Tech
This Week in AI: OpenAI is stretched thin

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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.
Tech
Volkswagen’s cheapest EV ever is the first to use Rivian software

Volkswagen’s ultra-cheap EV called the ID EVERY1 — a small four-door hatchback revealed Wednesday — will be the first to roll out with software and architecture from Rivian, according to a source familiar with the new model.
The EV is expected to go into production in 2027 with a starting price of 20,000 euros ($21,500). A second EV called the ID.2all, which will be priced in the 25,000 euro price category, will be available in 2026. Both vehicles are part of the automaker’s new of category electric urban front-wheel drive cars that are being developing under the so-called “Brand Group Core” that makes up the volume brands in the VW Group. And both vehicles are for the European market.
The EVERY1 will be the first to ship with Rivian’s vehicle architecture and software as part of a $5.8 billion joint venture struck last year between the German automaker and U.S. EV maker. The ID.2all is based on the E3 1.1 architecture and software developed by VW’s software unit Cariad.
VW didn’t name Rivian in its reveal Wednesday, although there were numerous nods to next-generation software. Kai Grünitz, member of the Volkswagen Brand Board of Management responsible for Technical Development, noted it would be the first model in the entire VW Group to use a “fundamentally new, particularly powerful software architecture.”
“This means the future entry-level Volkswagen can be equipped with new functions throughout its entire life cycle,” he said. “Even after purchase of a new car, the small Volkswagen can still be individually adapted to customer needs.”
Sources who didn’t want to be named because they were not authorized to speak publicly, confirmed to TechCrunch that Rivian’s software will be in the ID EVERY1 EV. TechCrunch has reached out to Rivian and VW and will update the article if the companies respond.
The new joint venture provides Rivian with a needed influx of cash and the opportunity to diversify its business. Meanwhile, VW Group gains a next-generation electrical architecture and software for EVs that will help it better compete. Both companies have said that the joint venture, called Rivian and Volkswagen Group Technologies, will reduce development costs and help scale new technologies more quickly.
The joint venture is a 50-50 partnership with co-CEOs. Rivian’s head of software, Wassym Bensaid, and Volkswagen Group’s chief technical engineer, Carsten Helbing, will lead the joint venture. The team will be based initially in Palo Alto, California. Three other sites are in development in North America and Europe, the companies have previously said.

“The ID. EVERY1 represents the last piece of the puzzle on our way to the widest model selection in the volume segment,” Thomas Schäfer, CEO of the Volkswagen Passenger Cars brand and Head of the Brand Group Core, said in a statement. “We will then offer every customer the right car with the right drive system–including affordable all-electric entry-level mobility. Our goal is to be the world’s technologically leading high-volume manufacturer by 2030. And as a brand for everyone–just as you would expect from Volkswagen.”
The Volkswagen ID EVERY1 is just a concept for now — and with only a few details attached to the unveiling. The concept vehicle reaches a top speed of 130 km/h (80 miles per hour) and is powered by a newly developed electric drive motor with 70 kW, according to Volkswagen. The German automaker said the range on the EVERY1 will be at least 250 kilometers (150 miles). The vehicle is small but larger than VW’s former UP! vehicle. The company said it will have enough space for four people and a luggage compartment volume of 305 liters.
Tech
The hottest AI models, what they do, and how to use them

