Connect with us

Tech

This Week in AI: OpenAI is stretched thin

Hiya, folks, welcome to TechCrunch’s regular AI newsletter. If you want this in your inbox every Wednesday, sign up here.

After a brief hiatus, we’re back with a few show notes on OpenAI’s DevDay.

The keynote yesterday morning in San Francisco was remarkable for its subdued tone — a contrast to the rah-rah, hypebeast-y address from CEO Sam Altman last year. This DevDay, Altman didn’t bound up onstage to pitch shiny new projects. He didn’t even make an appearance; head of platform product Olivier Godement emceed.

On the agenda for this first of several OpenAI DevDays — the next is in London this month, followed by the last in Singapore in November — were quality-of-life improvements. OpenAI released a real-time voice API, as well as vision fine-tuning, which allows developers to customize its GPT-4o model using images. And the company launched model distillation, which takes a large AI model like GPT-4o and uses it to fine-tune a smaller model.

The event’s narrow focus wasn’t unanticipated. OpenAI tempered expectations this summer, saying DevDay would focus on educating devs, not showcasing products. Nevertheless, what was omitted from Tuesday’s tight, 60-minute keynote raised questions about the progress — and status — of OpenAI’s countless AI endeavors.

We didn’t hear about what might succeed OpenAI’s nearly year-old image generator, DALL-E 3, nor did we get an update on the limited preview for Voice Engine, the company’s voice-cloning tool. There’s no launch timeline yet for OpenAI’s video generator, Sora, and mum’s the word on Media Manager, the app the company says it’s developing to let creators control how their content is used in model training.

When reached for comment, an OpenAI spokesperson told TechCrunch that OpenAI is “slowly rolling out the [Voice Engine] preview to more trusted partners” and that Media Manager is “still in development.”

But it seems clear OpenAI is stretched thin — and has been for some time.

According to recent reporting by The Wall Street Journal, the company’s teams working on GPT-4o were only given nine days to conduct safety assessments. Fortune reports that many OpenAI staff thought that o1, the company’s first “reasoning” model, wasn’t ready to be unveiled.

As it barrels toward a funding round that could bring in up to $6.5 billion, OpenAI has its fingers in many underbaked pies. DALL-3 underperforms image generators like Flux in many qualitative tests; Sora is reportedly so slow to generate footage that OpenAI is revamping the model; and OpenAI continues to delay the rollout of the revenue-sharing program for its bot marketplace, the GPT Store, that it initially pegged for the first quarter of this year.

I’m not surprised that OpenAI now finds itself beset with staff burnout and executive departures. When you try to be a jack-of-all-trades, you end up being a master of none — and pleasing nobody.

News

AI bill vetoed: California governor Gavin Newsom vetoed SB 1047, a high-profile bill that would’ve regulated the development of AI in the state. In a statement, Newsom called the bill “well-intentioned” but “[not] the best approach” to protecting the public from AI’s dangers.

AI bills passed: Newsom did sign other AI regulations into law — including bills dealing with AI training data disclosures, deepfake nudes, and more.

Y Combinator criticized: Startup accelerator Y Combinator is being criticized after it backed an AI venture, PearAI, whose founders admitted they basically cloned an open source project called Continue.

Copilot gets upgraded: Microsoft’s AI-powered Copilot assistant got a makeover on Tuesday. It can now read your screen, think deeply, and speak aloud to you, among other tricks.

OpenAI co-founder joins Anthropic: Durk Kingma, one of the lesser-known co-founders of OpenAI, this week announced he’ll be joining Anthropic. It’s unclear what he’ll be working on, however.

Training AI on customers’ photos: Meta’s AI-powered Ray-Bans have a camera on the front for various AR features. But it could turn out to be a privacy issue — the company won’t say whether it plans to train models on images from users.

Raspberry Pi’s AI camera: Raspberry Pi, the company that sells tiny, cheap, single-board computers, has released the Raspberry Pi AI Camera, an add-on with onboard AI processing.

Research paper of the week

AI coding platforms have nabbed millions of users and attracted hundreds of millions of dollars from VCs. But are they delivering on their promises to boost productivity?

Maybe not, according to a new analysis from Uplevel, an engineering analytics firm. Uplevel compared data from about 800 of its developer customers — some of whom reported using GitHub’s AI coding tool, Copilot, and some of whom didn’t. Uplevel found that devs relying on Copilot introduced 41% more bugs and weren’t any less susceptible to burnout than those who didn’t use the tool.

