With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.
You can even self-host it!
A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside ...
Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models ...
Abstract: Large Language Models (LLMs) are widely adopted for automated code generation with promising results. Although prior research has assessed LLM-generated code and identified various quality ...
Microsoft has warned that information-stealing attacks are "rapidly expanding" beyond Windows to target Apple macOS environments by leveraging cross-platform languages like Python and abusing trusted ...
A new framework from researchers Alexander and Jacob Roman rejects the complexity of current AI tools, offering a synchronous, type-safe alternative designed for reproducibility and cost-conscious ...
“Large Language Model (LLM) inference is hard. The autoregressive Decode phase of the underlying Transformer model makes LLM inference fundamentally different from training. Exacerbated by recent AI ...
They’re the mysterious numbers that make your favorite AI models tick. What are they and what do they do? MIT Technology Review Explains: Let our writers untangle the complex, messy world of ...
ABSTRACT: Large Language Models (LLMs) exhibit remarkable capabilities; however, they possess inherent limitations due to static training, which leads to outdated information and hallucinations.
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