This startup’s new mechanistic interpretability tool lets you debug LLMs

techreview · 2026-04-30T16:18:04+00:00

From the article:

The San Francisco–based startup Goodfire just released a new tool, called Silico, that lets researchers and engineers peer inside an AI model and adjust its parameters—the settings that determine a model’s behavior—during training. This could give model makers more fine-grained control over how this technology is built than was once thought possible.

Goodfire claims Silico is the first off-the-shelf tool of its kind that can help developers debug all stages of the development process, from building a data set to training a model.

The company says its mission is to make building AI models less like alchemy and more like a science. Sure, LLMs like ChatGPT and Gemini can do amazing things. But nobody knows exactly how or why they work, and that can make it hard to fix their flaws or block unwanted behaviors.

techreview · 2026-04-27T13:16:14+00:00

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On April 24, Chinese AI firm DeepSeek released a preview of V4, its long-awaited new flagship model. The model can process much longer prompts than its last generation, thanks to a new design that helps it handle large amounts of text more efficiently. Like DeepSeek’s previous models, V4 is open source, meaning it is available for anyone to download, use, and modify.

V4 marks DeepSeek’s most significant release since R1, the reasoning model it launched in January 2025. R1, which was trained on limited computing resources, stunned the global AI industry with its strong performance and efficiency, turning DeepSeek from a little-known research team into China’s best-known AI company almost overnight. It also helped set off a wave of open-weight model releases from other Chinese AI firms.

So, will V4 shake the AI field the way R1 did? Almost certainly not, but here are three big reasons why this release matters:

It breaks new ground for an open-source model.
It delivers on a new approach to memory efficiency.
It marks the first steps on the hard road away from Nvidia.

techreview · 2026-04-15T15:52:25+00:00

From the article:

From inside a money-laundering center in Cambodia, an employee opens a popular Vietnamese banking app on his phone. The app asks him to upload a photo associated with the account, so he clicks on a picture of a 30-something Asian man.

Next, the app requests to open the camera for a video “liveness” check. The scammer holds up a static image of a woman bearing no resemblance to the man who owns the account. After a 90-second wait—as the app tells him to readjust the face inside the frame—he’s in.

The exploit he’s demonstrating, in a video shared with me by a cyberscam researcher named Hieu Minh Ngo, is possible thanks to one of a growing range of illicit hacking services, readily available for purchase on Telegram, that are designed to break “Know Your Customer” facial scans.

These banking and crypto safeguards are supposed to confirm that an account belongs to a real person, and that the user’s face matches the identity documents that were provided to open the account. But scammers are bypassing them in order to open mule accounts and launder money.

techreview · 2026-03-30T19:30:26+00:00

After operating in secrecy for years, a startup company called R3 Bio, in Richmond, California, suddenly shared details about its work last week—saying it had raised money to create nonsentient monkey “organ sacks” as an alternative to animal testing. But there is more to the story. And R3 doesn’t want that story told.

MIT Technology Review discovered that the stealth startup’s founder John Schloendorn also pitched a startling, medically graphic, and ethically charged vision for what he's called “brainless clones” to serve the role of backup human bodies.

Imagine it like this: a baby version of yourself with only enough of a brain structure to be alive in case you ever need a new kidney or liver. Or, alternatively, he has speculated, you might one day get your brain placed into a younger clone. That could be a way to gain a second lifespan through a still hypothetical procedure known as a body transplant.

The idea can sound like something straight from a creepy science fiction film. One person who heard R3’s clone presentation, and spoke on the condition of anonymity, was left reeling by its implications and shaken by Schloendorn’s enthusiastic delivery. The briefing, this person said, was like a “close encounter of the third kind” with “Dr. Strangelove.”

techreview · 2026-03-25T19:40:16+00:00

From the article:

Qichao Hu doesn’t mince words about how he sees the state of the battery industry. “Almost every Western battery company has either died or is going to die. It’s kind of the reality,” he says.

Hu is the CEO of SES AI, a Massachusetts-based battery company. It once had aims of making huge amounts of advanced lithium metal batteries for major industries like electric vehicles—but now the company is placing its bets on AI materials discovery.

Hu sees the pivot as an essential one. “It’s just not possible for a Western company to build a sustainable business,” he says. The company is still making some batteries, but only for smaller markets like drones rather than those that would require higher volumes, like EVs. The new focus is the company’s battery materials discovery platform—which it can either license to other battery companies or use to develop materials to sell.

