#ai-gpus

#ai-gpus

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.

gamers are probably going to feel left out since Nvidia seems to have decided renting cloud rigs to them is better than selling consumer hardware, small companies looking for AI chip compromises will be excited, and agentic AI is gonna be so hot that our Mann on the ground this week in San Jose isn't gonna need a jacket.

Either way, I think the AI boom is alive and well, but with much of the short-term hype fading away, the big question is whether the long-term trajectory is still there and whether it makes sense for investors to hit the buy button now that the near-term is somewhat less hyped while the long-term is as exciting as ever.

Nvidia's investment portfolio operated as a modest initiative valued around $230 million two years ago, focusing on smaller companies and chip designers. By the end of 2025, however, the public equity portfolio alone had reached more than $13 billion, according to its 13F filing. This expansion stems directly from cash generated by Nvidia's core GPU sales, particularly in the data center segment, which have driven record revenue.

What we are beginning to see is that many open-source and other models are becoming compact enough and sufficiently optimized to run very efficiently on consumer GPUs,

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.