August 16, 2024

[AINews] not much happened today

This is AI News! an MVP of a service that goes thru all AI discords/Twitters/reddits and summarizes what people are talking about, so that you can keep up without the fatigue. Signing up here opts you in to the real thing when we launch it 🔜

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GPT5 delayed another day?

AI News for 8/14/2024-8/15/2024. We checked 7 subreddits, 384 Twitters and 29 Discords (254 channels, and 5043 messages) for you. Estimated reading time saved (at 200wpm): 945 minutes. You can now tag @smol_ai for AINews discussions!

A smattering of notables but no major story:

• Nous Research released their Hermes 3 finetune of Llama 3 base models, matching and in some places exceeding the 3.1 instruct tunes done by FAIR. Some controversy over their claimed emergent existential crisis behavior, especially with 6% of data being roleplay.
• Nvidia's Minitron is another interesting finetune of Llama 3.1
• Salesforce's new DEI agent with a 55% on SWE-Bench Lite
• Goodfire AI announced their $7m seed working on mechanistic interpretability.

Since it's a quiet day, you could check out our sponsor Box's AI API!

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[Sponsored by Box] You have files. The files are full of nonsense. Box AI has an API that extracts useful metadata from the nonsense. See for yourself.

Swyx's comment: compared to last week's sponsored post, this tutorial goes into metadata extraction from your Box items, aka structured data, and showing practical usecases for querying that metadata. All RAG eventually evolves into hybrid embedding + metadata queries, and Box's template approach is perhaps a more practical take on the JSONSchema API by the big labs.

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Table of Contents

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AI Twitter Recap

all recaps done by Claude 3.5 Sonnet, best of 4 runs.

AI Model Updates and Releases

• Anthropic API Prompt Caching: @alexalbert__ announced that Anthropic has rolled out prompt caching in their API, cutting input costs by up to 90% and reducing latency by up to 80%. The feature allows for reusing a book's worth of context across multiple API requests, beneficial for coding assistants, large document processing, and agentic tool use.

• Grok-2 Release: @_philschmid reported that xAI has released Grok-2, which matches frontier models like Claude 3.5 Sonnet and GPT-4-Turbo on the LMSYS leaderboard. It supports vision + text inputs and integrates external models for image generation.

• Claude 3.5 Sonnet Performance: @bindureddy claimed that Sonnet 3.5 is outperforming GPT-4 in key areas like coding and reasoning, suggesting a shift from "GPT-4 class" to "Sonnet class" for state-of-the-art models.

AI Research and Development

• Intelligence Definition: @fchollet proposed that intelligence is the efficiency of operationalizing past information to deal with the future, expressible as a conversion ratio using algorithmic information theory.

• Salesforce DEI Framework: @_akhaliq shared that Salesforce has released DEI (Diversity Empowered Intelligence), an open AI software engineering agents framework with a 55% resolve rate on SWE-Bench Lite, surpassing individual agent performance.

• AI in Scientific Discovery: @GoogleDeepMind featured a podcast discussion with CEO Demis Hassabis on how AGI could help explore the mysteries of the universe, current AI hype, and safe technology development.

AI Tools and Applications

• Dora AI Plugin: @svpino showcased the Dora AI Figma plugin, which can generate a complete landing page in less than 60 seconds, potentially making professional web teams 10 times more efficient.

• Box AI API: @svpino announced the beta release of Box's AI API, enabling users to chat with documents, extract data, summarize content, and generate derived content from their existing Box storage.

• LangChain Integration Updates: @LangChainAI reported revamped integration docs for Python & JavaScript, featuring standardized templates, streamlined index pages, and enhanced API references for over 1,000 integrations.

Memes and Humor

• @kylebrussell joked about using Apple Vision Pro to catch up on great cinema, poking fun at the device's capabilities.

• @teortaxesTex shared a meme about the consequences of "doing the bit" in reference to the anime Edgerunners, highlighting the potential dangers of taking fictional scenarios too seriously.

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AI Reddit Recap

/r/LocalLlama Recap

Theme 1. New Open Models

• Magnum 12b v2.5 KTO (Score: 62, Comments: 12): Anthracite HQ has released Magnum 12b v2.5, a new language model tuned with a hybrid reinforcement learning strategy combining KTO and DPOP. The model uses rejected data from the original model as "rejected" and the original finetuning dataset as "chosen", and is available in exl2, gguf, and fp16 formats on Hugging Face.
  • Users discussed the model's marketing tone, with some finding it overly enthusiastic. One commenter asked if the post was written by ChatGPT or the model itself.
  • A user reported that the model produced more coherent responses than other open-source models they've used, comparing its performance to 100B+ models. They noted it didn't fall for usual tricks to confuse models.
  • Discussion on sampling settings ensued, with recommendations for a min-p of ~0.03 and a low temperature of ~0.02. Some users expressed surprise at the low temperature setting.

