SambaNova last announced a $350m Series E raise in February.

Intel-backed SambaNova has secured $1bn in funding to expand its AI chipmaking business, as demand for its inference technology continues to grow.

The Series F round, which drives up SambaNova’s valuation to $11bn, was led by General Atlantic, with participation from long-term backer Intel Capital, alongside Cambium Capital, BlackRock and the Qatar Investment Authority.

A&E Investment, Assam Ventures, Battery Ventures, Kabila Capital, QFO Capital, Vista Equity Partners and Volantis also participated in the raise.

The new capital comes at a time of accelerating momentum for SambaNova, which last announced a $350m Series E in February.

In recent months, the company launched its specialised SN50 chips that prioritise token efficiency, and announced a multi-year collaboration with Intel to deliver cost-efficient AI inference solutions to customers and roll out an Intel-powered AI cloud.

The 2017-founded SambaNova has close ties with Intel, whose CEO Lip-Bu Tan serves as chair of SambaNova’s board.

SambaNova said it will use proceeds from the latest raise to expand capacity, accelerate product innovation and scale deployments. Continuing on its growth momentum, the chipmaker plans to continue investing across chips, systems, software and full-stack AI infrastructure.

Alongside the funding, SambaNova has announced JPMorganChase as its latest customer to deploy the SN40 and SN50 chips.

“SambaNova’s platform is differentiated, built for a market where inference has become foundational to enterprise and industry transformation,” said Martín Escobari, the co-president and head of global growth equity at General Atlantic.

“Rodrigo and the team are driving deep technical innovation to achieve growing commercial momentum while demand for inference is accelerating well ahead of supply. We are pleased to lead this round to support SambaNova in shaping the next generation of AI infrastructure.”

SambaNova co-founder and CEO Rodrigo Liang told CNBC last month that “business is growing at an incredibly rapid rate”, adding that he is “really excited” about the current IPO market.

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Earlier this week, Bloomberg reported that Microsoft was replacing some of OpenAI’s software with its own in-house models in an effort to cut costs. Those in-house models, known as MAI, were increasingly being used to power apps like Word and Excel, the outlet noted.

The story raised an increasingly common question about the two companies, which were once seemingly inseparable, and have recently sent mixed signals about the status of their situationship: Were the two companies drifting apart?

Now, OpenAI is attempting to put any insinuations of such a break to rest. During OpenAI’s launch of GPT 5.6 on Thursday, the company announced that it would become the “preferred model” powering Microsoft’s 365 Copilot.

OpenAI noted in a blog post published Thursday that GPT 5.6 would support Microsoft users across the company’s suite of productivity apps, including Word, Excel, PowerPoint, and Cowork.

“Our partnership with Microsoft has always been about bringing the benefits of advanced AI to more individuals and organizations, and we’re excited to continue building on that shared commitment,” OpenAI wrote in a blog post.

What being a “preferred model” actually means isn’t entirely clear, other than that OpenAI’s software will continue to power Microsoft’s apps.

That said, it was never reported that ChatGPT’s software would stop powering Microsoft’s apps — merely that Microsoft was relying increasingly on its own software in an effort to reduce costs. The new “preferred model” disclosure doesn’t appear to negate that previous reporting.

On Thursday, multiple news organizations accused OpenAI of withholding evidence about how the company trains its artificial intelligence models in a new motion that’s connected to a series of ongoing copyright lawsuits.

The motion was filed by 17 publishers, including The New York Times, the New York Daily News, the Chicago Tribune and Ziff Davis (CNET’s parent company). Ziff Davis sued OpenAI in 2025, alleging that OpenAI scraped its copyrighted works to train ChatGPT and other large language models.

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The initial lawsuit dates back to 2023 when The New York Times first sued OpenAI and Microsoft, alleging the companies built their AI technologies using millions of news articles written by journalists. Microsoft and OpenAI have denied the claims.

The motion asks the court to impose legal sanctions against OpenAI, but not Microsoft, for allegedly withholding evidence, such as datasets and output logs, and claims that “OpenAI chose obstruction” by failing to produce it. If those sanctions are granted, OpenAI could be ordered to pay financial penalties. 

“This motion asks the court to punish OpenAI for hiding and destroying evidence showing how ChatGPT was trained on stolen journalism,” New York Daily News attorney Steven Lieberman said, per the Associated Press. 

At the center of the lawsuits is how generative AI, such as ChatGPT, is trained and how it sources its information. The Times’ original lawsuit claims that OpenAI’s generative AI tools “can generate output that recites Times content verbatim, closely summarizes it, and mimics its expressive style,” raising questions of copyright infringement.  

