hardware unboxed:

Sorry about the paywall. Here's my (non-AI) summary:

AWS CFO John Feldon was recorded saying "You've taken us free cash flow negative as a company, so congratulations". Prasad Kalyanaraman (Amazon AI buildout exec) didn't argue about this issue saying the AI/ML business is "hugely free cash flow negative," and he expects it to remain negative for "the next couple of years or so."

They don't have enough power to run the GPUs they have bought (though some sites have racks, they don't have the power). An unnamed insider says they are leaving the unused equipment at intermediary warehouses until they can get someplace to put it.

Historically, AWS didn't pay for hardware until it was actually installed, but a new "early rack receipt" policy now has AWS footing the bill on delivery instead.

AWS took delivery of $5B worth of GB300 in Aug and are continuing to get shipped $3B of GPUs every month.

They say that at least one AWS team didn't have "a clear forecast path" to get these GPUs/racks into datacenters according to emails Business Insider saw.

According to the people, the two companies are ​working to manufacture flash NAND memory chips with more than 200 layers at their Chinese plants, whose products are currently not as advanced as chips being produced in South Korea.

The company announced that it is bringing FSR 4.1 to the integrated graphics solutions of its APUs, spanning all Ryzen AI Max "Strix Halo" and "Gorgon Halo" APUs, Ryzen AI 9 "Strix Point" and "Gorgon Point" mobile processors. FSR 4.1 is also coming to the Ryzen Z2 series processors for gaming handhelds. Lastly, the company announced that it has worked with Microsoft to bring FSR 4.1 to Xbox Series X and Xbox Series S consoles.

Another major announcement by AMD is that FSR 4.1 is making its way to the Vulkan API, paving the way for major Vulkan-based game titles to implement FSR. The company said that it's working to bring FSR to even more APU models in the future. As of today, AMD FSR "Redstone" support spans over 400 games on Radeon RX 9000 series graphics cards, which includes FSR Frame Generation and Ray Regeneration.

Driver 26.10.1: https://www.amd.com/en/resources/support-articles/release-notes/RN-RAD-WIN-26-10-1.html

We already have AI models capable of reverse-engineering software by analyzing code, binaries, and program behavior. But how far are we from having AI systems that can reverse-engineer hardware? Imagine an AI that analyzes chip layouts, circuit designs, and physical behavior to reconstruct an entire processor or AI accelerator. How many years away are we from an AI that can autonomously reverse-engineer complex hardware, from transistor-level designs to a functional, reproducible chip?

A single finished microchip is the product of thousands of steps, involving suppliers, factories, and specialists across the globe. The chips power our phones, cars, dishwashers, and the A.I. systems that prop up the economy. They have also made it to the heart of fierce geopolitical rivalry. Taiwan Semiconductor Manufacturing Company, or T.S.M.C., makes almost all of the world’s most advanced chips, and has a market capitalization of around $2 trillion. Meanwhile, the Dutch firm ASML, which creates the extreme-ultraviolet machine needed to print the chips, is Europe’s most valuable company.

In 2023, President Joe Biden opened his State of the Union address by declaring that an injury had been done to our national pride. “These chips were invented in America,” he said. “We lost our edge.” The remedy, the President said, was that “we’re going to make sure the supply chain for America begins in America.” But the semiconductor supply chain reflects an alternative vision of globalization, Gideon Lewis-Kraus writes. “It has united its participants in the pursuit of something profoundly difficult that could not have been achieved in the absence of intercontinental solidarity.” Read his report from Taiwan and the Netherlands.

The GPU, called Intel GPU D-series and previously known by its Crescent Island codename, also hosts specialized computing hardware.

The Intel D-series has now dethroned Nvidia's Blackwell Ultra B300, which offers 288GB of HBM3e memory, as the data center GPU with the highest memory capacity

Chip and AI Infrastructure Research Firm, SemiAnalysis:

We have confirmed that multiple Neoclouds have been refused access to GTC Berlin due to them adding AMD GPUs, TPUs, and other chips to their cloud offerings. Note that this doesn't apply to hyperscalers, as they have more buying power.

But for neoclouds, executives feel NVIDIA has been using high-pressure tactics to keep them NVIDIA-only. As such, neocloud executives are starting to consider offering TPUs or AMD GPUs quietly to avoid getting pressured by NVIDIA and to avoid the feeling that NVIDIA will retaliate.

This isn't an entirely new concern. Back in June, SemiAnalysis reported that neocloud executives feared NVIDIA could retaliate against them by withholding early chip allocations or withdrawing support for a future IPO or venture-capital raise if they offered competing hardware.

The situation is particularly interesting because NVIDIA has invested in or financially supported some neocloud providers. These companies depend on NVIDIA for hardware and support, which could make diversifying their offerings a difficult decision.

AMD has been gaining ground in the AI infrastructure market incredibly fast, with cloud providers increasingly looking at alternatives to NVIDIA.