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Topic: "human-eval-benchmark"
Andrew likes Agents
gpt-3.5 gpt-4 cyberrealistic_v40 platypus-xl sdxl-lightning openai stability-ai agents human-eval-benchmark fine-tuning local-llm-deployment inference-speed image-generation lora upscaling workflow-optimization andrew-ng lilian-weng emad
Andrew Ng's The Batch writeup on Agents highlighted the significant improvement in coding benchmark performance when using an iterative agent workflow, with GPT-3.5 wrapped in an agent loop achieving up to 95.1% correctness on HumanEval, surpassing GPT-4 zero-shot at 67.0%. The report also covers new developments in Stable Diffusion models like Cyberrealistic_v40, Platypus XL, and SDXL Lightning for Naruto-style image generation, alongside innovations in LoRA and upscaling techniques. Discussions on local LLM deployment and optimization focus on hardware setups and finetuning strategies for efficient inference and multi-user serving. Emad's departure from Stability AI and new Sora videos from OpenAI were also noted.