ๋ฐ ์†Œํ™”(rest and digest)โ€™ ๋ฐ˜์‘์„ ์ค€๋น„์‹œํ‚ต๋‹ˆ๋‹ค. ์ด ๋‘˜์€ ์Œ์–‘์ฒ˜๋Ÿผ ์„œ๋กœ ๊ธธํ•ญ ์ž‘์šฉ์„ ํ•˜๋ฉฐ ๋ฌด์˜์‹์ ์œผ๋กœ ๋ชธ์„ ์ œ์–ดํ•ฉ๋‹ˆ๋‹ค.
  • ํ˜ธ๋ฅด๋ชฌ ๋ฐฉ์ถœ: ๋‡Œ์—์„œ ๋ถ„๋น„๋˜๋Š” ํ˜ธ๋ฅด๋ชฌ์„ ํ†ตํ•ด ๋ชธ์„ ์ œ์–ดํ•  ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ํ˜ธ๋ฅด๋ชฌ์€ ๋‡Œํ•˜์ˆ˜์ฒด(pituitary gland)๋‚˜ ๋ถ€์‹ (adrenal gland) ๊ฐ™์€ ๊ธฐ๊ด€์— ์˜ํ–ฅ์„ ๋ฏธ์ณ ๋” ๋งŽ์€ ํ˜ธ๋ฅด๋ชฌ์„ ๋ถ„๋น„ํ•˜๊ฒŒ ํ•˜๊ณ , ์ด๋Š” ์ˆœํ™˜๊ณ„๋ฅผ ํ†ตํ•ด ๋ชธ ์ „์ฒด๋กœ ์ „๋‹ฌ๋˜์–ด ์ „๋ฐ˜์ ์ธ ํšจ๊ณผ๋ฅผ ๋‚˜ํƒ€๋ƒ…๋‹ˆ๋‹ค.
  • ๋ฉด์—ญ ์‹œ์Šคํ…œ ์ œ์–ด: ๋งˆ์ง€๋ง‰์œผ๋กœ โ€˜์‚ฌ์ดํ† ์นด์ธ(Cytokines)โ€˜์ด๋ผ๋Š” ๋ฉด์—ญ ์‹œ์Šคํ…œ ํŠนํ™” ํ˜ธ๋ฅด๋ชฌ ๋ถ„์ž๋ฅผ ํ†ตํ•ด ๋ฉด์—ญ ์‹œ์Šคํ…œ์„ ์ œ์–ดํ•ฉ๋‹ˆ๋‹ค.

2. GLP-1์œผ๋กœ ์‹์š• ์‹œ์Šคํ…œ ํ•ดํ‚นํ•˜๊ธฐ

์šฐ๋ฆฌ๋Š” ๋จน๊ณ  ๋ฐฐ๊ณ ํ”ˆ ๊ฒƒ์„ ๋‹จ์ˆœํ•˜๊ฒŒ ์ƒ๊ฐํ•˜์ง€๋งŒ, ์‹ค์ œ๋กœ๋Š” ๋ชธ๊ณผ ๋งˆ์Œ ์‚ฌ์ด์˜ ์ง€์†์ ์ธ ๋Œ€ํ™”๊ฐ€ ํ•„์š”ํ•˜๋ฉฐ, ์™ธ๋ถ€ ์ง€ํ–ฅ ๊ฐ๊ฐ๊ณผ ๋‚ด๋ถ€ ์ง€ํ–ฅ ๊ฐ๊ฐ์ด ๋ชจ๋‘ ๊ด€์—ฌํ•˜๋Š” ๋ณต์žกํ•œ ๊ณผ์ •์ž…๋‹ˆ๋‹ค.

์˜ˆ๋ฅผ ๋“ค์–ด, ๋‰ด์š• ๊ฑฐ๋ฆฌ์—์„œ ํ”ผ์ž ๋ƒ„์ƒˆ๋ฅผ ๋งก์•˜์„ ๋•Œ (์™ธ์ˆ˜์šฉ ๊ฐ๊ฐ), โ€œ๋ฐฐ๊ฐ€ ๊ณ ํ”ˆ๊ฐ€?โ€ (๋‚ด์ˆ˜์šฉ ๊ฐ๊ฐ)๋ผ๋Š” ์งˆ๋ฌธ์„ ๋˜์ง€๊ณ , โ€œํ”ผ์ž๋ฅผ ์ข‹์•„ํ•œ๋‹คโ€๋Š” ๊ธฐ์–ต์„ ๋– ์˜ฌ๋ฆฌ๋ฉฐ (๊ธฐ์–ต), ๋ƒ„์ƒˆ๊ฐ€ ๊ธ์ •์ ์ธ ์—ฐ๊ด€์„ฑ์„ ๋ถˆ๋Ÿฌ์ผ์œผ์ผœ ํ”ผ์ž๋ฅผ ์ฐพ์•„ ๋‚˜์„œ๋Š” ๊ฒฐ์ •์„ ๋‚ด๋ฆฝ๋‹ˆ๋‹ค. ํ”ผ์ž ์กฐ๊ฐ์„ ์†์— ๋“ค๊ณ  ๋ƒ„์ƒˆ๋ฅผ ๋งก๊ณ  (์™ธ์ˆ˜์šฉ ๊ฐ๊ฐ) โ€œ๋จน์„ ๊ฒƒ์ธ๊ฐ€ ๋ง ๊ฒƒ์ธ๊ฐ€โ€๋ฅผ ๊ฒฐ์ •ํ•ฉ๋‹ˆ๋‹ค. ํ•œ ์ž… ๋ฒ ์–ด ๋ฌผ๊ณ  ๋ง›๊ณผ ์‹๊ฐ์„ ๋А๋ผ๋ฉฐ (์™ธ์ˆ˜์šฉ ๊ฐ๊ฐ), โ€œ์‚ผํ‚ฌ ๊ฒƒ์ธ๊ฐ€ ๋ฑ‰์„ ๊ฒƒ์ธ๊ฐ€โ€๋ฅผ ๊ฒฐ์ •ํ•ฉ๋‹ˆ๋‹ค. ๊ณ„์† ๋จน์œผ๋ฉด์„œ โ€œ๋ฐฐ๊ฐ€ ๋ถ€๋ฅธ๊ฐ€?โ€๋ฅผ ๊ฒฐ์ •ํ•  ๋•Œ๋Š” ์œ„๊ฐ€ ์–ผ๋งˆ๋‚˜ ํŒฝ์ฐฝํ–ˆ๋Š”์ง€ (๋น ๋ฅธ ์‹ ๊ฒฝ ์‹ ํ˜ธ)์™€ ์Œ์‹์˜ ์˜์–‘ ์„ฑ๋ถ„ (์œ„๋ฒฝ ์„ธํฌ์˜ ๋น ๋ฅธ ์ •๋ณด) ๋“ฑ ์—ฌ๋Ÿฌ ์ •๋ณด๊ฐ€ ์‚ฌ์šฉ๋ฉ๋‹ˆ๋‹ค. ์œ„๋Š” ๋ฌผ๊ณผ ์Œ์‹, ๊ทธ๋ฆฌ๊ณ  ์Œ์‹์˜ ์ข…๋ฅ˜(์ง€๋ฐฉ, ๋‹จ๋ฐฑ์งˆ, ํƒ„์ˆ˜ํ™”๋ฌผ)๋ฅผ ๊ตฌ๋ณ„ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ด ์ •๋ณด๋Š” ๋‡Œ๋กœ ๋น ๋ฅด๊ฒŒ ์ „๋‹ฌ๋˜์–ด ์‹์‚ฌ๋ฅผ ์ค‘๋‹จํ• ์ง€ ๊ณ„์†ํ• ์ง€ ๊ฒฐ์ •ํ•˜๋Š” ๋ฐ ๋„์›€์„ ์ค๋‹ˆ๋‹ค.

์•ฝ 20๋ถ„ ํ›„, ๋‹ค์‹œ ์‹์‚ฌ๋ฅผ ํ• ์ง€ ๊ฒฐ์ •ํ•  ๋•Œ ์ž‘์€์ฐฝ์ž(์†Œ์žฅ)์˜ ์ฒซ ๋ถ€๋ถ„์— ์žˆ๋Š” ์„ผ์„œ๋“ค์ด ์Œ์‹์˜ ์˜์–‘ ์„ฑ๋ถ„์„ ํ‰๊ฐ€ํ•˜๊ณ  โ€œ์ถฉ๋ถ„ํ•œ ์˜์–‘๋ถ„์ด ์žˆ์œผ๋‹ˆ ๋‹น๋ถ„๊ฐ„์€ ๋จน์ง€ ์•Š๊ฒ ๋‹คโ€๋Š” ํฌ๋งŒ๊ฐ์„ ๋А๋ผ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” โ€˜๊ธ€๋ฃจ์นด๊ณค ์œ ์‚ฌ ํŽฉํƒ€์ด๋“œ-1(Glucagon-like Peptide-1, GLP-1)โ€˜์ด๋ผ๋Š” ๋А๋ฆฐ ํ˜ธ๋ฅด๋ชฌ ์‹ ํ˜ธ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. GLP-1์€ ์œ„ ์šด๋™์„ฑ์„ ๋Šฆ์ถฐ ์œ„๊ฐ€ ์ฒœ์ฒœํžˆ ๋น„์›Œ์ง€๊ฒŒ ํ•˜๊ณ , ๋” ์ค‘์š”ํ•˜๊ฒŒ๋Š” ๋‡Œ์˜ ์‹์š• ์กฐ์ ˆ ์ค‘์ถ”์— ์ž‘์šฉํ•˜์—ฌ ์ˆ˜์‹ญ ๋ถ„์—์„œ ํ•œ๋‘ ์‹œ๊ฐ„ ๋™์•ˆ ์‹์š•์„ ์–ต์ œํ•ฉ๋‹ˆ๋‹ค.

ํฅ๋ฏธ๋กญ๊ฒŒ๋„, ํ˜€์™€ ์ž…์•ˆ์—๋Š” ์„คํƒ•์„ ๊ฐ์ง€ํ•˜๋Š” ํŠน์ˆ˜ ์„ผ์„œ๊ฐ€ ์žˆ์ง€๋งŒ, ์œ„์™€ ์ž‘์€์ฐฝ์ž์—๋„ ๋น„์Šทํ•œ ์„คํƒ• ์„ผ์„œ๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์„ผ์„œ๋“ค์€ ๋‡Œ์— ์ •๋ณด๋ฅผ ๋ณด๋‚ด ์‹์‚ฌ๋ฅผ ์ค‘๋‹จํ• ์ง€ ๊ฒฐ์ •ํ•˜๋Š” ๋ฐ ๋„์›€์„ ์ค๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์Œ๋ฃŒ๋‚˜ ๋‹ค๋ฅธ ์‹ํ’ˆ์— ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๋Š” ์ธ๊ณต ๊ฐ๋ฏธ๋ฃŒ๋Š” ์ž…์•ˆ์˜ ์„ผ์„œ๋Š” ์†์ด์ง€๋งŒ, ์œ„์™€ ์žฅ์˜ ์„ผ์„œ๋Š” ์†์ด์ง€ ๋ชปํ•ฉ๋‹ˆ๋‹ค. ์ด ์„ผ์„œ๋“ค์€ ๋ถ„์ž์ ์œผ๋กœ ๋‹ค๋ฅด๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ์ฆ‰, ์ธ๊ณต ๊ฐ๋ฏธ๋ฃŒ๋ฅผ ์„ญ์ทจํ•˜๋ฉด ์ž…์€ โ€œ์ด๊ฒƒ์€ ์„คํƒ•์ด๋‹คโ€๋ผ๊ณ  ๋งํ•˜์ง€๋งŒ, ์žฅ์€ โ€œ์•„๋‹ˆ๋‹ค, ์ง„์งœ ์„คํƒ•์ด ์•„๋‹ˆ๋‹คโ€๋ผ๊ณ  ๋งํ•ด ๋‡Œ์— ์ƒ์ถฉ๋˜๋Š” ์‹ ํ˜ธ๊ฐ€ ์ „๋‹ฌ๋ฉ๋‹ˆ๋‹ค. ์ด๊ฒƒ์ด ๋ฐ”๋กœ ์ธ๊ณต ๊ฐ๋ฏธ๋ฃŒ๊ฐ€ ์ฒด์ค‘ ๊ฐ๋Ÿ‰์— ํšจ๊ณผ์ ์ธ ์ „๋žต์ด ์•„๋‹Œ ์ด์œ  ์ค‘ ํ•˜๋‚˜์ž…๋‹ˆ๋‹ค.

GLP-1 ๊ธฐ๋ฐ˜ ์ฒด์ค‘ ๊ฐ๋Ÿ‰ ์•ฝ๋ฌผ์˜ ํ˜๋ช… ์ง€๋‚œ ๋ช‡ ๋…„๊ฐ„ GLP-1 ํ˜ธ๋ฅด๋ชฌ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๋งค์šฐ ์ธ๊ธฐ ์žˆ๋Š” ๋‹ค์ด์–ดํŠธ ์•ฝ๋ฌผ์— ๋Œ€ํ•ด ๋“ค์–ด๋ณด์…จ์„ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ฒœ์—ฐ GLP-1์€ ํ˜ˆ๋ฅ˜์—์„œ ๋งค์šฐ ๋น ๋ฅด๊ฒŒ ๋ถ„ํ•ด๋˜์–ด ํšจ๊ณผ๊ฐ€ ์งง์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๋…ธ๋ณด ๋…ธ๋””์Šคํฌ(Novo Nordisk)์˜ ์˜๋ฆฌํ•œ ํ™”ํ•™์ž๋“ค์€ ์ฒœ์—ฐ GLP-1 ๋ถ„์ž์— ์ง€๋ฐฉ์‚ฐ ๊ฐ™์€ ํ™”ํ•™ ๊ทธ๋ฃน์„ ๋ถ™์—ฌ ํ˜ˆ์•ก ๋‚ด โ€˜์•Œ๋ถ€๋ฏผ(Albumin)โ€˜์ด๋ผ๋Š” ๋‹จ๋ฐฑ์งˆ์— ๊ฒฐํ•ฉํ•˜๊ฒŒ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค. ์•Œ๋ถ€๋ฏผ์— ๊ฒฐํ•ฉํ•˜๋ฉด ํšจ์†Œ์— ์˜ํ•ด ๋ถ„ํ•ด๋˜๊ฑฐ๋‚˜ ์‹ ์žฅ์—์„œ ๋ฐฐ์„ค๋˜๋Š” ๊ฒƒ์— ํ›จ์”ฌ ๋” ๊ฐ•ํ•ด์ง‘๋‹ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ์ฒœ์—ฐ GLP-1์ด ๋ช‡ ๋ถ„๋งŒ ์ž‘์šฉํ•˜๋Š” ๋ฐ˜๋ฉด, ์ด ๋ณ€ํ˜•๋œ GLP-1์€ ํ˜ˆ๋ฅ˜์— ์˜ค๋ž˜ ๋จธ๋ฌผ๋ฉฐ ์‹์š•์„ ๋งค์šฐ ์˜ค๋žซ๋™์•ˆ ์–ต์ œํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๊ฒƒ์ด ๋ฐ”๋กœ โ€˜์„ธ๋งˆ๊ธ€๋ฃจํƒ€์ด๋“œ(Semaglutide, ์œ„๊ณ ๋น„, ์˜ค์ ฌํ”ฝ)โ€˜๋‚˜ โ€˜ํ„ฐ์ œํŒŒํƒ€์ด๋“œ(Tirzepatide, ์ ญ๋ฐ”์šด๋“œ, ๋ฌธ์ž๋กœ)โ€˜์™€ ๊ฐ™์€ ์•ฝ๋ฌผ์ด ์ผ์ฃผ์ผ์— ํ•œ ๋ฒˆ ์ฃผ์‚ฌ๋กœ ๊ฐ•๋ ฅํ•œ ์‹์š• ์–ต์ œ ํšจ๊ณผ๋ฅผ ๋‚ด๋Š” ๋น„๊ฒฐ์ž…๋‹ˆ๋‹ค. ์ด ์•ฝ๋ฌผ์„ ๋ณต์šฉํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์€ ์ผ๋ฐ˜์ ์œผ๋กœ ์ฒด์ค‘์˜ 12~17%๋ฅผ ๊ฐ๋Ÿ‰ํ•ฉ๋‹ˆ๋‹ค.

ํ•˜์ง€๋งŒ ์ด ์•ฝ๋ฌผ์˜ ํšจ๊ณผ๋Š” ๋‹จ์ˆœํžˆ ์ฒด์ค‘ ๊ฐ๋Ÿ‰์„ ๋„˜์–ด์„ญ๋‹ˆ๋‹ค. GLP-1 ์ˆ˜์šฉ์ฒด๋Š” ์œ„์™€ ๋‡Œ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์‹ฌ์žฅ, ์‹ ์žฅ, ๊ฐ„ ๋“ฑ ๋‹ค์–‘ํ•œ ๊ธฐ๊ด€์— ์กด์žฌํ•˜๋ฉฐ, ์ด ์•ฝ๋ฌผ๋“ค์ด ํ™œ์„ฑํ™”์‹œํ‚ฌ ๋•Œ ์ฒด์ค‘ ๊ฐ๋Ÿ‰ ์ด์ƒ์˜ ์œ ์ตํ•œ ํšจ๊ณผ๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ž…๋‹ˆ๋‹ค. ์•„์ง ์ •ํ™•ํ•œ ๋ฉ”์ปค๋‹ˆ์ฆ˜์€ ์•Œ ์ˆ˜ ์—†์ง€๋งŒ, ์ผ์ข…์˜ ํ•ญ์—ผ์ฆ ํšจ๊ณผ๊ฐ€ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์ถ”์ •๋ฉ๋‹ˆ๋‹ค.

GLP-1 ๊ธฐ๋ฐ˜ ์•ฝ๋ฌผ์€ ์™„๋ฒฝํ•˜์ง€๋Š” ์•Š์Šต๋‹ˆ๋‹ค. ๋ฉ”์Šค๊บผ์›€, ์œ„์žฅ ์žฅ์• , ๋‡Œ ์•ˆ๊ฐœ(brain fog), ์—๋„ˆ์ง€ ์†์‹ค ๋“ฑ์˜ ๋ถ€์ž‘์šฉ์ด ๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋˜ํ•œ, ์ฒด์ค‘ ๊ฐ๋Ÿ‰ ์‹œ ์ง€๋ฐฉ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ทผ์œก๋Ÿ‰๋„ ํ•จ๊ป˜ ๊ฐ์†Œํ•˜๋ฏ€๋กœ, ๊ทผ๋ ฅ ์šด๋™๊ณผ ์ถฉ๋ถ„ํ•œ ๋‹จ๋ฐฑ์งˆ ์„ญ์ทจ๋ฅผ ํ†ตํ•ด ๊ทผ์œก๋Ÿ‰์„ ์œ ์ง€ํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ์ด ์•ฝ๋ฌผ์€ ๋ณต์šฉํ•˜๋Š” ๋™์•ˆ์—๋งŒ ํšจ๊ณผ๊ฐ€ ์ง€์†๋˜๋ฏ€๋กœ, ์žฅ๊ธฐ์ ์ธ ์‚ฌ์šฉ์ด ํ•„์š”ํ•˜๋ฉฐ ์ค‘๋‹จํ•˜๋ฉด ์ฒด์ค‘์ด ๋‹ค์‹œ ์ฆ๊ฐ€ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

์˜ˆ์ƒ์น˜ ๋ชปํ•œ ๋ณด๋„ˆ์Šค ํšจ๊ณผ: ์‹ ๊ฒฝ๊ณผํ•™์ž๋“ค์€ GLP-1 ์•ฝ๋ฌผ์ด ์‹์š• ์–ต์ œ ์™ธ์— ์•Œ์ฝ”์˜ฌ ์ค‘๋…, ์•ฝ๋ฌผ ๋‚จ์šฉ, ๊ฐ•๋ฐ•์ ์ธ ์‡ผํ•‘์ด๋‚˜ ๋„๋ฐ•๊ณผ ๊ฐ™์€ ๋‹ค๋ฅธ ํ˜•ํƒœ์˜ ๋ณด์ƒ ํšŒ๋กœ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•ด ์ฒ˜์Œ์—๋Š” ํšŒ์˜์ ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ดˆ๊ธฐ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด, GLP-1 ๊ธฐ๋ฐ˜ ์•ฝ๋ฌผ์ด ์•Œ์ฝ”์˜ฌ ์„ญ์ทจ๋ฅผ ์กฐ์ ˆํ•˜๊ณ , ํ–ฅ์ •์‹ ์„ฑ ์•ฝ๋ฌผ ์ค‘๋‹จ์— ๋„์›€์„ ์ฃผ๋ฉฐ, ๊ฐ•๋ฐ•์ ์ธ ํ–‰๋™์„ ๊ด€๋ฆฌํ•˜๋Š” ๋ฐ๋„ ํšจ๊ณผ๊ฐ€ ์žˆ์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ์œ ๋งํ•œ ์ง•ํ›„๋“ค์ด ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๋‡Œ์˜ ๋ณด์ƒ ํšŒ๋กœ๊ฐ€ ์‹์š•๊ณผ ๋‹ค๋ฅธ ์ค‘๋… ํ–‰๋™์— ๋ถ€๋ถ„์ ์œผ๋กœ ๊ณต์œ ๋  ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•˜๋ฉฐ, ์•ž์œผ๋กœ์˜ ์—ฐ๊ตฌ๊ฐ€ ์ฃผ๋ชฉ๋ฉ๋‹ˆ๋‹ค.

์šด๋™๊ณผ ์‹์š• ์กฐ์ ˆ: ๊ฒฉ๋ ฌํ•œ ์šด๋™์€ ์‹์š•์„ ์ž๊ทนํ•˜์—ฌ ์ผ๋ถ€ ์‚ฌ๋žŒ๋“ค์€ ์šด๋™ ํ›„ ๋” ๋งŽ์€ ์Œ์‹์„ ์„ญ์ทจํ•˜์—ฌ ์ˆœ์ด์ต์ด ์—†์„ ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ฒฉ๋ ฌํ•œ ์šด๋™์€ ํ™•์‹คํžˆ ์ˆœ์ด์ต์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์šด๋™ ์ค‘ ์ƒ์„ฑ๋˜๋Š” โ€˜์ –์‚ฐ(Lactate)โ€˜์ด โ€˜ํŽ˜๋‹์•Œ๋ผ๋‹Œ(Phenylalanine)โ€˜์ด๋ผ๋Š” ์•„๋ฏธ๋…ธ์‚ฐ๊ณผ ๊ฒฐํ•ฉํ•˜์—ฌ ๋‡Œ์— ๋„๋‹ฌํ•ด ์‹์š•์„ ์–ต์ œํ•˜๋Š” ๋ณต์žกํ•œ ์ƒํ™”ํ•™์  ๊ณผ์ •์„ ๊ฑฐ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ž…๋‹ˆ๋‹ค. ์šด๋™๋งŒ์œผ๋กœ ์›ํ•˜๋Š” ๋ชจ๋“  ์ฒด์ค‘์„ ๊ฐ๋Ÿ‰ํ•˜๊ธฐ๋Š” ์–ด๋ ต์ง€๋งŒ, ์ด๋Š” ๋ถ„๋ช…ํ•œ ์ด์ ์ด๋ฉฐ, ๊ธฐ๋ถ„ ๊ฐœ์„ , ์ธ์ง€ ๊ธฐ๋Šฅ ์œ ์ง€ ๋“ฑ ์ฒด์ค‘ ๊ฐ๋Ÿ‰ ์™ธ์—๋„ ์ˆ˜๋งŽ์€ ๊ฑด๊ฐ•์ƒ์˜ ์ด์ ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.

