[AINews] not much happened today • ButtondownTwitterTwitter

AI Twitter Recap

• Meta Releases SAM 2 for Object Segmentation
  • @AIatMeta announced the release of SAM 2, a real-time object segmentation model with a new SA-V dataset.
  • SAM 2 can be applied to diverse use cases and is available under Apache 2.0 license.
• New Web Development Framework: FastHTML
  • @jeremyphoward introduced FastHTML for creating web apps in Python, with integrations and easy deployment options.
• AI Model Developments and Benchmarks
  • Scale's SEAL Leaderboard, Gemini 1.5 Pro's success, and Apple's technical report on Intelligence Foundation Language Models were highlighted.
• Open Source AI and Compute Resources
  • Discussions on open source AI importance, GPU resources availability, and pricing in the AI development community.

AI Reddit Recap

/r/LocalLlama Recap

• Quantization Advancements for Efficient LLM Inference
  • A Visual Guide to Quantization explores various techniques like INT8, INT4, and binary quantization for LLM efficiency.
  • The post covers principles, trade-offs, and advanced methods like vector quantization and mixed-precision quantization.
  • MaartenGr explains the need for quantization and includes over 60 custom visuals for better understanding.
  • Llama 3.1 405B EXL2 quant results show superior performance in long context Q&A tasks.

The post compares the performance of Llama 3.1 405B and 70B models in long-context tasks, focusing on EXL2 quantizations of the 405B model for GPU use. The author notes that in the 125-150GB model size range, raw EXL2 quantization outperforms Meta's distillation to 70B in terms of perplexity (PPL). Despite benchmarks suggesting similar performance, the 405B model significantly outperforms the 70B model and closed-source LLMs like GPT-4 and Claude Sonnet 3.5 in tasks involving long context Q&A, fact analysis, and remembering details from stories, especially near the 128K context limit. Llama 3.1 405B model outperforms 70B in long-context tasks, but 2.5bpw quantization of 405B struggles beyond 4K tokens, while 3bpw lasts until about 12K tokens. Discussions focused on comparing different quantization levels and model sizes, with interest in how the 405B model compares to fp16 70B and DeepSeek MoE models. The author notes that raw compute and training duration may contribute to improved performance. Users expressed interest in comparisons with Mistral Large 2 and other models for complex tasks and long context use. The author is working on extracting open test benchmarks from internal datasets for more objective comparisons.

Several updates and discussions were highlighted in this section. These include the implementation of rope scaling support in Unsloth, a request for translation datasets for model training, and new capabilities of the WebGPU API. Additionally, advancements in CUDA Mode Discord were covered, such as Randomized SVD and discussions on CPU offload optimization. Members also expressed excitement for the upcoming CUDA MODE IRL event. In Nous Research AI Discord, topics ranged from the competitive edge of small models to benchmark insights from Apple AI models. Further discussions revolved around techniques for merging Hermes and Llama models and the enhancements in Midjourney V6.1. OpenAI Discord featured the rollout of Advanced Voice Mode and discussions on Search GPT access. Anticipation for GPT-4o features and issues with DALL-E bot commands were also addressed. Cohere Discord touched upon API functionality, successful projects, and tool usage vs. connectors. Modular Mojo Discord highlighted the recap of Mojo Community Meeting #5 and explored capabilities like CSV readers and image parsing in Mojo. LlamaIndex Discord showcased office hours and discussed the GraphRAG technique. OpenAccess AI Collective Discord covered topics such as Transformers error during indexing and exploring RAG implementation for chatbots. In LangChain AI Discord, discussions included issues with the Agent Executor, LangGraph for planning, and new features in Llama 3.1. OpenRouter Discord members discussed usage spikes, LiteLLM alternatives, and challenges with Claude models. In Latent Space Discord, SAM 2 enhancements, Leonardo AI acquisition, and Kagi LLM Benchmarking Project were outlined. OpenInterpreter Discord included talks on using OI for task management and AI-generated coding. Tinygrad Discord covered tasks related to merging views and discussions on parallel computing showcased in a YouTube video.

Token Limit Confusion for Meta LLaMA:

• Users discussed the token limits for the meta/meta-llama-3.1-405b-instruct, with confusion about whether it is 100 tokens, while others reported around 100 tokens in their replies.

Hugging Face Datasets Reliability Issues:

• Members expressed frustration regarding Hugging Face datasets being down for two days, with discussions on errors and unreliability.

Training Issues on Different GPUs:

• Users shared experiences of training models on various GPUs, mentioning issues with models freezing and out-of-memory errors while training on a 3060.

New Background Removal Model Available:

• A member announced the merging of a better background removal model on Hugging Face, providing excitement for improvements over the previous rmbg1.4 model.

Using Accelerator for TPUs:

• While trying to utilize the trainer API on TPUs, it was mentioned that simply running the script should automatically capture the device if Accelerate is installed.