• Mistral Nemo appreciation post (Score: 213, Comments: 49): Mistral's Nemo 12B model has been praised for its impressive capabilities, combining 12B parameters with a 128k context length. The model is noted to outperform Llama-2-13B significantly, offering 32 times the context length while providing a more robust conversational experience compared to 7B models.
  • Mistral's Nemo 12B model has been praised for its efficiency and functional calling capabilities. Users noted it outperforms Llama 3.1 in mixing text replies and function calls, with one commenter calling it their "new go-to model."
  • The model's 128k context length has been questioned, with some users reporting degradation in quality beyond 8k-16k tokens. Discussions suggest using techniques like DRY and modern samplers to improve performance at longer context lengths.
  • Users shared custom system prompts to enhance the model's performance, focusing on strategic problem-solving and innovative thinking. The community also compared Nemo to other models like Gemma 2 9B and InternLM 2.5 20B for various use cases.

Theme 2. Grok-2 and Grok-2 Mini: x.AI's Latest Benchmark Results

• Grok-2 and Grok-2 mini benchmark scores (Score: 82, Comments: 22): Grok-2 and Grok-2 Mini benchmark scores have been released, showing impressive performance across various tasks. Grok-2 achieved 92.1% on MMLU, 90.5% on HumanEval, and 82.4% on GSM8K, while Grok-2 Mini scored 86.5%, 80.5%, and 74.9% on the same tasks respectively. These results position Grok-2 competitively against other leading models like GPT-4 and Claude 2, particularly in coding and mathematical reasoning tasks.
  • Users discussed Sonnet 3.5's scores being placed at the far right of the chart, with some interpreting it as an attempt to downplay its performance. One commenter noted that Grok-2 beats Claude 3.5 Sonnet in two benchmarks.
  • The absence of open weights for Grok-2 was highlighted, with users questioning Elon Musk's stance on open-source AI. Some expressed skepticism about his statements, calling him a "conman of the highest order".
  • Commenters expressed surprise at Grok-2 Mini's performance, outperforming Claude 3 Opus and Gemini 1.5 Pro in main benchmarks. However, one user suggested this could be due to "contaminated madness", implying potential data contamination.

All AI Reddit Recap

r/machinelearning, r/openai, r/stablediffusion, r/ArtificialInteligence, /r/LLMDevs, /r/Singularity

AI Image Generation Advancements

• FLUX model demonstrates photorealistic textures: A low-rank LORA trained on 4K professional photos shows FLUX's capability to capture super photorealistic textures, surprising even professional photographers.
• GGUF quantization for FLUX: An unexpected development allows GGUF quantization techniques, typically used for LLMs, to be applied to the FLUX image generation model, potentially enabling larger models to run on consumer hardware.
• FLUX NF4 V2 released: An updated version of the FLUX NF4 model has been released on Civitai, with users reporting varied performance improvements across different hardware setups.
• Union ControlNet for FLUX: InstantX has released an alpha version of union ControlNet for FLUX, rapidly expanding the model's capabilities.

AI in Commercial Applications

• AI-generated Adidas advertisement: A 2-hour creation using FLUX and Runway demonstrates AI's potential to disrupt the advertising and modeling industries.
• AI-created product commercial: A real product commercial made entirely with AI showcases the technology's application in marketing.

AI Model Behavior and Capabilities

• ChatGPT voice interactions: A demonstration of ChatGPT's voice capabilities, including heavy breathing and shouting, raises discussions about emotional connections to AI and potential misuse.

Humor and Memes

• AI-generated feet images: A humorous post suggests getting rich by generating perfect feet images with AI, highlighting the model's improved capabilities in generating challenging anatomical features.

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AI Discord Recap

A summary of Summaries of Summaries by GPT4O (gpt-4o-2024-05-13)

1. LLM Advancements and Benchmarking

• Llama 405B Processing Milestone: Meta's Llama 405B model processed up to 300 million words this week on OpenRouter, showing significant usage despite low inference costs with Lepton's 128k context at $2.8 per 1 million words.
  • This usage suggests Llama 3.1 might be the second-best model for Aider, following DeepSeek, though conclusive results require more direct API usage data.
• Grok-2 and Grok-2 Mini Release: Grok-2 and Grok-2 Mini were released in beta, outperforming Claude 3.5 Sonnet and GPT-4-Turbo on the LMSYS leaderboard.
  • These models will be available through the enterprise API later this month, marking a significant step forward from Grok-1.5.

2. Model Optimization and Caching

• Anthropic API Gets Prompt Caching: Anthropic rolled out prompt caching for its API, reducing input costs by up to 90% and latency by up to 80%.
  • The feature works by caching frequently used prompts, similar to DeepSeek's implementation but faster and more efficient.
• OpenRouter Integrates Prompt Caching: OpenRouter will integrate prompt caching into its API, improving performance and cost efficiency, particularly for repetitive tasks.
  • This move aims to benefit tasks and prompts with consistent elements, reducing API usage and enhancing model performance.

