#ai-cpus

#ai-cpus

AI Armor provides dynamic runtime security and relies on a central policy engine in the Universal Management Suite (UMS) to meet compliance requirements, ensuring that organizations can manage their security effectively.

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.

AMD clarified those estimates are based on a comparison between an eight-GPU MI300X node and an MI500 rack system with an unspecified number of GPUs. The math works out to eight MI300Xs that are 1000x less powerful than X-number of MI500Xs. And since we know essentially nothing about the chip besides that it'll ship in 2027, pair TSMC's 2nm process tech with AMD's CDNA 6 compute architecture, and use HBM4e memory, we can't even begin to estimate what that 1000x claim actually means.

The company, which is based in San Francisco and has an office in Pune, India, is targeting up to $35 million this year as it builds a royalty-driven on-device AI business. That growth has buoyed the company, which now has post-money valuation of between $270 million and $300 million, up from around $100 million in its 2022 Series B, Kheterpal said.