์™œ ์šฐ๋ฆฌ๋Š” ๋” ๋ฌด๊ฑฐ์›Œ์กŒ๋Š”๊ฐ€? 1960๋…„ ์ด๋ž˜๋กœ ๋ฏธ๊ตญ์ธ์˜ ํ‰๊ท  ์ฒด์ค‘์€ 27ํŒŒ์šด๋“œ(์•ฝ 12kg) ์ฆ๊ฐ€ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ์œ ์ „์  ๋ณ€ํ™”๋‚˜ ์‹ ์ง„๋Œ€์‚ฌ์˜ ๋ณ€ํ™” ๋•Œ๋ฌธ์ด ์•„๋‹™๋‹ˆ๋‹ค. ์‹๋‹น๊ณผ ์Šˆํผ๋งˆ์ผ“์—์„œ ํŒŒ๋Š” ๊ณ ๋„๋กœ ๊ฐ€๊ณต๋œ ์‹ํ’ˆ์„ ๋งŒ๋“œ๋Š” ํšŒ์‚ฌ๋“ค์ด ์šฐ๋ฆฌ์˜ ์‹์š• ์‹œ์Šคํ…œ์„ ์กฐ์ž‘ํ•˜์—ฌ ๊ณผ์‹ํ•˜๊ฒŒ ๋งŒ๋“œ๋Š” ๋ฐฉ๋ฒ•์„ ์—ฐ๊ตฌํ•˜๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ์ธ๋ฅ˜๋Š” ๊ฐ„ํ—์ ์ธ ๊ธฐ๊ทผ ์†์—์„œ ์‚ด์•„์˜จ ์ง„ํ™”์  ์—ญ์‚ฌ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ณ ์นผ๋กœ๋ฆฌ, ๊ณ ์ง€๋ฐฉ, ๊ณ ๋‹น๋ถ„ ์Œ์‹์„ ๋งŒ๋‚˜๋ฉด ๋ชจ๋‘ ๋จน์–ด์น˜์›Œ ๋‹ค์Œ ๊ธฐ๊ทผ์— ๋Œ€๋น„ํ•˜๋Š” ๊ฒƒ์ด ์ƒ์กด์— ์œ ๋ฆฌํ–ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ํ˜„๋Œ€ ์‚ฌํšŒ๋Š” ๋” ์ด์ƒ ๊ธฐ๊ทผ์ด ๋งŒ์—ฐํ•œ ํ™˜๊ฒฝ์ด ์•„๋‹ˆ๋ฉฐ, ์‹ํ’ˆ ๊ธฐ์—…๋“ค์€ ๊ต๋ฌ˜ํ•œ ๊ณตํ•™ ๊ธฐ์ˆ ๋กœ ์šฐ๋ฆฌ์˜ ์ž์—ฐ์ ์ธ ์‹์‚ฌ ๋ฐ ์ค‘๋‹จ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๋ฌด๋ ฅํ™”์‹œํ‚ค๊ณ , ์ง€๋ฐฉ๊ณผ ๋‹จ ๊ฒƒ์„ ์ถ•์ ํ•˜๋ผ๋Š” ๋‡Œ์˜ ๊ณ ๋Œ€ ํšŒ๋กœ๋ฅผ ์•…์šฉํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

3. ๋ถ€๋‘ ์ฃฝ์Œ, ์ƒ์‹ฌ ์ฆํ›„๊ตฐ, ๊ทธ๋ฆฌ๊ณ  ํ”Œ๋ผ์‹œ๋ณด ํšจ๊ณผ

๋ฐ์ด๋น„๋“œ ๋ฆฐ๋“  ๋ฐ•์‚ฌ๋Š” ๋ชจ๋“  ๊ณผํ•™์ž๋“ค์ด ํฅ๋ฏธ๋กญ๊ฑฐ๋‚˜ ํ˜์‹ ์ ์ด๊ฑฐ๋‚˜ ๊ธฐ์ดํ•ด์„œ ๊ฐ„์งํ•˜๊ณ  ์‹ถ์€ ๋…ผ๋ฌธ๋“ค์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ๊ทธ์—๊ฒŒ ๊ทธ๋Ÿฌํ•œ ๋…ผ๋ฌธ ์ค‘ ํ•˜๋‚˜๋Š” 1942๋…„ ์ €๋ช…ํ•œ ๋ฏธ๊ตญ ์ƒ๋ฆฌํ•™์ž ์›”ํ„ฐ ์บ๋„Œ(Walter Cannon)์ด ๋ฐœํ‘œํ•œ โ€˜๋ถ€๋‘ ์ฃฝ์Œ(Voodoo Death)โ€™ ํ˜„์ƒ์— ๋Œ€ํ•œ ๋ณด๊ณ ์„œ์ž…๋‹ˆ๋‹ค.

๋ถ€๋‘ ์ฃฝ์Œ์˜ ์ƒ๋ฌผํ•™์  ์„ค๋ช…: ๋ถ€๋‘ ์ฃฝ์Œ์€ ์‚ฌ๋žŒ๋“ค์ด ์ €์ฃผ๋ฅผ ๋ฐ›์•˜๋‹ค๊ณ  ๋ฏฟ๊ณ  ๊ทธ ์ €์ฃผ๋กœ ์ธํ•ด ์ฃฝ์„ ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ•  ๋•Œ ์‹ค์ œ๋กœ ์‚ฌ๋งํ•˜๋Š” ํ˜„์ƒ์„ ๋งํ•ฉ๋‹ˆ๋‹ค. ์บ๋„Œ์€ ๋‹จ์ˆœํ•œ ์ผํ™”์  ๋ณด๊ณ ๊ฐ€ ์•„๋‹ˆ๋ผ, ์„ธ๊ณ„ ๊ณณ๊ณณ์—์„œ ์ €์ฃผ๋กœ ์ธํ•ด ์‚ฌ๋งํ•œ ๋งŽ์€ ์‚ฌ๋ก€๋ฅผ ๋ฌธ์„œํ™”ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ๊ต๊ฐ์‹ ๊ฒฝ๊ณ„๊ฐ€ ๊ณผ๋„ํ•˜๊ฒŒ ๊ฐ์„ฑ๋˜์–ด ์ผ๋ จ์˜ ์ƒ๋ฆฌ์  ๋ณ€ํ™”๋ฅผ ์ผ์œผ์ผœ ์‚ฌ๋ง์— ์ด๋ฅด๊ฒŒ ํ•œ๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ์Šต๋‹ˆ๋‹ค. ํ˜„๋Œ€ ์˜ํ•™์€ โ€˜์‹œ์ƒํ•˜๋ถ€-๋‡Œํ•˜์ˆ˜์ฒด-๋ถ€์‹  ์ถ•(Hypothalamic-Pituitary-Adrenal, HPA axis)โ€˜๊ณผ ์ŠคํŠธ๋ ˆ์Šค ํ˜ธ๋ฅด๋ชฌ โ€˜์ฝ”๋ฅดํ‹ฐ์†”(Cortisol)โ€˜์˜ ์—ญํ• , ๊ทธ๋ฆฌ๊ณ  ๋ถ€๊ต๊ฐ์‹ ๊ฒฝ๊ณ„์˜ ์ค‘์š”์„ฑ์— ๋Œ€ํ•ด ๋” ๋งŽ์ด ์•Œ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์บ๋„Œ์˜ ์ด๋ก ์€ ์ ˆ๋ฐ˜์€ ์˜ณ์•˜์Šต๋‹ˆ๋‹ค. ๊ต๊ฐ์‹ ๊ฒฝ๊ณ„๊ฐ€ ๊ด€์—ฌํ•˜์ง€๋งŒ, ๋ถ€๋‘ ์ฃฝ์Œ์€ โ€˜์›ํˆฌ ํŽ€์น˜โ€™์ฒ˜๋Ÿผ ์ž‘์šฉํ•ฉ๋‹ˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ๊ต๊ฐ์‹ ๊ฒฝ๊ณ„์˜ ๊ณผํ™œ์„ฑํ™”์ด๊ณ , ๋‘ ๋ฒˆ์งธ๋Š” ๋ถ€๊ต๊ฐ์‹ ๊ฒฝ๊ณ„๊ฐ€ ํ™œ์„ฑํ™”๋œ ์ƒํƒœ๋กœ ์ˆ˜ ์‹œ๊ฐ„ ๋˜๋Š” ์ˆ˜์ผ ๋™์•ˆ ์œ ์ง€๋˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด ๋‘ ๊ฐ€์ง€๊ฐ€ ํ•จ๊ป˜ ๋ชธ์˜ ๊ธฐ๋Šฅ์„ ๋ฉˆ์ถ”๊ฒŒ ํ•˜์—ฌ ๋ถ€๋‘ ์ฃฝ์Œ์— ์ด๋ฅด๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. ํ•ต์‹ฌ์€ ์ €์ฃผ๋‚˜ ์ฃผ์ˆ ์— ์˜ํ•ด ์ฃฝ์„ ์ˆ˜ ์žˆ๋‹ค๋Š” โ€˜๋ฏฟ์Œโ€™์ด ์žˆ์–ด์•ผ๋งŒ ์ž‘๋™ํ•œ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ์ดˆ์ž์—ฐ์ ์ธ ํ˜„์ƒ์ด ์•„๋‹ˆ๋ผ, ์ €์ฃผ๋ฅผ ๋ฐ›์€ ์‚ฌ๋žŒ์˜ ๋งˆ์Œ๊ณผ ๋ชธ์—์„œ ์ƒ๋ฌผํ•™์ ์œผ๋กœ ์ผ์–ด๋‚˜๋Š” ์ผ์ž…๋‹ˆ๋‹ค.

ํ˜„๋Œ€ ์˜ํ•™ ์†์˜ ๋ถ€๋‘ ์ฃฝ์Œ: ๋ถ€๋‘ ์ฃฝ์Œ์€ ํŠน์ • ์‚ฌํšŒ์—๋งŒ ๊ตญํ•œ๋œ ํ˜„์ƒ์ด ์•„๋‹™๋‹ˆ๋‹ค. 1970๋…„๋Œ€์— ๊ฐ„์•” ์ง„๋‹จ์„ ๋ฐ›์€ ํ•œ ๋‚จ์ž์˜ ์œ ๋ช…ํ•œ ์‚ฌ๋ก€๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ํฌ๋ฆฌ์Šค๋งˆ์Šค๋ฅผ ๊ฐ€์กฑ๊ณผ ํ•จ๊ป˜ ๋ณด๋‚ด๊ณ  ์‹ถ๋‹ค๊ณ  ๋งํ–ˆ๊ณ , ์™„ํ™” ์น˜๋ฃŒ๋ฅผ ๋ฐ›์œผ๋ฉฐ ํฌ๋ฆฌ์Šค๋งˆ์Šค๋ฅผ ๋„˜๊ฒผ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ƒˆํ•ด๊ฐ€ ๋˜์ž๋งˆ์ž ์‚ฌ๋งํ–ˆ์Šต๋‹ˆ๋‹ค. ์‚ฌ๋žŒ๋“ค์€ ์•”์œผ๋กœ ์ฃฝ์—ˆ๋‹ค๊ณ  ์ƒ๊ฐํ–ˆ์ง€๋งŒ, ๋ถ€๊ฒ€ ๊ฒฐ๊ณผ ๊ทธ๋Š” ๊ฐ„์•”์ด ์ „ํ˜€ ์—†์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋ฅผ ์ฃฝ์ธ ๊ฒƒ์€ โ€˜์น˜๋ช…์ ์ธ ์งˆ๋ณ‘์— ๊ฑธ๋ ธ๋‹คโ€™๋Š” ๊ทธ์˜ ๋ฏฟ์Œ์ด์—ˆ๊ณ , ์ด๋Š” ๋ถ€๋‘ ์ฃฝ์Œ๊ณผ ์ •ํ™•ํžˆ ๊ฐ™์€ ๋ฐฉ์‹์œผ๋กœ ์ž‘์šฉํ–ˆ์„ ๊ฒƒ์ž…๋‹ˆ๋‹ค.

์ƒ์‹ฌ ์ฆํ›„๊ตฐ(Broken Heart Syndrome): ์‚ฌ๋ž‘ํ•˜๋Š” ์‚ฌ๋žŒ์„ ์žƒ์€ ํ›„ ๋‹ค๋ฅธ ๋ฐฐ์šฐ์ž๊ฐ€ ์–ผ๋งˆ ์ง€๋‚˜์ง€ ์•Š์•„ โ€˜์ƒ์‹ฌํ•˜์—ฌโ€™ ์‚ฌ๋งํ–ˆ๋‹ค๋Š” ์ด์•ผ๊ธฐ๋Š” ํ”ํžˆ ๋“ค์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์—ญํ•™ ์—ฐ๊ตฌ์— ๋”ฐ๋ฅด๋ฉด, ์žฅ๊ธฐ์ ์ธ ํŒŒํŠธ๋„ˆ๊ฐ€ ์‚ฌ๋งํ•œ ํ›„ ์‚ฌ๋žŒ๋“ค์ด ์‚ฌ๋งํ•  ํ™•๋ฅ ์ด ์‹ค์ œ๋กœ ๋” ๋†’์Šต๋‹ˆ๋‹ค. ์‹ฌํ˜ˆ๊ด€ ์งˆํ™˜, ์•”, ์ž๊ฐ€๋ฉด์—ญ ์งˆํ™˜ ๋“ฑ ๋‹ค์–‘ํ•œ ์งˆ๋ณ‘์˜ ๋ฐœ์ƒ๋ฅ ์ด ์‚ฌ๋ž‘ํ•˜๋Š” ์‚ฌ๋žŒ(ํŒŒํŠธ๋„ˆ, ์นœํ•œ ์นœ๊ตฌ, ํ˜•์ œ์ž๋งค, ์‹ฌ์ง€์–ด ๋ฐ˜๋ ค๋™๋ฌผ)์„ ์žƒ์€ ํ›„ ์ฆ๊ฐ€ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์Šฌํ””์˜ ๊ฐ์ • ์ƒํƒœ๋Š” ์˜ˆํ›„๋ฅผ ์•…ํ™”์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ์ž˜ ํ™•๋ฆฝ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.

์ผ๋ณธ ์˜์‚ฌ๋“ค์ด ๋…ธ์ธ ์‚ฌ๋ง์ž๋“ค์—๊ฒŒ์„œ ์ฒ˜์Œ ๋ฐœ๊ฒฌํ•œ ๋งคํ˜น์ ์ธ ํ˜„์ƒ์ธ โ€˜ํƒ€์ฝ”์ธ ๋ณด ์‹ฌ๊ทผ๋ณ‘์ฆ(Takotsubo Cardiomyopathy)โ€˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค. ํƒ€์ฝ”(๋ฌธ์–ด)์™€ ์ธ ๋ณด(ํ•จ์ •)๋ฅผ ๋‹ฎ์€ ์‹ฌ์žฅ ๋ชจ์–‘ ๋•Œ๋ฌธ์— ๋ถ™์—ฌ์ง„ ์ด๋ฆ„์ธ๋ฐ, ์‹ฌ์žฅ ๊ธฐ๋Šฅ์— ์žฅ์• ๋ฅผ ์ผ์œผํ‚ต๋‹ˆ๋‹ค. ๋Œ€๋ถ€๋ถ„ ํšŒ๋ณต๋˜์ง€๋งŒ ์ผ๋ถ€๋Š” ์‚ฌ๋งํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ณ‘์€ ๊ต๊ฐ์‹ ๊ฒฝ๊ณ„์˜ ๊ณผ๋„ํ•œ ํ™œ์„ฑํ™”์˜ ๊ฒฐ๊ณผ๋กœ ์•Œ๋ ค์ ธ ์žˆ์œผ๋ฉฐ, ์Šฌํ””์ด๋ผ๋Š” ํ–‰๋™ ๊ฒฝํ—˜๊ณผ ์‹ฌ์žฅ ๊ธฐ๋Šฅ ์žฅ์• ๋ผ๋Š” ์‹ ์ฒด ๊ฒฝํ—˜์„ ์—ฐ๊ฒฐํ•˜๋Š” ์ƒ๋ฌผํ•™์  ์„ค๋ช…์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.

๊ธ์ •์ ์ธ ๋ฏฟ์Œ์˜ ํž˜: ํ”Œ๋ผ์‹œ๋ณด ํšจ๊ณผ(Placebo Effect) ๋‹คํ–‰ํžˆ๋„ ์ด๋Ÿฌํ•œ ํ˜„์ƒ์€ ๋ฐ˜๋Œ€ ๋ฐฉํ–ฅ์œผ๋กœ๋„ ์ž‘๋™ํ•ฉ๋‹ˆ๋‹ค. ๊ธ์ •์ ์ธ ๋ฏฟ์Œ๊ณผ ์ •์‹  ์ƒํƒœ๋Š” ํ†ต์ฆ ์™„ํ™”๋‚˜ ๋” ๋‚˜์€ ๊ฑด๊ฐ• ๊ฒฐ๊ณผ๋กœ ์ด์–ด์งˆ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์‹ฌ์‹  ์˜ํ•™์€ ๋ช…์ƒ, ํ˜ธํก ์กฐ์ ˆ, ๊ธฐ๋„, ์‹ฌ๋ฆฌ ์น˜๋ฃŒ์™€ ๊ฐ™์€ ํ–‰๋™์  ๊ฐœ์ž…์— ์ดˆ์ ์„ ๋งž์ถ”๋Š” ๊ฒฝํ–ฅ์ด ์žˆ์ง€๋งŒ, ์ด๋Ÿฌํ•œ ์ดํ•ด๋Š” ์•ฝ๋ฌผ์ด๋‚˜ ์˜๋ฃŒ ๊ธฐ๊ธฐ ๊ฐ™์€ ์ „ํ†ต์ ์ธ ์น˜๋ฃŒ๋ฒ•์˜ ๊ฐœ๋ฐœ์—๋„ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, GLP-1 ๊ธฐ๋ฐ˜ ์•ฝ๋ฌผ์€ ๋ชธ์—์„œ ๋งˆ์Œ์œผ๋กœ ํ๋ฅด๋Š” ์ •๋ณด์— ๋Œ€ํ•œ ์ดํ•ด์—์„œ ๋น„๋กฏ๋œ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋˜ํ•œ, ๋ฏธ์ฃผ์‹ ๊ฒฝ(Vagus Nerve)์„ ์ž๊ทนํ•˜์—ฌ ๋ถ€๊ต๊ฐ์‹ ๊ฒฝ๊ณ„๋ฅผ ํ™œ์„ฑํ™”ํ•˜๋Š” ์ด์‹ํ˜• ์žฅ์น˜๋Š” ์šฐ์šธ์ฆ, ๊ฐ„์งˆ ๋ฐ ๊ธฐํƒ€ ์งˆ๋ณ‘์— ์œ ์šฉํ•˜๋ฉฐ, ์ด๋Š” ๋งˆ์Œ์—์„œ ๋ชธ์œผ๋กœ ํ๋ฅด๋Š” ์ •๋ณด์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ•ฉ๋‹ˆ๋‹ค.

๋Œ€๋ถ€๋ถ„์˜ ์‚ฌ๋žŒ๋“ค์€ ์„คํƒ• ์•Œ์•ฝ์ด๋‚˜ ๊ฐ€์งœ ์น˜๋ฃŒ๋ฅผ ๋ฐ›์•˜์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์ด์ ์„ ๋ณด๋Š” โ€˜ํ”Œ๋ผ์‹œ๋ณด ํšจ๊ณผโ€™์— ๋Œ€ํ•ด ๋“ค์–ด๋ดค์„ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ํ†ต์ฆ ์™„ํ™”, ๊ฐ์—ผ ์น˜๋ฃŒ, ์‹ฌํ˜ˆ๊ด€ ๊ธฐ๋Šฅ ๊ฐœ์„  ๋“ฑ ๋‹ค์–‘ํ•œ ์ƒํ™ฉ์—์„œ ํ”Œ๋ผ์‹œ๋ณด ํšจ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚ฉ๋‹ˆ๋‹ค. ํŠนํžˆ ํ†ต์ฆ ์™„ํ™”์˜ ๊ฒฝ์šฐ, ํ”Œ๋ผ์‹œ๋ณด ํšจ๊ณผ๊ฐ€ ์–ด๋–ป๊ฒŒ ์ƒ๋ฌผํ•™์ ์œผ๋กœ ์ž‘๋™ํ•˜๋Š”์ง€์— ๋Œ€ํ•œ ์ดํ•ด๊ฐ€ ๋งค์šฐ ๋†’์Šต๋‹ˆ๋‹ค. ์„คํƒ• ์•Œ์•ฝ์ด๋‚˜ ๊ฐ€์งœ ์น˜๋ฃŒ๋ฅผ ๋ฐ›๊ณ  ํ†ต์ฆ์ด ์™„ํ™”๋  ๊ฒƒ์ด๋ผ๋Š” ๋ง์„ ๋“ค์—ˆ์„ ๋•Œ ์‹ค์ œ๋กœ ํ†ต์ฆ์ด ์ค„์–ด๋“œ๋Š” ํšจ๊ณผ๋Š” โ€˜๋‚ ๋ก์†(Naloxone)โ€˜์ด๋ผ๋Š” ์•ฝ๋ฌผ์— ์˜ํ•ด ์ฐจ๋‹จ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.