3. AI Tools and Plugins

• AI21 FusionLabs Plugin Progress: Development of the AI21 FusionLabs plugin for Bubble is progressing well, allowing seamless integration of AI21Labs models into Bubble applications.
  • The upcoming Conversation RAG portal will enable users to test and explore new features, with a dev test link to be provided soon.
• LlamaIndex Workflows for RAG Systems: LlamaIndex released Workflows for building advanced Retrieval-Augmented Generation (RAG) systems integrated with Azure services.
  • These workflows leverage custom data connectors for Azure AI Search and Azure OpenAI, enhancing data flow and functionality.

4. Open-Source AI Frameworks and Community Efforts

• Hyperbolic Embeddings in Research: Hyperbolic embeddings gain popularity for preserving graph distances and complex relationships, useful in knowledge base completion and NLP tasks.
  • Researchers are integrating these embeddings into applications like question answering, enhancing data representation in continuous spaces.
• Tinygrad Typechecking: A py.typed file was added to Tinygrad, ensuring type-checking works properly with the tinydreamer package.
  • This fix was necessary to enable mypy to function correctly, improving the development process for Tinygrad.

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PART 1: High level Discord summaries

aider (Paul Gauthier) Discord

• Llama 405B Processing on OpenRouter: OpenRouter has been processing an impressive 200-300 million words this week using Meta's Llama 405B model.
  • This is despite a relatively low inference cost, especially with Lepton's 128k context and $2.8 per 1 million words.
• Is 5-Minute Context Caching Effective for Aider?: A member questioned the effectiveness of 5-minute context caching for Aider, considering the typical user turnaround time.
  • However, others argue that even small text variations could hinder the effectiveness of caching, given that many prompts might be repetitive.
• Maintaining Aider Context through Scripting: A member sought guidance on maintaining Aider's context through scripting for iterative generations and testing.
  • The response highlighted that keeping the Coder object alive is crucial for preserving internal state, and using markdown files for chat history is not ideal for continuous chat.
• Llama 3.1 as a Potential Second Best Model: OpenRouter data suggests that Llama 3.1 could be the second best model for Aider, after DeepSeek.
  • However, conclusive results require direct API usage data.
• Grok-2 and Grok-2 Mini Now Available: Grok-2 and Grok-2 mini, described as a significant step forward from Grok-1.5, were released in beta on 𝕏.
  • They will be available through the enterprise API later this month and have reportedly outperformed Claude 3.5 Sonnet and GPT-4-Turbo on the LMSYS leaderboard.

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Stability.ai (Stable Diffusion) Discord

• Free Stable Diffusion Deployments: A user asked for free methods to deploy Stable Diffusion models and received suggestions for using Civitai, Shakker AI, and Hugging Face, with Civitai being the most popular.
  • They specifically noted that Civitai appears to be the most commonly used platform among community members.
• NFT Scams Targeting Artists: A member cautioned against suspicious NFT offers, sharing their experience of being contacted with offers that seemed too good to be true.
  • Other members confirmed that these offers are likely scams, emphasizing that legitimate businesses should be able to provide proof of their legitimacy.
• Stable Diffusion on Phones: A user inquired about free options for running Stable Diffusion on their phone, looking for generous generation credits or ad-supported alternatives.
  • Other users advised that running Stable Diffusion on mobile requires a powerful GPU, suggesting SD.Next as a possible web-based solution.
• Free Image-to-Video Solutions: A member requested recommendations for free image-to-video software, seeking the best options available.
  • Another member explained that GPUs naturally throttle for heat, recommending Afterburner for fine-tuning and utilizing the "Generate Forever" feature in various UIs.
• Flux Discord Server: Several members expressed interest in joining a Flux Discord server, recognizing the growing popularity of Flux.
  • One member suggested that the SD3 section of the current server has become somewhat of a Flux section, while another suggested starting a separate Discord dedicated to Flux.

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OpenRouter (Alex Atallah) Discord

• OpenRouter Removes "Flavor of the Week" Model: OpenRouter is removing the "Flavor of the Week" model next week due to low usage.
  • The model is available at https://openrouter.ai/models/openrouter/flavor-of-the-week and OpenRouter is asking for feedback on the experiment.
• OpenRouter Arena Struggles with LLM Performance Judgments: Some members are concerned that the OpenRouter Arena may not be a reliable judge of LLM performance due to the lack of clear details on testing methodologies and the possibility of bias from users with varying levels of expertise.
• OpenRouter Integrates Prompt Caching: OpenRouter will be integrating prompt caching into its API, which will allow for significant improvements in performance and cost efficiency.
  • This will be especially beneficial for repetitive tasks and prompts with consistent elements.
• OpenRouter Adds New LLM Model: Hermes 3: Nous Research has released their Hermes 3 models (8B, 70B, 405B), and they are now available on OpenRouter.
• 4oSo Agent Combines GPT-4o and Claude 3.5 Sonnet: 4oSo is a "mixture of agents" approach that combines GPT-4o with Claude 3.5 Sonnet.
  • This approach runs on OpenRouter.