The sections discuss various insights and findings related to quantization techniques in Large Language Models (LLMs) and the challenges faced in running these models on consumer hardware due to their size. Members share resources like articles and YouTube videos exploring the topic of quantization in relation to LLMs. The discussions also touch on diffusion models, TikTok trends in AI, and advancements in image generation technologies. Additionally, there are conversations on autoregressive music generation models, diffusion transformers, and memory-efficient techniques. The importance of effective quantization strategies to manage memory demands as models scale up is emphasized.

• Perplexity will introduce revenue sharing models for publishers in the near future, beginning with advertising on related questions to support sustainable growth for media organizations and provide users with relevant content.
• This initiative aims to build user trust and ensure that publishers receive proper credit.
• The introduction of revenue sharing responds to criticism over content sourcing practices and aims to foster ethical collaborations in the media industry.
• The program launch is a strategic move to address backlash from news outlets regarding content scraping.

• Inquiry about Translation Datasets: A member is looking for translation datasets for fine-tuning models from English to other languages, considering the use of DeepL, with a suggestion to explore resources like Wikipedia for this purpose.
• Insight on Continued Pretraining: Discussion on how Continued Pretraining (CPT) helps models learn new languages and domains, offering links to notebooks for further learning opportunities.
• Blockchain Engineer Portfolio Showcase: A member with 5 years of experience as a Blockchain Engineer specializing in Cosmos SDK and substrate shares their portfolio, highlighting their expertise in bridging protocols, zkProof, and cloud architecture.
• More Details: Share your portfolio as a Blockchain Engineer with 5 years of experience.
• Travel Projects and Hackathon Internship: A member dedicated to exploring underexplored domains and learning new tech, seeks internship opportunities for Hackathon events or similar programs. They encourage collaboration and sharing of knowledge and experience to enhance learning within the community.
• References and Resources: Links to educational materials and guides on continued learning, personal projects, and experiences in tech and blockchain for enthusiastic learners and professionals looking to expand their knowledge and skill set.

The section discusses various topics related to AI research, including Apple's work on HQQ+, quantization loss recovery techniques for LoRAs, and insights from Apple's paper on LoRA. It also covers discussions on CUDA mode, such as finetuning Llama 3.1, RoPE integration, SwiGLU implementation, and building modular training code. Furthermore, the section delves into WebGPU API, gpu.cpp usage, real-time multimodal integration, hybrid model computation, and local device computation. Lastly, it includes information on the upcoming event CUDA MODE IRL, keynotes recording, attendee guidelines, GPU access, and confirmation emails for registrants.

Expected GPT-4o Advanced Features:

Discussion sparked about the anticipated release of GPT-4o advanced vision and voice, with mixed expectations on timing, suggesting it may be pushed to next month. Another member mentioned a potential release at the end of this month in alpha.

Debate on AGI Understanding:

Some members engaged in a discussion about the ambiguity surrounding the AGI concept, noting the lack of a set definition. Opinions varied, with one emphasizing its interesting nature and complexity.

Excitement for Midjourney V6.1:

Members celebrated the recent launch of Midjourney V6.1, praising its impressive capabilities in image generation. Discussions highlighted how it excels in text transformations and potential use cases, with enthusiasm noted for its image-to-audio transformation potential.

This section provides updates on various AI-related developments and innovations. SAM 2, the Meta Segment Anything Model 2, has been released with real-time promptable object segmentation in images and videos, showing state-of-the-art performance. Leonardo AI has recently joined Canva, aiming to improve creative tools and empower creators. Additionally, there are discussions on LiteLLM alternatives, challenges with Claude models and instruct templates, the surge in Palm Chat 2 usage, and the capabilities of GPT-4o. The section also covers collaborations between OpenAI and Anthropic with brands, as well as a White House report on Open-Source AI.

The latest updates across different AI projects and initiatives include the Kagi LLM Benchmarking Project highlighting gpt-4o as a leader in accuracy and efficiency, discussions on strategic collaborations between OpenAI, Anthropic, and Google Analytics, and the release of a White House report advocating for open-source AI technology. The Apple Intelligence Beta launch on macOS and iPhone, discussions on open interpreter use cases, and the launch of Perplexica's Publishers Program were also notable. Additionally, insights were shared on recent developments such as Apple's use of TPUs for AI model training, Tim Dettmers joining the Allen Institute, and the recruitment of Sewon Kim. Furthermore, updates on technology events, parallel computing talks, challenges with OpenCL resource errors, and declines in email open rates due to Apple iCloud Private Relay issues were discussed.

Interconnects section includes a message about an article related to scaling exponents. In the DSPy Papers section, discussions revolve around topics like OPTO in Trace's framework, AI innovation in gaming history, growth of neural networks, and Microsoft's role in AI advancements. Each topic highlights significant developments and advancements in the field of AI.