Developers have shown enthusiasm for AI-powered assistive coding tools despite concerns pertaining not only to security but also copyright infringement and privacy. The vast majority of devs responding to GitHub’s latest poll said they’ve embraced AI tools in some form. Businesses are bullish too — Microsoft reported in April that Copilot had over 50,000 enterprise customers.

Model of the week

Liquid AI, an MIT spinoff, this week announced its first series of generative AI models: Liquid Foundation Models, or LFMs for short.

“So what?” you might ask. Models are a commodity — new ones are released practically every day. Well, LFMs use a novel model architecture and notch competitive scores on a range of industry benchmarks.

Most models are what’s known as a transformer. Proposed by a team of Google researchers back in 2017, the transformer has become the dominant generative AI model architecture by far. Transformers underpin Sora and the newest version of Stable Diffusion, as well as text-generating models like Anthropic’s Claude and Google’s Gemini.

But transformers have limitations. In particular, they’re not very efficient at processing and analyzing vast amounts of data.

Liquid claims its LFMs have a reduced memory footprint compared to transformer architectures, allowing them to take in larger amounts of data on the same hardware. “By efficiently compressing inputs, LFMs can process longer sequences [of data],” the company wrote in a blog post.

Liquid’s LFMs are available on a number of cloud platforms, and the team plans to continue refining the architecture with future releases.

Grab bag

If you blinked, you probably missed it: An AI company filed to go public this week.

Called Cerebras, the San Francisco-based startup develops hardware to run and train AI models, and it competes directly with Nvidia.

So how does Cerebras hope to compete against the chip giant, which commanded between 70% and 95% of the AI chip segment as of July? On performance, says Cerebras. The company claims that its flagship AI chip, which it both sells direct and offers as a service via its cloud, can outcompete Nvidia’s hardware.

But Cerebras has yet to translate this claimed performance advantage into profits. The firm had a net loss of $66.6 million in the first half of 2024, per filings with the SEC. And for last year, Cerebras reported a net loss of $127.2 million on revenue of $78.7 million.

Cerebras could seek to raise up to $1 billion through the IPO, according to Bloomberg. To date, the company has raised $715 million in venture capital and was valued at over $4 billion three years ago.

source

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

Tech

Can an Apple lawsuit derail OpenAI’s hardware plans?

Apple recently filed a trade secrets lawsuit against OpenAI, accusing the AI company of a pattern of misconduct aimed at getting current and former Apple employees to share confidential information. (In response, OpenAI said it is “not aware of any evidence that this complaint has merit.”)

On the latest episode of TechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I debated whether this lawsuit will cast a shadow over OpenAI’s much-discussed plans to get into the hardware business (starting with a mobile smart speaker) and go public.

“Even setting aside whether or not the court grants any kind of injunctive relief or any kind of restraining order over what OpenAI is doing, it just naturally can lead to that sort of situation where it’s going to cause some delays in what OpenAI is working on,” Sean suggested. “Which I’m sure was probably part of the reasoning behind Apple doing this. They don’t do this stuff willy nilly.”

With all those plans on the line, will OpenAI try to settle this as quickly as possible, or did it learn from its recent courtroom victory against Elon Musk that it can endure the cost and embarrassment of a trial? Kirsten, at least, predicts the latter.

Keep reading for a preview of our conversation, edited for length and clarity.

Kirsten: Sean, how do you feel about Sam Altman listening to you with a little device maybe in your pocket?

Sean: I’m good. Maybe that’s predictable, but I’m good. No thanks.

We’ll get into it, I’m sure, but this is allegedly the first product that OpenAI has been working on in its hardware division with Jony Ive and company. They’ve been really coy ever since that weird video they put out last year of them sitting at that coffee shop or bar in San Francisco and sort of talking very vaguely about hardware and legacy devices, meaning laptops and phones. And so if this is the direction they’re headed in, all power to people who want to have somebody like that always listening to them. This is not going to be for me.

Anthony: Part of what we have to remember about those kinds of devices is also that, depending on how mobile it is, it’s not just listening to you, it’s listening to the people around you. I might be fine with it — I’m not fine with it, but let’s say I was — but then if we met up in-person at Disrupt, then suddenly it might be listening to all of us. 

There are all kinds of social norms that are going to have to be renegotiated if these things become widespread. I think we should make fun of and criticize people who record other people without consent.