AI models are being cranked out at a dizzying pace, by everyone from Big Tech companies like Google to startups like OpenAI and Anthropic. Keeping track of the latest ones can be overwhelming.
Adding to the confusion is that AI models are often promoted based on industry benchmarks. But these technical metrics often reveal little about how real people and companies actually use them.
To cut through the noise, TechCrunch has compiled an overview of the most advanced AI models released since 2024, with details on how to use them and what they’re best for. We’ll keep this list updated with the latest launches, too.
There are literally over a million AI models out there: Hugging Face, for example, hosts over 1.4 million. So this list might miss some models that perform better, in one way or another.
AI models released in 2025
Cohere’s Aya Vision
Cohere released a multimodal model called Aya Vision that it claims is best in class at doing things like captioning images and answering questions about photos. It also excels in languages other than English, unlike other models, Cohere claims. It is available for free on WhatsApp.
OpenAI’s GPT 4.5 ‘Orion’
OpenAI calls Orion their largest model to date, touting its strong “world knowledge” and “emotional intelligence.” However, it underperforms on certain benchmarks compared to newer reasoning models. Orion is available to subscribers of OpenAI’s $200 a month plan.
Claude Sonnet 3.7
Anthropic says this is the industry’s first ‘hybrid’ reasoning model, because it can both fire off quick answers and really think things through when needed. It also gives users control over how long the model can think for, per Anthropic. Sonnet 3.7 is available to all Claude users, but heavier users will need a $20 a month Pro plan.
xAI’s Grok 3
Grok 3 is the latest flagship model from Elon Musk-founded startup xAI. It’s claimed to outperform other leading models on math, science, and coding. The model requires X Premium (which is $50 a month.) After one study found Grok 2 leaned left, Musk pledged to shift Grok more “politically neutral” but it’s not yet clear if that’s been achieved.
OpenAI o3-mini
This is OpenAI’s latest reasoning model and is optimized for STEM-related tasks like coding, math, and science. It’s not OpenAI’s most powerful model but because it’s smaller, the company says it’s significantly lower cost. It is available for free but requires a subscription for heavy users.
OpenAI Deep Research
OpenAI’s Deep Research is designed for doing in-depth research on a topic with clear citations. This service is only available with ChatGPT’s $200 per month Pro subscription. OpenAI recommends it for everything from science to shopping research, but beware that hallucinations remain a problem for AI.
Mistral Le Chat
Mistral has launched app versions of Le Chat, a multimodal AI personal assistant. Mistral claims Le Chat responds faster than any other chatbot. It also has a paid version with up-to-date journalism from the AFP. Tests from Le Monde found Le Chat’s performance impressive, although it made more errors than ChatGPT.
OpenAI Operator
OpenAI’s Operator is meant to be a personal intern that can do things independently, like help you buy groceries. It requires a $200 a month ChatGPT Pro subscription. AI agents hold a lot of promise, but they’re still experimental: a Washington Post reviewer says Operator decided on its own to order a dozen eggs for $31, paid with the reviewer’s credit card.
Google Gemini 2.0 Pro Experimental
Google Gemini’s much-awaited flagship model says it excels at coding and understanding general knowledge. It also has a super-long context window of 2 million tokens, helping users who need to quickly process massive chunks of text. The service requires (at minimum) a Google One AI Premium subscription of $19.99 a month.
AI models released in 2024
DeepSeek R1
This Chinese AI model took Silicon Valley by storm. DeepSeek’s R1 performs well on coding and math, while its open source nature means anyone can run it locally. Plus, it’s free. However, R1 integrates Chinese government censorship and faces rising bans for potentially sending user data back to China.
Gemini Deep Research
Deep Research summarizes Google’s search results in a simple and well-cited document. The service is helpful for students and anyone else who needs a quick research summary. However, its quality isn’t nearly as good as an actual peer-reviewed paper. Deep Research requires a $19.99 Google One AI Premium subscription.
Meta Llama 3.3 70B
This is the newest and most advanced version of Meta’s open source Llama AI models. Meta has touted this version as its cheapest and most efficient yet, especially for math, general knowledge, and instruction following. It is free and open source.
OpenAI Sora
Sora is a model that creates realistic videos based on text. While it can generate entire scenes rather than just clips, OpenAI admits that it often generates “unrealistic physics.” It’s currently only available on paid versions of ChatGPT, starting with Plus, which is $20 a month.
Alibaba Qwen QwQ-32B-Preview
This model is one of the few to rival OpenAI’s o1 on certain industry benchmarks, excelling in math and coding. Ironically for a “reasoning model,” it has “room for improvement in common sense reasoning,” Alibaba says. It also incorporates Chinese government censorship, TechCrunch testing shows. It’s free and open source.
Anthropic’s Computer Use
Claude’s Computer Use is meant to take control of your computer to complete tasks like coding or booking a plane ticket, making it a predecessor of OpenAI’s Operator. Computer use, however, remains in beta. Pricing is via API: $0.80 per million tokens of input and $4 per million tokens of output.
x.AI’s Grok 2
Elon Musk’s AI company, x.AI, has launched an enhanced version of its flagship Grok 2 chatbot it claims is “three times faster.” Free users are limited to 10 questions every two hours on Grok, while subscribers to X’s Premium and Premium+ plans enjoy higher usage limits. x.AI also launched an image generator, Aurora, that produces highly photorealistic images, including some graphic or violent content.
OpenAI o1
OpenAI’s o1 family is meant to produce better answers by “thinking” through responses through a hidden reasoning feature. The model excels at coding, math, and safety, OpenAI claims, but has issues deceiving humans, too. Using o1 requires subscribing to ChatGPT Plus, which is $20 a month.
Anthropic’s Claude Sonnet 3.5
Claude Sonnet 3.5 is a model Anthropic claims as being best in class. It’s become known for its coding capabilities and is considered a tech insider’s chatbot of choice. The model can be accessed for free on Claude although heavy users will need a $20 monthly Pro subscription. While it can understand images, it can’t generate them.
OpenAI GPT 4o-mini
OpenAI has touted GPT 4o-mini as its most affordable and fastest model yet thanks to its small size. It’s meant to enable a broad range of tasks like powering customer service chatbots. The model is available on ChatGPT’s free tier. It’s better suited for high-volume simple tasks compared to more complex ones.
Cohere Command R+
Cohere’s Command R+ model excels at complex Retrieval-Augmented Generation (or RAG) applications for enterprises. That means it can find and cite specific pieces of information really well. (The inventor of RAG actually works at Cohere.) Still, RAG doesn’t fully solve AI’s hallucination problem.
Tech
Not all cancer patients need chemo. Ataraxis AI raised $20M to fix that.

