All tags
Topic: "ai-hardware"
Softbank, NVIDIA and US Govt take 2%, 5% and 10% of Intel, will develop Intel x86 RTX SOCs for consumer & datacenters
magistral-1.2 moondream-3 nvidia intel meta-ai-fair mistral-ai multimodality vision model-optimization model-efficiency model-architecture reinforcement-learning fine-tuning ai-hardware gaussian-splatting live-demo visual-reasoning nearcyan _akhaliq vikhyatk
Nvidia and Intel announced a joint development partnership for multiple new generations of x86 products, marking a significant shift in the tech industry. This collaboration has been in the works for a year and impacts both consumer and data center markets, boosting hopes for Intel's Foundry business. On the AI hardware front, Meta showcased its neural band and Ray-Ban Display with a live demo that experienced hiccups but sparked discussion on live tech demos. Meta is also moving from Unity to its own Horizon Engine for AI rendering, including Gaussian splatting capture technology. In AI models, Mistral released Magistral 1.2, a compact multimodal vision-language model with improved benchmarks and local deployment capabilities, while Moondream 3 previewed a 9B-parameter, 2B-active MoE VLM focused on efficient visual reasoning.
s{imple|table|calable} Consistency Models
llama-3-70b llama-3-405b llama-3-1 stable-diffusion-3.5 gpt-4 stability-ai tesla cerebras cohere langchain model-distillation diffusion-models continuous-time-consistency-models image-generation ai-hardware inference-speed multilingual-models yang-song
Model distillation significantly accelerates diffusion models, enabling near real-time image generation with only 1-4 sampling steps, as seen in BlinkShot and Flux Schnell. Research led by Yang Song introduced simplified continuous-time consistency models (sCMs), achieving under 10% FID difference in just 2 steps and scaling up to 1.5B parameters for higher quality. On AI hardware, Tesla is deploying a 50k H100 cluster potentially capable of completing GPT-4 training in under three weeks, while Cerebras Systems set a new inference speed record on Llama 3.1 70B with their wafer-scale AI chips. Stability AI released Stable Diffusion 3.5 and its Turbo variant, and Cohere launched new multilingual models supporting 23 languages with state-of-the-art performance. LangChain also announced ecosystem updates.
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.
GPT4o August + 100% Structured Outputs for All (GPT4o August edition)
gpt-4o-2024-08-06 llama-3-1-405b llama-3 claude-3.5-sonnet gemini-1.5-pro gpt-4o yi-large-turbo openai meta-ai-fair google-deepmind yi-large nvidia groq langchain jamai langsmith structured-output context-windows model-pricing benchmarking parameter-efficient-expert-retrieval retrieval-augmented-generation mixture-of-experts model-performance ai-hardware model-deployment filtering multi-lingual vision john-carmack jonathan-ross rohanpaul_ai
OpenAI released the new gpt-4o-2024-08-06 model with 16k context window and 33-50% lower pricing than the previous 4o-May version, featuring a new Structured Output API that improves output quality and reduces retry costs. Meta AI launched Llama 3.1, a 405-billion parameter model surpassing GPT-4 and Claude 3.5 Sonnet on benchmarks, alongside expanding the Llama Impact Grant program. Google DeepMind quietly released Gemini 1.5 Pro, outperforming GPT-4o, Claude-3.5, and Llama 3.1 on LMSYS benchmarks and leading the Vision Leaderboard. Yi-Large Turbo was introduced as a cost-effective upgrade priced at $0.19 per million tokens. In hardware, NVIDIA H100 GPUs were highlighted by John Carmack for their massive AI workload power, and Groq announced plans to deploy 108,000 LPUs by Q1 2025. New AI tools and techniques include RAG (Retrieval-Augmented Generation), the JamAI Base platform for Mixture of Agents systems, and LangSmith's enhanced filtering capabilities. Google DeepMind also introduced PEER (Parameter Efficient Expert Retrieval) architecture.