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I Was There When: Facebook put profits over safety

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I Was There When: Facebook put profits over safety


Facebook has been under intense fire following revelations that the social media giant’s leadership repeatedly prioritized profits over safety. Now, a second whistleblower is accusing the company of turning a blind eye to disinformation campaigns on the platform. In this episode, we meet Sophie Zhang—a former data scientist at Facebook. Before she was fired, she had become consumed by the task of finding and taking down fake accounts that were being used to sway elections globally.

I Was There When is a new oral history project from the In Machines We Trust podcast. It features stories of how breakthroughs in artificial intelligence and computing happened, as told by the people who witnessed them.

Credits:

This episode was produced by Jennifer Strong, Anthony Green and Emma Cillekens. It’s edited by Michael Reilly and Mat Honan. It’s mixed by Garret Lang, with sound design and music by Jacob Gorski.

Full transcript:

[TR ID]

SOT: Frances Haugen: During my time at Facebook, I came to realize a devastating truth. Almost no one outside of Facebook knows what happens inside of Facebook. 

Jennifer: Frances Haugen is a former product manager at Facebook. She’s filed complaints with federal law enforcement claiming the social media giant’s leadership has repeatedly put profit over safety.

SOT: Frances Haugen: The company intentionally hides vital information from the public, from the U.S. government, and from governments around the world. 

Jennifer: Her complaints came with a trove of documents that Haugen gathered before quitting… in an attempt to demonstrate the company had willfully chosen not to fix the problems on its platform.

Among them… that algorithms like the one behind your Facebook newsfeed amplify hate, misinformation and political unrest. 

And she’s not the only whistleblower accusing the company of turning a blind eye to disinformation campaigns on the platform. 

Sophie Zhang worked as a Facebook data scientist… and up until she was fired, she consumed herself with finding and taking down fake accounts, comments and likes that were being used to sway elections globally. Her blockbuster exit memo was 8-thousand words… and it revealed just how little Facebook had done to mitigate the problem. 

I’m Jennifer Strong, and this is I Was There When.

It’s an oral history project featuring the stories of how watershed moments in artificial intelligence and computing happened… as told by the people who witnessed them.

[Show ID]

Sophie Zhang: I’m Sophie Zhang. At Facebook I was a data scientist and I worked on the engagement team. By fake I mean, for instance, fake accounts, but also hacked accounts. And by engagement, I mean, likes, comments, shares, et cetera. But in my spare time, when I began moonlighting in the area of finding inauthentic political activity. Often very sophisticated, inauthentic political activity. I could argue that this was also fake engagement, but it was not what I was expected to work on. 

When I began to look into the intersections between fake engagement and civic activity, very quickly found results worldwide. I found results in, in Brazil, in India, in Indonesia, in many nations, but also in Honduras, quite a bit in Honduras actually relative to its size. And I was putting together a report for leadership on the problem. I meant to take a screenshot of the page of the major recipient in Honduras, Juan Orlando Hernández, who after I looked him up turned out to be the president of Honduras.

I was going to his page to take a screenshot when they suddenly stopped, because I noticed something very unusual because the people who were, who were liking his page and commenting, many of them were not people at all. They were pages pretending to be users. And so just to step back here, what are pages? What are users? Pages are a Facebook feature meant for public figures, public organizations, etc. So for instance, MIT Tech Review has a Facebook page. MIT Tech Review is not a person. The page is ran by someone else on Facebook. 

And so the intent of how Facebook pages are, is that they’re supposed to reflect public entities and a single user can control many pages. So for instance, the same administrator can control the CNN page as well as CNN, Philippines, and CNN Europe, etcetera. But there was nothing preventing a user from setting up hundreds of pages, giving them names and profile pictures like real people and having them act as real people. In fact, it was easier on their end because they could quite easily switch between these pages without needing to log in and log off every time. 

Quite quickly realized that these fake pages pretending to be users, there was thousands of them in Honduras. And a few hundred of them were personally run by the page administrator of the president of Honduras. This was someone who clearly had a significant amount of trust on social media in the Honduran government. And they were not even hiding the fact that they were using thousands of fake assets to manipulate their own citizenry. 

