[AINews] not much happened today • ButtondownTwitterTwitter

The AI Twitter recap showcases new AI model releases like Aria by Rhymes AI and updates from OpenAI, Google Gemini, Meta AI, and more. The Reddit recap delves into discussions on AI hardware advancements like AMD's MI325X GPU, the GPU rental market dynamics, and challenges of running 8 GPUs in a home server setup. These recaps provide valuable insights into the latest developments, research, tools, industry trends, and humor in the AI community, offering informative content for AI engineers.

The Supermicro 4029 model is specifically designed for passive GPUs rather than desktop GPUs. Users have recommended utilizing the IPMI utility to adjust fan speeds and potentially swapping out fans with quieter options like Sunon Maglev fans. Some concerns were raised about the practicality of the setup, with suggestions to consider using 2-4 4090s instead of 8 GPUs for 32-bit models. Additionally, users suggested exploring passively cooled GPUs and desktop alternatives to address noise issues. Another interesting development is a home server running local AI on a Raspberry Pi over a 10-year period, evolving from Wolfram Alpha and Wit.ai to current LLMs. The latest version, MK II, operates on 8GB of memory, a new Raspberry Pi CPU, and 1 terabyte of storage, specifically designed for areas with limited or no internet access. The project aims to democratize AI access in areas without internet, serving as a home server/cloud with file management capabilities including 1TB storage for various media files. The AI tool Mela offers free, local AI capabilities for chat and document creation without a backend, developed over 6 months and prioritizing user privacy. It utilizes WebGPU for efficient processing, supports open-source models like Llama 2, Mistral, and Phi-2, and offers real-time text generation, document summarization, and a built-in vector database for context-aware responses.

A member inquired about resources and advice for a GPU Engineer internship, highlighting the importance of a strong CUDA background. The anticipated test formats include multiple-choice questions and coding tasks, indicating the need for mentorship and targeted resources for aspiring engineers. Additionally, discussions revolved around challenges in optimizing Llama 7B training on limited GPU resources, with suggestions such as utilizing tools like FSDP2 and activation checkpointing. The community also highlighted ROCm's new native support for Windows from version 6.3, expanding access for AMD users to GPU technology.

A member shared about Batch-GPT, a tool that reduces OpenAI API costs by 50%+ through its Batch API, enhancing cost-effective implementation. They discussed the benefits of an onboarding form for DSPy to guide new users and foster user experience. News on OpenAI implementing DSPy optimizations excited community members, hinting at improved service performance. Additionally, the community delved into topics like the GraphIC method for In-context Learning and handling ambiguity in LLM classification, showcasing a deep dive into AI advancements.

Users are sharing their experiences with NotebookLM's audio generation feature, noting fun yet inconsistent quality, such as hallucinations and repeated phrases. Concerns have been raised about AI-generated podcasts overwhelming platforms with low-quality content. Curiosity about NotebookLM's capabilities and limitations has sparked discussions including challenges with data formats. Users express enthusiasm for engaging with NotebookLM, share tips on maximizing features, and discuss future developments such as interactive features and enhanced user controls. The community anticipates potential transformations in their interaction with AI-generated content.

H100 Prices Plummet to $2/hr:

A guest post titled $2 H100s: How the GPU Rental Bubble Burst highlights the dramatic drop in H100 prices from $8/hr to under $2, with multiple vendors now in the mix.

• It raises the question of whether smaller AI companies should buy or rent as new Blackwell chips hit the market.
• Congrats on HN Feature!: Congrats were given to a member for publishing the first LS post to reach Hacker News in a long time, sparking excitement.

• Guest Post Outperforms Tesla Robotaxi: @picocreator's post saw better engagement than Tesla robotaxi, sparking discussions on HN feedback.
• SFCompute Gains Attention: During H100 pricing chatter, attention shifted to SFCompute's rising visibility post-private beta.
• Growing Competition in GPU Rental Market: Discussions highlight increasing competition as users explore alternative GPU rental options.

Links:

• Tweet from Latent.Space (@latentspacepod): Insights on GPU rental bubble burst and guest post.
• Tweet from swyx 🔜 NYC (@swyx): Comparison between @picocreator's post and Tesla robotaxi.

In this section, various user interactions and discussions within different AI-related channels are highlighted. Users seek endorsements for papers, discuss serious benchmarks, propose new benchmarks, contemplate AI evaluation processes, and delve into specific AI topics such as neural network statistics and AI interpretability. Additionally, users share experiences with tools, seek advice on handling AI warnings, and discuss the impact of intellectual property on AI innovation, showcasing a vibrant and collaborative community focused on enhancing AI technologies.

Here we delve into various conversations happening across different AI communities. From discussing challenges in training models on limited GPU memory to sharing insights on recent developments in GPU technology, the exchanges cover a wide range of topics. Members share experiences with different frameworks, express concerns about performance in coding tasks, and highlight advancements like the rollout of ROCm with native Windows support. Additionally, the interactions showcase camaraderie through shared experiences and humor, creating a welcoming and engaging atmosphere within these communities.

Users have reported that the v2 API is slower than v1, with response times of 2-3 seconds compared to 1-1.5 seconds in v1. Performance issues with the Cohere API toolcall were mentioned, although a related GitHub issue has been closed. Users seek insights and resolutions for performance problems. Questions arose about using tokens like <code><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|></code> in API requests and the impact on response quality. Understanding token requirements is highlighted for effective API usage.

Aria is introduced as an open multimodal native model with 3.9B and 3.5B activated parameters, outperforming Pixtral-12B and Llama3.2-11B in language understanding and multimodal tasks. Research emphasizes the importance of multimodal native AI models for effective integration of diverse real-world information, highlighting challenges in adapting proprietary models and the need for open approaches like Aria to drive adoption and innovation.