โ€œ669. Why Is 95 Percent of the Worldโ€™s Bourbon Made in Kentucky? | Freakonomics Radioโ€ โ€” Freakonomics Radio Network ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

์‹œ๊ฐ„์ด ๋นš์–ด๋‚ธ ํ™ฉํ™€๊ฒฝ, ์ผ„ํ„ฐํ‚ค ๋ฒ„๋ฒˆ์˜ ๋‹ฌ์ฝค ์Œ‰์‹ธ๋ฆ„ํ•œ ๊ฒฝ์ œํ•™

์ „ ์„ธ๊ณ„ ๋ฒ„๋ฒˆ ์œ„์Šคํ‚ค์˜ 95%๊ฐ€ ์ผ„ํ„ฐํ‚ค์—์„œ ์ƒ์‚ฐ๋˜๋Š” ๋น„๋ฐ€์€ ๋ฌด์—‡์ผ๊นŒ์š”? ๋‹จ์ˆœํ•œ ์ „ํ†ต์„ ๋„˜์–ด์„  ๋…ํŠนํ•œ ๊ฒฝ์ œํ•™์  ์š”์†Œ, ์—„๊ฒฉํ•œ ๊ทœ์ œ, ๊ทธ๋ฆฌ๊ณ  โ€˜์‹œ๊ฐ„โ€™์ด๋ผ๋Š” ํŠน๋ณ„ํ•œ ํˆฌ์ž์žฌ๊ฐ€ ์–ฝํ˜€ ๋ฒ„๋ฒˆ ์‚ฐ์—…์˜ ํฅ๋ง์„ฑ์‡ ๋ฅผ ์ขŒ์šฐํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํ•œ๋•Œ ํ™ฉ๊ธˆ๊ธฐ๋ฅผ ๊ตฌ๊ฐ€ํ•˜๋˜ ์ผ„ํ„ฐํ‚ค ๋ฒ„๋ฒˆ ์‚ฐ์—…์€ ์ง€๊ธˆ ์ˆ˜์š” ๊ฐ์†Œ์™€ ๊ณผ์ž‰ ๊ณต๊ธ‰์ด๋ผ๋Š” โ€˜์ˆ™์ทจโ€™์— ์‹œ๋‹ฌ๋ฆฌ๋ฉฐ ์ƒˆ๋กœ์šด ๋ณ€ํ™”์˜ ๊ธฐ๋กœ์— ์„œ ์žˆ์Šต๋‹ˆ๋‹ค. ํ”„๋ฆญ์ฝ”๋…ธ๋ฏน์Šค ๋ผ๋””์˜ค(Freakonomics Radio)๊ฐ€ ํŒŒํ—ค์นœ ๋ฒ„๋ฒˆ ์‚ฐ์—…์˜ ์ˆจ๊ฒจ์ง„ ๊ฒฝ์ œํ•™์„ ํ†ตํ•ด ๊ทธ ํฅ๋ฏธ๋กœ์šด ์ด์•ผ๊ธฐ๋ฅผ ๋“ค์—ฌ๋‹ค๋ด…๋‹ˆ๋‹ค.


์ผ„ํ„ฐํ‚ค, ๋ฒ„๋ฒˆ์˜ ์„ฑ์ง€๊ฐ€ ๋œ ์ด์œ : โ€˜์‹œ๊ฐ„โ€™์ด๋ผ๋Š” ํŠน๋ณ„ํ•œ ํˆฌ์ž

๋Œ€๋ถ€๋ถ„์˜ ์ œํ’ˆ์€ ์ƒ์‚ฐ๋˜๋Š” ์ฆ‰์‹œ ํŒ๋งค๋  ์ˆ˜ ์žˆ์–ด ํˆฌ์ž๊ธˆ์„ ๋น ๋ฅด๊ฒŒ ํšŒ์ˆ˜ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์–ด๋–ค ์ œํ’ˆ๋“ค์€ ์ œ์กฐ ํ›„์—๋„ ์ถ”๊ฐ€์ ์ธ โ€˜์‹œ๊ฐ„โ€™ ํˆฌ์ž๋ฅผ ํ•„์š”๋กœ ํ•ฉ๋‹ˆ๋‹ค. ์–ด๋–ค ์น˜์ฆˆ๋‚˜ ์™€์ธ์ฒ˜๋Ÿผ ๋ง์ด์ฃ . ๊ทธ๋ฆฌ๊ณ  ํŠนํžˆ ์œ„์Šคํ‚ค์™€ ๊ฐ™์€ ์ฆ๋ฅ˜์ฃผ๊ฐ€ ๊ทธ๋ ‡์Šต๋‹ˆ๋‹ค. ์˜ค๋ž˜๋œ ์Šค์นด์น˜ ์œ„์Šคํ‚ค ๋ฐฐ๋Ÿด์ด ๋น„์‹ผ ๋ณ‘์œผ๋กœ ์ด์–ด์ง€๋“ฏ, ๋ฏธ๊ตญ์˜ ๋Œ€ํ‘œ์ ์ธ ์ฆ๋ฅ˜์ฃผ์ธ ๋ฒ„๋ฒˆ(Bourbon) ์—ญ์‹œ ์ˆ™์„ฑ ์‹œ๊ฐ„์ด ๊ฐ€์น˜๋ฅผ ๊ฒฐ์ •ํ•˜๋Š” ํ•ต์‹ฌ ์š”์†Œ์ž…๋‹ˆ๋‹ค.

ํ”„๋ฆญ์ฝ”๋…ธ๋ฏน์Šค ๋ผ๋””์˜ค์˜ ์ง„ํ–‰์ž ์Šคํ‹ฐ๋ธ ๋”๋ธŒ๋„ˆ(Stephen Dubner)๋Š” ์ผ„ํ„ฐํ‚ค ๋ ‰์‹ฑํ„ด(Lexington) ์ฃผ๋ณ€์˜ ๋ธ”๋ฃจ๊ทธ๋ž˜์Šค ์ง€์—ญ์— ์„œ๋Ÿฌ๋ธŒ๋ ˆ๋“œ(Thoroughbred) ๊ฒฝ์ฃผ๋งˆ ์‚ฐ์—…์ด ์ง‘์ค‘๋˜์–ด ์žˆ๋Š” ํ˜„์ƒ์„ ์–ธ๊ธ‰ํ•˜๋ฉฐ, ๋˜ ๋‹ค๋ฅธ ์‚ฐ์—…์ด ์ด ์ž‘์€ ์ง€์—ญ์— ๋ฐ€์ง‘๋˜์–ด ์žˆ์Œ์„ ์‹œ์‚ฌํ•ฉ๋‹ˆ๋‹ค. ๊ทธ ๋‹ต์€ ๋ฐ”๋กœ ๋ฒ„๋ฒˆ์ž…๋‹ˆ๋‹ค. ์ „ ์„ธ๊ณ„ ๋ฒ„๋ฒˆ์˜ 95%๊ฐ€ ์ผ„ํ„ฐํ‚ค์—์„œ ์ƒ์‚ฐ๋˜๋Š” ์ด ๋†€๋ผ์šด ์ง‘์ค‘ ํ˜„์ƒ์€ ๋‹จ์ˆœํ•œ ์šฐ์—ฐ์ด ์•„๋‹™๋‹ˆ๋‹ค.

์ผ„ํ„ฐํ‚ค๋Œ€ํ•™๊ต ๊ฒฝ์ œํ•™๊ณผ ํ•™๊ณผ์žฅ์ด์ž ๋…ธ๋™๊ฒฝ์ œํ•™์ž์ธ ์ผ„ ํŠธ๋กœ์Šคํ‚ค(Ken Troske) ๊ต์ˆ˜๋Š” ์ž์‹ ์ด ์‚ฌ๋Š” ์ง‘์—์„œ 45๋ถ„ ์šด์ „ ๊ฑฐ๋ฆฌ ๋‚ด์— ์ „ ์„ธ๊ณ„ ๋ฒ„๋ฒˆ์˜ 95%๊ฐ€ ๋งŒ๋“ค์–ด์ง„๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๊ฐ€ ์ผ„ํ„ฐํ‚ค์— ์ฒ˜์Œ ์™”์„ ๋•Œ 4๋ฐฑ๋งŒ ๋ฐฐ๋Ÿด์— ๋ถˆ๊ณผํ–ˆ๋˜ ์ˆ™์„ฑ ์ค‘์ธ ๋ฒ„๋ฒˆ ๋ฐฐ๋Ÿด ์ˆ˜๋Š” ํ˜„์žฌ 1600๋งŒ ๋ฐฐ๋Ÿด๋กœ ๋Š˜์–ด๋‚ฌ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๋ฒ„๋ฒˆ ์‚ฐ์—…์ด ์นจ์ฒด๊ธฐ๋ฅผ ๊ฒช๋‹ค๊ฐ€ ํšŒ๋ณต์„ธ๋ฅผ ๋ณด์ด๋˜ ์‹œ๊ธฐ์™€ ๋งž๋ฌผ๋ฆฝ๋‹ˆ๋‹ค. ํŠธ๋กœ์Šคํ‚ค ๊ต์ˆ˜๋Š” ํ•œ๋•Œ 120๋‹ฌ๋Ÿฌ์— ํŒ”๋ฆฌ๋˜ 20๋…„์‚ฐ โ€˜ํŒŒํ”ผ ๋ฐด ์œ™ํด(Pappy Van Winkle)โ€™ ํ•œ ๋ณ‘์ด ํ˜„์žฌ 2,500~3,000๋‹ฌ๋Ÿฌ๋ฅผ ํ˜ธ๊ฐ€ํ•˜๋Š” ์‚ฌ๋ก€๋ฅผ ๋“ค๋ฉฐ, ๋ฒ„๋ฒˆ์˜ ๊ฐ€์น˜ ์ƒ์Šน์„ ์‹ค๊ฐ ๋‚˜๊ฒŒ ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค.

๋ฒ„๋ฒˆ์˜ ๊ฐ€์น˜๊ฐ€ ๋†’์•„์ง€์ž ์ ˆ๋„ ์‚ฌ๊ฑด๊นŒ์ง€ ๋ฐœ์ƒํ–ˆ์Šต๋‹ˆ๋‹ค. ํ˜ธํ™ฉ๊ธฐ ๋™์•ˆ 20๋…„์‚ฐ ํŒŒํ”ผ ๋ฐด ์œ™ํด 65์ƒ์ž๊ฐ€ ์ฐฝ๊ณ ์—์„œ ๋„๋‚œ๋‹นํ–ˆ๋Š”๋ฐ, ์•”์‹œ์žฅ ๊ฐ€์น˜๋Š” 10๋งŒ ๋‹ฌ๋Ÿฌ์— ๋‹ฌํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๊ตฌ๋ฆฌ ์ „์„ ์ด๋‚˜ ์ž๋™์ฐจ ์ด‰๋งค ๋ณ€ํ™˜๊ธฐ(catalytic converter) ์ ˆ๋„์™€ ์œ ์‚ฌํ•˜๊ฒŒ, ์ƒํ’ˆ์˜ ๊ฐ€์น˜๊ฐ€ ๋†’์•„์งˆ์ˆ˜๋ก ๋ฒ”์ฃ„์˜ ํ‘œ์ ์ด ๋œ๋‹ค๋Š” ๊ฒฝ์ œํ•™์  ํ†ต์ฐฐ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.

๋ฒ„๋ฒˆ์˜ ์ •์ฒด์„ฑ์„ ๊ทœ์ •ํ•˜๋Š” ์—„๊ฒฉํ•œ ๊ทœ์น™: ํ’ˆ์งˆ์ธ๊ฐ€, ๋ณดํ˜ธ์ฃผ์˜์ธ๊ฐ€?

๋ฒ„๋ฒˆ์€ ๋‹จ์ˆœํ•œ ์œ„์Šคํ‚ค๊ฐ€ ์•„๋‹™๋‹ˆ๋‹ค. ๋ฏธ๊ตญ ์—ฐ๋ฐฉ ๊ทœ์ •์ง‘(Code of Federal Regulations, CFR) 27์žฅ 5.143์กฐ์— ๋”ฐ๋ฅด๋ฉด, โ€˜์ŠคํŠธ๋ ˆ์ดํŠธ ๋ฒ„๋ฒˆ ์œ„์Šคํ‚ค(straight bourbon whiskey)โ€˜๋กœ ๋ถˆ๋ฆฌ๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์—„๊ฒฉํ•œ ์กฐ๊ฑด์„ ์ถฉ์กฑํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค.

  1. 51% ์ด์ƒ์˜ ์˜ฅ์ˆ˜์ˆ˜(corn)๋กœ ๋งŒ๋“  ๋ฐœํšจ ๋งค์‹œ(fermented mash) ์‚ฌ์šฉ.
  2. ๋ฏธ๊ตญ์—์„œ ์ฆ๋ฅ˜.
  3. 160 ํ”„๋ฃจํ”„(proof, ์•Œ์ฝ”์˜ฌ 80%)๋ฅผ ๋„˜์ง€ ์•Š๊ฒŒ ์ฆ๋ฅ˜.
  4. ์ƒˆ๋กญ๊ฒŒ ํƒ„ํ™”(charred)๋œ ๋ฏธ๊ตญ์‚ฐ ์˜คํฌ ๋ฐฐ๋Ÿด(oak barrels)์— 125 ํ”„๋ฃจํ”„๋ฅผ ๋„˜์ง€ ์•Š๋Š” ์ƒํƒœ๋กœ ์ฃผ์ž….
  5. ์ตœ์†Œ 2๋…„ ์ด์ƒ ์ˆ™์„ฑ.

์ด๋Ÿฌํ•œ ๊ทœ์ •์€ ์Šค์นด์น˜ ์œ„์Šคํ‚ค๊ฐ€ ์Šค์ฝ”ํ‹€๋žœ๋“œ์—์„œ๋งŒ ์ƒ์‚ฐ๋˜๊ณ , ์ƒดํŽ˜์ธ(Champagne)์ด ํ”„๋ž‘์Šค ์ƒนํŒŒ๋‰ด ์ง€์—ญ์—์„œ๋งŒ ์ƒ์‚ฐ๋˜๋Š” ๊ฒƒ๊ณผ ์œ ์‚ฌํ•˜๊ฒŒ, 1964๋…„ ๋ฏธ๊ตญ ์˜ํšŒ๊ฐ€ ๋ฒ„๋ฒˆ์„ ๋ฏธ๊ตญ์˜ โ€˜ํŠน์ƒ‰ ์žˆ๋Š” ์ œํ’ˆ(distinctive product)โ€˜์œผ๋กœ ์„ ์–ธํ•˜๋ฉด์„œ ์ œ์ •๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

์‚ฌ์ œ๋ฝ(Sazerac)์˜ ๋งˆ์Šคํ„ฐ ๋””์Šคํ‹ธ๋Ÿฌ(master distiller) ๋Œ€๋‹ˆ ์นธ(Danny Kahn)์€ ์ด ๊ทœ์ •๋“ค์ด ๋ฒ„๋ฒˆ์˜ ๋…ํŠนํ•œ ํ’๋ฏธ๋ฅผ ํ˜•์„ฑํ•˜๋Š” ๋ฐ ํ•„์ˆ˜์ ์ด๋ผ๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค.

  • ์˜ฅ์ˆ˜์ˆ˜: ๋ฏธ๊ตญ ์„œ๋ถ€ ๊ฐœ์ฒ™์ž๋“ค์ด ํ˜ธ๋ฐ€(rye) ๋Œ€์‹  ํ’๋ถ€ํ•˜๊ฒŒ ๊ตฌํ•  ์ˆ˜ ์žˆ์—ˆ๋˜ ์˜ฅ์ˆ˜์ˆ˜๋Š” ์ „๋ถ„ ํ•จ๋Ÿ‰์ด ๋†’์•„ ์•Œ์ฝ”์˜ฌ ์ƒ์„ฑ์— ์œ ๋ฆฌํ•˜๋ฉฐ, ๊ธฐ๋ฆ„๊ณผ ๋‹ค๋ฅธ ์„ฑ๋ถ„์—์„œ ์—„์ฒญ๋‚œ ํ’๋ฏธ๋ฅผ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.
  • ๋ฏธ๊ตญ์‚ฐ: ์ƒ์‚ฐ ๊ณผ์ •์„ ํ†ต์ œํ•˜๊ณ  ๋ฒ•๋ฅ ์„ ์ ์šฉํ•˜๊ธฐ ์œ„ํ•จ์ž…๋‹ˆ๋‹ค.
  • ์ฆ๋ฅ˜๋„ ์ œํ•œ (160 ํ”„๋ฃจํ”„ ์ดํ•˜): ์นธ์€ ์ผ๋ฐ˜์ ์œผ๋กœ 135~140 ํ”„๋ฃจํ”„๋กœ ์ฆ๋ฅ˜ํ•˜์—ฌ ๋” ๋งŽ์€ ํ’๋ฏธ๋ฅผ ๋ณด์กดํ•œ๋‹ค๊ณ  ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ์ฆ๋ฅ˜๋„๊ฐ€ ๋‚ฎ์„์ˆ˜๋ก ์ˆ™์„ฑ ๊ณผ์ •์—์„œ ๋ง›์žˆ๋Š” ์œ„์Šคํ‚ค๋ฅผ ๋งŒ๋“œ๋Š” ์ „๊ตฌ์ฒด(precursors)๊ฐ€ ๋˜๋Š” ๋‹ค์–‘ํ•œ ํ’๋ฏธ๊ฐ€ ์œ ์ง€๋˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
  • ์ƒˆ ํƒ„ํ™” ์˜คํฌ ๋ฐฐ๋Ÿด: ์ด ๋ถ€๋ถ„์ด ๋ฒ„๋ฒˆ์˜ ๊ฐ€์žฅ ํฐ ํŠน์ง• ์ค‘ ํ•˜๋‚˜์ž…๋‹ˆ๋‹ค. ๋ฐฐ๋Ÿด ์ œ์ž‘ ๊ณผ์ •์€ ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค.
    • ๋‚˜๋ฌด ๋ฒŒ๋ชฉ ๋ฐ ๊ฑด์กฐ(Seasoning): ์ฐธ๋‚˜๋ฌด๋ฅผ ์ผœ์„œ ๋งŒ๋“  ๋ฐฐ๋Ÿด ํŒ์žฌ(staves)๋ฅผ 1๋…„ ๊ฐ€๊นŒ์ด ์•ผ์™ธ์— ์Œ“์•„๋‘์–ด ๋น—๋ฌผ๋กœ ํƒ„๋‹Œ(tannins) ๋“ฑ ํŠน์ • ์„ฑ๋ถ„์„ ์”ป์–ด๋‚ด๊ณ , ๋ฏธ์ƒ๋ฌผ ํ™œ๋™์œผ๋กœ ๋‚˜๋ฌด ์† ์„ฑ๋ถ„๋“ค์„ ๋ถ„ํ•ด์‹œ์ผœ ๋‚˜์ค‘์— ์ค‘์š”ํ•œ ํ’๋ฏธ๋ฅผ ํ˜•์„ฑํ•˜๋„๋ก ํ•ฉ๋‹ˆ๋‹ค.
    • ๋ฐฐ๋Ÿด ์ œ์ž‘ ๋ฐ ํƒ„ํ™”(Charring): ํŒ์žฌ๋ฅผ ์—ฎ์–ด ๋ฐฐ๋Ÿด์„ ๋งŒ๋“  ํ›„, ๋‚ด๋ถ€๋ฅผ ์ฒœ์—ฐ๊ฐ€์Šค ๋ถˆ๊ฝƒ์œผ๋กœ ์•ฝ 30์ดˆ๊ฐ„ ์ง์ ‘ ๊ฐ€์—ดํ•˜์—ฌ ํƒ„ํ™”์‹œํ‚ต๋‹ˆ๋‹ค. ์ด ํƒ„ํ™”์ธต์€ ๋ถˆ์ˆœ๋ฌผ์„ ํก์ˆ˜ํ•˜๊ณ , ๊ทธ ์•„๋ž˜ ์กฐ๋ฆฌ๋œ(cooked) ๋‚˜๋ฌด์ธต์—์„œ๋Š” ํ—ค๋ฏธ์…€๋ฃฐ๋กœ์Šค(hemicellulose)์—์„œ ์นด๋ผ๋ฉœ, ๋ฒ„ํ„ฐ์Šค์นด์น˜ ํ’๋ฏธ๋ฅผ, ๋ฆฌ๊ทธ๋‹Œ(lignins)์—์„œ ๊ตฌ์šด ํ–ฅ์‹ ๋ฃŒ, ์œก๋‘๊ตฌ, ๋ฐ”๋‹๋ผ, ๊ณ„ํ”ผ ํ’๋ฏธ๋ฅผ, ๊ทธ๋ฆฌ๊ณ  ํƒ„๋‹Œ์—์„œ ๋ฐ”๋””๊ฐ(mouthfeel)๊ณผ ์ƒ‰์ƒ์„ ์–ป๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
  • ์ฃผ์ž… ํ”„๋ฃจํ”„ ์ œํ•œ (125 ํ”„๋ฃจํ”„ ์ดํ•˜): ์•Œ์ฝ”์˜ฌ ๋†๋„์— ๋”ฐ๋ผ ๋‚˜๋ฌด์—์„œ ์ถ”์ถœ๋˜๋Š” ์„ฑ๋ถ„์ด ๋‹ฌ๋ผ์ง€๋ฏ€๋กœ, ์›ํ•˜๋Š” ํ’๋ฏธ๋ฅผ ์–ป๊ธฐ ์œ„ํ•œ ์ค‘์š”ํ•œ ์กฐ์ ˆ ์š”์†Œ์ž…๋‹ˆ๋‹ค.

ํ•˜์ง€๋งŒ ํ…Œ๋„ค์‹œ ๋Œ€ํ•™๊ต ๋†์—…๊ฒฝ์ œํ•™์ž ์•ค๋“œ๋ฅ˜ ๋ฌดํ•˜๋งˆ๋“œ(Andrew Muhammad)๋Š” ์ด๋Ÿฌํ•œ โ€˜์ƒˆ ํƒ„ํ™” ์˜คํฌ ๋ฐฐ๋Ÿดโ€™ ๊ทœ์ •์— ๋Œ€ํ•ด โ€œ์ƒ๋‹นํžˆ ํŽธ๋ฆฌํ•œ ๋งˆ์ผ€ํŒ…โ€์ด๋ผ๊ณ  ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. ์ผ„ํ„ฐํ‚ค์™€ ํ…Œ๋„ค์‹œ์—์„œ ์‚ฌ์šฉ๋œ ๋ฒ„๋ฒˆ ๋ฐฐ๋Ÿด์€ ์บ๋‚˜๋‹ค ์œ„์Šคํ‚ค, ์•„์ด๋ฆฌ์‹œ ์œ„์Šคํ‚ค, ์Šค์นด์น˜ ์œ„์Šคํ‚ค, ์‹ฌ์ง€์–ด ๊ณ ๊ฐ€์˜ ์ผ๋ณธ ์œ„์Šคํ‚ค ์ƒ์‚ฐ์— ์žฌ์‚ฌ์šฉ๋˜๋ฉฐ ํ›Œ๋ฅญํ•œ ํ’ˆ์งˆ์„ ๋งŒ๋“ค์–ด๋‚ด๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Š” ๋ฒ„๋ฒˆ ๊ทœ์ •์ด ํ’ˆ์งˆ ํ–ฅ์ƒ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ธฐ์กด ์ฆ๋ฅ˜์†Œ๋“ค์˜ ์ด์ต์„ ๋ณดํ˜ธํ•˜๊ธฐ ์œ„ํ•œ ์ผ์ข…์˜ โ€˜์†Œํ”„ํŠธํ•œ ๋ณดํ˜ธ์ฃผ์˜(soft protectionism)โ€™ ์ธก๋ฉด๋„ ์žˆ๋‹ค๊ณ  ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค.