And so from the start, I was very naive. I thought that, okay, I found this. These people were stupid. We caught them. I will hand them over to others. They’ll take over it. I can cut back to my actual job and everything will be fine. It was instead the start of a two year sisyphean ordeal, because what happened when I raised it was everyone agreed that this was terrible. It was not controversial that this was bad. Everyone agreed that this should not be allowed, but the question was, what do we do about it? Do we have the ability to act on it? Is it within our policies to act on it, et cetera. From the start, I spoke about it to everyone who seemed to relate to it. I spoke about it to Pages Integrity, to Groups Integrity. I talked about it to the civic integrity team. I tried to get threat intelligence interested. Eventually I was talking to everyone who would listen. I spoke to everyone up to and including vice president Guy Rosen. Essentially it was like talking to the wind, like trying to empty the ocean with a colander. Eventually I figured out that the best way to get results was often not by trying to go through the proper channels, but by complaining publicly within the company on Workplace, which is essentially Facebook for the office, and making Workplace posts about the situation that others at the company could see. And many of them were of course upset about it because this was not the sort of company they thought they were working for and wanted to be working for. I don’t know whether it was by this means, by others, but eventually Facebook finally took down the operation of the Hondurian government, which was international news. 

A few weeks later, the operation came back using a different method. When we did get the take down in Honduras, I was still naive and idealistic at the start. I thought, okay, before this everyone was saying we didn’t have a precedent, we didn’t know what to do, but now we do have the precedent. Now we can say, we have created this precedent of doing this. We can solve it in this method. And so after this I thought, okay, I can send them over all the others that I found. They would take care of it. They did not take care of it. When I used the proper channels to send them over, they went essentially into a black box shredder where they were ignored. 

In the second half of 2019, I raised and flagged about three dozen more networks of inauthentic political activities from Afghanistan to Albania, from Brazil, to Bolivia, from India to Indonesia. And so it took a while to figure out the right way to actually get results and get people to actually respond. It depended on whether they were tied to politicians and prominent figures, because if something was tied to a political figure, it became much harder to take it down. I’m going to give you a number now that I did not leave when they first saw it. Because Azerbaijan certainly has less than 3% of the world’s population, much smaller, its network was creating perhaps a million comments every month. And this constituted something like 3% of all comments by Pages on posts by other Pages worldwide, globally, civic or non-civic. 

But even when I caught the Azerbajiani government red-handed, it took more than a year for the operation to be taken down. When I found that the Azerbaijan government had set up a massive toll farm of paid operatives to harass the opposition in large volumes. This was very clearly bad. It was very clearly tied to the Azerbajiani government. And it was massive in scale. But when we took it down, I’m sure somewhere at Facebook, there was a team that was very upset about why the numbers suddenly dropped for no reason that they could figure out. between my discovery and the take down Azerbaijan had cracked down on the opposition, arrested unimproved opposition figures, and started a war with Armenia. 

It became more and more stressful to work on the issue. It’s hard to, individually, to see what impact any of this had, but it quickly became clear that it was tied to activity in nations that were struggling because there was so much going on. And I was the one personally making decisions about what was important. It was essentially entirely up to me what I chose to go at further, what I chose to prioritize and try to get attention for. And I chose not to prioritize Bolivia because it was objectively very small and not very smart. Well after the election, there were mass protests that escalated into what has been called alternatively a coup d’etat or a popular uprising that resulted in the fall of the Bolivian government. I know that this should not have been personally my responsibility, but at the end of the day, there was no one else who stepped up. And so I chose to do it myself. And because I had put myself in this position, it was essentially up to myself, what was important enough to focus on, and I want to be clear. There were always others who were, who were in charge of refine my findings and in charge of actually taking it down at the end.

I decided from the start that I would only be the prosecutor, essentially, I would try my best to never be judge, jury and executioner, because I already had too much power in my hands. I don’t think anyone should be in the position of deciding if Albania is more important than Azerbaijan or questions like that. Because they also found in that book of accounts that were tied to supporting members of the Albanian government. But what I found in Azerbaijan was objectively worse in terms of size and scale. And so I knew I only had the political capital to very slowly push through one at a time. And so I chose to focus on Azerbaijan. It’s still going on in Albania. Albania had general elections earlier this year, and it was still going on at the time. I mean, more than two years after I discovered it, Facebook still hasn’t done anything.