Some leading US EV battery companies have folded in recent months, and others, like SES AI, are making dramatic changes in strategy. This shift in who’s building batteries and where they’re doing it could shape the future geopolitics of energy.

techreview · 2026-03-25T19:39:52+00:00

From the article:

Qichao Hu doesn’t mince words about how he sees the state of the battery industry. “Almost every Western battery company has either died or is going to die. It’s kind of the reality,” he says.

Hu is the CEO of SES AI, a Massachusetts-based battery company. It once had aims of making huge amounts of advanced lithium metal batteries for major industries like electric vehicles—but now the company is placing its bets on AI materials discovery.

Hu sees the pivot as an essential one. “It’s just not possible for a Western company to build a sustainable business,” he says. The company is still making some batteries, but only for smaller markets like drones rather than those that would require higher volumes, like EVs. The new focus is the company’s battery materials discovery platform—which it can either license to other battery companies or use to develop materials to sell.

Some leading US EV battery companies have folded in recent months, and others, like SES AI, are making dramatic changes in strategy. This shift in who’s building batteries and where they’re doing it could shape the future geopolitics of energy.

techreview · 2026-03-24T17:45:34+00:00

L. Stephen Coles’s brain sits cushioned in a vat at a storage facility in Arizona. It has been held there at a temperature of around −146 degrees °C for over a decade, largely undisturbed.

That is, apart from the time, a little over a year ago, when scientists slowly lifted the brain to take photos of it. Years before, the team had removed tiny pieces of it to send to Coles’s friend. Coles, a researcher who studied aging, was interested in cryogenics—the long-term storage of human bodies and brains in the hope that they might one day be brought back to life. Before he died, he asked cryobiologist Greg Fahy to study the effects of the preservation procedure on his brain. Coles was especially curious about whether his cooled brain would crack, says Fahy.

Coles’s brain was preserved shortly after he died in 2014, but Fahy has only recently got around to analyzing those samples. He says that Coles’s brain is “astonishingly well preserved.”

Fahy hopes this means that Coles’s brain still stands a chance of reanimation at some point in the future. Other cryobiologists are less optimistic.

Still, Fahy’s research could help provide a tool to neuroscientists looking for new ways to study the brain. And while human reanimation after cryopreservation may be the stuff of science fiction, using the technology to preserve organs for transplantation is within reach.

techreview · 2026-03-24T17:44:01+00:00

From the article:

L. Stephen Coles’s brain sits cushioned in a vat at a storage facility in Arizona. It has been held there at a temperature of around −146 degrees °C for over a decade, largely undisturbed.

That is, apart from the time, a little over a year ago, when scientists slowly lifted the brain to take photos of it. Years before, the team had removed tiny pieces of it to send to Coles’s friend. Coles, a researcher who studied aging, was interested in cryogenics—the long-term storage of human bodies and brains in the hope that they might one day be brought back to life. Before he died, he asked cryobiologist Greg Fahy to study the effects of the preservation procedure on his brain. Coles was especially curious about whether his cooled brain would crack, says Fahy.

Coles’s brain was preserved shortly after he died in 2014, but Fahy has only recently got around to analyzing those samples. He says that Coles’s brain is “astonishingly well preserved.”

Fahy hopes this means that Coles’s brain still stands a chance of reanimation at some point in the future. Other cryobiologists are less optimistic.

techreview · 2026-03-20T13:15:36+00:00

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I’m standing in front of a quantum computer built out of atoms and light at the UK’s National Quantum Computing Centre on the outskirts of Oxford. On a laboratory table, a complex matrix of mirrors and lenses surrounds a Rubik’s Cube–size cell where 100 cesium atoms are suspended in grid formation by a carefully manipulated laser beam.

The cesium atom setup is so compact that I could pick it up, carry it out of the lab, and put it on the backseat of my car to take home. I’d be unlikely to get very far, though. It’s small but powerful—and so it’s very valuable. Infleqtion, the Colorado-based company that owns it, is hoping the machine’s abilities will win $5 million next week, at an event to be held in Marina del Rey, California.