ํ™ฉํ™€๊ฒฝ ๋’ค ์ฐพ์•„์˜จ ์ˆ™์ทจ: ๋ฒ„๋ฒˆ ์‚ฐ์—…์˜ ํ˜„์žฌ ์œ„๊ธฐ

2012๋…„๋ถ€ํ„ฐ 2022๋…„๊นŒ์ง€ ๋ฒ„๋ฒˆ ์‚ฐ์—…์€ ์ „๋ก€ ์—†๋Š” ํ˜ธํ™ฉ์„ ๋ˆ„๋ ธ์Šต๋‹ˆ๋‹ค. ์ผ„ํ„ฐํ‚ค๋Œ€ํ•™๊ต ๊ฐœํŠผ ๊ฒฝ์˜๊ฒฝ์ œ๋Œ€ํ•™(Gatton College of Business and Economics)์˜ ๋ธŒ๋ž˜๋“œ ํŒจํŠธ๋ฆญ(Brad Patrick) ๊ต์ˆ˜๋Š” โ€œ์‚ฌ๋žŒ๋“ค์ด ์‚ฐ์—…์— ๋›ฐ์–ด๋“ค์–ด ๋ชจ๋“  ๊ฒƒ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋งŒ๋“ค์—ˆ๋‹คโ€๊ณ  ํšŒ์ƒํ•ฉ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ด์ œ ๋ฒ„๋ฒˆ ์‚ฐ์—…์€ โ€˜๋ฒฝ์— ๋ถ€๋”ชํ˜”๋‹ค(bumped into a wall)โ€˜๊ณ  ์ง„๋‹จํ•ฉ๋‹ˆ๋‹ค. ์›”์ŠคํŠธ๋ฆฌํŠธ์ €๋„(Wall Street Journal)์€ โ€œ๋ฏธ๊ตญ์˜ ๋ฒ„๋ฒˆ ๋ถ์€ ๋๋‚ฌ๋‹ค. ์ด์ œ ์ˆ™์ทจ๊ฐ€ ์ฐพ์•„์™”๋‹คโ€๋Š” ํ—ค๋“œ๋ผ์ธ์œผ๋กœ ์ด ์ƒํ™ฉ์„ ๋ณด๋„ํ–ˆ์Šต๋‹ˆ๋‹ค.

ํ˜„์žฌ ๋ฒ„๋ฒˆ ์‚ฐ์—…์€ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๋ณตํ•ฉ์ ์ธ ๋ฌธ์ œ์— ์ง๋ฉดํ•ด ์žˆ์Šต๋‹ˆ๋‹ค.

  • ์ˆ˜์š” ๊ฐ์†Œ: 2022๋…„ ์ดํ›„ ๋ฒ„๋ฒˆ ์ˆ˜์š”๊ฐ€ ๊ฐ์†Œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
    • Gen Z์˜ ์ทจํ–ฅ ๋ณ€ํ™”: ์ Š์€ ์†Œ๋น„์ž๋“ค์ด โ€˜ํ• ์•„๋ฒ„์ง€์˜ ์˜ค๋ž˜๋œ ๊ฐˆ์ƒ‰ ์ˆ (grandpaโ€™s old brown drink)โ€™ ๋Œ€์‹  RTD(Ready-To-Drink, ์ฆ‰์„ ์Œ๋ฃŒ) ์นตํ…Œ์ผ์ด๋‚˜ ๋ฌด์•Œ์ฝ”์˜ฌ ์Œ๋ฃŒ, ๋˜๋Š” ํ™”์ดํŠธ ์Šคํ”ผ๋ฆฟ(white spirits)์„ ์„ ํ˜ธํ•ฉ๋‹ˆ๋‹ค. RTD ์‹œ์žฅ์€ 20% ์ด์ƒ์˜ ์„ฑ์žฅ๋ฅ ์„ ๋ณด์ด๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
    • ๊ฑด๊ฐ• ๋ฌธ์ œ: ์ „๋ฐ˜์ ์ธ ์Œ์ฃผ๋Ÿ‰ ๊ฐ์†Œ ์ถ”์„ธ์™€ ๊ฑด๊ฐ•์— ๋Œ€ํ•œ ๊ด€์‹ฌ ์ฆ๊ฐ€.
    • ๊ฐ€๊ฒฉ ํ”ผ๋กœ ๋ฐ ๊ณผ๋„ํ•œ ๋‹ค์–‘์„ฑ: 800~1,000๊ฐœ์— ๋‹ฌํ•˜๋Š” SKU(Stock Keeping Unit)๋Š” ์†Œ๋น„์ž์—๊ฒŒ ๋„ˆ๋ฌด ๋งŽ์€ ์„ ํƒ์ง€๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ, ๊ณ ๊ฐ€ ๋ฒ„๋ฒˆ์— ๋Œ€ํ•œ ๊ฐ€๊ฒฉ ํ”ผ๋กœ๊ฐ๋„ ์กด์žฌํ•ฉ๋‹ˆ๋‹ค.
  • ๊ณต๊ธ‰ ๊ณผ์ž‰: ์ˆ˜์š” ๊ฐ์†Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์ˆ™์„ฑ ์ค‘์ธ 1600๋งŒ ๋ฐฐ๋Ÿด์˜ ๋ฒ„๋ฒˆ์€ ๊ณผ์ž‰ ๊ณต๊ธ‰ ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ•ฉ๋‹ˆ๋‹ค. ์ตœ๋Œ€ ๋ฒ„๋ฒˆ ์ƒ์‚ฐ์ž์ธ ์ง๋น”(Jim Beam)์€ ์ฃผ๋ ฅ ์ฆ๋ฅ˜์†Œ์˜ ์ƒ์‚ฐ์„ 1๋…„๊ฐ„ ์ค‘๋‹จํ•œ๋‹ค๊ณ  ๋ฐœํ‘œํ–ˆ์œผ๋ฉฐ, ๋‹ค๋ฅธ ๋Œ€ํ˜• ์ƒ์‚ฐ์ž๋“ค์—์„œ๋„ ์ •๋ฆฌํ•ด๊ณ ์™€ ํ†ตํํ•ฉ์ด ์ง„ํ–‰๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
  • ๊ด€์„ธ ๋ฌธ์ œ: ๋„๋„๋“œ ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€์˜ ๋ฌด์—ญ ์ „์Ÿ ๋‹น์‹œ, EU๋Š” ๋ฏธ๊ตญ์‚ฐ ์ฒ ๊ฐ• ๋ฐ ์•Œ๋ฃจ๋ฏธ๋Š„ ๊ด€์„ธ์— ๋Œ€ํ•œ ๋ณด๋ณต์œผ๋กœ ๋ฏธ๊ตญ ์œ„์Šคํ‚ค(ํ…Œ๋„ค์‹œ ์œ„์Šคํ‚ค ๋ฐ ์ผ„ํ„ฐํ‚ค ๋ฒ„๋ฒˆ ํฌํ•จ)์— 25%์˜ ๋ณด๋ณต ๊ด€์„ธ๋ฅผ ๋ถ€๊ณผํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋กœ ์ธํ•ด ํ•ด์™ธ ์‹œ์žฅ ๊ฐœ์ฒ™์— ์–ด๋ ค์›€์„ ๊ฒช๊ณ  ์žˆ์œผ๋ฉฐ, ํŠนํžˆ ์บ๋‚˜๋‹ค๋Š” ๋ฏธ๊ตญ์‚ฐ ์ฃผ๋ฅ˜ ์ œํ’ˆ์„ ์„ ๋ฐ˜์—์„œ ์น˜์šฐ๋Š” ๋ฐฉ์‹์œผ๋กœ ๋Œ€์‘ํ•˜๊ธฐ๋„ ํ–ˆ์Šต๋‹ˆ๋‹ค.
  • ๋ฐฐ๋Ÿด์„ธ(Barrel Tax): ์ผ„ํ„ฐํ‚ค ์ฃผ๋Š” ์ˆ˜์‹ญ ๋…„๊ฐ„ ์ˆ™์„ฑ ์ค‘์ธ ๋ฒ„๋ฒˆ์— ๋Œ€ํ•ด ์—ฐ๊ฐ„ ์„ธ๊ธˆ์„ ๋ถ€๊ณผํ•ด์™”์Šต๋‹ˆ๋‹ค. 2025๋…„ ๋ฒ„๋ฒˆ ์ฆ๋ฅ˜์†Œ๋“ค์€ 7500๋งŒ ๋‹ฌ๋Ÿฌ๋ฅผ ๋ฐฐ๋Ÿด์„ธ๋กœ ์ง€๋ถˆํ•  ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋˜์ง€๋งŒ, ์ด ์„ธ๊ธˆ์€ 2043๋…„๊นŒ์ง€ ๋‹จ๊ณ„์ ์œผ๋กœ ํ์ง€๋  ์˜ˆ์ •์ž…๋‹ˆ๋‹ค.

๋ฒ„๋ฒˆ ์‚ฐ์—…์˜ ๋ฏธ๋ž˜: ํŒŒ๊ดด์  ํ˜์‹ ์ธ๊ฐ€, ์ ์ง„์  ๋ณ€ํ™”์ธ๊ฐ€?

๋ธŒ๋ž˜๋“œ ํŒจํŠธ๋ฆญ ๊ต์ˆ˜๋Š” ์•ž์œผ๋กœ 5~10๋…„ ํ›„ ๋ฒ„๋ฒˆ ์‚ฐ์—…์€ โ€œ๊ณ ํ’ˆ์งˆ ๋ฒ„๋ฒˆ์ด ๋Œ€๋Ÿ‰์œผ๋กœ ์กด์žฌํ•  ๊ฒƒโ€์ด๋ผ๊ณ  ์˜ˆ์ธกํ•ฉ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ด ๋ฒ„๋ฒˆ์„ ์–ด๋–ป๊ฒŒ ์ฒ˜๋ฆฌํ•˜๊ณ  ํŒ๋งคํ•  ๊ฒƒ์ธ๊ฐ€๊ฐ€ ํ•ต์‹ฌ ๊ณผ์ œ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Š” ์Šค์นด์น˜ ์œ„์Šคํ‚ค ์‚ฐ์—…์ด 1980๋…„๋Œ€ ๊ณผ์ž‰ ์ƒ์‚ฐ์œผ๋กœ 140๊ฐœ ์ด์ƒ์˜ ์ฆ๋ฅ˜์†Œ์—์„œ 5๊ฐœ ์ฃผ์š” ์—…์ฒด๋กœ ํ†ตํ•ฉ๋œ ์‚ฌ๋ก€๋ฅผ ๋“ค๋ฉฐ, ๋ฒ„๋ฒˆ ์‚ฐ์—…์—์„œ๋„ โ€˜์ ์ ˆํ•œ ์‚ฌ์—…์ฒด ์ •๋ฆฌ(appropriate weeding out of businesses)โ€˜๊ฐ€ ์ผ์–ด๋‚  ๊ฒƒ์ด๋ผ๊ณ  ์ „๋งํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ ๋Œ€๊ทœ๋ชจ ๊ณ„์•ฝ ์ฆ๋ฅ˜ ์‚ฌ์—…์— ์˜์กดํ–ˆ๋˜ ์†Œ๊ทœ๋ชจ ์ฆ๋ฅ˜์†Œ๋“ค์ด ๊ฐ€์žฅ ํฐ ์–ด๋ ค์›€์— ์ง๋ฉดํ•  ๊ฒƒ์ด๋ฉฐ, ๊ฒฐ๊ตญ โ€˜๋ธŒ๋žœ๋“œ๋ฅผ ๊ฐ€์ง„ ์ฆ๋ฅ˜์†Œโ€™๋งŒ์ด ์‚ด์•„๋‚จ์„ ๊ฒƒ์ด๋ผ๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค.

๋ฒ„๋ฒˆ ์‚ฐ์—…์€ ์ด๋Ÿฌํ•œ ์œ„๊ธฐ๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์ „๋žต์„ ๋ชจ์ƒ‰ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

  • ํ•ด์™ธ ์‹œ์žฅ ๊ฐœ์ฒ™: ์ธ๋„์™€ ์ค‘๊ตญ ์‹œ์žฅ์€ ์—ฌ์ „ํžˆ ์ž ์žฌ๋ ฅ์ด ํฌ๋‹ค๊ณ  ํ‰๊ฐ€๋ฉ๋‹ˆ๋‹ค. ๊ด€์„ธ ๋ฌธ์ œ๊ฐ€ ํ•ด๊ฒฐ๋œ๋‹ค๋ฉด ์ƒˆ๋กœ์šด ๋ŒํŒŒ๊ตฌ๊ฐ€ ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
  • ๊ด€๊ด‘ ์‚ฐ์—… ํ™œ์„ฑํ™”: ์ผ„ํ„ฐํ‚ค์˜ โ€˜๋ฒ„๋ฒˆ ํŠธ๋ ˆ์ผ(Bourbon Trail)โ€™ ๊ด€๊ด‘์€ ๋งค์šฐ ์ธ๊ธฐ๊ฐ€ ๋งŽ์Šต๋‹ˆ๋‹ค. ์ฆ๋ฅ˜์†Œ๋“ค์€ ์ด๋ฅผ ๋ผ์ดํ”„์Šคํƒ€์ผ, ๋Ÿญ์…”๋ฆฌ ์ด๋ฒคํŠธ ๋“ฑ๊ณผ ์—ฐ๊ณ„ํ•˜์—ฌ ํ˜์‹ ์ ์ธ ๋งˆ์ผ€ํŒ…์„ ์‹œ๋„ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
  • RTD(Ready-To-Drink) ์‹œ์žฅ ์ง„์ถœ: ์‚ฌ์ œ๋ฝ์€ RTD ์ „๋ฌธ ๊ธฐ์—…์ธ โ€˜๋ฒ„์ฆˆ๋ณผ์ฆˆ(BuzzBallz)โ€˜๋ฅผ ์ธ์ˆ˜ํ•˜๋ฉฐ ๋น ๋ฅด๊ฒŒ ์„ฑ์žฅํ•˜๋Š” RTD ์‹œ์žฅ์— ๋›ฐ์–ด๋“ค์—ˆ์Šต๋‹ˆ๋‹ค. ํ™”๋ คํ•œ ์ƒ‰์ƒ๊ณผ ๋…ํŠนํ•œ ๋ชจ์–‘์˜ ์บ” ์นตํ…Œ์ผ์ธ ๋ฒ„์ฆˆ๋ณผ์ฆˆ๋Š” ์ Š์€ ์†Œ๋น„์ž์ธต๊ณผ ๊ตญ์ œ ์‹œ์žฅ์—์„œ ํฐ ์ธ๊ธฐ๋ฅผ ์–ป๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋Œ€๋‹ˆ ์นธ ๋งˆ์Šคํ„ฐ ๋””์Šคํ‹ธ๋Ÿฌ๋Š” โ€œ์•Œ์ฝ”์˜ฌ ์‹œ์žฅ ํŒŒ์ด ์ž์ฒด๊ฐ€ ํฌ๊ฒŒ ์„ฑ์žฅํ•˜์ง€ ์•Š๋Š” ์ƒํ™ฉ์—์„œ, ์šฐ๋ฆฌ๊ฐ€ ์ง„์ถœํ•˜์ง€ ์•Š์€ ์‹œ์žฅ์ด ์–ด๋””์ธ์ง€ ํŒŒ์•…ํ•˜๊ณ  ์ฐธ์—ฌํ•ด์•ผ ํ•œ๋‹คโ€๋ฉฐ ๋‹ค์–‘ํ•œ ์‹œ์žฅ ์„ธ๊ทธ๋จผํŠธ์˜ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค.

์ผ„ํ„ฐํ‚ค ๋ฒ„๋ฒˆ ์‚ฐ์—…์€ โ€˜์‹œ๊ฐ„โ€™์ด๋ผ๋Š” ์ „ํ†ต์ ์ธ ๊ฐ€์น˜์™€ โ€˜๋ณ€ํ™”โ€™๋ผ๋Š” ์ƒˆ๋กœ์šด ๋„์ „ ์‚ฌ์ด์—์„œ ๊ท ํ˜•์ ์„ ์ฐพ์•„์•ผ ํ•˜๋Š” ์‹œ๊ธฐ๋ฅผ ๋งž์ดํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ณผ์ž‰ ๊ณต๊ธ‰๊ณผ ์†Œ๋น„์ž ์ทจํ–ฅ ๋ณ€ํ™”๋ผ๋Š” โ€˜์ˆ™์ทจโ€™๋ฅผ ๊ทน๋ณตํ•˜๊ณ , ์ƒˆ๋กœ์šด ์‹œ์žฅ๊ณผ ํ˜์‹ ์ ์ธ ์ œํ’ˆ์œผ๋กœ โ€˜์ฐฝ์กฐ์  ํŒŒ๊ดด(creative destruction)โ€˜์˜ ๊ธฐํšŒ๋ฅผ ๋งŒ๋“ค์–ด๋‚ผ ์ˆ˜ ์žˆ์„์ง€ ์ „ ์„ธ๊ณ„๊ฐ€ ์ฃผ๋ชฉํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.


โ€œAI for Atoms: How Periodic Labs is Revolutionizing Materials Engineering with Co-Founder Liam Fedusโ€ โ€” No Priors: AI, Machine Learning, Tech, & Startups ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

์ฑ—GPT๋ฅผ ๋„˜์–ด ์›์ž์˜ ์‹œ๋Œ€๋กœ: ๋ฆฌ์•” ํŽ˜๋”์Šค, AI๋กœ ๋ฌผ์งˆ ๊ณตํ•™ ํ˜์‹ ์„ ๊ฟˆ๊พธ๋‹ค

์ธ๊ณต์ง€๋Šฅ(AI)์ด ๋””์ง€ํ„ธ ์„ธ๊ณ„๋ฅผ ๋„˜์–ด ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„๋กœ ๊ทธ ์˜ํ–ฅ๋ ฅ์„ ํ™•์žฅํ•˜๋ฉฐ ์ƒˆ๋กœ์šด ํ˜๋ช…์˜ ๋ฌผ๊ฒฐ์„ ์˜ˆ๊ณ ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ฑ—GPT(ChatGPT)์˜ ๊ณต๋™ ์ฐฝ๋ฆฝ์ž์ด์ž ์˜คํ”ˆAI(OpenAI)์˜ ์ „ ๋ถ€์‚ฌ์žฅ์ธ ๋ฆฌ์•” ํŽ˜๋”์Šค(Liam Fedus)๋Š” ์ด๋Ÿฌํ•œ ๋ณ€ํ™”์˜ ์ตœ์ „์„ ์—์„œ โ€˜์›์ž๋ฅผ ์œ„ํ•œ AI ํŒŒ์šด๋ฐ์ด์…˜ ๋žฉโ€™์ธ ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค(Periodic Labs)๋ฅผ ์ด๋Œ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ์˜ ๋ชฉํ‘œ๋Š” AI๋ฅผ ํ™œ์šฉํ•ด ์žฌ๋ฃŒ ๊ณผํ•™, ํ™”ํ•™ ๋“ฑ ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„์˜ ๋‚œ์ œ๋“ค์„ ํ•ด๊ฒฐํ•˜๊ณ  ์ธ๋ฅ˜์˜ ๋ฌผ์งˆ์  ๋ฐœ์ „์„ ๊ฐ€์†ํ™”ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

์ตœ๊ทผ ํŒŸ์บ์ŠคํŠธ โ€˜๋…ธ ํ”„๋ผ์ด์–ด์Šค(No Priors)โ€˜์— ์ถœ์—ฐํ•œ ํŽ˜๋”์Šค CEO๋Š” ์ž์‹ ์˜ ๋…ํŠนํ•œ ์—ฌ์ •๊ณผ ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค์˜ ๋น„์ „์„ ๊ณต์œ ํ•˜๋ฉฐ, AI๊ฐ€ ๋ฌผ์งˆ ๊ณตํ•™ ๋ถ„์•ผ์— ๊ฐ€์ ธ์˜ฌ ํ˜์‹ ์ ์ธ ๋ณ€ํ™”์— ๋Œ€ํ•œ ๊นŠ์ด ์žˆ๋Š” ํ†ต์ฐฐ์„ ์ œ์‹œํ–ˆ์Šต๋‹ˆ๋‹ค.

์ฑ—GPT๋ฅผ ํƒ„์ƒ์‹œํ‚จ ์ฃผ์—ญ์—์„œ ์›์ž์˜ ์„ธ๊ณ„๋กœ

๋ฆฌ์•” ํŽ˜๋”์Šค CEO์˜ ๊ฒฝ๋ ฅ์€ AI ๋ถ„์•ผ์˜ ์ฃผ์š” ๋ณ€๊ณก์ ๋“ค๊ณผ ๊ถค๋ฅผ ๊ฐ™์ดํ•ฉ๋‹ˆ๋‹ค. ํ•™๋ถ€ ์‹œ์ ˆ ๋ฌผ๋ฆฌํ•™์„ ์ „๊ณตํ•˜๋ฉฐ ์•”ํ‘ ๋ฌผ์งˆ(Dark Matter) ์—ฐ๊ตฌ์— ๋งค์ง„ํ–ˆ๋˜ ๊ทธ๋Š”, ๋‹น์‹œ ๋ฌผ๋ฆฌํ•™๊ณ„์— ๋งŒ์—ฐํ–ˆ๋˜ โ€˜๋‹ค์Œ ํ˜๋ช…์€ ๋ฌด์—‡์ธ๊ฐ€โ€™๋ผ๋Š” ์งˆ๋ฌธ์— ๋‹ต์„ ์ฐพ์•„ AI๋กœ ๋ˆˆ์„ ๋Œ๋ ธ์Šต๋‹ˆ๋‹ค. โ€œ๋ฌผ๋ฆฌํ•™์ž๋“ค์€ ์„ธ์ƒ์„ ์›๋ฆฌ์ ์œผ๋กœ, ๋งค์šฐ ์‹ ์ค‘ํ•˜๊ฒŒ ์‚ฌ๊ณ ํ•˜๋Š” ๋ฐ ์ต์ˆ™ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์‚ฌ๊ณ ๋ฐฉ์‹์ด ์ปดํ“จํ„ฐ ๊ณผํ•™, ํŠนํžˆ AI ๋ถ„์•ผ์—์„œ ์—„์ฒญ๋‚œ ๋ ˆ๋ฒ„๋ฆฌ์ง€(Leverage)๋ฅผ ๊ฐ€์งˆ ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋ดค์Šต๋‹ˆ๋‹ค.โ€ ๊ทธ๋Š” ํŠนํžˆ ํž‰์Šค ์ž…์ž(Higgs Boson) ๋ฐœ๊ฒฌ ์ดํ›„, ๋งŽ์€ ๊ณ ์—๋„ˆ์ง€ ๋ฌผ๋ฆฌํ•™์ž๋“ค์ด AI ๋ถ„์•ผ์—์„œ ์ƒˆ๋กœ์šด ๋ŒํŒŒ๊ตฌ๋ฅผ ์ฐพ๊ณ  ์žˆ์—ˆ๋‹ค๊ณ  ํšŒ์ƒํ•ฉ๋‹ˆ๋‹ค.