Artificial intelligence is a big trend in cancer care, and it’s mostly focused detecting cancer at the earliest possible stage. That makes a lot of sense, given that cancer is less deadly the earlier it’s detected.
But fewer are asking another fundamental question: if someone does have cancer, is an aggressive treatment like chemotherapy necessary? That’s the problem Ataraxis AI is trying to solve.
The New York-based startup is focused on using AI to accurately predict not only if a patient has cancer, but also what their cancer outcome looks like in 5 to 10 years. If there’s only a small chance of the cancer coming back, chemo can be avoided altogether – saving a lot of money, while avoiding the treatment’s notorious side effects.
Ataraxis AI now plans to launch their first commercial test, for breast cancer, to U.S. oncologists in the coming months, its co-founder Jan Witowski tells TechCrunch. To bolster the launch and expand into other types of cancer, the startup has raised a $20.4 million Series A, it told TechCrunch exclusively.
The round was led by AIX Ventures with participation from Thiel Bio, Founders Fund, Floating Point, Bertelsmann, and existing investors Giant Ventures and Obvious Ventures. Ataraxis emerged from stealth last year with a $4 million seed round.
Ataraxis was co-founded by Witowski and Krzysztof Geras, an assistant professor at NYU’s medical school who focuses on AI.
Ataraxis’ tech is powered by an AI model that extracts information from high-resolution images of cancer cells. The model is trained on hundreds of millions of real images from thousands of patients, Witowski said. A recent study showed Ataraxis’ tech was 30% more accurate than the current standard of care for breast cancer, per Ataraxis.
Long term, Ataraxis has big ambitions. It wants its tests to impact at least half of new cancer cases by 2030. It also views itself as a frontier AI company that builds its own models, touting Meta’s chief AI scientist Yann LeCun as an AI advisor.
“I think at Ataraxis we are trying to build what is essentially an AI frontier lab, but for healthcare applications,” Witowski said. “Because so many of those problems require a very novel technology.”
The AI boom has led to a rush of fundraises for cancer care startups. Valar Labs raised $22 million to help patients figure out their treatment plan in May 2024, for example. There’s also a bevvy of AI-powered drug discovery firms in the cancer space, like Manas AI which raised $24.6 million in January 2025 and was co-founded by Reid Hoffman, the LinkedIn co-founder.