Kirsten: Well, I bring up the device that has been speculated about for a really long time, and we’ll see what it really ends up being once it’s officially introduced, but it’s important in the context of this lawsuit that Apple filed last Friday. 

It was the biggest news of the week, certainly, and this is a trade secret lawsuit. It has some pretty wild allegations and we should very much emphasize these are allegations that have been filed in a complaint by Apple. But what it is accusing OpenAI of is a pattern of misconduct at the highest levels, specifically directed towards OpenAI employees who used to work at Apple. And in fact they’ve named the chief hardware officer Tang Tan in this lawsuit.

This is all important because Apple is accusing OpenAI of essentially stealing their trade secrets, but in the context of that, this could be then used for a competing hardware product. I’m wondering if maybe we don’t get into whether this lawsuit has merits, because we haven’t gone through full discovery, but what are your initial impressions of the lawsuit aside from the fact that wow, this is going to be entertaining?

Sean: Two things. One, this is a pretty big risk potentially to whatever it is OpenAI is working on. Even setting aside whether or not the court grants any kind of injunctive relief or any kind of restraining order over what OpenAI is doing, it just naturally can lead to that sort of situation where it’s going to cause some delays in what OpenAI is working on, which I’m sure was probably part of the reasoning behind Apple doing this. They don’t do this stuff willy nilly.

The other is that we think that OpenAI is — we know that they’ve filed confidentially for an IPO. We think it might happen as early as the end of this year, or early next year, if you believe Sam Altman’s cautious language around the IPO. And this just raises a whole bunch of questions around that because, on the one hand, we think their business right now is probably overwhelmingly the software; they’re not really factoring in any hardware business into that picture at the moment.

They’re about to go to the markets and they’re going to be pitching bankers and investors on where they think their addressable market should be, and if they have a big amount of that pegged to a potential hardware division and hardware products, this could be a huge risk to that and changes a lot of the calculus of sort of how the IPO gets priced. So that’s where my head’s at.

Anthony: One [allegation] that I assume that Apple must have pretty solid numbers on is, they said more than 400 Apple employees now work at OpenAI. Granted, both of them are very large companies with many thousands or tens of thousands of employees. So as a percentage, it’s not necessarily huge. But that seems like a lot of people and a pretty serious talent drain. 

And the other thing I’m wondering is related to Sean’s point. With the context of the potential IPO, how much damage did OpenAI ultimately take from a marketing and brand perspective from the trial it already went through? That it seemed to basically win, but there was a lot of not-terrible-but-kind-of-embarrassing dirty laundry that came out in the testimony. To what extent are they just like, “We do not want to go through that again”? Or did they take the lesson of, “Hey, we went through it and we survived and we’ll be okay if we have to do another trial with Apple”?

Kirsten: I fully predict the latter, by the way.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

source

Continue Reading

Tech

What to watch for after Jensen Huang’s Japan visit

Nvidia’s chief Jensen Huang spent two days — July 15 and 16 — in Tokyo, courting Japan’s industrial and chip-supply elite, weeks after a keynote in Taiwan, and months after a visit to South Korea. He left with deals spanning Japan’s entire tech ecosystem: a national AI factory, partnerships with the country’s leading robotics companies, and agreements with the chip-material suppliers powering Nvidia’s next generation of AI chips. His message was clear. Nvidia is targeting Japan’s factory floor, and many of the country’s biggest manufacturers are joining in. AI’s next chapter, Huang said, belongs to factory floors, robots, and machines, and he wants Japan to build it.

Thirty years ago, a $5 million Sega investment helped keep a near-bankrupt Nvidia afloat; today, Nvidia and Japan’s industrial giants need each other again — this time to build the physical-AI era, starting with these three projects:

Noetra — Japan’s sovereign-AI play. The country doesn’t want to run its factories and robots on American or Chinese AI. So, the government pulled together roughly 44 domestic firms, with SoftBank, Sony, NEC, and Honda at the core, to build its own AI for robots, vehicles, and factory floors. Tokyo is committing up to 1 trillion yen ($6.2 billion) over five years, a bet on homegrown “physical AI,”  foundation models built to run machines. Japan wants to own the software brain. The hardware to build it, though, still comes from Nvidia. The U.S. chip giant is building “a Vera Rubin AI factory,” a massive data center packed with its next-generation chips, expected to launch in 2028, with 13,750 Vera CPUs and 27,500 Rubin GPUs, delivering 140 megawatts. Noetra will oversee the effort, with plans to build the data center. Noetra’s plan runs in three stages: a reasoning model heavy on Japanese-language skills starting in fiscal 2026; an omni-modal version handling text, images, video, and audio by 2028; and “Real-world Native AI” built to run robots by 2030, released to outside Noetra developers in phases.

