The Hot Take: Interesting shift in markets....
If you know the name Allbirds, it's probably for the company's longstanding stated commitment to "sustainable shoes and apparel." Going forward, though, the corporate entity wants to be known for its "long-term vision to become a fully integrated GPU-as-a-Service (GPUaaS) and AI-native cloud solutions provider."
In a news release Wednesday morning, Allbirds announced that it has secured a $50 million convertible finance facility to help power this unexpected "pivot ... to AI compute infrastructure." If all goes to plan, the company will soon be known as NewBird AI, by which point it will presumably change the image of a spandex-clad hiker that still sits atop its News Release page.
Just weeks ago, Allbirds announced the $39 million sale of the "Allbirds brand and footwear assets" to American Exchange Group, owner of Aerosoles, Ecko Unlimited, and other fashion brands. Today's AI pivot announcement certainly casts that sale in a new light. But Allbirds also announced a new line of colorful Canvas Cruiser shoes just last week, so it's unclear how much long-term planning went into this new AI-related direction.Read full article
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The Hot Take: Apple can't compete so it's going the ASICs route from the looks of it.
Apple generally tries to keep its cards hidden, preferring a grand unveiling, replete with mega-flourishes, to a gradual trickle of information and unvarnished product launches. However, when you have a supply chain as expansive as Apple's, leaks abound nonetheless. And today, we've received a juicy tidbit regarding the tech giant's intentions for its upcoming ASIC, dubbed Baltra. Apple intends to move the production of its upcoming AI ASIC in-house According to a South Korean publication, Samsung Electro-Mechanics (SEMCO) - a company that specializes in core electronic components, multilayer ceramic capacitors, and chip substrates - has provided samples of its glass [ā¦]Read full article at https://wccftech.com/apple-shows-its-cards-plans-to-move-the-production-of-its-upcoming-baltra-asic-in-house/
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The Hot Take: Google, Nvidia and not Intel all the suddenly make this amazing new tech at around the same time? Not buying it.
Intel is advancing texture compression techniques with its newly introduced Texture Set Neural Compression (TSNC) technology, a neural network-based approach designed to significantly reduce the size of texture assets used in modern graphics workloads.
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The Hot Take: Interesting.
Nvidia has just demoed its Neural Texture Compression technique again at a GTC talk, where it showed VRAM usage dropping from 6.5 GB to just 970 MB in a scene. NTC uses a neural network to decompress textures instead of standard block-based compression, reducing texture size and VRAM usage while also improving final image quality.
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The Hot Take: We need more competition, AMD seems to be very quiet lately and might come out of no where with a beast but they haven't yet. So intel coming back in even to do an Ai bubble grab it still helps us all. Especially when that bubble pops.
Intel's Arc Pro B70 is designed to offer accessible local inference for AI users, delivering more memory at half the price of the competition. Intel Arc Pro B70 vs NVIDIA RTX PRO 4000 Blackwell: 32 GB vs 24 GB, $949 vs $1800, More AI Context, 2x Tokens Per Dollar So we talked about the unveiling of the Intel Arc Pro B70 graphics card in our other post, where we highlighted the specifications, availability, and prices of the product. The B70 is going to be the flagship Pro & AI product from Intel within its Arc Pro stack, and they have [ā¦]Read full article at https://wccftech.com/intel-arc-pro-b70-outclasses-nvidia-rtx-pro-4000-in-ai-at-half-the-cost/
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The Hot Take: Uh oh, Ai king looks to be in trouble.
U.S. senators Elizabeth Warren (D-Mass.) and Jim Banks (R-Ind.) told Commerce Secretary Howard Lutnick that he should suspend all active export licenses to China for Nvidia AI chips, saying that Nvidia's most advanced AI GPUs are being diverted into the country despite Jensen Huang's assurances.
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The Hot Take: Green New agenda doesn't fit in with Ai replacement of the plebes for sure. So they push us to Solar & Wind while they get viable power options for a bot?
Microsoft and Nvidia are joining forces to accelerate the construction of nuclear power plants for power-hungry AI data centers. The partnership combines generative AI, digital twin simulation, and Nvidia's Omniverse platform to streamline the nuclear lifecycle from permitting through operations.
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The Hot Take: Nvidia starting to feel the heat of competition and see those $ evaporate as they try other vendors.
Nvidia is preparing to launch a new chip designed to speed up AI responses, breaking with its long-running habit of flogging the same processor for every job.
Nvidia chief executive Jensen Huang is expected to unveil a chip focused on āinferenceā, meaning running models rather than training them.
According to people familiar with the plans for GTC next week, the chip is the first new product to emerge from Decemberās $20bn deal to hire the founders of Groq, a start-up building ālanguage processing unitsā tuned for high-speed answers to complex AI queries.
Three months after that deal, Nvidia is expected to debut a Groq-based LPU to sit alongside its forthcoming flagship Vera Rubin graphics processing unit. It is part of a product family meant to head off challengers and meet new kinds of AI applications.
The move lands as the worldās most valuable company gets grief from start-ups and customers, such as Google, all busy cooking up their own AI chips. This week, Meta announced a new family of four inference-focused processors.
One Silicon Valley venture investor said: āWe are entering an interesting phase that is not āNvidia dominantā,ā
For the past three years, Nvidiaās $4.5tn market capitalisation has been built on its GPUs, which have become the backbone of generative AI. They train models such as the ones behind OpenAIās ChatGPT.
Huang has insisted that a single system can handle training and then run the chatbots and coding tools built on top. Big Tech has spent hundreds of billions deploying these boxes while funding their own specialised silicon.
But the growing sophistication of AI tools, including āagenticā coding systems, is pushing Huang to ditch the mantra that one GPU fits every workload.
The Groq deal was worth about $20bn, according to people familiar with the transaction, making it one of the biggest deals in Nvidiaās 33-year history. It includes licensing and the hiring of key talent, including Groq founder and former Google chip executive Jonathan Ross.
Groq, which had been working with Samsung to manufacture its products, previously bragged that its LPUs were faster and more efficient than Nvidiaās GPUs for inference. Nvidia clearly listened.
Nvidiaās flagship Blackwell and Rubin systems lean on high-bandwidth memory to cope with the massive data loads that AI models fling around. But HBM is expensive and in increasingly short supply as SK Hynix and Micron struggle to keep up with demand.
The Groq-style chip will use SRam rather than the dynamic Ram used for HBM, according to people familiar with Nvidiaās plans, because SRam is more available and better suited to speeding up AI āreasoningā tasks.
Bank of America reckons that by 2030, inference will account for 75 per cent of AI data centre spending, up from about 50 per cent last year, and it expects a ābroadened AI portfolioā at GTC.
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The Hot Take: Interesting place to put an Ai Data-Center, giving it's probably hardened against military attacks.
10GW server farm, 10GW of new generation, and $4.2bn grid upgrade. And someone else is paying for the uranium cleanup Softbank's SB Energy is redeveloping Department of Energy (DoE) land in Ohio for a massive datacenter campus, adding extra generation facilities and power infrastructure alongside it.ā¦
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The Hot Take: Only going to shoot costs up on Ai accelerators and RAM or Samsung Chips.
Samsung Electronics' labor union has voted overwhelmingly to initiate dispute proceedings following a breakdown in wage negotiations, raising concerns over potential disruptions to the supply of HBM4 memory for Nvidia's next-generation AI accelerators.
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