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Topic: "ar-interfaces"
A quiet weekend
llama-3 dolphin-2.9 pixart-sigma llama-3-70b microsoft coca-cola uber lmsys nous-research mistral-ai ar-interfaces transformers algorithmic-tasks turing-test graph-algorithms embeddings generative-ai model-optimization llm-inference quantization model-deployment yann-lecun
Yann LeCun predicts a shift to AR interfaces with AI assistants in 10-15 years, moving away from smartphones. The Dolphin-2.9 model based on Llama-3 was released, improving quality issues. PixArt Sigma, a 0.6B parameter model, achieves Stable Diffusion 3.0 level performance with complete prompt adherence and local usability. Research shows transformers can use meaningless filler tokens for algorithmic tasks with dense supervision. AI-generated restaurant reviews can pass the Turing test, fooling humans and AI detectors. Uber uses graph algorithms and learned embeddings for ETA prediction. Coca-Cola and Microsoft announced a 5-year AI partnership to accelerate cloud and generative AI initiatives. The Llama-3 70B model can run on a single 4GB GPU using AirLLM optimization without quantization but is slow. Mistral.rs is introduced as a fast LLM inference platform with quantization and OpenAI API compatibility. Only 5% of LLMs make it from prototype to production due to challenges, especially in enterprise. EXL2 and GGUF quantization methods for Llama models show similar perplexity vs model size, with Llama-3 and Llama-2 degrading more under quantization compared to full precision.