The lawsuits come amid a broader conversation in the journalism industry: declining traffic across digital media outlets. AI overviews are often cited as a major reason for the decline in clicks to original reporting by writers and editors, which in turn impacts publishers’ advertising revenue. 

A growing reliance on AI chatbots for finding news and other content is also a major concern for publishers, as it siphons off loyal readership and audience. Some data shows that small publishers have been hit the hardest, with a reported 60% traffic drop, while another analysis predicts traffic declines of more than 40% by 2029.

A statement by Ziff Davis notes that “OpenAI has copied and monetized Ziff Davis content without permission on a massive scale.” Lance Koonce, partner at Klaris Law and counsel for Ziff Davis, said that, since the lawsuit, “OpenAI repeatedly lied about its ability to search its own data sets for Ziff Davis content and engaged in other serious litigation misconduct.”

An ongoing debate over copyright and AI 

OpenAI has long maintained that AI training is fair use. An OpenAI spokesperson denied the allegations in a statement to CNET, stating: “As the Times’ case weakens and they’ve been forced to drop claims against us, they’re persisting with their efforts to invade the privacy of people who have nothing to do with this case, including by making these blatantly false allegations.” The statement went on to say: “We’ll continue defending our users’ privacy and the long-established principles of fair use.”

In a 2024 rebuttal to the original lawsuit filed by The New York Times, OpenAI said the publisher falsely accused the company of destroying data and instead accused the newspaper of “secretly” deleting its own data that would have shown internal use of OpenAI products. Although the Times has dropped one claim against OpenAI, the larger lawsuit remains in litigation.

Other tech giants, including Meta, have also been accused by authors and news publishers of copyright infringement. Many of those cases are still in litigation as courts decide where to draw the line between fair use and infringement in the age of AI.

A walk through the trees turned up more than expected a few years ago. One person spotted a plastic Nintendo 64 cartridge half-hidden on the forest floor. Its paper labels had vanished completely, leaving no hint of what game sat inside. The finder brought it home, then passed it along to someone who fixes old consoles for a closer look.

Rust had plainly gotten hold of the metal shield that covers the back, which is normally sealed up tight. The plastic shell that surrounded it had accumulated stains and scrapes from all of its time spent outside over the months or years, not to mention wear and tear. Inside, the circuit board, which is what actually matters, revealed some considerable corrosion around the vias on one side and a rougher surface on the other, and to top it all off, some of the screws had come free, adding to the overall ‘battered’ aspect. The real test would be when someone finally opened it up and attempted to get the parts to work again. First, you’ll need the right screwdriver, which should be a game-bit. When you take the shield off, you’re left with a wonderful mess of heavy crust and pitting across the metal underneath. Given the state of the outside, the board itself appears to be far superior to what you might assume. The pins on the edge connector are still in good condition, with no major damaged traces or fried components visible at first examination.

The next step was to clean it, starting with the board, then using high-strength isopropyl alcohol and a delicate brush. The residue is quickly removed without causing any damage, and the contacts can be polished with a Q-tip to look their finest. To be honest, the board appears very clean, nearly immaculate in sections. And the rusting hasn’t really taken hold, which is a comfort. In contrast, the shield and plastic shell told a different tale. Vinegar soaks appeared to dislodge some of the rust, and a combination of wire brushing and hot soapy water removed the most of the gunk. Some of the lighter stuff was removed with a magic eraser, but there is still some discoloration. If you were to restore it to its original condition, you’d probably have to replace the entire shell and shield, which would be a significant undertaking.

Before even attempting to boot the thing, he gave the N64 console a quick scrub just to be safe, and used an old cleaning kit to thoroughly clean the cartridge slot. One of the other known functional games proved that the device boots up normally. Then it was time to verify if our mystery cartridge was still functional. Slide it in, hit the power button, and the familiar title screen shows immediately.

The game was, of course, Super Mario 64, as the markings on the ROM chip showed that it was the regular version, with no special hardware or hidden modifications.The save data was particularly noteworthy, as someone’s previous progress was still present, intact, after years of exposure to moisture and temperature fluctuations. Unlike several other N64 games, Super Mario 64 keeps its saves in a non-battery-dependent manner. That was a pleasant surprise, even if the cartridge still appeared a little rough.

You have to give Nintendo credit because these cartridges were engineered to survive far more than a few scrapes and scuffs. They’re designed to endure dust and harsh handling by children, as well as repetitive insertion and removal, and it turns out the strong plastic shell and metal shield worked harder than we thought. They shielded the electronics within from the woodland environment considerably better than anyone could have anticipated. The shield, in particular, did an excellent job of soaking the majority of the corrosion that had developed in, leaving the board and pins in good shape. One final touch: a quick print of a new label to cover up the old one.
[Source]

Strands is the NYT’s latest word game after the likes of Wordle, Spelling Bee and Connections – and it’s great fun. It can be difficult, though, so read on for my Strands hints.

