IEEE Spectrum on MSN
Why are large language models so terrible at video games?
AI models code simple games, but struggle to play them ...
Morning Overview on MSN
Google’s TurboQuant claims 6x lower memory use for large AI models
Google researchers have proposed TurboQuant, a method for compressing the key-value caches that large language models rely on ...
As large language models (LLMs) continue to improve at coding, the benchmarks used to evaluate their performance are steadily becoming less useful. That's because though many LLMs have similar high ...
Google's TurboQuant reduces the KV cache of large language models to 3 bits. Accuracy is said to remain, speed to multiply.
This study introduces MathEval, a comprehensive benchmarking framework designed to systematically evaluate the mathematical reasoning capabilities of large language models (LLMs). Addressing key ...
As large language models (LLMs) continue their rapid evolution and domination of the generative AI landscape, a quieter evolution is unfolding at the edge of two emerging domains: quantum computing ...
A new academic study challenges a core assumption in developing large language models (LLMs), warning that more pre-training data may not always lead to better models. Researchers from some of the ...
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