Nvidia

Two weeks ago, Allbirds was a corpse. On Wednesday, it was an “AI company” — up 582% intraday, peaks near 700%, $127 million in market cap added in a single session. Nothing about the business changed. No GPUs. No customers. No data center. No team. Just a rename: NewBird AI, a $50 million convertible note, and a press release with the magic phrase “low-latency AI compute hardware.” If 2026 needed a tombstone for market rationality, this is it. ...

If you’ve been waiting for the AI hardware story to stop being “Nvidia, Nvidia, and also Nvidia,” circle April 14, 2026. That’s when Meta and Broadcom went public with an expanded partnership to co-design multiple generations of Meta’s MTIA accelerators through 2029, anchored by a 1-gigawatt initial deployment and a path to multiple gigawatts after that. The headline spec: the first AI silicon built on TSMC’s 2nm process. This isn’t a routine vendor press release. It’s the loudest signal yet that the era of hyperscalers handing blank checks to Jensen is ending. ...

Quantum computing has been “almost here” for about two decades. Every year brings another breathless announcement about qubit counts and quantum supremacy. Every year the practical reality stays the same: these machines are fragile, error-prone, and maddeningly difficult to keep running. It’s like owning a Formula 1 car that breaks down every time you turn the key. NVIDIA thinks it found the mechanic. On April 14, 2026, the company launched NVIDIA Ising — the world’s first family of open-source AI models designed to tackle the two biggest bottlenecks in quantum computing: processor calibration and error correction. If the early benchmarks hold up, this could be the most consequential bridge between classical AI and quantum hardware we’ve seen yet. ...

Two deals. Two days. Two of the biggest names in AI writing checks to the same company. On Thursday, Meta committed an additional $21 billion to CoreWeave for AI cloud capacity through 2032. On Friday, Anthropic — the company behind Claude — signed a multiyear agreement to run its workloads on CoreWeave’s infrastructure. CoreWeave’s stock ripped past $103, and its total revenue backlog now exceeds $66.8 billion. For a company that started out mining Ethereum, that’s not a bad week. ...

The Nvidia Era Is Over — At Least in China DeepSeek’s next flagship model, V4, will run exclusively on Huawei Ascend chips. Not as a backup. Not as a proof of concept. As the entire inference stack. That’s not a press release talking point. That’s a tectonic shift. For years, China’s AI labs quietly depended on Nvidia silicon — H100s, A100s, whatever they could get their hands on through official channels or creative workarounds. That dependency is now ending, and it’s ending fast. ...

Jensen Huang dropped another $2 billion like it was couch change. The recipient? Marvell Technology — a company whose core business is helping hyperscalers build custom chips so they don’t have to buy Nvidia GPUs. Read that again. Nvidia just invested $2 billion in a competitor enabler. Huang called it “a marvelous investment” on CNBC. Yes, he really said that. Marvell’s stock popped 13%. Nvidia climbed 3-4%. Everyone made money. But the real story isn’t the dad joke — it’s the strategy hiding behind it. ...

There’s a new unicorn in AI — and it’s literally in orbit. Starcloud, a Redmond-based startup building solar-powered data centers in space, just announced a $170 million raise at a $1.1 billion valuation. Led by Benchmark and EQT Ventures, the round brings total funding to $200 million and launches what might be the most audacious infrastructure play in AI history. But Starcloud isn’t alone up there. SpaceX has filed FCC plans for up to one million orbital data center satellites. Blue Origin is circling the same idea. Nvidia is providing the chips. And here’s the kicker — Starcloud already has an H100 GPU running Google’s Gemma model in orbit right now. ...

Nvidia’s deepest moat was never the silicon. It was CUDA — the software ecosystem that made every AI developer on Earth, including China’s, completely dependent on Nvidia’s way of doing things. You could build a faster chip, but if developers had to rewrite their entire codebase to use it? Dead on arrival. Huawei just found the side door. The Ascend 950PR, paired with Huawei’s overhauled CANN Next software stack, has reportedly won over ByteDance and Alibaba — two of China’s largest AI consumers. After years of Beijing practically begging its tech giants to go domestic, Huawei may have finally built a chip they actually want to use. ...

Four words from the most powerful man in AI just broke the internet: “We’ve achieved AGI.” Jensen Huang — CEO of NVIDIA, the $4 trillion company whose GPUs power essentially every AI system on the planet — sat down with Lex Fridman this week and casually dropped what should be the most consequential claim in the history of technology. Artificial general intelligence, the holy grail researchers have chased for decades, is apparently already here. ...

Jensen Huang just told the world Nvidia expects $1 trillion in revenue by 2027. That’s double last year’s forecast. But the real story from GTC 2026 isn’t the number — it’s the machine that’s supposed to earn it. Vera Rubin Isn’t a Chip. It’s an Ecosystem. Stop thinking about Nvidia as a GPU company. The star of this year’s GTC is the Vera Rubin platform — a five-rack-scale AI supercomputer built from seven different chips, each purpose-designed for a specific slice of the AI workload. ...