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Eleuther Discord

• Meteorologist Needs Help: A user is looking for someone to contract or work full time on meteorological ML models for a customer.
  • This project would likely be of interest to those who enjoy working with graph networks.
• LLM Training Stopping Conditions Are Not Complicated: A user inquired about stopping conditions for pretrained LLMs.
  • The state of affairs is currently simple, with a recent paper suggesting a high constant learning rate for 80% of training followed by a decay to 0% for the remaining 20%.
• Cosine Decay Is The Traditional Regime: A user described the traditional LLM training regime.
  • It involves a one-and-done cosine decay across the entire pre-determined run length, typically to around 10% of the original learning rate.
• Hyperbolic Embeddings: A New Way to Represent Data: Hyperbolic embeddings, a technique for representing data in a continuous space, have gained popularity for their ability to preserve graph distances and complex relationships, particularly for hierarchical graphs.
  • Researchers are releasing hyperbolic embeddings that can be further integrated into applications like knowledge base completion and NLP tasks like question answering.
• Tackling Activation Quantization in Language Models: A new research paper tackles the challenge of accurate quantization for language models, specifically focusing on activation quantization.
  • The paper proposes a strategy using quantization-aware training (QAT) and activation kurtosis regularization to address the issue of outlier channels that emerge during training.

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Interconnects (Nathan Lambert) Discord

• Anthropic API Gets Prompt Caching: Anthropic has just released prompt caching for its API, which cuts API input costs by up to 90% and reduces latency by up to 80%.
  • The feature works by caching frequently used prompts, similar to Deepseek's implementation, but Anthropic's implementation is faster and more efficient.
• SB 1047 Amended: The California Appropriations Committee passed SB 1047 with amendments that change the bill, particularly impacting the requirement for AI labs to submit certifications of safety test results.
  • AI labs will now be required to submit public statements outlining their safety practices, but the bill no longer imposes any criminal liability for those statements.
• Impact of SB 1047: The passing of SB 1047 with these amendments could have a significant impact on the entire AI ecosystem, including in the EU and Asia.
  • The bill aims to prevent AI disasters by implementing safeguards, but opponents argue that it could stifle innovation and hinder the development of AI.
• ACL Controversy: Bender's Talk Sparks Debate: A talk by Emily Bender at the ACL conference sparked controversy, and a response was published addressing the concerns raised.
  • The response, available as a GitHub Gist, delves into the issues surrounding the talk and aims to provide a balanced perspective.
• The Talk's Impact on the Community: The talk has sparked considerable discussion within the NLP community, with some expressing agreement with Bender's concerns while others disagree.
  • The controversy has highlighted the importance of responsible AI development and the need for open dialogue about ethical considerations.

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Modular (Mojo 🔥) Discord

• MAX: Mojo's New Focus: The Mojo team is prioritizing MAX, a platform for accelerated compute, over networking, arguing that it has a broader impact in the compute space.
  • MAX is a library for controlling hardware beyond the CPU, including GPUs, DPUs, and potentially even custom NICs.
• Mojo's Package Management: Modular Approach: The Mojo team plans to manage packages in a modular fashion, focusing on smaller, more manageable units.
  • They are prioritizing key features like GPU support before exploring package splitting options.
• MAX: Universal Matrix Multiplication: MAX aims to offer a single implementation for matrix multiplication that can be compiled to optimal instructions for various hardware platforms.
  • This involves using MLIR for high-level representation and selecting optimized kernels based on available hardware.
• Mojo's Brand: MAX Takes the Stage: While Mojo is the programming language, the entire platform's brand is MAX, the Modular Accelerated Xecution Platform.
  • MAX will encompass components like GPUs, graph API, and evolving features as new capabilities are developed.
• Mojo Community Meeting #6: Recordings Available: The latest Mojo Community Meeting, covering small buffer and string optimizations, DuckDB bindings, and MAX, is now available on YouTube.
  • You can access the recording at https://youtu.be/6huytcgQgk8.

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LlamaIndex Discord

• LlamaIndex Unveils New Workflows for Robust RAG Systems: LlamaIndex's newly released Workflows empower the construction of advanced Retrieval-Augmented Generation (RAG) systems, seamlessly integrated with Azure services like AI Search and OpenAI.
  • This integration leverages custom data connectors, allowing for streamlined data flow and enhanced functionality within these Azure platforms.
• Citation Query Engine Gets a Workflow Makeover: A video demonstration highlights the rebuilding of the Citation Query Engine using LlamaIndex's powerful Workflows, showcasing a more robust and efficient approach.
  • This re-implementation leverages techniques like chunking and citing retrieved text, enabling the generation of responses with clear source attribution, effectively leveraging workflows and events for citation-enhanced retrieval.
• LlamaIndex's GraphRAG: A Quest for Production Apps: A community member expressed a desire to see production-ready GraphRAG applications, emphasizing the need to visually demonstrate how graphs enhance retrieval by providing additional context beyond just the LLM-generated answer.
  • Their own application, utilizing a property graph and RAG implementation for chat questions, aims to combine these approaches, seeking inspiration and best practices from other projects.
• Demystifying LlamaIndex Agent's Tool Call Expectations: A user inquired about the expected behavior of LlamaIndex Agent's tool calls within the astream_chat() function, particularly when receiving tools for use within the Agent.
  • Their specific concern focused on determining the most effective approach: either detecting tool calls and buffering the response before sending it, or continuing to stream tokens and sending the tools in the final response.
• Unlocking the Potential of LlamaIndex Agent with Chat History: A user sought guidance on feeding a list of messages to an OpenAIAgent, as the existing methods seem to accept only strings.
  • They explored the possibility of using a pop-off strategy for the last message, but needed confirmation on the proper usage and best practices for handling Agent interactions.