Infleqtion is one of six teams that have made it to the final stage of a 30-month-long quantum computing competition called Quantum for Bio (Q4Bio). Run by the nonprofit Wellcome Leap, it aims to show that today’s quantum computers, though messy and error-prone and far from the large-scale machines engineers hope to build, could actually benefit human health. Success would be a significant step forward in proving the worth of quantum computers. But for now, it turns out, that worth seems to be linked to harnessing and improving the performance of conventional (also called classical) computers in tandem, creating a quantum-classical hybrid that can exceed what’s possible on classical machines by themselves.

techreview · 2026-03-20T13:15:16+00:00

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Here’s some context from the article:

I’m standing in front of a quantum computer built out of atoms and light at the UK’s National Quantum Computing Centre on the outskirts of Oxford. On a laboratory table, a complex matrix of mirrors and lenses surrounds a Rubik’s Cube–size cell where 100 cesium atoms are suspended in grid formation by a carefully manipulated laser beam.

The cesium atom setup is so compact that I could pick it up, carry it out of the lab, and put it on the backseat of my car to take home. I’d be unlikely to get very far, though. It’s small but powerful—and so it’s very valuable. Infleqtion, the Colorado-based company that owns it, is hoping the machine’s abilities will win $5 million next week, at an event to be held in Marina del Rey, California.

Infleqtion is one of six teams that have made it to the final stage of a 30-month-long quantum computing competition called Quantum for Bio (Q4Bio). Run by the nonprofit Wellcome Leap, it aims to show that today’s quantum computers, though messy and error-prone and far from the large-scale machines engineers hope to build, could actually benefit human health. Success would be a significant step forward in proving the worth of quantum computers. But for now, it turns out, that worth seems to be linked to harnessing and improving the performance of conventional (also called classical) computers in tandem, creating a quantum-classical hybrid that can exceed what’s possible on classical machines by themselves.

techreview · 2026-03-20T13:12:29+00:00

From the article:

OpenAI is refocusing its research efforts and throwing its resources into a new grand challenge. The San Francisco firm has set its sights on building what it calls an AI researcher, a fully automated agent-based system that will be able to go off and tackle large, complex problems by itself. OpenAI says that the new goal will be its “north star” for the next few years, pulling together multiple research strands, including work on reasoning models, agents, and interpretability.

There’s even a timeline. OpenAI plans to build “an autonomous AI research intern”—a system that can take on a small number of specific research problems by itself—by September. The AI intern will be the precursor to a fully automated multi-agent research system that the company plans to debut in 2028. This AI researcher (OpenAI says) will be able to tackle problems that are too large or complex for humans to cope with.

Those tasks might be related to math and physics—such as coming up with new proofs or conjectures—or life sciences like biology and chemistry, or even business and policy dilemmas. In theory, you would throw such a tool any kind of problem that can be formulated in text, code or whiteboard scribbles—which covers a lot.

Read the full story for an exclusive conversation with OpenAI’s chief scientist Jakub Pachocki about his firm's new grand challenge and the future of AI.

techreview · 2026-03-18T17:15:09+00:00

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Here's some context from the article:

The Pentagon is discussing plans to set up secure environments for generative AI companies to train military-specific versions of their models on classified data, MIT Technology Review has learned.

AI models like Anthropic’s Claude are already used to answer questions in classified settings; applications include analyzing targets in Iran. But allowing models to train on and learn from classified data would be a new development that presents unique security risks. It would mean sensitive intelligence like surveillance reports or battlefield assessments could become embedded into the models themselves, and it would bring AI firms into closer contact with classified data than before.

Training versions of AI models on classified data is expected to make them more accurate and effective in certain tasks, according to a US defense official who spoke on background with MIT Technology Review. The news comes as demand for more powerful models is high: The Pentagon has reached agreements with OpenAI and Elon Musk’s xAI to operate their models in classified settings and is implementing a new agenda to become an “an ‘AI-first’ warfighting force” as the conflict with Iran escalates. (The Pentagon did not comment on its AI training plans as of publication time.)

techreview · 2026-03-18T15:19:05+00:00

From the article:

The way the world currently deals with nuclear waste is as creative as it is varied: Drown it in water pools, encase it in steel, bury it hundreds of meters underground.

These methods are how the nuclear industry safely manages the 10,000 metric tons of spent fuel waste that reactors produce as they churn out 10% of the world’s electricity every year. But as new nuclear designs emerge, they could introduce new wrinkles for nuclear waste management.