๋Œ€ํ•™์› ์‹œ์ ˆ๋ถ€ํ„ฐ ๋จธ์‹ ๋Ÿฌ๋‹ ๋ฌธ์ œ์— ๋งค๋ฃŒ๋˜์—ˆ๋˜ ํŽ˜๋”์Šค CEO๋Š” ๊ฒฐ๊ตญ ๊ตฌ๊ธ€ ๋ธŒ๋ ˆ์ธ(Google Brain)์— ํ•ฉ๋ฅ˜ํ•˜๋ฉฐ AI ์—ฐ๊ตฌ์˜ ์ตœ์ „์„ ์— ์„œ๊ฒŒ ๋ฉ๋‹ˆ๋‹ค. 2016-2017๋…„์€ ๊ตฌ๊ธ€ ๋ธŒ๋ ˆ์ธ์˜ ํ™ฉ๊ธˆ๊ธฐ์˜€์Šต๋‹ˆ๋‹ค. ๋ถ„์‚ฐ ํ•™์Šต(Distributed Training) ์ „๋žต, ์ „๋ฌธ๊ฐ€ ํ˜ผํ•ฉ(Mixture of Experts), ํŠธ๋žœ์Šคํฌ๋จธ(Transformer) ์•„ํ‚คํ…์ฒ˜ ๋“ฑ ํ˜„๋Œ€ AI์˜ ๊ธฐ๋ฐ˜์„ ๋‹ค์ง€๋Š” ํ˜์‹ ๋“ค์ด ์Ÿ์•„์ ธ ๋‚˜์˜ค๋˜ ์‹œ๊ธฐ์˜€์ฃ . ๊ทธ๋Š” ๋‹น์‹œ๋ฅผ โ€œ์บ ๋ธŒ๋ฆฌ์•„๊ธฐ(Cambrian era)์™€ ๊ฐ™์•˜๋‹คโ€๊ณ  ํ‘œํ˜„ํ•˜๋ฉฐ, ์†Œ์ˆ˜์˜ GPU์™€ ์—ฐ๊ตฌ์ž๋“ค์ด ํ˜‘๋ ฅํ•˜์—ฌ ์—ฐ๊ตฌ์˜ ๋‹ค์–‘์„ฑ๊ณผ ์—”ํŠธ๋กœํ”ผ๋ฅผ ๊ทน๋Œ€ํ™”ํ–ˆ๋˜ ์ฆ๊ฑฐ์šด ๊ฒฝํ—˜์„ ํšŒ์ƒํ–ˆ์Šต๋‹ˆ๋‹ค.

์ดํ›„ ์˜คํ”ˆAI๋กœ ์ž๋ฆฌ๋ฅผ ์˜ฎ๊ธด ๊ทธ๋Š” GPT-4(Generative Pre-trained Transformer 4)์˜ ์ƒ์šฉํ™”(Productionization)์— ํ•ต์‹ฌ์ ์ธ ์—ญํ• ์„ ๋‹ด๋‹นํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‹น์‹œ ํšŒ์˜์—์„œ ์กด ์А๋งŒ(John Schulman)์€ โ€œ๋งค์šฐ ์ผ๋ฐ˜์ ์ธ ์ฑ—๋ด‡์„ ๋งŒ๋“ค์žโ€๋Š” ์˜๊ฒฌ์„ ๊ฐ•๋ ฅํ•˜๊ฒŒ ์ฃผ์žฅํ–ˆ๊ณ , ์ด๋Š” ์ฑ—GPT ํƒ„์ƒ์˜ ๊ฒฐ์ •์ ์ธ ๊ณ„๊ธฐ๊ฐ€ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์ฑ—GPT์˜ ๋“ฑ์žฅ์€ ๋Œ€์ค‘์—๊ฒŒ AI ํ˜๋ช…์˜ ์‹œ์ž‘์„ ์•Œ๋ฆฌ๋Š” ์‹ ํ˜ธํƒ„์ด ๋˜์—ˆ๊ณ , ํŽ˜๋”์Šค CEO๋Š” ์ด ๊ฑฐ๋Œ€ํ•œ ํ๋ฆ„์˜ ์ค‘์‹ฌ์— ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.

์–ธ์–ด๋ฅผ ๋„˜์–ด ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„๋กœ: ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค์˜ ๋น„์ „

์ฑ—GPT์˜ ์„ฑ๊ณต ์ดํ›„, ํŽ˜๋”์Šค CEO๋Š” ์™œ ๋‹ค์‹œ ๋ฌผ์งˆ๊ณผ ์›์ž์˜ ์„ธ๊ณ„๋กœ ๋Œ์•„์™”์„๊นŒ์š”? ๊ทธ๋Š” โ€œ์ด๋Ÿฌํ•œ ์‹œ์Šคํ…œ์„ ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„์™€ ์—ฐ๊ฒฐํ•˜๋Š” ๊ฒƒ์€ ํ•„์—ฐ์ โ€์ด๋ผ๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ๊ณผํ•™์€ ๋‹จ์ˆœํžˆ ๋ฐฉ์— ์•‰์•„ ๊นŠ์ด ์ƒ๊ฐํ•˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•˜๊ณ , ํ˜„์‹ค๊ณผ ์ƒํ˜ธ์ž‘์šฉํ•˜๋ฉฐ ๋ฐฐ์›Œ์•ผ ํ•œ๋‹ค๋Š” ์‹ ๋… ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. 2022๋…„ ๋‹น์‹œ ์ฑ—GPT ์ˆ˜์ค€์˜ ๊ธฐ์ˆ ๋กœ๋Š” ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค์™€ ๊ฐ™์€ ์‹œ๋„๋ฅผ ํ•˜๊ธฐ์— ์—ญ๋ถ€์กฑ์ด์—ˆ์ง€๋งŒ, ์ดํ›„ ๋ชจ๋ธ๋“ค์˜ ์ถ”๋ก  ๋Šฅ๋ ฅ, ์˜ค๋ฅ˜ ์ˆ˜์ •, ๋„๊ตฌ ์‚ฌ์šฉ ๋Šฅ๋ ฅ(์˜ˆ: ์ฝ”๋”ฉ ์—์ด์ „ํŠธ)์ด ๋น„์•ฝ์ ์œผ๋กœ ๋ฐœ์ „ํ•˜๋ฉด์„œ ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„์™€ AI๋ฅผ ์—ฐ๊ฒฐํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•ด์กŒ๋‹ค๊ณ  ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค.

ํ•˜์ง€๋งŒ ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„๋Š” ์–ธ์–ด ๋ชจ๋ธ์ฒ˜๋Ÿผ ์ธํ„ฐ๋„ท์ด๋ผ๋Š” ๊ฑฐ๋Œ€ํ•œ ๋ฐ์ดํ„ฐ ์ฝ”ํผ์Šค(Corpus)๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์ง€ ์•Š์Šต๋‹ˆ๋‹ค. ํŽ˜๋”์Šค CEO๋Š” ์ด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์‹œ๋ฎฌ๋ ˆ์ด์…˜(Simulation)๊ณผ ์‹ค์ œ ์‹คํ—˜ ๋ฐ์ดํ„ฐ๋ฅผ ๊ฒฐํ•ฉํ•˜๋Š” ์ „๋žต์„ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. AI ์‹œ์Šคํ…œ์€ ํ•™์Šต๋œ ๋ฐ์ดํ„ฐ์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ์ž‘๋™ํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ์‹ค์ œ ์„ธ๊ณ„์— ๋Œ€ํ•œ ์ •๋ณด ์—†์ด๋Š” ํ•œ๊ณ„์— ๋ถ€๋”ชํž ์ˆ˜๋ฐ–์— ์—†์Šต๋‹ˆ๋‹ค.

ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค๋Š” ์ฝ”๋“œ ์ƒ์„ฑ ๋“ฑ ์ผ๋ฐ˜์ ์ธ AI ๊ธฐ๋Šฅ์—์„œ๋Š” ์˜คํ”ˆ์†Œ์Šค ๋ชจ๋ธ(Open-source Models)์˜ ์ˆ˜์‹ญ์กฐ ๊ฐœ ํ† ํฐ(Tokens) ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ธฐ๋ณธ์ ์ธ ์ดํ•ด๋ฅผ ํ™•๋ณดํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํŠน์ • ๋ฌผ์งˆ ๋ฐœ๊ฒฌ ์˜์—ญ์—์„œ๋Š” ๊ธฐ์กด ๋ฌธํ—Œ ๋ฐ์ดํ„ฐ์˜ ํ•œ๊ณ„๋ฅผ ์ ˆ๊ฐํ–ˆ์Šต๋‹ˆ๋‹ค. ๋ฌธํ—Œ์— ๋ณด๊ณ ๋œ ๋ฌผ์งˆ ํŠน์„ฑ ๊ฐ’์ด ์ˆ˜์‹ญ ๋ฐฐ ์ด์ƒ ์ฐจ์ด ๋‚˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ํ—ˆ๋‹คํ–ˆ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ถˆํ™•์‹ค์„ฑ ์†์—์„œ๋Š” AI๊ฐ€ โ€˜์ง€์ƒ ์ง„์‹ค(Ground Truth)โ€˜์— ๋„๋‹ฌํ•˜๊ธฐ ์–ด๋ ต์Šต๋‹ˆ๋‹ค.

๋”ฐ๋ผ์„œ ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค๋Š” **์ƒํ˜ธ์ž‘์šฉ์  ํ์‡„ ๋ฃจํ”„ ์‹œ์Šคํ…œ(Interactive Closed-Loop System)**์„ ๊ตฌ์ถ•ํ•ฉ๋‹ˆ๋‹ค. AI๊ฐ€ ์‹คํ—˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„ํ•˜๊ณ , ์ด์ƒ ์ง•ํ›„๋‚˜ ํŒจํ„ด์„ ์ฐพ์•„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ ๋ฌธํ—Œ ๋ฐ์ดํ„ฐ์™€ ๋น„๊ตํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋‹ค์Œ ์‹คํ—˜์„ ์„ค๊ณ„ํ•˜๊ณ  ์‹คํ–‰ํ•˜๋Š” ๋Šฅ๋™์ ์ธ ๋ฐ์ดํ„ฐ ์ˆœํ™˜ ๊ตฌ์กฐ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๋‹จ์ˆœํžˆ ๋ฐ์ดํ„ฐ๋ฅผ ์Œ“๋Š” ๊ฒƒ์„ ๋„˜์–ด, AI๊ฐ€ ํ˜„์‹ค๊ณผ์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ํ†ตํ•ด ์Šค์Šค๋กœ ํ•™์Šตํ•˜๊ณ  ๊ฐœ์„ ํ•˜๋Š” ํ•ต์‹ฌ ๋ฉ”์ปค๋‹ˆ์ฆ˜์ด ๋ฉ๋‹ˆ๋‹ค.

์›์ž ์ง€๋Šฅ์˜ ์•„ํ‚คํ…์ฒ˜์™€ ์ƒ์—…ํ™” ์ „๋žต

ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค์˜ AI ์•„ํ‚คํ…์ฒ˜๋Š” ์–ธ์–ด ๋ชจ๋ธ์„ **์˜ค์ผ€์ŠคํŠธ๋ ˆ์ด์…˜ ๋ ˆ์ด์–ด(Orchestration Layer)**๋กœ ํ™œ์šฉํ•˜๋Š” ๊ฒƒ์ด ํŠน์ง•์ž…๋‹ˆ๋‹ค. ์–ธ์–ด ๋ชจ๋ธ์€ ์กฐ์ข…์‚ฌ(Co-pilot) ๋˜๋Š” ์กฐ์ˆ˜ ์—ญํ• ๋กœ์„œ ๋ฌธํ—Œ์„ ์ดํ•ดํ•˜๊ณ , ์‹คํ—˜ ๋ฐ์ดํ„ฐ๋ฅผ ๊ฒ€ํ† ํ•˜๋ฉฐ, ๋‹ค๋ฅธ ์ „๋ฌธํ™”๋œ ๋ชจ๋ธ๋“ค์„ ์ง€์‹œํ•˜๋Š” ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค. ์—ฌ๊ธฐ์— ์›์ž ์‹œ์Šคํ…œ์˜ ๋Œ€์นญ์„ฑ(Symmetry)์„ ์ธ์ง€ํ•˜๋„๋ก ํŠน๋ณ„ํžˆ ์„ค๊ณ„๋œ **์ „๋ฌธํ™”๋œ ์‹ ๊ฒฝ๋ง(Specialized Neural Networks)**์ด ๊ฒฐํ•ฉ๋ฉ๋‹ˆ๋‹ค. ์ด ์‹ ๊ฒฝ๋ง๋“ค์€ ํ›จ์”ฌ ๋‚ฎ์€ ์ง€์—ฐ ์‹œ๊ฐ„(Latency)์œผ๋กœ ์›์ž ์ˆ˜์ค€์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ์ •ํ™•ํ•˜๊ฒŒ ๋ชจ๋ธ๋งํ•˜๋ฉฐ, ์–ธ์–ด ๋ชจ๋ธ์˜ โ€˜๋„๊ตฌโ€™์ด์ž โ€˜๋ณด์ƒ ํ•จ์ˆ˜(Reward Function)โ€™ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ์ ‘๊ทผ ๋ฐฉ์‹์€ ๋ณต์žกํ•œ ๋ฌผ์งˆ ๊ณตํ•™ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐ ํ•„์ˆ˜์ ์ž…๋‹ˆ๋‹ค.

์ƒ์—…ํ™” ์ „๋žต์— ๋Œ€ํ•ด ํŽ˜๋”์Šค CEO๋Š” ์–ธ์–ด ๋ชจ๋ธ์ด ์ธ๊ฐ„ ์ƒํ˜ธ์ž‘์šฉ์˜ ๊ฑฐ๋Œ€ํ•œ ์˜์—ญ์„ ํฌ๊ด„ํ•˜๋Š” ๊ฒƒ๊ณผ ๋‹ฌ๋ฆฌ, ๋กœ๋ด‡ ๊ณตํ•™์ด๋‚˜ ์žฌ๋ฃŒ ๊ณผํ•™์€ ์•„์ง ์ดˆ๊ธฐ ๋‹จ๊ณ„๋ผ๊ณ  ์ธ์ •ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ทธ๋Š” ๋ฌผ์งˆ ๊ณตํ•™ ๋ฐ ๊ณต์ • ๊ณตํ•™์—์„œ ๋ณ‘๋ชฉ ํ˜„์ƒ์„ ๊ฒช๋Š” ๋ชจ๋“  ์‚ฐ์—…์—์„œ ์—„์ฒญ๋‚œ ๊ธฐํšŒ๋ฅผ ๋ณด๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค๋Š” ์šฐ์„  ์Šค์Šค๋กœ๋ฅผ โ€œ๊ณ ๊ฐ ์ œ๋กœ(Customer Zero)โ€œ๋กœ ์‚ผ์•„ ๊ณผํ•™ ์—ฐ๊ตฌ ๋ฐฉ์‹์„ ํ˜์‹ ํ•˜๋Š” ๋ฐ ์ง‘์ค‘ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ถ๊ทน์ ์œผ๋กœ๋Š” ์ด๋Ÿฌํ•œ ํšŒ์‚ฌ๋“ค์„ ์œ„ํ•œ **์ง€๋Šฅํ˜• ๋ ˆ์ด์–ด(Intelligence Layer)**๊ฐ€ ๋˜์–ด, ๊ธฐ๋ก ์‹œ์Šคํ…œ(System of Record)๊ณผ ์ œ์–ด ์‹œ์Šคํ…œ(Control Plane) ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๋ฉฐ ์†”๋ฃจ์…˜์„ ์ œ๊ณตํ•˜๋Š” ์†Œํ”„ํŠธ์›จ์–ด ๋น„์ฆˆ๋‹ˆ์Šค๋ฅผ ์ง€ํ–ฅํ•ฉ๋‹ˆ๋‹ค. ์žฅ๊ธฐ์ ์œผ๋กœ๋Š” ๋ฐ”์ด์˜คํ…Œํฌ(Biotech)์˜ ์‹ ์•ฝ ๊ฐœ๋ฐœ ๋ชจ๋ธ์ฒ˜๋Ÿผ, ํ˜์‹ ์ ์ธ ๋ฌผ์งˆ ๋ฐœ๊ฒฌ์„ ํ†ตํ•ด ๋†’์€ ๊ฐ€์น˜๋ฅผ ์ฐฝ์ถœํ•˜๋Š” ๋ชจ๋ธ๋„ ๊ณ ๋ คํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

10๋…„ ํ›„์˜ ์„ธ์ƒ: ๋ฌผ์งˆ ์ƒ์„ฑ AI๊ฐ€ ์—ด์–ด๊ฐˆ ๋ฏธ๋ž˜

ํŽ˜๋”์Šค CEO๋Š” ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค๊ฐ€ ์„ฑ๊ณตํ•œ๋‹ค๋ฉด 10๋…„ ํ›„ ์„ธ์ƒ์€ ๊ทน์ ์œผ๋กœ ๋ณ€ํ•  ๊ฒƒ์ด๋ผ๊ณ  ์˜ˆ์ธกํ•ฉ๋‹ˆ๋‹ค. โ€œ๋” ์ด์ƒ ๋‹จ์ˆœํžˆ ์—์„ธ์ด๋‚˜ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ์ž‘์„ฑํ•˜๋Š” ์‹œ์Šคํ…œ์„ ๋„˜์–ด, ๋ฌธ์ž ๊ทธ๋Œ€๋กœ ๋ฌผ์งˆ(Matter)์„ ์ƒ์„ฑํ•˜๋Š” ์‹œ์Šคํ…œ์œผ๋กœ ๋‚˜์•„๊ฐ€๋Š” ๊ฒƒโ€์ด๋ผ๊ณ  ๊ทธ๋Š” ๋งํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋ฐ˜๋„์ฒด, ํ•ญ๊ณต์šฐ์ฃผ, ์—๋„ˆ์ง€ ๋“ฑ ํ•ต์‹ฌ ์‚ฐ์—…์— ์ง€๋Œ€ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น  ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๋””์ง€ํ„ธ ์˜์—ญ์ด 6๊ฐœ์›” ์ „๊ณผ๋„ ํ™•์—ฐํžˆ ๋‹ค๋ฅผ ์ •๋„๋กœ ๋น ๋ฅด๊ฒŒ ๋ณ€ํ™”ํ•˜๋Š” ๊ฒƒ์ฒ˜๋Ÿผ, ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„์—์„œ๋„ ์œ ์‚ฌํ•œ ๊ฐ€์†ํ™”๋ฅผ ๊ธฐ๋Œ€ํ•ฉ๋‹ˆ๋‹ค. ๋ฌผ๋ก  ์›์ž๋Š” ๋‹ค๋ฃจ๊ธฐ ์–ด๋ ต์ง€๋งŒ, ๋ฐฉ๋Œ€ํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ํ•ด์„ํ•˜๊ณ  ์†”๋ฃจ์…˜์— ๋„๋‹ฌํ•˜๋Š” ์†๋„๋ฅผ 1~2๋‹จ๊ณ„ ๋†’์ด๋Š” ๊ฒƒ์€ ์ถฉ๋ถ„ํžˆ ๊ฐ€๋Šฅํ•˜๋‹ค๊ณ  ๋ด…๋‹ˆ๋‹ค. ๊ถ๊ทน์ ์œผ๋กœ ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค๋Š” ์ธ๋ฅ˜์—๊ฒŒ โ€œ์›์ž ์žฌ๋ฐฐ์—ด(Atomic Rearrangement) ๋ฐ ํ•ฉ์„ฑ(Synthesis)์— ๋Œ€ํ•œ ์ฃผ์ฒด์„ฑ(Agency)โ€œ์„ ๋ถ€์—ฌํ•˜์—ฌ ์—„์ฒญ๋‚œ ๊ฐ€์†์„ ๊ฐ€์ ธ์˜ฌ ๊ฒƒ์ด๋ผ๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋งˆ์น˜ ๋†์—… ํ˜๋ช…์ด ์ธ๋ฅ˜์˜ ์ƒ์‚ฐ์„ฑ์„ ํญ๋ฐœ์ ์œผ๋กœ ์ฆ๊ฐ€์‹œ์ผฐ๋˜ ๊ฒƒ์ฒ˜๋Ÿผ, ๋ฌผ์งˆ ๊ณตํ•™ ๋ถ„์•ผ์— ๋น„๊ฒฌํ•  ๋งŒํ•œ ํ˜๋ช…์„ ๊ฐ€์ ธ์˜ฌ ์ž ์žฌ๋ ฅ์„ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

๊ทธ๋Š” ๊ฐ€์žฅ ํฅ๋ถ„๋˜๋Š” ๋ถ€๋ถ„์œผ๋กœ **๋‹คํ•™์ œ ๊ฐ„ ํ˜‘๋ ฅ(Multi-disciplinary Collaboration)**์„ ๊ผฝ์Šต๋‹ˆ๋‹ค. ๋ฌผ๋ฆฌํ•™์ž, ํ™”ํ•™์ž, ์„ธ๊ณ„ ์ตœ๊ณ ์˜ AI ์—ฐ๊ตฌ์ž, ์—”์ง€๋‹ˆ์–ด๋“ค์ด ๊ธด๋ฐ€ํ•˜๊ฒŒ ํ˜‘๋ ฅํ•˜๋ฉฐ ์ˆ˜์‹ญ ๋…„๊ฐ„ ์ง€์†๋œ ๋ถ„์•ผ์˜ ์—ฐ๊ตฌ ๋ฐฉ์‹์ด ๊ทผ๋ณธ์ ์œผ๋กœ ๋ณ€ํ™”ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉ๊ฒฉํ•˜๋Š” ๊ฒƒ์€ ๋†€๋ผ์šด ๊ฒฝํ—˜์ด๋ผ๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๊ณผ๊ฑฐ ์†Œ์ˆ˜์˜ GPU๋กœ ์‹œ์ž‘ํ•ด ์ˆ˜์‹ญ๋งŒ ๋Œ€์˜ GPU์™€ ์Šค์ผ€์ผ๋ง ๋ฒ•์น™(Scaling Laws)์— ์˜ํ•ด ์‚ฐ์—…ํ™”๋œ ๋จธ์‹ ๋Ÿฌ๋‹ ๋ถ„์•ผ์˜ ๋ฐœ์ „ ๊ฒฝ๋กœ์™€ ์œ ์‚ฌํ•ฉ๋‹ˆ๋‹ค. ๋ฌผ๋ฆฌ ๊ณผํ•™ ๋ฐ ๊ณตํ•™ ๋˜ํ•œ ์ด์™€ ๊ฐ™์€ ์Šค์ผ€์ผ๋ง ํŠน์„ฑ์„ ํ™•๋ฆฝํ•˜๊ณ  ๋” ํฐ ๊ทœ๋ชจ์˜ ์‹คํ—˜๊ณผ ์ง€๋Šฅํ˜• ์‹œ์Šคํ…œ์„ ๊ฒฐํ•ฉํ•˜์—ฌ ํ˜„์žฌ ๊ณผํ•™์ž๋“ค์ด ๊ฐ๋‹นํ•˜๊ธฐ ์–ด๋ ค์šด ๋ฐฉ๋Œ€ํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋  ๊ฒƒ์ด๋ผ๋Š” ๋น„์ „์ž…๋‹ˆ๋‹ค.