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OpenAccess AI Collective (axolotl) Discord

• Mistral Large 2 Training Progress: A member asked about the training status of Mistral Large 2, receiving a response that inputs are masked even in KTO.
• KTO Trainer Explained: A member requested information about whether KTO supports multi-turn or system prompts.
  • Another member directed them to the KTO Trainer documentation on Hugging Face, explaining the trainer's purpose and expected dataset format.
• KTO Trainer vs SFT: The KTO Trainer is designed for aligning language models with binary feedback data (e.g., upvote/downvote).
  • Depending on the base model's quality, SFT may not be necessary before KTO, unlike RLHF and DPO which always require it.
• SmolLM Model Fine-tuning: A member expressed interest in fine-tuning the SmolLM 130m or 350m models.
• GGUF Conversion with llama.cpp: A user asked for the commonly used repository for converting models to GGUF format and quantizing them.
  • A reply suggested using llama.cpp and its associated commands, noting that the process is relatively straightforward.

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tinygrad (George Hotz) Discord

• Tinygrad Typechecking Works Now: A member added a py.typed file to the Tinygrad repository to ensure type-checking functions properly with the tinydreamer package.
  • This fix was needed on their machine to enable the mypy function properly.
• Compiler Book Recommendations Needed: A member sought recommendations for a good book on compilers, likely looking for guidance on how to build a compiler for Tinygrad.
  • No specific book recommendations were given in the conversation.
• Exploring Cuda.py in Tinygrad: A member expressed interest in finding detailed documentation or blogs specific to the cuda.py file within the Tinygrad repository.
  • Specifically, they wanted to gain a deeper understanding of this file's role in Tinygrad, which handles CUDA acceleration.
• ONNX Support for Tinygrad: A member suggested adding ONNX support to the Tinygrad repository, aiming to support the majority of ONNX features within tensor.py.
  • This addition would potentially enable seamless integration of Tinygrad with other frameworks that use ONNX.
• Tinygrad vs Jax/Flux: A member inquired about Tinygrad's competitiveness against Jax/Flux, highlighting Jax's impressive capabilities.
  • Another member weighed in, suggesting that Jax prioritizes using Google's TPUs and fixing bugs for Google, while supporting other accelerators is merely for prototyping before migrating to Google's infrastructure.

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OpenInterpreter Discord

• Running LLMs Locally Requires Serious Power: A user pointed out that running LLMs locally, like OpenInterpreter (OI) and 01, requires significant computational power and isn't for everyone.
• Home Server Setup for OI and 01: One user suggested using a home server setup for running OpenInterpreter (OI) and 01.
  • They suggested Umbrel or TuringPi as potential hardware solutions.
• Three Key Components for Distributed Setup: A user detailed the three key components of a distributed setup for LLMs, OI, and 01.
• Personalized AI Tutors for Kids: The Future of Education?: The idea of personalized AI tutors for kids was discussed, specifically focusing on the emotional and personalized aspect of the tutor.
  • The goal is to create a system where the AI tutor can adjust to each child's learning style and personality.
• AI Tutors for Science Education: The conversation centered on using AI tutors to teach fundamental principles of the natural sciences.

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Alignment Lab AI Discord

• Jala: Automating Text Data Labeling: Jala, a new tool aiming to reduce the cost and time of manual text data labeling, is now accepting users on its waitlist.
  • This end-to-end solution uses AI to support diverse data formats, including CSV, JSON, TXT, and XML, with a user interface for fine-tuning a variety of models.
• Jala: Diverse Applications: Jala can be used for a variety of NLP, ML, and AI-related purposes, including data annotation for research and development, as well as automated content categorization.
  • Users can sign up for the waitlist at https://heimdall-3jl.pages.dev/pages/jala to get early access.

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MLOps @Chipro Discord

• AI Capabilities and Risks Demo-Jam Hackathon: The AI Capabilities and Risks Demo-Jam Hackathon is happening in 7 days!
  • It's a great opportunity to showcase AI risks and potential, win $2,000 in prizes, and network with AI safety experts and enthusiasts.
• Pre-Hackathon Workshop: A pre-hackathon workshop is happening tomorrow, August 18th at 3 pm UTC.
  • Participants can meet judges and mentors, and get a head start on brewing ideas for the hackathon.
• Join the Discord: Join the Discord server to learn more about the hackathon and connect with other participants.
  • The link to the Discord server is https://discord.gg/A4GZ9UKb?event=1270997649260281968.