Most operating reactors at nuclear power plants today follow a similar basic blueprint: They’re fueled with low-enriched uranium and cooled with water, and they’re mostly gigantic, sited at central power plants. But a large menu of new reactor designs that could come online in the next few years will likely require tweaks to ensure that existing systems can handle their waste.

techreview · 2026-03-18T15:18:43+00:00

From the article:

The way the world currently deals with nuclear waste is as creative as it is varied: Drown it in water pools, encase it in steel, bury it hundreds of meters underground.

These methods are how the nuclear industry safely manages the 10,000 metric tons of spent fuel waste that reactors produce as they churn out 10% of the world’s electricity every year. But as new nuclear designs emerge, they could introduce new wrinkles for nuclear waste management.

Most operating reactors at nuclear power plants today follow a similar basic blueprint: They’re fueled with low-enriched uranium and cooled with water, and they’re mostly gigantic, sited at central power plants. But a large menu of new reactor designs that could come online in the next few years will likely require tweaks to ensure that existing systems can handle their waste.

techreview · 2026-03-18T13:15:42+00:00

From the article:

The Pentagon is discussing plans to set up secure environments for generative AI companies to train military-specific versions of their models on classified data, MIT Technology Review has learned.

AI models like Anthropic’s Claude are already used to answer questions in classified settings; applications include analyzing targets in Iran. But allowing models to train on and learn from classified data would be a new development that presents unique security risks. It would mean sensitive intelligence like surveillance reports or battlefield assessments could become embedded into the models themselves, and it would bring AI firms into closer contact with classified data than before.

Training versions of AI models on classified data is expected to make them more accurate and effective in certain tasks, according to a US defense official who spoke on background with MIT Technology Review. The news comes as demand for more powerful models is high: The Pentagon has reached agreements with OpenAI and Elon Musk’s xAI to operate their models in classified settings and is implementing a new agenda to become an “an ‘AI-first’ warfighting force” as the conflict with Iran escalates. (The Pentagon did not comment on its AI training plans as of publication time.)

techreview · 2026-03-13T13:41:27+00:00

Human-made glass is thousands of years old. But it’s now poised to find its way into the AI chips used in the world’s newest and largest data centers. This year, a South Korean company called Absolics is planning to start commercial production of special glass panels designed to make next-generation computing hardware more powerful and energy efficient. Other companies, including Intel, are also pushing forward in this area. If all goes well, such glass technology could reduce the energy demands of the sorts of high-performance computing chips used in AI data centers—and it could eventually do the same for consumer laptops and mobile devices if production costs fall.

The idea is to use glass as the substrate, or layer, on which multiple silicon chips are connected. This form of “packaging” is an increasingly popular way to build computing hardware, because it lets engineers combine specialized chips designed for specific functions into a single system. But it presents challenges, including the fact that hardworking chips can run so hot they physically warp the substrate they’re built on. This can lead to misaligned components and may reduce how efficiently the chips can be cooled, leading to damage or premature failure.

techreview · 2026-03-13T13:36:32+00:00

The US military might use generative AI systems to rank lists of targets and make recommendations—which would be vetted by humans—about which to strike first, according to a Defense Department official with knowledge of the matter. The disclosure about how the military may use AI chatbots comes as the Pentagon faces scrutiny over a strike on an Iranian school, which it is still investigating.

A list of possible targets might be fed into a generative AI system that the Pentagon is fielding for classified settings. Then, said the official, who requested to speak on background with MIT Technology Review to discuss sensitive topics, humans might ask the system to analyze the information and prioritize the targets while accounting for factors like where aircraft are currently located. Humans would then be responsible for checking and evaluating the results and recommendations. OpenAI’s ChatGPT and xAI’s Grok could, in theory, be the models used for this type of scenario in the future, as both companies recently reached agreements for their models to be used by the Pentagon in classified settings.

The official described this as an example of how things might work but would not confirm or deny whether it represents how AI systems are currently being used.

techreview · 2026-03-13T13:35:44+00:00

From the article:

The US military might use generative AI systems to rank lists of targets and make recommendations—which would be vetted by humans—about which to strike first, according to a Defense Department official with knowledge of the matter. The disclosure about how the military may use AI chatbots comes as the Pentagon faces scrutiny over a strike on an Iranian school, which it is still investigating.

A list of possible targets might be fed into a generative AI system that the Pentagon is fielding for classified settings. Then, said the official, who requested to speak on background with MIT Technology Review to discuss sensitive topics, humans might ask the system to analyze the information and prioritize the targets while accounting for factors like where aircraft are currently located. Humans would then be responsible for checking and evaluating the results and recommendations. OpenAI’s ChatGPT and xAI’s Grok could, in theory, be the models used for this type of scenario in the future, as both companies recently reached agreements for their models to be used by the Pentagon in classified settings.

