Tech
Our favorite stories of 2021
Published
3 years agoon
By
Terry Power
The end of the year is always a good time for a bit of introspection and self-reflection. It also seems right to pause to celebrate some of the high points from a challenging year.
We asked our writers and editors to look back over all the stories we published in 2021 and tell us which ones really stood out. Which stories did their colleagues publish that made them proud to work for MIT Technology Review? (And no, they weren’t allowed to choose their own.)
An edited version of the list runs below, but there was one story that our team kept coming back to as a touchstone for the kind of coverage that we do: Karen Hao’s investigation into Facebook.
Abby Ivory-Ganja, our audience engagement editor, said it was “showstopping.” She added: “It’s easy to think of tech companies as monoliths and CEOs and not as groups of people. But Karen did such a great job explaining problems at Facebook through Joaquin Quiñonero Candela. This was one of TR’s most widely read stories of the year, and it’s no surprise why once you read it.”
Charlotte Jee, news editor, said: “This article was a bombshell when it came out in March. It revealed, in painstaking detail, the full extent to which Facebook knew its algorithms drove people towards harmful, hateful content—and chose not to do anything about it. Why? Because, as Karen so perfectly put it, ‘The reason is simple. Everything the company does and chooses not to do flows from a single motivation: [Mark] Zuckerberg’s relentless desire for growth.’ If you read it now, in the light of the Facebook Papers, it looks so prescient.”
How Facebook got addicted to spreading misinformation
See if you agree. And then once you’re done reading that one, see what else the rest of our team chose as their top hits of the year.
Have a happy new year!
Michael Reilly, executive editor
Inside the machine that saved Moore’s Law
A story about a giant, almost unbelievably complex machine that pushes engineering to the absolute max? Yes, please. Chip fabrication is not an easy subject to write about, but in Clive’s hands it’s a romp.
Meet Altos Labs, Silicon Valley’s latest wild bet on living forever
“It’s been said that young people dream of being rich, and rich people dream of being young.” Mix that sentiment together with a bit of exciting science and some investment from Jeff Bezos and other billionaires and you’ve got Antonio Regalado’s deep dive into the frothy world of longevity research.
Beauty filters are changing the way young girls see themselves
We know algorithms are out there always nudging our thinking on things like shopping decisions and political opinions. Even so, this piece from Tate Ryan-Mosley is a stunner, showing just how far the algorithmic “optimization” of everything has seeped into young girls’ view of their own physical appearance.
Tanya Basu, senior reporter, humans and technology
First he held a superspreader event. Then he recommended fake cures.
Eileen has a knack for not only finding these stories but being able to investigate and piece together what some people in tech might not want exposed. Written in March, it was a sign of themes to come in the rest of 2021: covid deniers, snake oil treatments, and people with egos that supersede common sense and safety.
Some artists found a lifeline selling NFTs. Others worry it’s a trap.
I feel like every NFT story is snarky and/or exclusionary, making them really hard for the average person to find something to care about in what’s arguably an important topic. Abby is able to hit that nerve here and exposes how a group of really vulnerable people who simply want to make art and a decent living are getting thrown under the bus by scammers.
A feminist internet would be better for everyone
It’s kind of sad that we have to make this statement in 2021, but here we are. What I love about this piece as a writer is the futuristic fiction that leads it off—and the realization that this isn’t science fiction anymore. What I love about this piece as a reader is that Charlotte has genuine hope and practical thoughts about the future of the internet that don’t make me feel like everything is lost. (Linda, our copy chief, agreed, saying: “As usual, Charlotte finds the brighter side.”)
Abby Ivory-Ganja, audience engagement editor
Why the ransomware crisis suddenly feels so relentless
I loved this story from Patrick because it helped me understand the ransomware universe a little more. He really gives a view of the landscape from 36,000 feet, which I always appreciate.
Podcast: How pricing algorithms learn to collude
This episode of our podcast In Machines We Trust about how pricing algorithms learn to collude really blew my mind. Our podcast team did such a great job of pulling back the curtain behind the price of an Uber ride or books on Amazon. They make it so easy to understand something complicated, and we are all better for it.
Amy Nordrum, editorial director, special projects and operations
Inside the FBI, Russia, and Ukraine’s failed cybercrime investigation
This was a riveting tale of how an effort to crack down on cybercriminals by one of the world’s top law enforcement agencies went sideways. It’s a richly reported piece chock full of detail that will make you feel you were along for the ride amid the investigation’s many twists and turns. By the end, the FBI agents’ frustration is palpable and you’ll have a greater appreciation of why it’s so difficult to bring cybercriminals to justice.