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AI21 Labs (Jamba) Discord

• AI21 FusionLabs Plugin Progress: The development for the AI21 FusionLabs plugin for Bubble is moving along well.
  • This plugin will allow users to seamlessly integrate AI21Labs models into their Bubble applications.
• Conversation RAG Rollout: The rollout of a portal for trying out the newly released Conversation RAG is in the works.
  • This will give users a chance to test and explore the new features of Conversation RAG.
• AI21Labs Models on Bubble: Once the Conversation RAG portal is launched, a dev test link will be provided.
  • This will show developers how AI21Labs models work on Bubble, enabling them to experiment with the capabilities of AI21Labs models within the Bubble environment.

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The LLM Finetuning (Hamel + Dan) Discord has no new messages. If this guild has been quiet for too long, let us know and we will remove it.

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The Mozilla AI Discord has no new messages. If this guild has been quiet for too long, let us know and we will remove it.

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The DiscoResearch Discord has no new messages. If this guild has been quiet for too long, let us know and we will remove it.

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PART 2: Detailed by-Channel summaries and links

aider (Paul Gauthier) ▷ #general (148 messages🔥🔥):

• OpenRouter Aider Usage
• Model Caching
• Aider Scripting
• LLM Caching
• OpenAI Update

• Llama 405B usage on OpenRouter: A member shared that Meta's LLama 405B model is being used significantly on OpenRouter, with approximately 200-300 million words processed this week.
  • They also mentioned that the inference costs seem low, particularly with the Lepton offer at 128k context and $2.8 per 1 million words.
• Concerns about Model Caching's Effectiveness: A member questioned the effectiveness of 5-minute context caching for Aider, given the typical turnaround time of users.
  • Others argued that while the majority of prompts may be repetitive, even a small difference in text could prevent caching from being effective.
• Maintaining Aider Context via Scripting: A member inquired about maintaining Aider context through scripting to perform iterative generations with testing.
  • The response indicated that keeping the Coder object alive is the only way to preserve internal state, and that using a markdown file for chat history is not ideal for continuous chat.
• Caching Benefits and Use Cases: A member discussed the potential benefits of caching system prompts and user input to reduce API usage.
  • They highlighted the possibility of caching large prompts containing examples, repo maps, and system prompts, leading to significant cost savings and potential for enhanced model performance.
• OpenAI's ChatGPT-4o Update: A member shared that the new ChatGPT-4o-latest model is reportedly worse at code editing compared to previous versions.
  • They mentioned that this trend of model updates being less effective than previous versions is consistent with OpenAI's focus on optimizing speed and cost.

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aider (Paul Gauthier) ▷ #questions-and-tips (17 messages🔥):

• Llama 3.1
• Grok-2
• Aider Image Support
• OpenRouter
• Prompt Caching

• Llama 3.1 Might Be Strong Second To DeepSeek: Based on OpenRouter data, Llama 3.1 might be the second best model for Aider, after DeepSeek.
  • However, conclusive results would require direct API usage data.
• Grok-2 and Grok-2 Mini Released: Grok-2 and Grok-2 mini were released in beta on 𝕏, and will be available through the enterprise API later this month.
  • Grok-2 is described as a significant step forward from Grok-1.5, outperforming Claude 3.5 Sonnet and GPT-4-Turbo on the LMSYS leaderboard.
• Aider Supports Images For Some Models: Aider can handle image files for models like GPT-4o and Claude 3.5 Sonnet.
  • Users can add images to their chats using /add <image-filename>, /clipboard, or by launching Aider with the image filename on the command line.
• OpenRouter Does Not Support Prompt Caching Yet: OpenRouter does not support prompt caching, meaning that it does not save the prompts for future use.
  • This means that each prompt will be processed from scratch, even if it's the same as a previous prompt.
• Aider's .aider Files Need To Be Present: Aider creates files with the .aider extension to store configuration information.
  • These files should not be ignored by Git, as they are necessary for Aider to function properly. They can be ignored globally by adding .aider* to your global .gitignore.

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aider (Paul Gauthier) ▷ #links (6 messages):

• Aider UI in IDE
• Aider Conflict Resolution
• Aider Edit Confirmation

• Aider UI in IDE?: A user noted that the UI in a screenshot appeared different from the UI they had seen in Aider before. They inquired about the "Approve" button in Aider.
  • Another user clarified that the screenshot was likely taken from a code editor or IDE viewing Aider's output text, which mimics Git merge conflict resolution syntax. The "Approve" buttons are likely added by the editor/IDE because it recognizes the syntax as a merge conflict.
• Aider Misinterpretation of Edits: A user suggested that the overlay in Aider may not function properly based on their description of the behavior.
  • Another user countered that the screenshot showed "Applied edit to..." which indicates Aider applied the edit correctly.
• Aider Edit Confirmation Request: A user expressed support for a feature request to allow users to confirm each change made by Aider before applying it.
  • The user linked to a relevant GitHub issue on the Aider project (Add option to force the AI to ask the user to confirm each change before doing it · Issue #649 · paul-gauthier/aider) that explores the need for this feature.

