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The Download: the next big thing in LLMs and how AI academic research is shifting
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.
These startups are chasing the next big thing in LLMs
Nine years after Google researchers introduced the transformer, this family of neural networks has become the engine inside every major large language model. But transformers are starting to show their age.
As LLMs get bigger and better, transformers have become a bottleneck. Their dense attention mechanism becomes increasingly expensive as the amount of text grows, and they’re not great at keeping track of a lot of information at once.
Here are four new ideas for how to solve the transformer problem—innovations that could change LLMs for good, making them faster, far more efficient, and (maybe) even smarter.
—Will Douglas Heaven
This story is from MIT Technology Review’s What’s Next series, which looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here.
AI professors are negotiating the new realities of academic research
—Grace Huckins
Last week, I headed to a hotel in Mountain View, California, to join some of the most accomplished, and some of the most promising, AI researchers in the world. I was hosting roundtable interviews and speaking at a media training for a convening of the Schmidt Sciences AI2050 program, an initiative funded by Eric and Wendy Schmidt that supports academics whose work involves AI.
The fellows list is a who’s who of AI luminaries, and though not all of them made it out to the Bay, every time I turned a corner I saw a scientist whom I’d interviewed previously or whose research I admired. It’s a weird time for university AI researchers, who make up most of the AI2050 group. Read Grace’s story to find out why, and what could be coming next.
This story is from The Algorithm, our weekly AI newsletter. Sign up to receive it in your inbox every Monday.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Nvidia has secured $500 billion from Wall Street for AI infrastructure
It’s struck deals with BlackRock, Goldman Sachs, and four others. (BBC)
+ Showing the pull of AI compute for institutional investors. (Reuters $)
+ And that AI infrastructure is becoming a new asset class. (CNBC)
2 Mark Zuckerberg’s new manifesto says open-source AI can save the US
It presents a utopian vision of personalized “superintelligence.” (Guardian)
+ And arrived the same day as Meta’s new, open-source model. (NYT $)
+ Zuckerberg said he plans to launch more of these models. (WSJ $)
+ And pit Meta against Chinese open-weight developers. (SCMP)
3 Bernie Sanders has called on Silicon Valley to “pause AI development”
He noted that AI giants have pledged to do this if necessary for safety.
+ And warned that lawmakers will step in if no action is taken. (Guardian)
+ House Democrats are already pressing AI leaders over rogue models. (WP $)
+ A populist backlash is building against AI. (MIT Technology Review)
4 A US court will allow thousands of social media lawsuits to proceed
The suits target addictive mechanisms used by Meta, TikTok, Google, and Snapchat. (Axios)
+ They claim the platforms are designed to hook young users. (Reuters $)
+ Can we repair the internet? (MIT Technology Review)
5 Unitree’s IPO is more than 8,000 times oversubscribed by retail
The Chinese humanoid firm raised $900 million ahead of its listing. (Reuters $)
+ Its pricing for the Shanghai IPO values the company at $9 billion. (FT $)
6 Flock’s car-tracking cameras are facing a bipartisan backlash
The surveillance network has spread rapidly across the US. (NYT $)
+ Flock also plans to chase shoplifters with drones. (MIT Technology Review)
7 China is breaking up AI relationships
Beijing has introduced new rules for emotionally interactive AI. (Rest of World)
+ It’s surprisingly easy to fall for a chatbot. (MIT Technology Review)
8 An AI tool claims to pick the best 1% of scientific papers
But researchers doubt that AI can reliably judge scientific quality. (Nature)
9 The AI slop backlash is working
It’s pushing platforms to restrict AI-generated content. (Wired $)
10 An 82-year-old rejected $26 million to turn her farm into a data center
She criticised the environmental impacts of data centers. (Fortune)
Quote of the day
“It is not too late to avoid disaster. Stop building machines that humans cannot control.”
—Senator Bernie Sanders urges Sam Altman, Dario Amodei, and Mark Zuckerberg to pause all AI development in a letter.
One More Thing
The race to make the perfect baby is creating an ethical mess
A new field of science is using genetic sequencing to predict what kind of person an embryo might become. Some parents turn to these tests to avoid devastating genetic disorders, while a much smaller group are willing to pay tens of thousands of dollars to optimize for intelligence, appearance, and personality.
Customers, however, may not be getting what they’re paying for. Genetics experts have highlighted the potential deficiencies of this testing for years, while its underlying assumptions have made these companies a political lightning rod.
As this technology edges toward the mainstream, scientists and ethicists are racing to confront the implications—for our social contract, for future generations, and for our very understanding of what it means to be human. Read the full story.
—Julia Black
We can still have nice things
A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)
+ An eagle-eyed border collie is taking the game of fetch into new waters.
+ musicForprogramming has made a valiant attempt to produce the perfect tunes for sustained concentration.
+ When kids design playgrounds, they create a cheerful mix of giant chess, pink basketball courts—and lava.
+ This power metal version of the “Back to the Future” music is an epic reinvention of the film’s classic theme.