The robotics coalition  — Japan’s industrial giants line up behind Cosmos. Nvidia is targeting Japan’s factory floor, and many of the country’s top robotics and manufacturing players are signing on. Fanuc, Yaskawa, Kawasaki Heavy, Fujitsu, Hitachi, NEC, Sony, SoftBank, Kubota, and robotics group AIRoA say they plan to build on Nvidia’s Cosmos models, an open-model effort Nvidia started in May with a handful of global AI labs. In Tokyo, Nvidia gave them a reason to commit, unveiling Cosmos 3 Edge, a version of the model that runs on its Jetson Thor chips inside the machines themselves. Some are already testing a shared control system; others, like Honda R&D and Omron, are building on the tools now. “The next frontier of AI is in the physical world, and this is a once-in-a-generation opportunity for Japan,” Huang said in the company’s statement. “Japan invented modern manufacturing. Now, it has the opportunity to reinvent it for the age of intelligent industries.”

Toyota — cars and physical AI. Toyota uses Nvidia chips across much of its stack. It committed its next-generation vehicles to Nvidia’s Drive platform at CES in January 2025; the newer work extends Nvidia into its manufacturing, where simulations are used to design production lines, into the software that runs its vehicles, and into systems that read road traffic. Toyota’s cars will run advanced driver assistance, which steers and brakes but still requires a driver, a more conservative approach than Waymo and Tesla, which are developing systems that rely less on a human driver.

Huang’s visit put physical AI at the center of Japan’s industrial strategy, and Tokyo is spending to back it. Facing a shrinking workforce, Japan wants 10 million AI-equipped robots across 18 sectors by 2040, backed by $65 billion in public and private physical-AI investment.  

The longer game is bigger. Japan’s AI Robotics Strategy, released in March, aims to capture more than 30% of the global AI robotics market by 2040, a market Tokyo values at roughly ¥20 trillion, or about $133 billion. METI is funding a domestic foundation model to run the machines, and Noetra’s Nvidia-powered factory is where models of that scale, into the trillions of parameters, would be trained.

Underneath the industrial case is a sovereign one. As the U.S. and China pull ahead in large-scale AI, Tokyo wants its own data, its own compute, and less dependence on infrastructure it doesn’t control. Huang appeared on July 16 alongside trade minister Ryosei Akazawa at the government’s physical-AI launch, with Prime Minister Sanae Takaichi joining by video. The Takaichi administration has made AI and semiconductors the centerpiece of a growth plan chasing ¥370 trillion ($2.3 trillion) in public and private investment by 2040. Noetra’s factory — which Nvidia bills as “the world’s first national AI infrastructure” — is the clearest bet yet. Japan’s push for independence, at least for now, rests on American chips.

In two days, Huang sat across from nearly every name that matters in Japanese tech — the CEOs of Toyota, Fanuc, Yaskawa, Fujitsu, and Kawasaki over lunch, and dozens of supply-chain chiefs over skewers and whisky in a Kanda izakaya.

It’s the same playbook he ran weeks earlier — a homecoming keynote in Taiwan, fried chicken, and a 50,000-GPU deal in Seoul last fall. This time, it was Tokyo’s turn, with the robots, the supply chain, and the chips underneath.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

source

Continue Reading

Tech

Netflix paid $587M for Ben Affleck’s AI filmmaking startup

In a new regulatory filing, Netflix revealed that it paid $587 million in cash for InterPositive, a startup co-founded by actor and director Ben Affleck.

The streaming company announced the acquisition in March, with a statement from Affleck saying he wanted to “protect the power of human creativity.” According to Affleck, InterPublic’s AI tools help filmmakers improve their footage in post-production, particularly when it comes to making up for “real-world production challenges such as missing shots, background replacements or incorrect lighting.”

At the time, Netflix announced that the entire InterPositive team would be joining the company, with Affleck joining as a senior advisor, but it didn’t disclose the financial terms of the deal. A subsequent report in Bloomberg suggested that the deal could be worth up to $600 million.

In its most recent earnings report, Netflix said that around 300 of its titles have already used generative AI.

source

Continue Reading