All tags
Topic: "parameter-efficient-fine-tuning"
Everybody shipped small things this holiday weekend
gpt-4o-voice gemini claude jamba-1.5 mistral-nemo-minitron-8b xai google anthropic openai cognition ai21-labs nvidia langchain fine-tuning long-context parameter-efficient-fine-tuning latex-rendering real-time-audio virtual-try-on resource-tags low-code ai-agents workspace-organization model-benchmarking dario-amodei scott-wu fchollet svpino
xAI announced the Colossus 100k H100 cluster capable of training an FP8 GPT-4 class model in 4 days. Google introduced Structured Output for Gemini. Anthropic discussed Claude's performance issues possibly due to API prompt modifications. OpenAI enhanced controls for File Search in their Assistants API. Cognition and Anthropic leaders appeared on podcasts. The viral Kwai-Kolors virtual try-on model and the open-source real-time audio conversational model Mini-Omni (similar to gpt-4o-voice) were released. Tutorials on parameter-efficient fine-tuning with LoRA and QLoRA, long-context embedding challenges, and Claude's LaTeX rendering feature were highlighted. AI21 Labs released Jamba 1.5 models with a 256K context window and faster long-context performance. NVIDIA debuted Mistral-Nemo-Minitron-8B on the Open LLM Leaderboard. LangChain introduced resource tags for workspace organization, and a low-code AI app toolkit was shared by svpino. Legal AI agents and financial agent evaluations using LangSmith were also featured.
5 small news items
llama-3 xLSTM openai cohere deepmind hugging-face nvidia mistral-ai uncertainty-quantification parameter-efficient-fine-tuning automated-alignment model-efficiency long-context agentic-ai fine-tuning inference-optimization leopold-aschenbrenner will-brown rohanpaul_ai richardmcngo omarsar0 hwchase17 clementdelangue sophiamyang
OpenAI announces that ChatGPT's voice mode is "coming soon." Leopold Aschenbrenner launched a 5-part AGI timelines series predicting a trillion dollar cluster from current AI progress. Will Brown released a comprehensive GenAI Handbook. Cohere completed a $450 million funding round at a $5 billion valuation. DeepMind research on uncertainty quantification in LLMs and an xLSTM model outperforming transformers were highlighted. Studies on the geometry of concepts in LLMs and methods to eliminate matrix multiplication for efficiency gains were shared. Discussions on parameter-efficient fine-tuning (PEFT) and automated alignment of LLMs were noted. New tools include LangGraph for AI agents, LlamaIndex with longer context windows, and Hugging Face's integration with NVIDIA NIM for Llama3. Mistral AI released a fine-tuning API for their models.
$100k to predict LMSYS human preferences in a Kaggle contest
llama-3-70b llama-3 gpt-4 claude-3-opus prometheus-2 groq openai lmsys scale-ai ai2 nvidia benchmarking datasets fine-tuning reinforcement-learning model-alignment hallucination parameter-efficient-fine-tuning scalable-training factuality chatbot-performance bindureddy drjimfan percyliang seungonekim mobicham clefourrier
Llama 3 models are making breakthroughs with Groq's 70B model achieving record low costs per million tokens. A new Kaggle competition offers a $100,000 prize to develop models predicting human preferences from a dataset of over 55,000 user-LLM conversations. Open source evaluator LLMs like Prometheus 2 outperform proprietary models such as GPT-4 and Claude 3 Opus in judgment tasks. New datasets like WildChat1M provide over 1 million ChatGPT interaction logs with diverse and toxic examples. Techniques like LoRA fine-tuning show significant performance gains, and NVIDIA's NeMo-Aligner toolkit enables scalable LLM alignment across hundreds of GPUs. Factuality-aware alignment methods are proposed to reduce hallucinations in LLM outputs.