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Testing shows 8x RTX PRO 6000 rigs excel at parallel serving, not giant model sharding

Jerry James benchmarked an 8-GPU NVIDIA RTX PRO 6000 Blackwell system paired with an AMD EPYC 9555 CPU, offering 768GB of combined GDDR7 memory. Rather than splitting huge models like Llama-3.1 405B or DeepSeek-R1 671B across all eight PCIe cards, which introduces heavy latency, the team found the setup performs best running independent single-GPU model instances in parallel.

Cognitive scientists probe why children learn language with far less data than AI models

Researchers highlight a stark 'data efficiency gap': large language models require orders of magnitude more text than a human child hears to master language basics. Stanford's Michael Frank and Georgetown's Ethan Wilcox note that while frontier models train on trillions of tokens, children pick up language fundamentals from a fraction of that input within their first year or two of life. Scientists are studying how kids achieve this to both understand human cognition and potentially inform more efficient AI training methods.