Link mentioned: Add option to force the AI to ask the user to confirm each change before doing it · Issue #649 · paul-gauthier/aider: Issue Sometimes it is necessary to supervise each atomic change to the code or to the project configurations. Aider already shows us every atomic change like a diff. It would be great if, when spec...

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Stability.ai (Stable Diffusion) ▷ #general-chat (166 messages🔥🔥):

• Free SD model deployment
• NFT scams
• Stable Diffusion on phone
• Free image to video
• GPU throttling

• Where to Deploy SD models for Free?: A user asked where they could deploy their Stable Diffusion models for free.
  • Other users suggested using Civitai, Shakker AI, or Hugging Face, with Civitai being the most commonly used.
• NFT scams are common: A member shared concerns about receiving requests to convert their artwork into NFTs, with offers that seemed too good to be true.
  • Other members confirmed that these offers are likely scams, as real businesses can usually prove their legitimacy.
• Stable Diffusion on Phones?: A user inquired about accessing Stable Diffusion on their phone, seeking free options with generous generation credits or ad-supported alternatives.
  • Other users pointed out that Stable Diffusion on mobile requires a powerful GPU, suggesting web services like SD.Next as a potential solution.
• Free Image-to-Video Alternatives: A member asked for recommendations for the best free image-to-video software.
  • Another member explained that GPUs will naturally throttle down for heat, suggesting using Afterburner for fine-tuning and utilizing the "Generate Forever" feature in various UI options.
• Flux Discord Server?: Several users expressed interest in joining a Flux Discord server.
  • One user suggested that the SD3 section of the current Discord server has become somewhat of a Flux section, while another proposed starting a separate Flux Discord.

Link mentioned: Humanity is Doomed: Asmongold Clips / Asmongold Reacts To: AI catfishing is getting out of handAI Videos By: https://x.com/ai_for_success/status/1821975861698154993https://x.com...

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OpenRouter (Alex Atallah) ▷ #announcements (1 messages):

• Flavor of the Week Model Removal

• OpenRouter Removes "Flavor of the Week" Model: OpenRouter is planning to remove the "Flavor of the Week" model next week due to low usage.
  • The model is available at https://openrouter.ai/models/openrouter/flavor-of-the-week and OpenRouter is asking for feedback on the experiment.
• OpenRouter Asks for Feedback on Flavor of the Week Experiment: OpenRouter is seeking feedback from users about the "Flavor of the Week" experiment.
  • They are asking for input on whether the experiment was successful or not, and what could be improved.

Link mentioned: Flavor of The Week - API, Providers, Stats: This is a router model that rotates its underlying model weekly. It aims to be a simple way to explore the capabilities of new models while using the same model ID. Run Flavor of The Week with API

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OpenRouter (Alex Atallah) ▷ #app-showcase (3 messages):

• 4oSo agent
• OpenRouter
• Claude 3.5 Sonnet
• GPT-4o

• 4oSo agent combines GPT-4o and Claude 3.5 Sonnet: 4oSo is a "mixture of agents" approach that combines GPT-4o with Claude 3.5 Sonnet.
  • This approach runs on OpenRouter.
• Pre-emptive Thread Creation: A member created a pre-emptive thread to avoid cluttering the channel.

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OpenRouter (Alex Atallah) ▷ #general (120 messages🔥🔥):

• OpenRouter Arena
• OpenRouter LLM API
• OpenRouter LLM Model Availability
• OpenRouter Privacy
• OpenRouter PDF upload

• OpenRouter Arena has problems with judging LLM performance: Some members are concerned that the OpenRouter Arena may not be a reliable judge of LLM performance due to the lack of clear details on testing methodologies and the possibility of bias from users with varying levels of expertise.
• OpenRouter integrates prompt caching: OpenRouter will be integrating prompt caching into its API, which will allow for significant improvements in performance and cost efficiency, particularly for repetitive tasks and prompts with consistent elements.
• OpenRouter has a new LLM model: Hermes 3: Nous Research has released their Hermes 3 models (8B, 70B, 405B) and they are now available on OpenRouter.
• OpenRouter struggles with PDF upload: Some members are reporting that they cannot upload PDF files to OpenRouter for models to interact with, although the platform supports image uploads.
• OpenRouter API key integration still in beta: A new member expressed interest in integrating their own API keys for services like DeepSeek on OpenRouter, which is currently in beta.

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Eleuther ▷ #general (7 messages):

• Meteorological ML Models
• LLM Training Stopping Conditions

• Meteorologist Needs Help: A user is looking for someone to contract or work full time on meteorological ML models for a customer.
  • This project would likely be of interest to those who enjoy working with graph networks.
• LLM Training Stopping Conditions Are Not Complicated: A user inquired about stopping conditions for pretrained LLMs.
  • The state of affairs is currently simple, with a recent paper suggesting a high constant learning rate for 80% of training followed by a decay to 0% for the remaining 20%.
• Cosine Decay Is The Traditional Regime: A user described the traditional LLM training regime.
  • It involves a one-and-done cosine decay across the entire pre-determined run length, typically to around 10% of the original learning rate.