And I can only apologize profusely to the Albanian people. I should not have been in a position in which I needed to choose was Albania or Azerbaijan more important. I stand by my decision because what they found in Azerbaijan was objectively worse, but still, no single person should be in charge of questions like this. There have been many news reports about how Facebook is under-resourced in the area of integrity. I haven’t seen any news reports complaining that Facebook has too little resources in ads marketing. And I think that states volumes about the company’s priorities at the end.

What I found most difficult was in certain authoritarian countries. The democratic opposition was benefiting from employing and savory tactics. And I had the most thought over those cases. But I still took them down without hesitation because I believed very firmly that my allegiance was to the ideas of democracy and the rule of law. And that fundamentally democracy cannot stand on a bed of lies. As a very low level employee in my own spare time, without any oversight whatsoever was making decisions personally, that directly affected national governments.

 It’s a hard question to answer what I believe should happen, because part of it is like, it’s like asking if you could make the sky any color, what color would you like it to be? Because it’s a, it’s a mostly theoretical question and your answer will have no real have no actual effect on the real world.

I can’t make Mark change his mind anymore than they can make the sky pink overnight. This is up to the people listening to me, to people like yourself, because I can’t change anything myself. I only have as much power as others grant me. If you want things to change, you should be personally asking your representatives because ultimately this is a problem that isn’t experienced by a few single people. This is the problem in which the costs are borne by society, by democracy, by civic discourse as a whole. And as a company, Facebook has no incentive to fix this anymore than we expected Philip Morris to develop non addictive cigarettes.

Jennifer: I Was There When is an oral history project featuring the stories of people who have witnessed or created breakthroughs in artificial intelligence and computing. 

Do you have a story to tell? Know someone who does? Drop us an email at podcasts at technology review dot com.

[MIDROLL]

[CREDITS]

Jennifer: This episode was produced by me with help from Anthony Green and Emma Cillekens. We’re edited by Niall Firth and Mat Honan. Our mix engineer is Garret Lang… and our theme music is by Jacob Gorski. 

Thanks for listening, I’m Jennifer Strong. 

[TR ID]

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Why I became a TechTrekker

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group jumps into the air with snowy mountains in the background


My senior spring in high school, I decided to defer my MIT enrollment by a year. I had always planned to take a gap year, but after receiving the silver tube in the mail and seeing all my college-bound friends plan out their classes and dorm decor, I got cold feet. Every time I mentioned my plans, I was met with questions like “But what about school?” and “MIT is cool with this?”

Yeah. MIT totally is. Postponing your MIT start date is as simple as clicking a checkbox. 

Sofia Pronina (right) was among those who hiked to the Katla Glacier during this year’s TechTrek to Iceland.

COURTESY PHOTO

Now, having finished my first year of classes, I’m really grateful that I stuck with my decision to delay MIT, as I realized that having a full year of unstructured time is a gift. I could let my creative juices run. Pick up hobbies for fun. Do cool things like work at an AI startup and teach myself how to create latte art. My favorite part of the year, however, was backpacking across Europe. I traveled through Austria, Slovakia, Russia, Spain, France, the UK, Greece, Italy, Germany, Poland, Romania, and Hungary. 

Moreover, despite my fear that I’d be losing a valuable year, traveling turned out to be the most productive thing I could have done with my time. I got to explore different cultures, meet new people from all over the world, and gain unique perspectives that I couldn’t have gotten otherwise. My travels throughout Europe allowed me to leave my comfort zone and expand my understanding of the greater human experience. 

“In Iceland there’s less focus on hustle culture, and this relaxed approach to work-life balance ends up fostering creativity. This was a wild revelation to a bunch of MIT students.”

