All tags
Topic: "superintelligence"
FlashAttention 3, PaliGemma, OpenAI's 5 Levels to Superintelligence
flashattention-3 paligemma-3b gemma-2b numinamath-7b deepseekmath-7b codellama-34b wizardcoder-python-34b-v1.0 chatgpt-3.5 openai together-ai google hugging-face deepseek code-llama attention-mechanisms fp8-training vision prefix-lm superintelligence fine-tuning chain-of-thought tool-integrated-reasoning self-consistency-decoding python coding-capabilities elo-ratings ilya-sutskever lucas-giffman
FlashAttention-3 introduces fast and accurate attention optimized for H100 GPUs, advancing native FP8 training. PaliGemma, a versatile 3B Vision-Language Model (VLM) combining a SigLIP-So400m ViT encoder with the Gemma-2B language model, emphasizes a prefix-LM architecture for improved image-query interaction. OpenAI reveals a framework on levels of superintelligence, signaling progress toward Level 2 and highlighting internal safety disagreements. On Reddit, NuminaMath 7B, fine-tuned from DeepSeekMath-7B, wins the AI Math Olympiad by solving 29 problems using iterative supervised fine-tuning and tool-integrated reasoning. Open-source LLMs like CodeLlama-34b and WizardCoder-Python-34B-V1.0 are closing the coding performance gap with closed models such as ChatGPT-3.5.
Ways to use Anthropic's Tool Use GA
claude-3-opus haiku opus convnext anthropic amazon google tool-use function-calling agentic-ai streaming vision parallelization delegation debate specialization open-science superintelligence convolutional-networks self-attention ai-research yann-lecun alex-albert sainingxie
Anthropic launched general availability of tool use/function calling with support for streaming, forced use, and vision, alongside Amazon and Google. Alex Albert shared five architectures for agentic tool use: delegation, parallelization, debate, specialization, and tool suite experts. Anthropic also introduced a self-guided course on tool use. Yann LeCun emphasized ethical open science funding, gradual emergence of superintelligence with safety guardrails, and convolutional networks for image/video processing as competitive with vision transformers. He also noted growth in AI researchers across industry, academia, and government.