Want more word-based fun? Then check out my NYT Connections today and Quordle today pages for hints and answers for those games, and Marc’s Wordle today page for the original viral word game.

Quordle was one of the original Wordle alternatives and is still going strong now more than 1,500 games later. It offers a genuine challenge, though, so read on if you need some Quordle hints today — or scroll down further for the answers.

Enjoy playing word games? You can also check out my NYT Connections today and NYT Strands today pages for hints and answers for those puzzles, while Marc’s Wordle today column covers the original viral word game.

Good morning! Let’s play Connections, the NYT’s clever word game that challenges you to group answers in various categories. It can be tough, so read on if you need Connections hints.

What should you do once you’ve finished? Why, play some more word games of course. I’ve also got daily Strands hints and answers and Quordle hints and answers articles if you need help for those too, while Marc’s Wordle today page covers the original viral word game.

Jeff Bezos is letting outside investors into Blue Origin for the first time since he founded it in 2000. The rocket company is seeking about $10bn in fresh capital at a $130bn pre-money valuation, according to CNBC.

For 26 years, Bezos bankrolled the company himself, selling billions in Amazon stock rather than sharing ownership. That solo-funding era is now over.

He is not stepping back entirely, with reporting suggesting he will put around $2bn into the round himself. Hedge fund Coatue Management is expected to add roughly $4bn, with strong institutional interest for the rest.

The obvious question is what changed. The blunt answer is that staying in the space race has outgrown even one of the world’s richest people.

A costly stretch of bad timing

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Blue Origin is trying to do several expensive things at once. It is recovering from a failed New Glenn static-fire test that destroyed a launch pad, while scaling production of that same heavy-lift rocket.

New Glenn is the vehicle Blue Origin is counting on for lunar and national-security missions. Chief executive Dave Limp has committed to returning it to flight before the end of 2026, with launches planned for NASA, Amazon’s Leo satellite network, and AST SpaceMobile.

That combination of recovery and scale-up, more than any single rival’s move, is the sharper reason for the timing. Founder wealth alone cannot comfortably absorb costs at this pace.

Chasing a rival worth far more

The backdrop is SpaceX, which just pulled off the largest IPO in history. It raised a record sum, reportedly near $86bn, at a valuation around $2tn, even as its filing confirmed Musk keeps dominant voting control.

SpaceX’s lead is built on reusable rockets, Starlink, and government work, including a $2.29bn Space Force contract. Catching up on lunar and defence launches now takes tens of billions, not a founder’s cheque.

Investor appetite for space has swelled since that listing, as money that once flowed into SpaceX proxies now has the real thing to chase. Rivals from Stoke Space to Firefly have raised or gone public on the same wave.

Blue Origin has taken only limited outside money before, including a 2021 grant and a 2022 acquisition, and it has not disclosed a closing timeline. Whether $10bn narrows the SpaceX gap or merely buys time depends far less on the capital than on one thing: getting New Glenn back to the launch pad, and off it.

Every time you use ChatGPT or generate an image with AI, there is a memory chip working at extreme speed behind the scenes. However, that chip has a memory bottleneck problem, and a Korean research team may have just solved it.

Researchers at POSTECH (Pohang University of Science and Technology) developed a new way to stack more than 10 ultrathin semiconductor chips on top of each other, achieving a memory density roughly four times higher than the best commercial chips available today (via TechXplore).

Why is stacking chips so hard, and what makes this one different?

High-bandwidth memory, or HBM, is the type of memory that powers AI accelerators. It works by stacking multiple chips vertically, much like building a high-rise instead of spreading out across land.

The problem is that as chips get thinner, they become incredibly fragile. At one-fifth the thickness of a human hair, they bend, warp, and crack under pressure. Current manufacturing methods make this worse, often damaging chips before they even make it into a stack.

The POSTECH team solved this by combining two techniques into one process. Transfer printing precisely places each chip where it needs to go, while in-situ bonding forms the metallic connections at the same moment, all under low heat below 180 degrees Celsius and low pressure below 20 kilopascals. The result is a stack of more than 10 chips with almost no misalignment and very little warping.

Why this matters for the future of AI

More memory packed into the same space means AI tools can run faster and handle bigger tasks without needing larger or more expensive hardware. The researchers also see uses beyond AI, including next-generation micro-LED displays and advanced processor designs that need the same kind of ultra-precise stacking this method delivers.

Getting this into commercial production is the next step, but if it gets there, the memory ceiling that has been quietly holding AI back could finally start to lift.