These impossible instruments could change the future of music
This is a fun little story about how software is changing what it means to make music, in part by allowing musicians to create and play instruments that defy physics and that literally could not exist in the real world. There’s a funny backstory, too, about how one group’s painstaking effort to design software that very precisely imitates actual instruments was upended when real musicians got hold of it and started messing around.
Auditors are testing AI hiring algorithms for bias, but there’s no easy fix
Much has been written about the problem of AI bias. One potential solution involves auditing the underlying algorithms for bias. A cottage industry of consultants has sprung up to do just that, but it’s far from perfect. This story breaks down one particular AI audit to illustrate the limits of this particular approach.
Niall Firth, editorial director, digital
What an octopus’s mind can teach us about AI’s ultimate mystery
Back in 2020, Will had ventured into controversial territory, tackling one of the most hotly contested topics in AI—whether a true artificial general intelligence is even possible. In 2021 he decided to go one step further and ask: Could a machine ever be conscious? Drawing on philosophy of mind—and not afraid to get into truly deep conversations about the nature of consciousness—the story started out by asking what it would take for a machine to become conscious and self-aware. But it ended up with an even more complex conclusion: If a machine became conscious, would we even know? Come for the mind-bending philosophy, stay for the octopus anecdotes.
She risked everything to expose Facebook. Now she’s telling her story.
Karen’s tenacious reporting over Facebook misinformation and troll farms has rightly been praised, but I thought this story was brilliantly done. Sophie Zhang was a whistleblower who had exposed how fake accounts and likes on Facebook were allowing politicians to sway the public in countries outside the US, and potentially enable election interference. The story had been told, but no one had written a profile of her before. Karen showed readers that “for Zhang, the explanation of why she cared so much is tied up in her identity.” Telling that story was an expert piece of profile-writing that required sensitivity and compassion.
James Temple, senior editor, climate and energy
First he held a superspreader event. Then he recommended fake cures.
One of my favorite Tech Review reads this year was Eileen Guo’s scoop on a high-priced business conference that went forth in defiance of regional public health orders, and turned into a superspreader event. It was hosted by a high-profile Silicon Valley entrepreneur who had cofounded a covid-19 vaccine company. The deeply sourced story described in fine detail both the warnings that were made in advance of the event and the aftermath, including the apparent effort to limit communications about the ensuing covid-19 infections.
They called it a conspiracy theory. But Alina Chan tweeted life into the idea that the virus came from a lab.
Antonio Regalado wrote a must-read profile of Alina Chan, the Broad Institute postdoc who helped revive the idea that covid-19 could have leaked from a lab in China. The story details how she researched and communicated the possibilities, the virologists she angered in doing so, and the pushback and even threats she’s received. But ultimately hers is a story about the nature of scientific uncertainty, and the sometimes fuzzy line between crackpot conspiracies, conjecture and unlikely ideas still in need of vigorous intellectual debate.
Charlotte Jee, news editor
How to talk to unvaccinated people
The stakes for conversations about the vaccines are sky-high, and the debate has caused private, painful rifts in so many families. Many of us see the shots as the only meaningful way out of the pandemic, and the primary means to keep loved ones alive and well, so it’s deeply infuriating when others don’t see it the same way. This thoughtful, well-researched piece by Tanya was a timely reminder that people who don’t want to get vaccinated are still people, and while it may still be worth your while to try to persuade them, you should do so in a respectful manner. No one ever persuaded anyone by yelling at them.
How beauty filters perpetuate colorism
Lots of us know by now that rather than erasing existing biases, many technologies amplify them. But every now and then you read something that makes you realize that the problem is even bigger—and more harmful—than you appreciated. This piece, which exposed how beauty filters perpetuate colorism (a form of discrimination against people with darker complexions), had that effect on me. It made me sad, it made me worried, and most of all it made me angry.
This piece can (and should) be read as a companion piece building on the excellent article Tate wrote in April about the impact of beauty filters on young girls’ self-image.
Eileen Guo, senior reporter, features and investigations
I asked an AI to tell me how beautiful I am
I loved Tate’s story series on how tech and tech platforms affect perceptions of beauty. All three stories are excellent and worth a read (“I asked an AI to tell me how beautiful I am,” “Beauty filters are changing the way young girls see themselves,” and “How digital beauty filters perpetuate digital colorism”), as is the accompanying podcast episode. I love Tate’s willingness to include herself in her stories and her ability to do so in a way that is relatable: in the first story, she asks questions that the reader likely has as well, and she is empathetic in digging into the nuances of how beauty tech affects different communities differently. It’s also noteworthy to have this kind of in-depth treatment of “women + tech” issues, and I really hope she does more of it!