AGI, ๋กœ๋ด‡ ๊ณตํ•™, ๊ทธ๋ฆฌ๊ณ  AI์˜ ์ž๊ธฐ ๊ฐœ์„ 

๋ฆฌ์•” ํŽ˜๋”์Šค CEO๋Š” ์ธ๊ณต์ผ๋ฐ˜์ง€๋Šฅ(AGI)์ด๋‚˜ ์ธ๊ณต์ดˆ์ง€๋Šฅ(ASI)์— ๋Œ€ํ•œ ๋…ผ์˜์—์„œ โ€œ์ง€๋Šฅ์„ ๋‹จ์ผํ•œ ์ฒ™๋„๋กœ ์ƒ๊ฐํ•˜๋Š” ๊ฒƒ์€ ์˜ค๋ฅ˜โ€๋ผ๊ณ  ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. AI ์‹œ์Šคํ…œ์€ ํŠน์ • ์ˆ˜ํ•™ ์˜์—ญ์—์„œ๋Š” ์„ธ๊ณ„ ์ตœ๊ณ  ์ˆ˜์ค€์ด์ง€๋งŒ, ์งˆ๋ฌธ์„ ์•ฝ๊ฐ„๋งŒ ๋ฐ”๊ฟ”๋„ ๊ณ ๋“ฑํ•™์ƒ๋ณด๋‹ค ๋ชปํ•œ ์„ฑ๋Šฅ์„ ๋ณด์ผ ์ˆ˜ ์žˆ๋Š” โ€œ์ด์ƒํ•œ ๋พฐ์กฑํ•จ(Spikiness)โ€œ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ฆ‰, ํ•œ ๋ถ„์•ผ์—์„œ๋Š” ์ฒœ์žฌ์ ์ด์ง€๋งŒ ๋‹ค๋ฅธ ์ธ์ ‘ ๋ถ„์•ผ์—์„œ๋Š” ๊ทธ๋ ‡์ง€ ๋ชปํ•œ ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๋‹ค๋Š” ์„ค๋ช…์ž…๋‹ˆ๋‹ค.

๊ทธ๋Š” AI์˜ ์ž๊ธฐ ๊ฐœ์„ (Self-improvement)์ด ์†Œํ”„ํŠธ์›จ์–ด ๊ณตํ•™ ๋ถ„์•ผ์—์„œ ์ด๋ฏธ โ€œ์ง€๊ธˆ์ฏค(nowish)โ€ ์ผ์–ด๋‚˜๊ณ  ์žˆ๋‹ค๊ณ  ๋ด…๋‹ˆ๋‹ค. ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ์€ ๊ฒ€์ฆ ๊ฐ€๋Šฅํ•œ ํ™˜๊ฒฝ(Verifiable Environments)๊ณผ ์ €๋ ดํ•œ ์ปดํ“จํŒ… ์ž์›์„ ํ†ตํ•ด ๋ฒ„๊ทธ๋ฅผ ์‹๋ณ„ํ•˜๊ณ  ์ฝ”๋“œ๋ฅผ ๋ฆฌํŒฉํ† ๋ง(Refactor)ํ•˜๋Š” ๋“ฑ ํ์‡„ ๋ฃจํ”„(Closed Loop) ํ•™์Šต์ด ์šฉ์ดํ•˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ณผํ•™ ์—ฐ๊ตฌ๋‚˜ AI ์—ฐ๊ตฌ์˜ ์ž๊ธฐ ๊ฐœ์„ ์€ ๋” ๋А๋ฆฐ ์™ธ๋ถ€ ๋ฃจํ”„(Outer Loop)๋ฅผ ๊ฐ€์งˆ ์ˆ˜๋ฐ–์— ์—†์Šต๋‹ˆ๋‹ค. ์‹คํ—˜์— GPU๊ฐ€ ํ•„์š”ํ•˜๊ณ  ์ˆ˜๋งŽ์€ ์‹œ๊ฐ„์ด ์†Œ์š”๋˜๋ฉฐ, ๊ฒ€์ฆ ๊ณผ์ •๋„ ๋ณต์žกํ•˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค์˜ ์ „์ œ๋Š” ๋ฐ”๋กœ ์ด๋Ÿฌํ•œ ๊ณผํ•™ ๋ฐ ๊ณตํ•™ ๋ถ„์•ผ์—์„œ ํ์‡„ ๋ฃจํ”„ ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๋กœ๋ด‡ ๊ณตํ•™(Robotics)์€ ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค์˜ ํ•ต์‹ฌ ๋ชฉํ‘œ์ธ ๊ณ ํ’ˆ์งˆ, ๋‹ค๋Ÿ‰์˜ ๋ฐ์ดํ„ฐ ์ƒ์„ฑ์„ ์œ„ํ•œ โ€œ์—„์ฒญ๋‚œ ๊ฐ€์†๊ธฐ(Huge Accelerator)โ€ ์—ญํ• ์„ ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ํ˜„์žฌ๋Š” ์‹œํŒ๋˜๋Š” ๋กœ๋ด‡ ์‹œ์Šคํ…œ์„ ํ™œ์šฉํ•˜๊ณ  ์žˆ์ง€๋งŒ, ๋ฏธ๋ž˜์— ๋”์šฑ ์ •๊ตํ•˜๊ณ  ๋‹ค์žฌ๋‹ค๋Šฅํ•œ ๋กœ๋ด‡์ด ๋“ฑ์žฅํ•œ๋‹ค๋ฉด ์ƒˆ๋กœ์šด ์—ฐ๊ตฌ์‹ค์„ ๊ตฌ์ถ•ํ•˜๊ณ  ์‹คํ—˜์„ ์ž๋™ํ™”ํ•˜๋Š” ์†๋„๊ฐ€ ๋”์šฑ ๋นจ๋ผ์งˆ ๊ฒƒ์ด๋ผ๊ณ  ๊ธฐ๋Œ€ํ•ฉ๋‹ˆ๋‹ค.

๋ฆฌ์•” ํŽ˜๋”์Šค CEO๋Š” ๊ตฌ๊ธ€ ๋ธŒ๋ ˆ์ธ์—์„œ ํŠธ๋žœ์Šคํฌ๋จธ ๋ชจ๋ธ์˜ ํƒ„์ƒ๊ณผ ์˜คํ”ˆAI์—์„œ ์ฑ—GPT์˜ ํƒ„์ƒ์„ ๋ชจ๋‘ ๊ฒฝํ—˜ํ•œ AI ๋ถ„์•ผ์˜ ์‚ฐ์ฆ์ธ์ž…๋‹ˆ๋‹ค. ๊ทธ๊ฐ€ ํ”ผ๋ฆฌ์–ด๋”• ๋žฉ์Šค๋ฅผ ํ†ตํ•ด AI์™€ ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„์˜ ์ ‘์ ์—์„œ ๋งŒ๋“ค์–ด๋‚ผ ํ˜์‹ ์€ ์•ž์œผ๋กœ 10๋…„๊ฐ„ ์ธ๋ฅ˜์˜ ์‚ถ์„ ๊ทผ๋ณธ์ ์œผ๋กœ ๋ณ€ํ™”์‹œํ‚ฌ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ๋™๋ ฅ ์ค‘ ํ•˜๋‚˜๊ฐ€ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Š” ํŠนํžˆ AI ์‹œ์Šคํ…œ๊ณผ ๋ฌผ๋ฆฌ์  ์„ธ๊ณ„์˜ ์ธํ„ฐํŽ˜์ด์Šค(Interface)๊ฐ€ ๊ฐ€์ ธ์˜ฌ ๋ณ€ํ™”์— ํฐ ๊ธฐ๋Œ€๋ฅผ ๊ฑธ๊ณ  ์žˆ์œผ๋ฉฐ, โ€œ๋งค์šฐ ํฅ๋ฏธ๋กœ์šด 10๋…„์ด ๋  ๊ฒƒโ€์ด๋ผ๊ณ  ๋งˆ๋ฌด๋ฆฌํ–ˆ์Šต๋‹ˆ๋‹ค.


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๋”์ฐํ•œ ์ฃ„๋ฅผ ์ €์ง€๋ฅธ ๊ฐ€์กฑ: โ€˜๋‹จ์ ˆโ€™์ด ์•„๋‹Œ โ€˜์—ฐ๊ฒฐโ€™์˜ ๊ธธ์„ ๋ฌป๋‹ค

๋‰ด์š•ํƒ€์ž„์Šค ํŒŸ์บ์ŠคํŠธ โ€˜๋”” ์˜คํ”ผ๋‹ˆ์–ธ์Šคโ€™, ์ˆ˜๊ฐ๋œ ๊ฐ€์กฑ๊ณผ์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์‹ฌ์ธต ํƒ๊ตฌ

๊ฐ€์กฑ ๊ตฌ์„ฑ์› ์ค‘ ๋ˆ„๊ตฐ๊ฐ€๊ฐ€ ๋”์ฐํ•œ ๋ฒ”์ฃ„๋ฅผ ์ €์งˆ๋ €์„ ๋•Œ, ์šฐ๋ฆฌ๋Š” ์–ด๋–ป๊ฒŒ ํ•ด์•ผ ํ• ๊นŒ? ๊ทธ ์‚ฌ๋žŒ๊ณผ์˜ ๊ด€๊ณ„๋ฅผ ๋Š์–ด์•ผ ํ• ๊นŒ, ์•„๋‹ˆ๋ฉด ์–ด๋–ค ์‹์œผ๋กœ๋“  ์œ ์ง€ํ•ด์•ผ ํ• ๊นŒ? ๋‰ด์š•ํƒ€์ž„์Šค ์˜คํ”ผ๋‹ˆ์–ธ ์นผ๋Ÿผ๋‹ˆ์ŠคํŠธ M. ๊ฒŒ์Šจ(M. Gesson)์ด ์ง„ํ–‰ํ•˜๋Š” ํŒŸ์บ์ŠคํŠธ โ€˜๋”” ์˜คํ”ผ๋‹ˆ์–ธ์Šค(The Opinions)โ€˜๋Š” ์ด ์งˆ๋ฌธ์— ๋Œ€ํ•œ ๊นŠ์ด ์žˆ๋Š” ํ†ต์ฐฐ์„ ์ œ๊ณตํ•œ๋‹ค. ๊ฒŒ์Šจ์€ ์ž์‹ ์˜ ์‚ฌ์ดŒ์ด ์ €์ง€๋ฅธ ์ถฉ๊ฒฉ์ ์ธ ๋ฒ”์ฃ„๋ฅผ ๋‹ค๋ฃฌ ์ƒˆ๋กœ์šด ํŒŸ์บ์ŠคํŠธ โ€˜๋”” ์ด๋””์—‡(The Idiot)โ€˜์„ ์ œ์ž‘ํ•˜๋ฉฐ ๋А๊ผˆ๋˜ ํ˜ผ๋ž€๊ณผ ํ•จ๊ป˜, ์ˆ˜๊ฐ๋œ ๋ถ€๋ชจ๋ฅผ ๋‘” ์ž๋…€๋“ค์˜ ์‚ถ์„ ์—ฐ๊ตฌํ•ด ์˜จ ์ž‘๊ฐ€ ํ•ด๋ฆฌ์—‡ ํด๋ฝ(Harriet Clark)๊ณผ์˜ ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด โ€˜๋‹จ์ ˆโ€™์ด ์•„๋‹Œ โ€˜์—ฐ๊ฒฐโ€™์˜ ์ค‘์š”์„ฑ์— ๋Œ€ํ•ด ์กฐ๋ช…ํ•œ๋‹ค.


โ€˜๋ฐ”๋ณดโ€™ ํŒŸ์บ์ŠคํŠธ: ์ฃ„์™€ ๊ฐ€์กฑ์˜ ๋”œ๋ ˆ๋งˆ

M. ๊ฒŒ์Šจ์˜ ์‚ฌ์ดŒ ์•จ๋Ÿฐ(Alan)์€ 2022๋…„ ์ „์ฒ˜๋ฅผ ์‚ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด ์ฒญ๋ถ€์‚ด์ธ์—…์ž๋ฅผ ๊ณ ์šฉํ•œ ํ˜์˜๋กœ ์ฒดํฌ๋˜์–ด ํ˜„์žฌ ์—ฐ๋ฐฉ ๊ต๋„์†Œ์—์„œ 10๋…„ํ˜•์„ ๋ณต์—ญ ์ค‘์ด๋‹ค. ์•จ๋Ÿฐ์€ ์ „์ฒ˜์™€์˜ ์‚ฌ์ด์— ๋‘ ์ž๋…€๋ฅผ ๋‘๊ณ  ์žˆ์œผ๋ฉฐ, ๋ฌด์—‡๋ณด๋‹ค ์•„์ด๋“ค๊ณผ ๊ด€๊ณ„๋ฅผ ๋งบ๊ณ  ์‹ถ์–ด ํ•œ๋‹ค. ๊ฒŒ์Šจ์€ ์ž์‹ ์˜ ํŒŸ์บ์ŠคํŠธ โ€˜๋”” ์ด๋””์—‡โ€™์„ ์ œ์ž‘ํ•˜๋ฉด์„œ, ์ˆ˜๊ฐ๋œ ๋ถ€๋ชจ๊ฐ€ ์•„์ด๋“ค๊ณผ ์–ด๋–ป๊ฒŒ ๊ด€๊ณ„๋ฅผ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ๋Š”์ง€ ์ดํ•ดํ•˜๊ณ ์ž ํ–ˆ๋‹ค. ๊ทธ๋Š” ์ด ๊ณผ์ •์—์„œ ์•จ๋Ÿฐ์—๊ฒŒ ๊ณต๊ฐ์„ ๋А๋ผ๊ธฐ ์–ด๋ ค์› ๊ณ , ์ด๋Š” ๊ทธ์—๊ฒŒ ํฐ ๋”œ๋ ˆ๋งˆ๋กœ ๋‹ค๊ฐ€์™”๋‹ค.

์ด๋Ÿฌํ•œ ๊ฒŒ์Šจ์˜ ๊ณ ๋ฏผ์€ ํ•ด๋ฆฌ์—‡ ํด๋ฝ๊ณผ์˜ ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด ์ƒˆ๋กœ์šด ๊ด€์ ์„ ์–ป๊ฒŒ ๋œ๋‹ค. ํ•ด๋ฆฌ์—‡์˜ ์–ด๋จธ๋‹ˆ ์ฃผ๋”” ํด๋ฝ(Judy Clark)์€ 3๋ช…์˜ ์‚ฌ๋ง์ž๋ฅผ ๋‚ธ ๋ธŒ๋งํฌ์Šค ๊ฐ•๋„ ์‚ฌ๊ฑด์—์„œ ๋„์ฃผ ์ฐจ๋Ÿ‰์„ ์šด์ „ํ•œ ํ˜์˜๋กœ 37๋…„๊ฐ„ ์ˆ˜๊ฐ์ƒํ™œ์„ ํ–ˆ๋‹ค. ํ•ด๋ฆฌ์—‡์€ ์ž์‹ ์˜ ๊ฒฝํ—˜์„ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ ์†Œ์„ค ใ€Ž๋” ํž(The Hill)ใ€์˜ ์ž‘๊ฐ€์ด๊ธฐ๋„ ํ•˜๋‹ค. ๊ทธ๋…€๋Š” ๋”์ฐํ•œ ์ผ์„ ์ €์ง€๋ฅธ ์‚ฌ๋žŒ๋“ค์—๊ฒŒ๋„ ๊ณต๊ฐ์„ ํ’ˆ์„ ์ค„ ์•„๋Š” ํŠน๋ณ„ํ•œ ๋Šฅ๋ ฅ์„ ๊ฐ€์กŒ๋‹ค.

์ˆ˜๊ฐ๋œ ๋ถ€๋ชจ์™€ ์ž๋…€์˜ ์œ ๋Œ€: ํ•ด๋ฆฌ์—‡ ํด๋ฝ์˜ ํŠน๋ณ„ํ•œ ๊ฒฝํ—˜

ํ•ด๋ฆฌ์—‡์€ ์–ด๋ฆฐ ์‹œ์ ˆ, ๋งค์ฃผ ์–ด๋จธ๋‹ˆ๋ฅผ ๋ฉดํšŒํ•  ์ˆ˜ ์žˆ์—ˆ๋˜ ๊ฒƒ์„ โ€œ๊นŠ์ด ๋ถˆ์šดํ•œ ์ƒํ™ฉ ์†์—์„œ ๋งค์šฐ ์šด์ด ์ข‹์€ ๊ฒฝ์šฐโ€๋ผ๊ณ  ํšŒ์ƒํ•œ๋‹ค. ๊ทธ๋…€์˜ ์–ด๋จธ๋‹ˆ๊ฐ€ ์ˆ˜๊ฐ๋˜์—ˆ๋˜ ์‹œ์„ค์€ ๋ถ€๋ชจ์™€ ์ž๋…€ ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ์ด‰์ง„ํ•˜๊ธฐ ์œ„ํ•ด ๋…ธ๋ ฅํ–ˆ๊ณ , ๋ฉดํšŒ์‹ค์—๋Š” โ€˜์–ด๋ฆฐ์ด ์„ผํ„ฐโ€™๊ฐ€ ๋งˆ๋ จ๋˜์–ด ์•„์ด๋“ค์ด ์–ด๋จธ๋‹ˆ์™€ ํ•จ๊ป˜ ๋†€๊ณ  ๊ณต์˜ˆ ํ™œ๋™์„ ํ•˜๋ฉฐ ์‹œ๊ฐ„์„ ๋ณด๋‚ผ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ต๋„์†Œ๋ผ๋Š” ํ˜„์‹ค์ด ์•„์ด์˜ ํ˜„์‹ค ์•ˆ์— ์ตœ๋Œ€ํ•œ ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ์Šค๋ฉฐ๋“ค๋„๋ก ๋…ธ๋ ฅํ•œ ๊ฒƒ์ด๋‹ค.

์–ด๋จธ๋‹ˆ์˜ ๋ฒ”์ฃ„๋กœ ์ธํ•ด ๊ฐ€์กฑ ๊ด€๊ณ„๊ฐ€ ๊ทน์‹ฌํ•˜๊ฒŒ ๋ถ•๊ดด๋˜์—ˆ์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ํ•ด๋ฆฌ์—‡์˜ ๊ฐ€์กฑ ๋ชจ๋‘๋Š” ๊ทธ๋…€์™€ ์–ด๋จธ๋‹ˆ๊ฐ€ ๊ฐ€๋Šฅํ•œ ํ•œ ๊ธด๋ฐ€ํ•œ ๊ด€๊ณ„๋ฅผ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋„์™”๋‹ค. ์–ด๋ฆฐ ํ•ด๋ฆฌ์—‡์ด ์ „ํ™” ํ†ตํ™”๋ฅผ ์˜ค๋ž˜ ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋„์™€์ฃผ๋Š” ํŠน๋ณ„ํ•œ ์ธํ˜•์ด ์ „ํ™”๊ธฐ ์˜†์— ๋†“์—ฌ ์žˆ์—ˆ๊ณ , ๊ฐ€์กฑ๋“ค์€ ์–ด๋จธ๋‹ˆ์˜ ํŽธ์ง€๋ฅผ ์ฝ์–ด์ฃผ๋ฉฐ ๊ทธ๋…€๊ฐ€ ๊ฐ๋ฐฉ์—์„œ ๋ณผ ์ˆ˜ ์žˆ์—ˆ๋˜ ์ƒˆ๋“ค์— ๋Œ€ํ•ด ์ด์•ผ๊ธฐํ•ด ์ฃผ์—ˆ๋‹ค. ํ•ด๋ฆฌ์—‡์€ โ€œ๋งŽ์€ ์‚ฌ๋žŒ๋“ค์ด ์–ด๋จธ๋‹ˆ๊ฐ€ ๊ณ„์†ํ•ด์„œ ๋‚˜์˜ ์–ด๋จธ๋‹ˆ๋กœ ๋‚จ์„ ์ˆ˜ ์žˆ๋„๋ก ์—„์ฒญ๋‚œ ๋…ธ๋ ฅ์„ ๊ธฐ์šธ์˜€๋‹คโ€๊ณ  ๋งํ•œ๋‹ค. ์ด๋Š” ์ข…์ข… ์‚ฌ๋žŒ๋“ค์˜ ๋ถ€๋ชจ๋ฅผ ๊ทธ๋“ค์—๊ฒŒ์„œ ๋นผ์•—์œผ๋ ค ํ•˜๋Š” ์‹œ์Šคํ…œ ์•ˆ์—์„œ ํฐ ํ–‰์šด์ด์—ˆ๋‹ค.

๊ทธ๋Ÿฌ๋‚˜ ํ•ด๋ฆฌ์—‡์˜ ์•„๋ฒ„์ง€์˜ ๊ฒฝ์šฐ๋Š” ๋‹ฌ๋ž๋‹ค. ๊ทธ๋…€๋Š” ์•„๋ฒ„์ง€๋ฅผ ๊ฑฐ์˜ ๋ฉดํšŒํ•˜์ง€ ๋ชปํ–ˆ๋Š”๋ฐ, ํ• ์•„๋ฒ„์ง€์™€ ํ• ๋จธ๋‹ˆ๋Š” ์•„๋ฒ„์ง€๊ฐ€ ์ˆ˜๊ฐ๋œ ์‹œ์„ค์ด ์•„์ด์—๊ฒŒ ๋” ํ•ด๋กœ์šธ ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ–ˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ํ”Œ๋ผ์Šคํ‹ฑ ๋ฒฝ์„ ์‚ฌ์ด์— ๋‘” ๋ฉดํšŒ, ๋”์ฐํ•œ ๊ต๋„์†Œ ๋ณ‘์›์—์„œ ๋ณ‘์ƒ์— ์ˆ˜๊ฐ‘์ด ์ฑ„์›Œ์ ธ ์žˆ๋˜ ์•„๋ฒ„์ง€์˜ ๋ชจ์Šต์€ ์–ด๋ฆฐ ํ•ด๋ฆฌ์—‡์—๊ฒŒ ๋„ˆ๋ฌด ํฐ ์ถฉ๊ฒฉ์ด ๋  ๊ฒƒ์ด๋ผ๊ณ  ํŒ๋‹จํ–ˆ๋˜ ๊ฒƒ์ด๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ํ•ด๋ฆฌ์—‡์€ ์•„๋ฒ„์ง€์— ๋Œ€ํ•ด ๋” ํฐ ์ƒ์‹ค๊ฐ๊ณผ ๋ฒ„๋ ค์กŒ๋‹ค๋Š” ๋А๋‚Œ์„ ๋ฐ›์•˜์œผ๋ฉฐ, ๊ทธ์—๊ฒŒ ๋ฌด์Šจ ์ผ์ด ์ผ์–ด๋‚ฌ๋Š”์ง€ ์ œ๋Œ€๋กœ ์ดํ•ดํ•˜์ง€ ๋ชปํ–ˆ๋‹ค. ๊ทธ๋…€๋Š” ์ด ๊ฒฝํ—˜์„ ํ†ตํ•ด โ€œ๋ถ€์žฌ๊ฐ€ ๋” ๋‚˜์  ์ˆ˜ ์žˆ๋‹คโ€๊ณ  ๊ฐ•์กฐํ•œ๋‹ค.