When I became a full-time student last fall, I realized that StartLabs, the premier undergraduate entrepreneurship club on campus, gives MIT undergrads a similar opportunity to expand their horizons and experience new things. I immediately signed up. At StartLabs, we host fireside chats and ideathons throughout the year. But our flagship event is our annual TechTrek over spring break. In previous years, StartLabs has gone on TechTrek trips to Germany, Switzerland, and Israel. On these fully funded trips, StartLabs members have visited and collaborated with industry leaders, incubators, startups, and academic institutions. They take these treks both to connect with the global startup sphere and to build closer relationships within the club itself.

Most important, however, the process of organizing the TechTrek is itself an expedited introduction to entrepreneurship. The trip is entirely planned by StartLabs members; we figure out travel logistics, find sponsors, and then discover ways to optimize our funding. 

two students soaking in a hot spring in Iceland

COURTESY PHOTO

In organizing this year’s trip to Iceland, we had to learn how to delegate roles to all the planners and how to maintain morale when making this trip a reality seemed to be an impossible task. We woke up extra early to take 6 a.m. calls with Icelandic founders and sponsors. We came up with options for different levels of sponsorship, used pattern recognition to deduce the email addresses of hundreds of potential contacts at organizations we wanted to visit, and all got scrappy with utilizing our LinkedIn connections.

And as any good entrepreneur must, we had to learn how to be lean and maximize our resources. To stretch our food budget, we planned all our incubator and company visits around lunchtime in hopes of getting fed, played human Tetris as we fit 16 people into a six-person Airbnb, and emailed grocery stores to get their nearly expired foods for a discount. We even made a deal with the local bus company to give us free tickets in exchange for a story post on our Instagram account. 

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The Download: spying keyboard software, and why boring AI is best

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🧠


This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

How ubiquitous keyboard software puts hundreds of millions of Chinese users at risk

For millions of Chinese people, the first software they download onto devices is always the same: a keyboard app. Yet few of them are aware that it may make everything they type vulnerable to spying eyes. 

QWERTY keyboards are inefficient as many Chinese characters share the same latinized spelling. As a result, many switch to smart, localized keyboard apps to save time and frustration. Today, over 800 million Chinese people use third-party keyboard apps on their PCs, laptops, and mobile phones. 

But a recent report by the Citizen Lab, a University of Toronto–affiliated research group, revealed that Sogou, one of the most popular Chinese keyboard apps, had a massive security loophole. Read the full story. 

—Zeyi Yang

Why we should all be rooting for boring AI

Earlier this month, the US Department of Defense announced it is setting up a Generative AI Task Force, aimed at “analyzing and integrating” AI tools such as large language models across the department. It hopes they could improve intelligence and operational planning. 

But those might not be the right use cases, writes our senior AI reporter Melissa Heikkila. Generative AI tools, such as language models, are glitchy and unpredictable, and they make things up. They also have massive security vulnerabilities, privacy problems, and deeply ingrained biases. 

Applying these technologies in high-stakes settings could lead to deadly accidents where it’s unclear who or what should be held responsible, or even why the problem occurred. The DoD’s best bet is to apply generative AI to more mundane things like Excel, email, or word processing. Read the full story. 

This story is from The Algorithm, Melissa’s weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.

The ice cores that will let us look 1.5 million years into the past

To better understand the role atmospheric carbon dioxide plays in Earth’s climate cycles, scientists have long turned to ice cores drilled in Antarctica, where snow layers accumulate and compact over hundreds of thousands of years, trapping samples of ancient air in a lattice of bubbles that serve as tiny time capsules. 

By analyzing those cores, scientists can connect greenhouse-gas concentrations with temperatures going back 800,000 years. Now, a new European-led initiative hopes to eventually retrieve the oldest core yet, dating back 1.5 million years. But that impressive feat is still only the first step. Once they’ve done that, they’ll have to figure out how they’re going to extract the air from the ice. Read the full story.