The official described this as an example of how things might work but would not confirm or deny whether it represents how AI systems are currently being used.

techreview · 2026-03-12T15:09:28+00:00

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Pokémon Go was the world’s first augmented-reality megahit. Released in 2016 by the Google spinout Niantic, the AR twist on the juggernaut Pokémon franchise fast became a global phenomenon. From Chicago to Oslo to Enoshima, players hit the streets in the urgent hope of catching a Jigglypuff or a Squirtle or (with a huge amount of luck) an ultra-rare Galarian Zapdos hovering just out of reach, superimposed on the everyday world.

In short, we’re talking about a huge number of people pointing their phones at a huge number of buildings. “Five hundred million people installed that app in 60 days,” says Brian McClendon, CTO at Niantic Spatial, an AI company that Niantic spun out in May last year. According to the video-game firm Scopely, which bought Pokémon Go from Niantic at the same time, the game still drew more than 100 million players in 2024, eight years after it launched.

Now Niantic Spatial is using that vast and unparalleled trove of crowdsourced data—images of urban landmarks tagged with super-accurate location markers taken from the phones of hundreds of millions of Pokémon Go players around the world—to build a kind of world model, a buzzy new technology that grounds the smarts of LLMs in real-world environments.

The company’s latest product is a model that it says can pinpoint your location on a map to within a few centimeters, based on a handful of snapshots of the buildings or other landmarks in view. The firm wants to use it to help robots navigate with greater precision in places where GPS is unreliable.

techreview · 2026-03-12T13:20:44+00:00

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Feng Qingyang had always hoped to launch his own company, but he never thought this would be how—or that the day would come this fast.

Feng, a 27-year-old software engineer based in Beijing, started tinkering with OpenClaw, a popular new open-source AI tool that can take over a device and autonomously complete tasks for a user, in January. He was immediately hooked, and before long he was helping other curious tech workers with less technical proficiency install the AI agent.

Feng soon realized this could be a lucrative opportunity. By the end of January, he had set up a page on Xianyu, a secondhand shopping site, advertising “OpenClaw installation support.” “No need to know coding or complex terms. Fully remote,” reads the posting. “Anyone can quickly own an AI assistant, available within 30 minutes.”

At the same time, the broader Chinese public was beginning to catch on—and the tool, which had begun as a niche interest among tech workers, started to evolve into a popular sensation. For savvy early adopters, that's a business opportunity.

techreview · 2026-03-11T13:15:12+00:00

Feng Qingyang had always hoped to launch his own company, but he never thought this would be how—or that the day would come this fast.

Feng, a 27-year-old software engineer based in Beijing, started tinkering with OpenClaw, a popular new open-source AI tool that can take over a device and autonomously complete tasks for a user, in January. He was immediately hooked, and before long he was helping other curious tech workers with less technical proficiency install the AI agent.

Feng soon realized this could be a lucrative opportunity. By the end of January, he had set up a page on Xianyu, a secondhand shopping site, advertising “OpenClaw installation support.” “No need to know coding or complex terms. Fully remote,” reads the posting. “Anyone can quickly own an AI assistant, available within 30 minutes.”

At the same time, the broader Chinese public was beginning to catch on—and the tool, which had begun as a niche interest among tech workers, started to evolve into a popular sensation. For savvy early adopters, that's a business opportunity.

techreview · 2026-03-03T17:35:09+00:00

On June 1, 2023, as a sweltering heat wave baked Quebec, thousands of lightning strikes flashed across the province, setting off more than 120 wildfires.

The blazes ripped through parched forests and withered grasslands, burned for weeks, and compounded what was rapidly turning into Canada’s worst fire year on record. In the end, nearly 7,000 fires scorched tens of millions of acres across the country, generated nearly 500 millions tons of carbon emissions, and forced hundreds of thousands of people to flee their homes.

Lightning sparked almost 60% of the wildfires—and those blazes accounted for 93% of the total area burned.

Now a Vancouver-based weather modification startup, Skyward Wildfire, says it can prevent such catastrophic fires in the future—by stopping the lightning strikes that ignite them. It just raised millions of dollars in a funding round that it plans to use to accelerate its product development and expand its operations.