์™œ โ€˜์—ฐ๊ฒฐโ€™์ธ๊ฐ€: ๋‹จ์ ˆ์ด ๋‚ณ๋Š” โ€˜๋ธ”๋ž™ํ™€โ€™

๋งŽ์€ ์‚ฌ๋žŒ๋“ค์€ โ€œ๋”์ฐํ•œ ์ผ์„ ์ €์ง€๋ฅธ ๋ถ€๋ชจ์™€ ์™œ ๊ด€๊ณ„๋ฅผ ์œ ์ง€ํ•ด์•ผ ํ•˜๋Š”๊ฐ€?โ€๋ผ๋Š” ์งˆ๋ฌธ์„ ๋˜์ง„๋‹ค. ๊ฒŒ์Šจ ์—ญ์‹œ ์ž์‹ ์˜ ์‚ฌ์ดŒ ์•จ๋Ÿฐ์ด ์ž๋…€์˜ ์–ด๋จธ๋‹ˆ๋ฅผ ์‚ดํ•ดํ•˜๋ ค ํ–ˆ๋‹ค๋Š” ์‚ฌ์‹ค์„ ์ƒ๊ฐํ•˜๋ฉฐ ์ด ์งˆ๋ฌธ์— ๋Œ€ํ•œ ๋‹ต์„ ์ฐพ๊ธฐ ์–ด๋ ค์›Œํ–ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ•ด๋ฆฌ์—‡์€ โ€œ์ˆ˜๊ฐ๋œ ๋ถ€๋ชจ๋ฅผ ๋‘” ์ž๋…€๋“ค์€ ๋ถ€๋ชจ์™€์˜ ๊ด€๊ณ„๋ฅผ ์œ ์ง€ํ•จ์œผ๋กœ์จ ๋„์›€์„ ๋ฐ›๋Š”๋‹คโ€๋Š” ์ ์„ ๊ฑฐ๋“ญ ๊ฐ•์กฐํ•œ๋‹ค.

  • โ€˜๋ฒ„๋ ค์งˆ ์ˆ˜ ์žˆ๋Š” ์กด์žฌโ€™๋ผ๋Š” ๊ณ ํ†ต์Šค๋Ÿฌ์šด ์ง€์‹: ๋ถ€๋ชจ๊ฐ€ ๊ต๋„์†Œ์— ๊ฐ€๋ฉด, ์•„์ด๋“ค์€ ์ž์‹ ์ด โ€˜๋ฒ„๋ ค์งˆ ์ˆ˜ ์žˆ๋Š” ์กด์žฌโ€™๋ผ๋Š” ๊ณ ํ†ต์Šค๋Ÿฌ์šด ์ง€์‹์„ ๋ฌผ๋ ค๋ฐ›๊ฒŒ ๋œ๋‹ค. ์ด๋Š” ์•„์ด์—๊ฒŒ ๋งค์šฐ ๋‘๋ ค์šด ์‚ฌ์‹ค์ด๋ฉฐ, ๋ถ€๋ชจ๊ฐ€ ๊ณ„์†ํ•ด์„œ ์—ฐ๊ฒฐํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์„ ํ†ตํ•ด ์ด ์ง€์‹์— ๋Œ€์‘ํ•ด์•ผ ํ•œ๋‹ค. ์•„์ด๋“ค์€ ๋ถ€๋ชจ๊ฐ€ ์—ฌ์ „ํžˆ ์ž์‹ ์„ ์ƒ๊ฐํ•˜๊ณ , ์—ฐ๋ฝํ•˜๋ ค ๋…ธ๋ ฅํ•˜๋ฉฐ, ์ง€์ง€ํ•˜๋ ค ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ์•„์•ผ ํ•œ๋‹ค.
  • โ€˜๋ธ”๋ž™ํ™€โ€™์ด ๋˜๋Š” ๋ถ€๋ชจ: ์•„์ด์™€ ์ˆ˜๊ฐ๋œ ๋ถ€๋ชจ ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ์ด‰์ง„ํ•˜์ง€ ์•Š์œผ๋ฉด, ๋ถ€์žฌํ•˜๋Š” ๋ถ€๋ชจ๋Š” ๊ทธ์ € โ€˜๋ธ”๋ž™ํ™€(black hole)โ€˜์ด ๋˜์–ด ์‹ ํ™”์ ์ธ ์กด์žฌ๋กœ ๋ณ€๋ชจํ•œ๋‹ค. ์•„์ด๋“ค์€ ํ˜ผ๋ž€, ๋ถˆ๋งŒ, ์š”๊ตฌ, ๋ถ„๋…ธ๋ฅผ ํ„ธ์–ด๋†“์„ ์ˆ˜ ์žˆ๋Š” โ€˜์‚ฌ๋žŒโ€™์ด ํ•„์š”ํ•˜๋‹ค. ๋ธ”๋ž™ํ™€์€ ์•„์ด๋“ค์—๊ฒŒ ์•„๋ฌด๋Ÿฐ ๋„์›€์ด ๋˜์ง€ ์•Š๋Š”๋‹ค.
  • ๊ฐ๊ธˆ ๋…ผ๋ฆฌ์˜ ๋ฐ˜๋ณต: ํ•ด๋ฆฌ์—‡์€ ์ˆ˜๊ฐ๋œ ๋ถ€๋ชจ๋ฅผ ์ œ๊ฑฐํ•˜๊ณ  ์•„์ด๊ฐ€ ์ ์‘ํ•˜๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ด๋Š” ์ƒํ™ฉ์„ โ€œ๊ฐ€์กฑ์ด ์ œ๊ฑฐ์™€ ์†Œ๋ฉธ์ด๋ผ๋Š” ๊ฐ๊ธˆ ๋…ผ๋ฆฌ(carceral logic)๋ฅผ ๋ฐ˜๋ณตํ•˜๋Š” ๊ฒƒโ€์ด๋ผ๊ณ  ์ง€์ ํ•œ๋‹ค. ๋ฌธ์ œ๊ฐ€ ๋˜๋Š” ์š”์ธ์„ ์ œ๊ฑฐํ•˜๋ฉด ์•„์ด๊ฐ€ ์•ˆ์ „ํ•ด์ง„๋‹ค๊ณ  ์ƒ๊ฐํ•˜์ง€๋งŒ, ์‹ค์ œ๋กœ๋Š” ๊ทธ๋ ‡์ง€ ์•Š๋‹ค. ๋ถ€์žฌ๋Š” ์กด์žฌ๋งŒํผ์ด๋‚˜ ๊ฐ•๋ ฅํ•˜๊ฒŒ ์•„์ด์˜ ์‚ถ์— ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค.
  • ๋ถ€๋ชจ์˜ ์„ฑ์žฅ ๊ธฐํšŒ: ์ˆ˜๊ฐ๋œ ์‚ฌ๋žŒ๋“ค๋„ ์ž๋…€์™€ ์—ฐ๊ฒฐ๋  ๊ถŒ๋ฆฌ๊ฐ€ ์žˆ์œผ๋ฉฐ, ์•ˆ์—์„œ ์ž๋…€๋ฅผ ์–‘์œกํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์ด ๊ทธ๋“ค์ด ์›ํ•˜๋Š” ๋ถ€๋ชจ๊ฐ€ ๋˜๋Š” ๊ณ„๊ธฐ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ๊ฐ€์กฑ๊ณผ ๊ณต๋™์ฒด๋Š” โ€œ๋‹น์‹ ์˜ ๋ถ€๋ชจ๊ฐ€ ๋”์ฐํ•œ ์ผ์„ ์ €์งˆ๋ €์„์ง€๋ผ๋„, ๊ทธ๋“ค์€ ๋‹น์‹ ์„ ์‚ฌ๋ž‘ํ•˜๊ณ  ์—ฌ์ „ํžˆ ์• ์ •๊ณผ ๋ณด์‚ดํ•Œ์„ ๋ฐ›์„ ๊ฐ€์น˜๊ฐ€ ์žˆ๋‹คโ€๊ณ  ๋งํ•ด์•ผ ํ•œ๋‹ค.

โ€˜์•„์ด์—๊ฒŒ ๋„ˆ๋ฌด ํž˜๋“  ์ผโ€™์ด๋ผ๋Š” ํ†ต๋…์— ๋„์ „ํ•˜๋‹ค

๊ฒŒ์Šจ์€ ์‚ฌ์ดŒ ์•จ๋Ÿฐ์˜ ์ž๋…€๋“ค(O์™€ L)์„ ๊ฑฑ์ •ํ•˜๋ฉฐ, 12์‚ด์ธ O๊ฐ€ ์•„๋ฒ„์ง€์˜ ๋ฒ”์ฃ„๋ฅผ ์ธํ„ฐ๋„ท์„ ํ†ตํ•ด ์•Œ๊ฒŒ ๋œ ์ƒํ™ฉ์—์„œ โ€œ์•„์ด์—๊ฒŒ ๋„ˆ๋ฌด ํž˜๋“  ์ผโ€์ด๋ผ๋Š” ํ†ต๋…์— ๊ฐ‡ํ˜€ ์žˆ์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ•ด๋ฆฌ์—‡์€ โ€œ์•„์ด๋ฅผ ํ˜„์‹ค๋กœ๋ถ€ํ„ฐ ๋ณดํ˜ธํ•˜๋ ค ํ•˜๊ธฐ๋ณด๋‹ค, ๊ทธ ํ˜„์‹ค ์†์—์„œ ์•„์ด์—๊ฒŒ ๋™๋ฐ˜์ž๊ฐ€ ๋˜์–ด์ฃผ๊ณ  ์‚ฌ๋ž‘์„ ๋ฒ ํ’€์–ด์•ผ ํ•œ๋‹คโ€๊ณ  ์ฃผ์žฅํ•œ๋‹ค. ์•„์ด์˜ ์•„๋ฒ„์ง€๊ฐ€ ๊ต๋„์†Œ์— ์žˆ๋‹ค๋Š” ํ˜„์‹ค์„ ์ˆจ๊ธธ ์ˆ˜ ์—†์œผ๋ฏ€๋กœ, ๊ทธ ํ˜„์‹ค ์•ˆ์—์„œ ์•„์ด๊ฐ€ ์‚ฌ๋ž‘๋ฐ›๊ณ  ๋™๋ฐ˜์ž๊ฐ€ ๋˜์–ด์•ผ ํ•œ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ์•„๋ฒ„์ง€๋Š” ์—ฌ์ „ํžˆ ์•„์ด์˜ ์‚ถ์—์„œ ๊ธฐ์จ, ์ง€์ง€, ํ™•์‹ ์˜ ์›์ฒœ์ด ๋  ์ˆ˜ ์žˆ๋‹ค.

ํ•ด๋ฆฌ์—‡์˜ ์–ด๋จธ๋‹ˆ๋Š” ๊ทธ๋…€๊ฐ€ ์–ด๋ ธ์„ ๋•Œ โ€œ๋‚˜์— ๋Œ€ํ•œ ๋งŽ์€ ์ด์•ผ๊ธฐ์™€ ๋‚ด ๋ฒ”์ฃ„๋ฅผ ์ดํ•ดํ•˜๋Š” ๋‹ค์–‘ํ•œ ๋ฐฉ์‹๋“ค์„ ๋“ฃ๊ฒŒ ๋  ๊ฑฐ์•ผ. ํ•˜์ง€๋งŒ ๋„ค๊ฐ€ ์•Œ์•„์•ผ ํ•  ํ•œ ๊ฐ€์ง€๋Š” ๋‚ด๊ฐ€ ๋„ˆ๋ฅผ ์‚ฌ๋ž‘ํ•œ๋‹ค๋Š” ๊ฑฐ์•ผ. ๋ชจ๋‘๊ฐ€ ๋„ˆ๋ฅผ ์‚ฌ๋ž‘ํ•˜๊ณ , ๋„ˆ๋Š” ์•„๋ฌด ์ž˜๋ชป๋„ ํ•˜์ง€ ์•Š์•˜์œผ๋ฉฐ, ์šฐ๋ฆฌ๊ฐ€ ๋ชจ๋‘ ๋„ˆ๋ฅผ ๋Œ๋ณผ ๊ฒƒ์ด๋ผ๋Š” ์‚ฌ์‹ค์ด์•ผโ€๋ผ๊ณ  ๋งํ•ด์ฃผ์—ˆ๋‹ค. ์ด๋Š” ์•„์ด์—๊ฒŒ ํ˜„์‹ค์„ ์ง๋ฉดํ•˜๊ฒŒ ํ•˜๋ฉด์„œ๋„ ์•ˆ์ •๊ฐ๊ณผ ์‚ฌ๋ž‘์„ ์ „๋‹ฌํ•˜๋Š” ํ˜„๋ช…ํ•œ ๋ฐฉ์‹์ด์—ˆ๋‹ค.

์‚ฌ๋ฒ• ์‹œ์Šคํ…œ๊ณผ ๋ณต์ˆ˜์˜ ๊ฐ์ •: ๊ฐœ์ธ๊ณผ ์‚ฌํšŒ์˜ ๋”œ๋ ˆ๋งˆ

M. ๊ฒŒ์Šจ์€ ์•จ๋Ÿฐ์˜ ์žฌํŒ์„ ์ง€์ผœ๋ณด๋ฉฐ ์ž์‹ ๋„ ๋ชจ๋ฅด๊ฒŒ ๊ฒ€์‚ฌ๋ฅผ ์‘์›ํ•˜๊ณ  ์•จ๋Ÿฐ์ด ๊ฐ€๋Šฅํ•œ ํ•œ ์˜ค๋žซ๋™์•ˆ ์ˆ˜๊ฐ๋˜๊ธฐ๋ฅผ ๋ฐ”๋ผ๋Š” ์ž์‹ ์„ ๋ฐœ๊ฒฌํ•˜๊ณ  ์ถฉ๊ฒฉ์„ ๋ฐ›์•˜๋‹ค. ๊ทธ๋Š” ์‚ฌ๋ฒ• ์‹œ์Šคํ…œ์ด ๋ณต์ˆ˜์‹ฌ์„ ์–ต์ œํ•˜๋Š” ๊ธฐ๋Šฅ์„ ํ•œ๋‹ค๊ณ  ๋ฏฟ์—ˆ์ง€๋งŒ, ์‹ค์ œ๋กœ๋Š” ๊ฒ€์‚ฌ๋ฅผ ํ†ตํ•ด ์ž์‹ ์˜ ๋ณต์ˆ˜์‹ฌ์ด ํ•ด์†Œ๋˜๊ณ  ์žˆ๋‹ค๋Š” ๋А๋‚Œ์„ ๋ฐ›์•˜๋‹ค.

์ด์— ๋Œ€ํ•ด ํ•ด๋ฆฌ์—‡์€ โ€œ์‚ฌ๋ฒ• ์‹œ์Šคํ…œ์ด ๋ณต์ˆ˜์‹ฌ์„ ์ œ์ž๋ฆฌ์— ๋‘๊ธฐ๋ฅผ ๋ฐ”๋ผ์ง€๋งŒ, ํ˜„์‹ค์€ ๊ทธ๋ ‡์ง€ ์•Š๋‹คโ€๊ณ  ์ง€์ ํ•œ๋‹ค. ๋‰ด์š•์ฃผ ๊ต๋„์†Œ ์‹œ์Šคํ…œ์˜ ๊ฒฝ์šฐ, ๋งŽ์€ ์‚ฌ๋žŒ๋“ค์ด ํ„ฐ๋ฌด๋‹ˆ์—†์ด ๊ธด ํ˜•๋Ÿ‰์„ ๋ณต์—ญํ•˜๋Š” ์ฃผ๋œ ์ด์œ ๋Š” ๊ฐ€์„๋ฐฉ์ด ๊ฑฐ๋ถ€๋˜๊ธฐ ๋•Œ๋ฌธ์ธ๋ฐ, ์ด๋Š” ์ฃผ๋กœ ํ”ผํ•ด์ž ๊ณต๋™์ฒด์˜ ๋…ธ๋ ฅ๊ณผ ๊ฐ€์„๋ฐฉ ์œ„์›ํšŒ ๋‚ด์˜ ๋ณต์ˆ˜์‹ฌ ๋•Œ๋ฌธ์ด๋ผ๋Š” ๊ฒƒ์ด๋‹ค. ํ•ด๋ฆฌ์—‡์€ ๋ฒ•์ด ์ด๋Ÿฌํ•œ ์›์ดˆ์ ์ธ ์ถฉ๋™์„ ์–ต์ œํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•˜์ง€ ์•Š๋Š”๋‹ค.

๊ทธ๋…€๋Š” โ€œ์–ด๋–ค ๊ฐ์ •์„ ๋А๋ผ๋“  ์ž์œ ๋กญ์ง€๋งŒ, ๊ทธ๊ฒƒ์ด โ€˜์ง„ํ–‰ ์ค‘์ธ ๊ณผ์ •โ€™์˜ ์ผ๋ถ€์ž„์„ ์ธ์ •ํ•˜๋Š” ๊ฒƒ์ด ์œ ์šฉํ•˜๋‹คโ€๊ณ  ์กฐ์–ธํ•œ๋‹ค. ๋ถ„๋…ธ, ํ˜์˜ค๊ฐ, ๋ณต์ˆ˜์‹ฌ์„ ๋А๋ผ๋Š” ๊ฒƒ์€ ์ž์—ฐ์Šค๋Ÿฝ์ง€๋งŒ, ์šฐ๋ฆฌ๋Š” ํ•ญ์ƒ ์ด ๊ณผ์ •์˜ ๋‹ค์Œ ๋‹จ๊ณ„, ์ฆ‰ ์•„์ด๋“ค ์ฃผ๋ณ€์— ๋œ ์ ๋Œ€์ ์ธ ํ™˜๊ฒฝ์„ ๋งŒ๋“ค ์ˆ˜ ์žˆ๋Š” ๋” ๊ฑด๊ฐ•ํ•œ ๋‹จ๊ณ„๋กœ ๋‚˜์•„๊ฐ€๋„๋ก ์„œ๋กœ๋ฅผ ๋•๋Š”๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ๊ฐ๊ธˆ ๋…ผ๋ฆฌ๊ฐ€ โ€˜ํ”ผํ•ด ํ›„ ๋‹จ์ ˆ์ด ํšŒ๋ณต์˜ ๊ธธโ€™์ด๋ผ๊ณ  ๋งํ•˜์ง€๋งŒ, ํ•ด๋ฆฌ์—‡์€ โ€œ์‹ค์ œ๋กœ ๊ฐ€์กฑ์„ ํšŒ๋ณต์‹œํ‚ค๋Š” ๊ฒƒ์€ ๊ฐ€๋Šฅํ•œ ํ•œ ์—ฐ๊ฒฐ์„ ์žฌ๊ฑดํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ฐพ๋Š” ๊ฒƒโ€์ด๋ผ๊ณ  ๊ฐ•๋ ฅํžˆ ์ฃผ์žฅํ•œ๋‹ค.

๊ต๋„์†Œ ๋ฐฉ๋ฌธ์˜ ์ค‘์š”์„ฑ: โ€˜์ง‘๋‹จ์  ํ˜„์‹คโ€™ ์†์˜ ์˜์›…๋“ค

๊ฒŒ์Šจ์€ ์‚ฌ์ดŒ ์•จ๋Ÿฐ๊ณผ ์ฃผ๋กœ ์ „ํ™” ํ†ตํ™”๋งŒ ํ–ˆ๊ณ , ๊ต๋„์†Œ ๋ฉดํšŒ๋Š” ํ•œ ๋ฒˆ๋„ ๊ฐ€์ง€ ์•Š์•˜๋‹ค. ํ•ด๋ฆฌ์—‡์€ ์ˆ˜๊ฐ์ž์™€์˜ ์ „ํ™” ํ†ตํ™”๋Š” ๋งค์šฐ ๊ณ ๋ฆฝ๋œ ํ˜•ํƒœ์˜ ์ƒํ˜ธ์ž‘์šฉ์ด๋ฉฐ, ๊ต๋„์†Œ ๋ฐฉ๋ฌธ๊ณผ๋Š” ๋งค์šฐ ๋‹ค๋ฅด๋‹ค๊ณ  ๋งํ•œ๋‹ค. ๊ต๋„์†Œ๋ฅผ ๋ฐฉ๋ฌธํ•˜๋ฉด, ๋‹ค๋ฅธ ์ˆ˜๊ฐ์ž๋“ค์„ ๋ฉดํšŒ ์˜จ ๋งŽ์€ ์‚ฌ๋žŒ๋“ค๊ณผ ํ•จ๊ป˜ ์žˆ๊ฒŒ ๋œ๋‹ค. ํ•ด๋ฆฌ์—‡์€ ๋งค์ฃผ ์–ด๋จธ๋‹ˆ๋ฅผ ๋ฉดํšŒํ•  ๋•Œ๋งˆ๋‹ค ๋‹ค๋ฅธ ์•„์ด๋“ค๊ณผ ํ•จ๊ป˜ ์žˆ์—ˆ๊ธฐ ๋•Œ๋ฌธ์— โ€œ๋‚˜์—๊ฒŒ๋งŒ ์ด๋Ÿฐ ์ผ์ด ์ผ์–ด๋‚œ ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ•  ํ•„์š”๊ฐ€ ์—†์—ˆ๋‹ค. ๋‚˜๋Š” ์ง‘๋‹จ์  ํ˜„์‹ค(collective reality) ์•ˆ์— ์žˆ์—ˆ๋‹คโ€๊ณ  ๋งํ•œ๋‹ค.

๋ฏธ๊ตญ์—์„œ๋Š” 500๋งŒ ๋ช…์˜ ์•„์ด๋“ค์ด ์–ด๋ฆฐ ์‹œ์ ˆ ์–ด๋А ์‹œ์ ์— ๋ถ€๋ชจ ์ค‘ ํ•œ ๋ช…์ด ์ˆ˜๊ฐ๋˜๋Š” ๊ฒฝํ—˜์„ ํ•˜๊ฒŒ ๋œ๋‹ค. ๊ต๋„์†Œ๋ฅผ ๋ฐฉ๋ฌธํ•˜๋ฉด, ๊ทธ ๋ชจ๋“  ๊ณ ํ†ต๊ณผ ๊ณ ๋‚œ ์†์—์„œ๋„ ๊ฐ€์กฑ์„ ์ฐข์–ด๋†“์œผ๋ ค๋Š” ๊ตญ๊ฐ€์˜ ์‹œ๋„์— ๋งž์„œ ์˜์›…์ ์ธ ๋…ธ๋ ฅ์„ ๊ธฐ์šธ์ด๋Š” ๋†€๋ผ์šด ์‚ฌ๋žŒ๋“ค์„ ๋งŒ๋‚  ์ˆ˜ ์žˆ๋‹ค. ํ•ด๋ฆฌ์—‡์€ โ€œ๊ทธ๊ฒƒ์ด ๋‚ด๊ฐ€ ์ž๋ผ๋ฉด์„œ ๋ณด์•˜๋˜ ์‚ฌ๋žŒ๋“คโ€์ด๋ผ๊ณ  ๋งํ•œ๋‹ค. ์ƒˆ๋ฒฝ 4์‹œ์— ์ผ์–ด๋‚˜ 7์‹œ๊ฐ„ ๋ฒ„์Šค๋ฅผ ํƒ€๊ณ  ์†์ฃผ๋“ค์„ ๋ฐ๋ฆฌ๊ณ  ์•„๋ฒ„์ง€๋ฅผ ๋ฉดํšŒ ๊ฐ€๋Š” ํ• ๋จธ๋‹ˆ๋“ค. ๊ทธ ์•„๋ฒ„์ง€๋“ค์ด ๋”์ฐํ•œ ์ผ์„ ์ €์งˆ๋ €์„์ง€๋ผ๋„, ๊ทธ ์—ฌ์„ฑ๋“ค์€ ๋Š์ž„์—†์ด โ€œ๋‚˜๋Š” ๋‹น์‹ ์„ ๋ฒ„๋ฆฌ์ง€ ์•Š์„ ๊ฒƒ์ด๋‹ค. ๋‹น์‹ ์€ ์—ฌ์ „ํžˆ ๋‚˜์˜ ์•„๋“ค, ์†์ž, ์•„๋ฒ„์ง€, ํ˜•์ œ, ๋‚จํŽธ์ด๋‹ค. ๋‹น์‹ ์€ ์—ฌ์ „ํžˆ ์ด ์•„์ด๋“ค์˜ ์•„๋ฒ„์ง€์ด๋‹คโ€๋ผ๊ณ  ๋งํ•œ๋‹ค. ํ•ด๋ฆฌ์—‡์€ ์ด๋Ÿฌํ•œ ๋…ธ๋ ฅ์ด ์–ผ๋งˆ๋‚˜ ์•„๋ฆ„๋‹ค์šด์ง€ ๋” ๋งŽ์ด ๋ณผ์ˆ˜๋ก, ๋ณต์ˆ˜์‹ฌ์„ ์–ต์ œํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋  ๊ฒƒ์ด๋ผ๊ณ  ๊ฐ•์กฐํ•œ๋‹ค.