—Christian Elliott

This story is from the latest edition of our print magazine, set to go live tomorrow. Subscribe today for as low as $8/month to ensure you receive full access to the new Ethics issue and in-depth stories on experimental drugs, AI assisted warfare, microfinance, and more.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 How AI got dragged into the culture wars
Fears about ‘woke’ AI fundamentally misunderstand how it works. Yet they’re gaining traction. (The Guardian
+ Why it’s impossible to build an unbiased AI language model. (MIT Technology Review)
 
2 Researchers are racing to understand a new coronavirus variant 
It’s unlikely to be cause for concern, but it shows this virus still has plenty of tricks up its sleeve. (Nature)
Covid hasn’t entirely gone away—here’s where we stand. (MIT Technology Review)
+ Why we can’t afford to stop monitoring it. (Ars Technica)
 
3 How Hilary became such a monster storm
Much of it is down to unusually hot sea surface temperatures. (Wired $)
+ The era of simultaneous climate disasters is here to stay. (Axios)
People are donning cooling vests so they can work through the heat. (Wired $)
 
4 Brain privacy is set to become important 
Scientists are getting better at decoding our brain data. It’s surely only a matter of time before others want a peek. (The Atlantic $)
How your brain data could be used against you. (MIT Technology Review)
 
5 How Nvidia built such a big competitive advantage in AI chips
Today it accounts for 70% of all AI chip sales—and an even greater share for training generative models. (NYT $)
The chips it’s selling to China are less effective due to US export controls. (Ars Technica)
+ These simple design rules could turn the chip industry on its head. (MIT Technology Review)
 
6 Inside the complex world of dissociative identity disorder on TikTok 
Reducing stigma is great, but doctors fear people are self-diagnosing or even imitating the disorder. (The Verge)
 
7 What TikTok might have to give up to keep operating in the US
This shows just how hollow the authorities’ purported data-collection concerns really are. (Forbes)
 
8 Soldiers in Ukraine are playing World of Tanks on their phones
It’s eerily similar to the war they are themselves fighting, but they say it helps them to dissociate from the horror. (NYT $)
 
9 Conspiracy theorists are sharing mad ideas on what causes wildfires
But it’s all just a convoluted way to try to avoid having to tackle climate change. (Slate $)
 
10 Christie’s accidentally leaked the location of tons of valuable art 🖼📍
Seemingly thanks to the metadata that often automatically attaches to smartphone photos. (WP $)

Quote of the day

“Is it going to take people dying for something to move forward?”

—An anonymous air traffic controller warns that staffing shortages in their industry, plus other factors, are starting to threaten passenger safety, the New York Times reports.

The big story

Inside effective altruism, where the far future counts a lot more than the present

" "

VICTOR KERLOW

October 2022

Since its birth in the late 2000s, effective altruism has aimed to answer the question “How can those with means have the most impact on the world in a quantifiable way?”—and supplied methods for calculating the answer.

It’s no surprise that effective altruisms’ ideas have long faced criticism for reflecting white Western saviorism, alongside an avoidance of structural problems in favor of abstract math. And as believers pour even greater amounts of money into the movement’s increasingly sci-fi ideals, such charges are only intensifying. Read the full story.

—Rebecca Ackermann

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Watch Andrew Scott’s electrifying reading of the 1965 commencement address ‘Choose One of Five’ by Edith Sampson.
+ Here’s how Metallica makes sure its live performances ROCK. ($)
+ Cannot deal with this utterly ludicrous wooden vehicle
+ Learn about a weird and wonderful new instrument called a harpejji.



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Why we should all be rooting for boring AI

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Why we should all be rooting for boring AI


This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

I’m back from a wholesome week off picking blueberries in a forest. So this story we published last week about the messy ethics of AI in warfare is just the antidote, bringing my blood pressure right back up again. 

Arthur Holland Michel does a great job looking at the complicated and nuanced ethical questions around warfare and the military’s increasing use of artificial-intelligence tools. There are myriad ways AI could fail catastrophically or be abused in conflict situations, and there don’t seem to be any real rules constraining it yet. Holland Michel’s story illustrates how little there is to hold people accountable when things go wrong.  

Last year I wrote about how the war in Ukraine kick-started a new boom in business for defense AI startups. The latest hype cycle has only added to that, as companies—and now the military too—race to embed generative AI in products and services. 