What went wrong with America’s $44 million vaccine data system?
Cat Ferguson’s timely and well-told investigation into the CDC’s Vaccine Administration Management System (VAMS), the largely ineffective and incredibly expensive website to schedule vaccine appointments, was the type of investigation that MIT Technology Review is best positioned to do. It answered the question everyone had, back in that phase of the pandemic, about why it was so hard to schedule vaccine appointments, and it did so with depth and detail that comes out of Cat’s deep expertise in health tech and her great sleuthing and reporting skills. And it shed light on an area that doesn’t get as much scrutiny as it should: government tech. Much less sexy than investigating Facebook, but just as important.
Tate Ryan-Mosely, reporter, digital rights and democracy
The climate solution actually adding millions of tons of CO2 into the atmosphere
James’s investigative reporting, a collaboration with ProPublica’s Lisa Song, was a momentous accounting of California’s carbon offset program. It found that companies could be gaming the system and undermining the climate goals of the project. It’s a super complicated subject, and James and Lisa were able to achieve an explanatory tone that made it accessible; it might be the story that I learned the most from this year. They also leaned into the nuances here, looking into questions of stewardship and how the program is impacting Native American tribes.
This is the real story of the Afghan biometric databases abandoned to the Taliban
Eileen and Hikmat’s super-impressive reporting added much-needed evidence about the tools the Taliban were likely to have at their disposal following the US withdrawal from the country. It will become an essential history lesson about the dangers of propping up a government with surveillance tools, only to have them fall into the wrong hands.
Of course you could have seen this coming
Abby’s quick take on the January 6 riot squarely placed the event as a continuation of forces that have been gathering for a long time. At the time of publishing, the noise around the riot was all-consuming and blurry, and her take offered clarity and analysis based on her years of reporting.
Will Douglas Heaven, senior editor, AI
Inside the fight to reclaim AI from Big Tech’s control
Karen Hao takes us behind the scenes at the birth of a movement, introducing the hopes and fears of the AI researchers pushing back against a status quo in which the world’s most powerful technology is fast becoming monopolised by the world’s most powerful companies.
This US company sold iPhone hacking tools to UAE spies
In a scoop that made other investigative journalists jealous, Patrick Howell O’Neill succeeded where others failed in unmasking a controversial company selling cyberweapons to foreign intelligence agencies. Few expose the shadowy international workings of cyber security so well.
You may like
-
Revived, implanted, and analyzed—the personal stories at the heart of cutting-edge biotech
-
The complex math of counterfactuals could help Spotify pick your next favorite song
-
The EU wants to regulate your favorite AI tools
-
The Download: 2022’s best stories, and what’s next for AI
-
Our favorite stories of 2022
-
The Download: the mortality issue, and America’s new favorite shopping app
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.
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.
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.
Tech
The Download: spying keyboard software, and why boring AI is best
Published
1 year agoon
22 August 2023By
Terry Power
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 $)
Quote of the day
“Is it going to take people dying for something to move forward?”
—An anonymous air traffic controller warns that staffing shortages in their industry, plus other factors, are starting to threaten passenger safety, the New York Times reports.
The big story
Inside effective altruism, where the far future counts a lot more than the present
October 2022
Since its birth in the late 2000s, effective altruism has aimed to answer the question “How can those with means have the most impact on the world in a quantifiable way?”—and supplied methods for calculating the answer.
It’s no surprise that effective altruisms’ ideas have long faced criticism for reflecting white Western saviorism, alongside an avoidance of structural problems in favor of abstract math. And as believers pour even greater amounts of money into the movement’s increasingly sci-fi ideals, such charges are only intensifying. Read the full story.
—Rebecca Ackermann
We can still have nice things
A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)
+ Watch Andrew Scott’s electrifying reading of the 1965 commencement address ‘Choose One of Five’ by Edith Sampson.
+ Here’s how Metallica makes sure its live performances ROCK. ($)
+ Cannot deal with this utterly ludicrous wooden vehicle.
+ Learn about a weird and wonderful new instrument called a harpejji.
Tech
Why we should all be rooting for boring AI
Published
1 year agoon
22 August 2023By
Terry Power
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)