[AINews] not much happened today • ButtondownTwitterTwitter

In this section, the AI Twitter Recap covers updates on AI models and research from organizations like Meta FAIR, Anthropic AI, and NVIDIA. It also highlights advancements in AI tools and infrastructure from LangChain, Kestra, and OpenFLUX. Moreover, insights on AI safety and ethics, economic impacts of AI, applications like LlamaIndex's Knowledge-Backed Agents and Perplexity's Financial Search API, and community events are discussed. The section concludes with some memes and humor surrounding AI. The AI Reddit Recap gives a snapshot of discussions on /r/LocalLlama, focusing on Meta's Quantized Llama Models and their impact on on-device AI. The recap provides insights into the release of quantized Llama models, emphasizing increased speed and reduced memory footprint.

Cerebras Inference has achieved a 3x performance boost, now running Llama 3.1-70B at 2,100 tokens per second, which is 16x faster than the fastest GPU solution. Companies like Tavus and GSK are utilizing Cerebras Inference for video generation and drug discovery. The hardware features of Cerebras CS-2, such as its 15U size, 23kW power draw, and unique architecture using pizza-sized wafers, were also highlighted. Users have found impressive performance on the Cerebras chat demo, with discussions on translation tasks and API usage limits. The potential applications and comparisons metrics for scaled thinking, inference-time compute scaling, and better samplers were explored. Furthermore, power scaling tests were conducted using 4 RTX 3090 GPUs with MLC LLM and Mistral Large Instruct 2407 q4f16_1, testing a power range of 150 to 350 watts. The experiments aimed to evaluate the performance and efficiency of these high-end GPUs in running large language models at various power levels.

E2B Desktop Sandbox Launches

The E2B Desktop Sandbox is now in beta, offering isolated environments tailored for LLM applications with full filesystem support and customizable features. User feedback is encouraged to enhance the platform's utility in cloud environments. Claude 3.5 introduces advanced privacy controls, allowing screen monitoring and device control. Cerebras Chip sets impressive inference records, outperforming GPUs. OpenAI hints at launching Orion model, sparking debates. Cohere introduces Embed 3 model for multimodal capabilities, aiming for real-time data processing efficiency.

This section showcases various discussions within different AI communities. Members lauded the Coherere community for its quality discussions, while others discussed challenges with Claud's rate limits in the OpenInterpreter Discord. LAION members shared bottlenecks observed during video model training and engaged in a discussion about new webinar highlights. The OpenAccess AI Collective discussed handling DPO evaluations, while LangChain AI inquired about evaluating datasets from PDF files. Members on the LLM Agents Discord exchanged useful resources for LLM Finetuning. Torchtune Discord reported new issues and called for collaboration, and Mozilla AI discussions revolved around AI creators' compensation rights and data marketplace initiatives. Gorilla LLM Discord focused on function calling improvements. Lastly, the HuggingFace channel explored high-speed AI models, data ethics, generative AI advancements, and data processing strategies.

The section discusses seeking suggestions for enhancements on a transformer model, highlighting a request for feedback to foster community input and collaborative enhancement. It also features a Streamlit calculator project replication, protein phenotypes exploration, self-supervised learning in autonomous driving blog, an AI RPG adventure proof-of-concept, and galleries showcasing artistic styles. The content emphasizes the openness to community contributions and project developments within the HuggingFace community.

The latest advancements in AI technology are showcased in this section. Cerebras has launched a new chip that delivers 3x faster inference, setting records with Llama3.1-70B at over 2,100 tokens/s. This chip is stated to be 16x faster than the fastest GPU solutions, marking a significant improvement in AI processing capabilities. OpenAI's upcoming model named Orion has faced controversies regarding its release timeline, with CEO Sam Altman hinting at upcoming technology without confirming specific plans. Cohere has introduced its Embed 3 model, enabling enterprise-level search across text and image data sources, enhancing AI system capabilities. This update allows for real-time data processing across various document types, aiming to enhance efficiency in AI applications.

Nous Research engaged in revenue-sharing partnerships with Hyperbolic for its Hermes 3 model, discussing AI hype trends, performance benchmark debates, quantization techniques, and interest in decentralized AI development. They tackled the limitations of the softmax function in decision-making, proposed an adaptive temperature mechanism for sharper attention, and explored the potential of linear attention. Members shared information about Hermes datasets, open-source SFT datasets, and highlighted research papers regarding attention mechanisms and model performance enhancements.

This section presents highlights from various Discord channels discussing a range of topics related to AI models, API usage, model performance, and technical troubleshooting. Members share insights on using different models like ChatGPT, Pythia, and Claude, discuss the significance of BOS tokens for model performance, and explore the challenges and advancements in AI technology. Additionally, the community engages in conversations about the upcoming releases of AI models, the value of Pro subscriptions, and the application of AI in fields like legal research and comic creation.

Summary:

• A member shared a document outlining how the Discord cluster manager should function, serving as a foundational guide for future development. Another member planned to start development actively on November 3 with a completion goal of November 10, encouraging others to contribute.
• Kitty Ket reported significant progress on an LED matrix project, aiming for response times below 10ms. Discussions also included integrating PostgreSQL for Mojo, resources for learning Mojo language, and a bug report related to Mojo's memory management issues.

In this section, insights on creating knowledge-backed agents using LlamaIndex workflows were shared in an AI Agents Masterclass. Key components like LLM routers were highlighted, with a comparison between event-based and graph-based architectures favoring LLM routers. Additionally, a successful case study of NVIDIA's internal AI assistant deployment for sales was detailed, utilizing Llama 3.1 405b for simple queries and a 70b model for document searches. The system retrieves information from internal documents and the NVIDIA site. Links to further details and resources were provided.

In this section, members of the AI News community share updates and discussions on various topics. From techniques for automated prompt generation using MIPROv2 to a call for community support on Torchtune GitHub. Creators are seeking fair compensation for their AI training data, and initiatives like Human Native AI are addressing this need with an AI data marketplace. Mozilla's Data Futures Lab is also focusing on equitable data ecosystems in the generative AI era. Join the insightful discussions and stay updated with the latest in AI news!