Earlier this month, the US Department of Defense announced it is setting up a Generative AI Task Force, aimed at “analyzing and integrating” AI tools such as large language models across the department. 

The department sees tons of potential to “improve intelligence, operational planning, and administrative and business processes.” 

But Holland Michel’s story highlights why the first two use cases might be a bad idea. Generative AI tools, such as language models, are glitchy and unpredictable, and they make things up. They also have massive security vulnerabilities, privacy problems, and deeply ingrained biases.  

Applying these technologies in high-stakes settings could lead to deadly accidents where it’s unclear who or what should be held responsible, or even why the problem occurred. Everyone agrees that humans should make the final call, but that is made harder by technology that acts unpredictably, especially in fast-moving conflict situations. 

Some worry that the people lowest on the hierarchy will pay the highest price when things go wrong: “In the event of an accident—regardless of whether the human was wrong, the computer was wrong, or they were wrong together—the person who made the ‘decision’ will absorb the blame and protect everyone else along the chain of command from the full impact of accountability,” Holland Michel writes. 

The only ones who seem likely to face no consequences when AI fails in war are the companies supplying the technology.

It helps companies when the rules the US has set to govern AI in warfare are mere recommendations, not laws. That makes it really hard to hold anyone accountable. Even the AI Act, the EU’s sweeping upcoming regulation for high-risk AI systems, exempts military uses, which arguably are the highest-risk applications of them all. 

While everyone is looking for exciting new uses for generative AI, I personally can’t wait for it to become boring. 

Amid early signs that people are starting to lose interest in the technology, companies might find that these sorts of tools are better suited for mundane, low-risk applications than solving humanity’s biggest problems.

Applying AI in, for example, productivity software such as Excel, email, or word processing might not be the sexiest idea, but compared to warfare it’s a relatively low-stakes application, and simple enough to have the potential to actually work as advertised. It could help us do the tedious bits of our jobs faster and better.

Boring AI is unlikely to break as easily and, most important, won’t kill anyone. Hopefully, soon we’ll forget we’re interacting with AI at all. (It wasn’t that long ago when machine translation was an exciting new thing in AI. Now most people don’t even think about its role in powering Google Translate.) 

That’s why I’m more confident that organizations like the DoD will find success applying generative AI in administrative and business processes. 

Boring AI is not morally complex. It’s not magic. But it works. 

Deeper Learning

AI isn’t great at decoding human emotions. So why are regulators targeting the tech?

Amid all the chatter about ChatGPT, artificial general intelligence, and the prospect of robots taking people’s jobs, regulators in the EU and the US have been ramping up warnings against AI and emotion recognition. Emotion recognition is the attempt to identify a person’s feelings or state of mind using AI analysis of video, facial images, or audio recordings. 

But why is this a top concern? Western regulators are particularly concerned about China’s use of the technology, and its potential to enable social control. And there’s also evidence that it simply does not work properly. Tate Ryan-Mosley dissected the thorny questions around the technology in last week’s edition of The Technocrat, our weekly newsletter on tech policy.

Bits and Bytes

Meta is preparing to launch free code-generating software
A version of its new LLaMA 2 language model that is able to generate programming code will pose a stiff challenge to similar proprietary code-generating programs from rivals such as OpenAI, Microsoft, and Google. The open-source program is called Code Llama, and its launch is imminent, according to The Information. (The Information

OpenAI is testing GPT-4 for content moderation
Using the language model to moderate online content could really help alleviate the mental toll content moderation takes on humans. OpenAI says it’s seen some promising first results, although the tech does not outperform highly trained humans. A lot of big, open questions remain, such as whether the tool can be attuned to different cultures and pick up context and nuance. (OpenAI)

Google is working on an AI assistant that offers life advice
The generative AI tools could function as a life coach, offering up ideas, planning instructions, and tutoring tips. (The New York Times)

Two tech luminaries have quit their jobs to build AI systems inspired by bees
Sakana, a new AI research lab, draws inspiration from the animal kingdom. Founded by two prominent industry researchers and former Googlers, the company plans to make multiple smaller AI models that work together, the idea being that a “swarm” of programs could be as powerful as a single large AI model. (Bloomberg)

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