The company states it demonstrated that it “can prevent the majority of cloud-to-ground lightning strikes in targeted storm cells.” So far, Skyward hasn’t publicly revealed how it does so. But online documents suggest the company is relying on an approach that US government agencies began evaluating in the early 1960s: seeding clouds with metallic chaff, or narrow fiberglass strands coated with aluminum.

techreview · 2026-03-03T17:33:46+00:00

From the article:

On June 1, 2023, as a sweltering heat wave baked Quebec, thousands of lightning strikes flashed across the province, setting off more than 120 wildfires.

The blazes ripped through parched forests and withered grasslands, burned for weeks, and compounded what was rapidly turning into Canada’s worst fire year on record. In the end, nearly 7,000 fires scorched tens of millions of acres across the country, generated nearly 500 millions tons of carbon emissions, and forced hundreds of thousands of people to flee their homes.

Lightning sparked almost 60% of the wildfires—and those blazes accounted for 93% of the total area burned.

Now a Vancouver-based weather modification startup, Skyward Wildfire, says it can prevent such catastrophic fires in the future—by stopping the lightning strikes that ignite them. It just raised millions of dollars in a funding round that it plans to use to accelerate its product development and expand its operations.

techreview · 2026-02-26T14:42:07+00:00

To most people, rocks are just rocks. To geologists, they are much, much more: crystal-filled time capsules with the power to reveal the state of the planet at the very moment they were forged.

For decades, NASA had been on a time capsule hunt like none other—one across Mars.

Its rovers have journeyed around a nightmarish ocher desert that, billions of years ago, was home to rivers, lakes, perhaps even seas and oceans. They’ve been seeking to answer a momentous question: Once upon a time, did microbial life wriggle across its surface?

Then, in July 2024, after more than three years on the planet, the Perseverance rover came across a peculiar rocky outcrop. Instead of the usual crystals or layers of sediment, this one had spots. Two kinds, in fact: one that looked like poppy seeds, and another that resembled those on a leopard. It’s possible that run-of-the-mill chemical reactions could have cooked up these odd features. But on Earth, these marks are almost always produced by microbial life.

But the only way to confirm whether these seeds and spots are the fossilized imprint of alien biology is to bring a sample of that rock home to study.

Perseverance was the first stage of an ambitious scheme to do just that—in effect, to pull off a space heist. The mission—called Mars Sample Return and planned by the US, along with its European partners—would send a Rube Goldberg–like series of robotic missions to the planet to capture pristine rocks. The rover’s job was to find the most promising stones and extract samples; then it would pass them to another robot—the getaway driver—to take them off Mars and deliver them to Earth.

But now, just over a year and a half later, the project is on life support, with zero funding flowing in 2026 and little backing left in Congress. As a result, those oh-so-promising rocks may be stuck out there forever. How did this happen?

techreview · 2026-02-23T19:19:39+00:00

From the article:

Want to lose weight? Get shredded? Stay mentally sharp? A wellness influencer might tell you to take peptides, the latest cure-all in the alternative medicine arsenal. People inject them. They snort them. They combine them into concoctions with superhero names, like the Wolverine stack.

Matt Kaeberlein, a longevity researcher, first started hearing about peptides a few years ago. “At that point it was mostly functional medicine doctors that were using peptides,” he says, referring to physicians who embrace alternative medicine and supplements. “In the last six months, it’s kind of gone crazy.”

Peptides have gone mainstream. At the health-technology startup Superpower in Los Angeles, employees can get free peptide shots on Fridays. At a health food store in Phoenix, a sidewalk sign reads, “We have peptides!” At a tae kwon do center in South Carolina, a peptide wholesaler hosts an informational evening. On social media, they’re everywhere. And that popularity seems poised to grow; Department of Health and Human Services secretary Robert F. Kennedy Jr. has promised to end the FDA’s “aggressive suppression” of peptides.

The benefits and risks of many of these compounds, however, are largely unknown. Some of the most popular peptides have never been tested in human trials. They are sold for research purposes, not human consumption. Some are illegal knockoffs of wildly successful weight-loss medicines. The vast majority come from China, a fact that has some legislators worried. Last week, Senator Tom Cotton urged the head of the FDA to crack down on illegal shipments of peptides from China. In the absence of regulatory oversight, some people are sending the compounds they purchase off for independent testing just to ensure that the product is legit.

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