โ€˜๊ทธ ์ดํ›„โ€™์˜ ์‚ถ: ์ฑ…์ž„๊ฐ๊ณผ ์กด์—„์„ฑ์„ ํ–ฅํ•œ ์—ฌ์ •

๊ฒŒ์Šจ์€ ์•จ๋Ÿฐ์ด ์ €์ง€๋ฅธ ์ผ์—๋งŒ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์—ˆ์ง€๋งŒ, ํ•ด๋ฆฌ์—‡์€ ๊ทธ์—๊ฒŒ โ€œ๊ทธ ์ดํ›„์— ๋ฌด์Šจ ์ผ์ด ์ผ์–ด๋‚˜๋Š”๊ฐ€โ€์— ์ง‘์ค‘ํ•˜๋„๋ก ๋„์™”๋‹ค. ํ•ด๋ฆฌ์—‡์€ โ€œ๋‹ค์Œ ๋‹จ๊ณ„๋Š” ๊ฐ€์กฑ ๊ตฌ์„ฑ์›๋“ค์ด ์•จ๋Ÿฐ๊ณผ ํ”„๋ฆฌ์‹ค๋ผ(์•จ๋Ÿฐ์˜ ์ „์ฒ˜), ๊ทธ๋ฆฌ๊ณ  ๊ทธ๋“ค์˜ ์ž๋…€, ๋‚˜์•„๊ฐ€ ๋ชจ๋“  ๊ฐ€์กฑ์—๊ฒŒ ๊ฐ€๋Šฅํ•œ ํ•œ ์ข‹์€ ๋ฏธ๋ž˜๋ฅผ ์ด‰์ง„ํ•˜๊ธฐ ์œ„ํ•ด ์–ด๋–ป๊ฒŒ ๊ฒฐ์ •ํ•˜๋Š”์ง€์— ๋‹ฌ๋ ค ์žˆ๋‹คโ€๊ณ  ๋งํ•œ๋‹ค. ํฐ ํ•ด๋ฅผ ๋ผ์นœ ์‚ฌ๋žŒ๋“ค๊ณผ ํ•จ๊ป˜ ์‚ด์•„๊ฐ€๋Š” ๋ฐฉ๋ฒ•์„ ์ฐพ๋Š” ๊ฒƒ์€ ์—„์ฒญ๋‚˜๊ฒŒ ์–ด๋ ค์šด ์ผ์ด๋‹ค. ์•จ๋Ÿฐ์˜ ๊ฒฝ์šฐ, ๊ทธ๊ฐ€ ์ €์ง€๋ฅธ ์ผ์— ๋Œ€ํ•œ ๋ถ„๋…ธ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ๊ฒŒ์Šจ์ด ๊ทธ๋ฅผ ๋ณ„๋กœ ์ข‹์•„ํ•˜์ง€ ์•Š๊ณ  ๊ท€์ฐฎ์•„ํ•œ๋‹ค๋Š” ๊ฐœ์ธ์ ์ธ ๊ฐ์ •๊นŒ์ง€ ๋”ํ•ด์ ธ ๋”์šฑ ๋ณต์žกํ•˜๋‹ค.

๊ทธ๋Ÿฌ๋‚˜ ํ•ด๋ฆฌ์—‡์€ โ€œ์„œ๋กœ์˜ ์‚ถ์—์„œ ์ข‹์€ ์‚ฌ๋žŒ์ด ๋˜๋Š” ๋ฐฉ๋ฒ•์„ ์ฐพ๋Š” ๊ฒƒ์€ ๊ธธ๊ณ  ํž˜๋“  ์—ฌ์ •์ด์ง€๋งŒ, ๋งค์šฐ ์กด์—„ํ•œ ์—ฌ์ •โ€์ด๋ผ๊ณ  ๋งํ•œ๋‹ค. ์•จ๋Ÿฐ์ด ์ˆ˜๊ฐ๋˜์–ด ์žˆ๋Š” ๋™์•ˆ, ๊ทธ๋ฆฌ๊ณ  ์ถœ์†Œ ํ›„์—๋„ O์™€ L์—๊ฒŒ ๊ฐ€๋Šฅํ•œ ํ•œ ์ตœ๊ณ ์˜ ๋ถ€๋ชจ๊ฐ€ ๋  ์ˆ˜ ์žˆ๋„๋ก ์–ด๋–ป๊ฒŒ ๋„์šธ ์ˆ˜ ์žˆ์„๊นŒ? ์•จ๋Ÿฐ์˜ ์ถœ์†Œ ํ›„ ํ”„๋ฆฌ์‹ค๋ผ๊ฐ€ ์•ˆ์ „ํ•˜๊ณ  ์•ˆ์ „ํ•˜๋‹ค๊ณ  ๋А๋‚„ ์ˆ˜ ์žˆ๋„๋ก ์–ด๋–ป๊ฒŒ ๋ณด์žฅํ•  ์ˆ˜ ์žˆ์„๊นŒ? ์ด๋Ÿฌํ•œ ์งˆ๋ฌธ๋“ค์— ๋Œ€ํ•œ ๋‹ต์„ ์ง‘๋‹จ์ ์œผ๋กœ ์ฐพ๋Š” ๊ณผ์ •์€ ๋งค์šฐ ์˜๋ฏธ ์žˆ์„ ๊ฒƒ์ด๋‹ค.

ํญ๋ ฅ์€ ์ข…์ข… ๊ฐœ์ธ์ด ๊ฐ๋‹นํ•  ์ˆ˜ ์—†๋Š” ๊ณ ๋ฆฝ๋œ ํ˜„์‹ค ์†์—์„œ ๋ฒ—์–ด๋‚˜๊ธฐ ์œ„ํ•œ ์‹œ๋„๋กœ ๋ฐœ์ƒํ•˜๋ฉฐ, ๋„์›€์„ ์ฒญํ•  ๊ณณ์ด ์—†๋‹ค๊ณ  ๋А๋‚„ ๋•Œ ์„ ํƒํ•˜๋Š” ๋ฐฉ์‹์ด๋‹ค. ๋”ฐ๋ผ์„œ ํญ๋ ฅ๊ณผ ๋‹จ์ ˆ ์ดํ›„์—๋Š” ํ•ญ์ƒ โ€œ๊ณต๋™์ฒด์˜ ๊ฐœ์ž…โ€์ด ํ•„์š”ํ•˜๋‹ค. โ€œ์šฐ๋ฆฌ๋Š” ์ด ๋ฌธ์ œ๋ฅผ ํ•จ๊ป˜ ํ•ด๊ฒฐํ•ด์•ผ ํ•  ๊ฒƒ์ด๋‹คโ€๋ผ๊ณ  ๋งํ•˜๋Š” ๋ฐ˜๋Œ€ ๋…ผ๋ฆฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค.

โ€˜์ง„์‹คโ€™์˜ ์š”๊ตฌ์™€ โ€˜์ฑ…์ž„โ€™์˜ ๊ณผ์ •: ๋ณต์žกํ•œ ํ˜„์‹ค

๊ฒŒ์Šจ์€ ํŒŸ์บ์ŠคํŠธ ์‹œ๋ฆฌ์ฆˆ์˜ ๋งˆ์ง€๋ง‰ ๋ถ€๋ถ„์—์„œ ์‚ฌ์ดŒ์—๊ฒŒ โ€œ๋„ค๊ฐ€ ํ•œ ์ผ์„ ๊ณ ๋ฐฑํ•ด์•ผ๋งŒ ๊ฐ€์กฑ์œผ๋กœ ๋‹ค์‹œ ๋“ค์–ด์˜ฌ ์ˆ˜ ์žˆ๋‹คโ€๋Š” ์ตœํ›„ํ†ต์ฒฉ์„ ๋ณด๋ƒˆ๋‹ค. ์•จ๋Ÿฐ์€ ์—ฌ์ „ํžˆ ์ž์‹ ์˜ ํ˜์˜๋ฅผ ๋ถ€์ธํ•˜๊ณ  ์žˆ๋‹ค. ํ•ด๋ฆฌ์—‡์€ ์ด๋Ÿฌํ•œ ์ตœํ›„ํ†ต์ฒฉ์— ๋Œ€ํ•ด ๋น„ํŒ์ ์ธ ์‹œ๊ฐ์„ ์ œ์‹œํ•œ๋‹ค. ๊ทธ๋…€๋Š” ์ฑ…์ž„(accountability)์˜ ๊ณผ์ •์ด ํ›จ์”ฌ ๊ธธ๊ณ  ๋ณต์žกํ•˜๋‹ค๊ณ  ๋งํ•œ๋‹ค.

๊ต๋„์†Œ๋Š” ์ง„์‹ค์„ ๋งํ•˜๊ธฐ ๋งค์šฐ ์–ด๋ ค์šด ํ™˜๊ฒฝ์ด๋‹ค. ํ™œ๋ฐœํ•œ ํ•ญ์†Œ๊ฐ€ ์ง„ํ–‰ ์ค‘์ด๋ผ๋ฉด ๋ฒ”์ฃ„๋ฅผ ๊ณ ๋ฐฑํ•˜์ง€ ์•Š์„ ๊ฒƒ์ด๊ณ , ์ž๋…€์™€์˜ ๊ด€๊ณ„๋ฅผ ์œ„ํƒœ๋กญ๊ฒŒ ํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•˜๋ฉด ๊ณ ๋ฐฑํ•˜์ง€ ์•Š์„ ์ˆ˜๋„ ์žˆ๋‹ค. ํ•ด๋ฆฌ์—‡์€ โ€œ์ง„์‹ค์— ๋Œ€ํ•œ ์š”๊ตฌ๊ฐ€ ๋งค์šฐ ํ•ฉ๋ฆฌ์ ์ด๊ณ  ์œค๋ฆฌ์ ์œผ๋กœ ๋ณด์ผ ์ˆ˜ ์žˆ์ง€๋งŒ, ๊ทธ๊ฒƒ์ด ์‚ฌ๋žŒ๋“ค๊ณผ์˜ ๊ด€๊ณ„์—์„œ ๋ชจ๋“  ๊ฒƒ์˜ ์‹œ์ž‘์ด์ž ๋(be all and end all)์ด ๋˜์–ด์„œ๋Š” ์•ˆ ๋œ๋‹คโ€๊ณ  ์ฃผ์žฅํ•œ๋‹ค. ๊ทธ๋…€์˜ ์ƒ๊ฐ์€ โ€œ์‚ฌ์ดŒ์ด ์ง€๊ธˆ ์ง„์‹ค์„ ๋งํ•˜์ง€ ์•Š์œผ๋ฉด ๊ฐ€์กฑ์—์„œ ์ œ์™ธ๋œ๋‹คโ€๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, โ€œ์‚ฌ์ดŒ๊ณผ ์˜จ ๊ฐ€์กฑ์ด ์ฑ…์ž„์˜ ๋งค์šฐ ๊ธด ๊ธธ์„ ๊ฐ€๋Š” ๋ฐ ์–ด๋–ป๊ฒŒ ๋„์šธ ์ˆ˜ ์žˆ์„๊นŒ?โ€์— ์ดˆ์ ์ด ๋งž์ถฐ์ ธ ์žˆ๋‹ค. ์ง„์‹ค ์ด์ „์— ๊ทธ๊ฐ€ ๊ฐ€์กฑ๊ณผ ์ž๋…€์—๊ฒŒ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋Š” ๋‹ค๋ฅธ ๊ธ์ •์ ์ธ ๊ฒƒ๋“ค์ด ์žˆ์„ ์ˆ˜๋„ ์žˆ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค.

โ€˜์‹ ๋ขฐํ•  ์ˆ˜ ์—†๋Š” ๊ฐ€์กฑ ๊ตฌ์„ฑ์›โ€™๊ณผ์˜ ๊ณต์กด

๊ฒŒ์Šจ์€ ์‚ฌ์ดŒ ์•จ๋Ÿฐ์˜ ์Šต๊ด€์ ์ธ ๊ฑฐ์ง“๋ง๊ณผ ์กฐ์ž‘์ ์ธ ํ–‰๋™(์ž๋…€๋ฅผ ๋‚ฉ์น˜ํ•˜๊ณ , ์ „์ฒ˜๋ฅผ ์‚ดํ•ดํ•˜๋ ค ํ•˜๋ฉด์„œ ์–‘์œก๊ถŒ ํ•ฉ์˜๋ฅผ ๊ฐ€์žฅํ•˜๊ณ , FBI์—๊ฒŒ ์กฐ์ž‘๋‹นํ–ˆ๋‹ค๊ณ  ์ฃผ์žฅํ•˜๋Š” ๋“ฑ) ๋•Œ๋ฌธ์— ๊ทธ๋ฅผ ์‹ ๋ขฐํ•˜๊ธฐ ์–ด๋ ต๋‹ค๊ณ  ๊ณ ๋ฐฑํ•œ๋‹ค. ๊ทธ๋Š” ์•จ๋Ÿฐ์˜ 35์‹œ๊ฐ„์— ๊ฑธ์นœ ์ธํ„ฐ๋ทฐ๊ฐ€ ์ž์‹ ์„ ์กฐ์ž‘ํ•˜๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด์—ˆ์„๊นŒ ๋‘๋ ค์›Œํ•˜๋ฉฐ, ์ด๋Ÿฌํ•œ ๋ถ„๋…ธ ๋•Œ๋ฌธ์— โ€œํ„ฐ๋ฌด๋‹ˆ์—†์–ด ๋ณด์ด๋Š” ์ง„์‹ค ์š”๊ตฌโ€๋ฅผ ํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ๋งํ•œ๋‹ค.

ํ•ด๋ฆฌ์—‡์€ ์กฐ์ž‘๋‹นํ•˜๋Š” ๊ฒƒ์ด โ€œ๋ถ„๋…ธ๋ฅผ ์œ ๋ฐœํ•œ๋‹คโ€๋Š” ๊ฒŒ์Šจ์˜ ๋ง์— ๊ณต๊ฐํ•˜๋ฉด์„œ๋„, โ€œ๊ฑฐ์ง“๋ง๊ณผ ์กฐ์ž‘์˜ ์˜์—ญ์—์„œ, ๊ทธ๊ฒƒ๋“ค์€ ๋‚ด๊ฐ€ ์ž๋ผ๋ฉด์„œ ๊ฒช์—ˆ๋˜ ๋ฌธ์ œ ํ–‰๋™์˜ ์ผ๋ถ€์˜€๋‹คโ€๊ณ  ๋งํ•œ๋‹ค. ๊ทธ๋…€๋Š” โ€œ๊ฐ€์กฑ ๋‚ด์—์„œ ๊ทธ์˜ ์—ญํ• ์— ๋Œ€ํ•œ ์ตœ์„ ์˜ ๋ฒ„์ „์€ ๋ฌด์—‡์ธ๊ฐ€?โ€๋ผ๋Š” ์งˆ๋ฌธ์„ ๋˜์ง„๋‹ค. ๊ทธ๋ฅผ ์‹ ๋ขฐํ•˜์ง€ ์•Š๋Š”๋‹ค๋ฉด, ๊ทธ๋ ‡๊ฒŒ ํ•˜๋ผ. ๊ทธ๋ฅผ ์ž๋…€์™€ ๋‹จ๋‘˜์ด ๋‘์ง€ ๋งˆ๋ผ. ๊ทธ๊ฐ€ ์ถœ์†Œํ–ˆ์„ ๋•Œ ๊ทธ ์—ญ๋™์„ฑ์„ ์™„ํ™”ํ•  ์ˆ˜ ์žˆ๋„๋ก ์˜†์— ์žˆ์–ด ์ฃผ๊ฒ ๋‹ค๊ณ  ์ œ์•ˆํ•˜๋ผ. ํ”„๋ฆฌ์‹ค๋ผ์— ๋Œ€ํ•ด ์‹ ๋ขฐํ•˜์ง€ ์•Š๋Š”๋‹ค๋ฉด, ๊ทธ๋…€๋ฅผ ๋Œ๋ณด๋Š” ๋ฐ ๋„์›€์„ ์ฃผ๋ผ. ํ•ด๋ฆฌ์—‡์€ โ€œ์•„์ง ์‹ ๋ขฐ๋ฅผ ์–ป์ง€ ๋ชปํ•œ ์‚ฌ๋žŒ๋“ค์—๊ฒŒ ์‹ ๋ขฐ๋ฅผ ์ฃผ๋ผ๊ณ  ์ œ์•ˆํ•˜๋Š” ๊ฒƒ์ด ๊ฒฐ์ฝ” ์•„๋‹ˆ๋‹คโ€๋ผ๊ณ  ๋ช…ํ™•ํžˆ ๋ฐํžŒ๋‹ค. ์šฐ๋ฆฌ๋Š” ํ•ญ์ƒ ํ˜„์‹ค์„ ๋ƒ‰์ฒ ํ•˜๊ฒŒ ์ง์‹œํ•ด์•ผ ํ•œ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค.

๊ทธ๋Ÿฌ๋‚˜ ๊ฐ๊ธˆ ๋…ผ๋ฆฌ๊ฐ€ โ€œ์ด ์‚ฌ๋žŒ์€ ๋ฌธ์ œ๋ฅผ ์ผ์œผ์ผฐ์œผ๋‹ˆ ์ œ๊ฑฐํ•˜๋Š” ๊ฒƒ์ด ํ•ด๊ฒฐ์ฑ…์ด๋‹คโ€๋ผ๊ณ  ๋งํ•˜๋Š” ๋ฐ˜๋ฉด, ํ•ด๋ฆฌ์—‡์€ โ€œ๊ทธ๊ฒƒ์ด ์œ ์ผํ•œ ํ•ด๊ฒฐ์ฑ…์ด๋ผ๊ณ  ๋ฏฟ์ง€ ์•Š๋Š”๋‹คโ€๊ณ  ๋งํ•œ๋‹ค. ๊ทธ๋…€๋Š” โ€œ์‹ ๋ขฐํ•  ์ˆ˜ ์—†๋Š” ๊ฐ€์กฑ ๊ตฌ์„ฑ์›, ๊ฑฐ์ง“๋ง์„ ํ•˜๋Š” ๊ฐ€์กฑ ๊ตฌ์„ฑ์›, ์‚ฌ๋žŒ๋“ค์„ ์กฐ์ž‘ํ•˜๋ ค ํ•˜๋Š” ๊ฐ€์กฑ ๊ตฌ์„ฑ์›์ด ์žˆ๋‹ค๋Š” ์‚ฌ์‹ค์— ๋Œ€ํ•ด ์ง‘๋‹จ์ ์ธ ํ•ด๊ฒฐ์ฑ…์„ ์ฐพ์•„์•ผ ํ•œ๋‹คโ€๊ณ  ์ฃผ์žฅํ•œ๋‹ค. ๊ฐ€์กฑ์€ ๋ฌธ์ž ๊ทธ๋Œ€๋กœ ๊ทธ๋ฆฌ๊ณ  ๋น„์œ ์ ์œผ๋กœ ๋ชจ๋‘๋ฅผ ์•ˆ์ „ํ•˜๊ฒŒ ์ง€ํ‚ค๋Š” ๋ฐฉ๋ฒ•์„ ์ฐพ์•„์•ผ ํ•˜๋ฉฐ, ๋™์‹œ์— ์„œ๋กœ๋ฅผ ์ฆ๊ธธ ์ˆ˜ ์žˆ๋Š” ์‚ฌ๋žŒ๋“ค์„(๋‹น์‹ ๊ณผ ์‚ฌ์ดŒ์ด ์•„๋‹์ง€๋ผ๋„) ์ฆ๊ธธ ์ˆ˜ ์žˆ๋„๋ก ํ•ด์•ผ ํ•œ๋‹ค. ๊ฐ€์žฅ ์‹œ๊ธ‰ํ•˜๊ฒŒ๋Š” ์•จ๋Ÿฐ๊ณผ ๊ทธ์˜ ์ž๋…€๋“ค์ด๋‹ค.

ํ•ด๋ฆฌ์—‡์€ ๊ฒŒ์Šจ์—๊ฒŒ โ€œ๋‹น์‹ ์€ ๊ฑฐ์ง“๋ง์„ ํ•œ ์ ์ด ์žˆ๋‚˜์š”? ์‚ฌ๋žŒ๋“ค์„ ์กฐ์ž‘ํ•œ ์ ์ด ์žˆ๋‚˜์š”?โ€๋ผ๊ณ  ๋ฌป๋Š”๋‹ค. ๊ฒŒ์Šจ์€ ๊ทธ๋ ‡๋‹ค๊ณ  ๋‹ตํ•œ๋‹ค. ํ•ด๋ฆฌ์—‡์€ โ€œ์šฐ๋ฆฌ ๋ชจ๋‘๋Š” ํ•ด๋ฅผ ๋ผ์น  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์ด ์žˆ๋‹คโ€๊ณ  ์ง€์ ํ•˜๋ฉฐ, ๊ฐ๊ธˆ ๋…ผ๋ฆฌ๊ฐ€ ์ฃ„์•… ๋œ ํ–‰๋™์„ ํŠน์ • ์ง‘๋‹จ์—๋งŒ ์†ํ•œ ๊ฒƒ์œผ๋กœ ๊ฐ„์ฃผํ•˜๋ ค ํ•œ๋‹ค๊ณ  ๋น„ํŒํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ์„œ๋กœ ๊ด€๊ณ„๋ฅผ ๋งบ๊ณ  ์žˆ๋‹ค๋Š” ์ง„์‹ค ์†์— ์žˆ์–ด์•ผ ํ•˜๋ฉฐ, ๊ทธ ๊ด€๊ณ„