#486-chip-support

#486-chip-support

RAM prices are skyrocketing, driving up the cost of products that rely heavily on memory. The price of Raspberry Pi boards has now soared to the point where two 16GB Raspberry Pi 5 boards will cost you as much as a new laptop.

"I *really* don't think i486 class hardware is relevant any more," Torvalds said in 2022, noting that while some people may still operate 486 systems they aren't relevant from a kernel development standpoint. "At some point, people have them as museum pieces. They might as well run museum kernels."

Meta is building these chips because buying AI hardware at scale is expensive, and relying too heavily on external suppliers leaves less room to shape that hardware to its own needs. Building more in-house could help the company keep AI costs in check.

Four generations, MTIA 300, 400, 450, and 500, have been produced within less than two years, with several already in production and others scheduled for mass deployment in 2026 and 2027. The quick pace is deliberate. Rather than betting on a single chip generation and waiting years for results, Meta has adopted a roughly six-month cadence per generation, using modular chiplet architecture to enable incremental upgrades without replacing entire rack systems.

Sorano will be available with up to 84 Zen 5 cores - up from 64 on Siena - in a power envelope of just 225 watts. AMD isn't ready to spill all the beans on its latest Epyc just yet, but based on core count alone, we surmise the chip will either feature six density-optimized Zen 5c chiplets with 14 of 16 cores enabled or 12 of the frequency-optimized Zen 5 variety with one of the eight cores fused off.

The idea of machines that can build even better machines sounds like sci-fi, but the concept is becoming a reality as companies like Cadence tap into generative AI to design and validate next-gen processors that also use AI. In the early days of integrated circuits, chips were designed by hand. In the more than half a century since then, semiconductors have grown so complex and their physical features so small that it's only possible to design chips using other chips.

When I asked him how bad things really were, Clarke looked at me with a sigh. "Look, I've been at this a long time. This is the worst shortage I've ever seen. Demand is way ahead of supply. And it's driven by AI. It's driven by infrastructure. You've seen the spot market price-it's up to five times from September. That will manifest. It already has in contract pricing."

Scientists are showing that neuromorphic computers, designed to mimic the human brain, are not only useful for AI, but also for complex computational problems that normally run on supercomputers. This is reported by The Register. Neuromorphic computing differs fundamentally from the classic von Neumann architecture. Instead of a strict separation between memory and processing, these functions are closely intertwined. This limits data transport, a major source of energy consumption in modern computers. The human brain illustrates how efficient such an approach can be.