NVIDIA, Ineffable Intelligence Team Up to Build the Future of Reinforcement Learning Infrastructure
Reinforcement-learning agents — AI systems that learn by trial and error — can convert computation into new knowledge.

Reinforcement-learning agents — AI systems that learn by trial and error — can convert computation into new knowledge.

Notton Arguably better than dummy DIMMs in your A1/B1 slots of ATX mobos with 4 dimm slots. Undoubtedly wouldn’t fit in server style mobos or mITX. Probably even some OC mobos like the MSI Z790Mpower, etc. could never fi…

Huawei, Alibaba, and five other domestic vendors make the cut, but Cambricon and Kunlunxin are absent.

Thunder64 I wouldn’t touch them with a 10 foot pole. Forget who is behind them, just the fact that they charge subscriptions for certain features that cost them nothing. To hell with that. Reply

The shift to agentic AI creates a new CPU requirement for the AI factory: fast cores, massive memory bandwidth and the ability to sustain high performance when all cores are active.

Despite its potential, x32 ABI also had several disadvantages. Using x32 ABI adds additional complexity for developers to deal with and requires compilers to support the feature. Arguably, its biggest technical problem r…

Thunder64 I wouldn’t touch them with a 10 foot pole. Forget who is behind them, just the fact that they charge subscriptions for certain features that cost them nothing. To hell with that. Reply

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But given what we know about GB10 already, the appeal of this type of system could be narrow at first. Because they share the same pool of LPDDR5X memory, the GB10 GPU enjoys just 273 GB/s of raw bandwidth, far less than…
