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Model: "mistral-large-2"
Too Cheap To Meter: AI prices cut 50-70% in last 30 days
gpt-4o gpt-4o-mini llama-3-1-405b mistral-large-2 gemini-1.5-flash deepseek-v2 sonnet-3.5 exaone-3.0 minicpm-v-2.6 claude-3.5 gpt-4o-2024-08-06 llamaindex together-ai deepinfra deepseek-ai mistral-ai google-deepmind lg-ai-research llamaindex llamaindex llamaindex price-cuts context-caching instruction-tuning vision benchmarks pytorch attention-mechanisms reinforcement-learning-from-human-feedback compute-optimal-scaling rohanpaul_ai akhaliq mervenoyann sophiamyang chhillee karpathy
Gemini 1.5 Flash has cut prices by approximately 70%, offering a highly competitive free tier of 1 million tokens per minute at $0.075/mtok, intensifying the AI model price war. Other significant price reductions include GPT-4o (~50% cut to $2.50/mtok), GPT-4o mini (70-98.5% cut to $0.15/mtok), Llama 3.1 405b (46% cut to $2.7/mtok), and Mistral Large 2 (62% cut to $3/mtok). Deepseek v2 introduced context caching, reducing input token costs by up to 90% to $0.014/mtok. New model releases include Llama 3.1 405b, Sonnet 3.5, EXAONE-3.0 (7.8B instruction-tuned by LG AI Research), and MiniCPM V 2.6 (vision-language model combining SigLIP 400M and Qwen2-7B). Benchmarks show Mistral Large performing well on ZebraLogic and Claude-3.5 leading LiveBench. FlexAttention, a new PyTorch API, simplifies and optimizes attention mechanisms. Andrej Karpathy analyzed RLHF, highlighting its limitations compared to traditional reinforcement learning. Google DeepMind research on compute-optimal scaling was also summarized.
not much happened today
gpt-4-0613 gpt-3.5-turbo-0613 gpt-4o-2024-08-06 mistral-large-2 gpt4-turbo claude-3-opus idefics3-llama bigllama-3.1-1t-instruct llama-3-120b-instruct openai mistral-ai meta-ai-fair structured-outputs function-calling json-schema benchmarking multimodality context-windows model-scaling ai-hardware vision speech-processing robotics ai-regulation sama rohanpaul_ai corbtt guillaumelample mervenoyann maximelabonne aidan_mclau adcock_brett ylecun
OpenAI introduced structured outputs in their API with a new "strict" mode and a "response_format" parameter, supporting models like gpt-4-0613, gpt-3.5-turbo-0613, and the new gpt-4o-2024-08-06. They also halved the price of gpt-4o to $2.50 per million tokens. Mistral Large 2 outperforms gpt4-turbo and claude-3-opus on hard benchmarks and coding tasks. Idefics3-Llama offers multimodal capabilities with a 10k token context window. BigLlama-3.1-1T-Instruct is an upscaled version of llama-3-120b-instruct. New benchmark "big_model_smell" measures creativity and reliability. Figure 02 robot features advanced AI hardware with onboard vision language model, enhanced battery, and speech-to-speech reasoning. Yann LeCun expressed concerns about California's SB1047 regulation.
AlphaProof + AlphaGeometry2 reach 1 point short of IMO Gold
gemini alphageometry-2 alphaproof llama-3-1-405b llama-3-70b llama-3-8b mistral-large-2 google-deepmind meta-ai-fair mistral-ai neurosymbolic-ai mathematical-reasoning synthetic-data knowledge-sharing model-fine-tuning alpha-zero multilinguality context-windows model-scaling benchmarking performance-comparison tim-gowers guillaume-lample osanseviero
Search+Verifier highlights advances in neurosymbolic AI during the 2024 Math Olympics. Google DeepMind's combination of AlphaProof and AlphaGeometry 2 solved four out of six IMO problems, with AlphaProof being a finetuned Gemini model using an AlphaZero approach, and AlphaGeometry 2 trained on significantly more synthetic data with a novel knowledge-sharing mechanism. Despite impressive results, human judges noted the AI required much longer time than human competitors. Meanwhile, Meta AI released Llama 3.1 with a 405B parameter model and smaller variants, and Mistral AI launched Mistral Large 2 with 123B parameters and 128k context windows, outperforming Llama 3.1 on coding tasks and multilingual benchmarks. This marks significant progress in AI mathematical reasoning, model scaling, and multilingual capabilities.
Mistral Large 2 + RIP Mistral 7B, 8x7B, 8x22B
mistral-large-2 mistral-nemo-12b llama-3.1-8b llama-3.1-70b llama-3.1 llama-3-405b yi-34b-200k gpt-4o mistral-ai meta-ai-fair groq togethercompute code-generation math function-calling reasoning context-windows model-deprecation pretraining posttraining benchmarking
Mistral Large 2 introduces 123B parameters with Open Weights under a Research License, focusing on code generation, math performance, and a massive 128k context window, improving over Mistral Large 1's 32k context. It claims better function calling capabilities than GPT-4o and enhanced reasoning. Meanwhile, Meta officially released Llama-3.1 models including Llama-3.1-70B and Llama-3.1-8B with detailed pre-training and post-training insights. The Llama-3.1 8B model's 128k context performance was found underwhelming compared to Mistral Nemo and Yi 34B 200K. Mistral is deprecating older Apache open-source models, focusing on Large 2 and Mistral Nemo 12B. The news also highlights community discussions and benchmarking comparisons.