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Eleuther ▷ #research (58 messages🔥🔥):

• Hyperbolic Embeddings
• Activation Quantization
• Boundary Attention
• NAS

• Hyperbolic Embeddings: A New Way to Represent Data: Hyperbolic embeddings, a technique for representing data in a continuous space, have gained popularity for their ability to preserve graph distances and complex relationships, particularly for hierarchical graphs.
  • Researchers are releasing hyperbolic embeddings that can be further integrated into applications like knowledge base completion and NLP tasks like question answering.
• Tackling Activation Quantization in Language Models: A new research paper tackles the challenge of accurate quantization for language models, specifically focusing on activation quantization.
  • The paper proposes a strategy using quantization-aware training (QAT) and activation kurtosis regularization to address the issue of outlier channels that emerge during training.
• Boundary Attention: A New Approach to Image Segmentation: A new approach called boundary attention is introduced, which infers unrasterized boundaries from the bottom-up.
  • This lightweight model infers color-based boundaries with high-precision and uses output boundaries represented as embeddings that encode three-way partitions.
• NAS: A Glimpse into the Future of Neural Architecture Search: Members discussed the potential of using Neural Architecture Search (NAS) to optimize models.
  • The conversation explored the use of LLMs to conduct NAS, and potential applications for techniques like repulsive shells in training.

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Eleuther ▷ #lm-thunderdome (57 messages🔥🔥):

• Meta Llama benchmarks
• Benchmark differences
• Eval Harness settings
• Prompt engineering
• Eval harness differences

• Meta Llama benchmarks differences: A user is trying to reproduce Meta Llama benchmarks but is getting significantly lower results, around 2-3% lower.
  • The user has confirmed they are using the same model, but has not yet been able to figure out the reason for the differences in the benchmark results.
• Evaluating with the Eval Harness: The discussion is centered around how to replicate Meta Llama benchmarks using the EleutherAI lm-evaluation-harness.
  • The user is using the correct model and settings, but is still encountering discrepancies in the benchmark results, leading to speculation about potential differences in the prompt formatting, evaluation methods, and even potential discrepancies in the data used for evaluation.
• Prompt engineering impact: The discussion focuses on the impact of prompt engineering on the benchmark results.
  • The user is exploring different prompt formats and settings to see if they can improve their benchmark scores, with the understanding that Meta Llama's prompt engineering might be a contributing factor to the differences.
• Llama 3.1 data release: A user mentions that Meta has released the evaluation data for Llama 3.1, but not the code.
  • This data release is potentially helpful for understanding how Meta conducts their evaluations, but the lack of code release leaves room for uncertainty and might contribute to the difficulty in replicating their results.
• Meta's evaluation methods: A user suggests that Meta may be employing undisclosed generation techniques that contribute to the discrepancy in benchmarks.
  • This speculation highlights the challenge of replicating complex evaluations performed by large companies, where details of their methodologies might not be fully transparent.

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Interconnects (Nathan Lambert) ▷ #news (87 messages🔥🔥):

• Anthropic API
• Deepseek
• SB1047

• Anthropic API gets prompt caching: Anthropic has just rolled out prompt caching for its API, which cuts API input costs by up to 90% and reduces latency by up to 80%.
  • The feature works by caching frequently used prompts, similar to Deepseek's implementation, but Anthropic's implementation is faster and more efficient.
• SB 1047 Amended: The California Appropriations Committee passed SB 1047 with significant amendments that change the bill, particularly impacting the requirement for AI labs to submit certifications of safety test results.
  • AI labs will now be required to submit public statements outlining their safety practices, but the bill no longer imposes any criminal liability for those statements.
• Impact of SB 1047: The passing of SB 1047 with these amendments could have a significant impact on the entire AI ecosystem, including in the EU and Asia.
  • The bill aims to prevent AI disasters by implementing safeguards, but opponents argue that it could stifle innovation and hinder the development of AI.

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Interconnects (Nathan Lambert) ▷ #ml-drama (1 messages):

• ACL
• Emily Bender's Talk
• Response to Bender's Talk

• ACL Controversy: Bender's Talk Sparks Debate: A talk by Emily Bender at the ACL conference sparked controversy, and a response was published addressing the concerns raised.
  • The response, available as a GitHub Gist, delves into the issues surrounding the talk and aims to provide a balanced perspective.
• The Talk's Impact on the Community: The talk has sparked considerable discussion within the NLP community, with some expressing agreement with Bender's concerns while others disagree.
  • The controversy has highlighted the importance of responsible AI development and the need for open dialogue about ethical considerations.

Link mentioned: acl-presedential-response.md: GitHub Gist: instantly share code, notes, and snippets.

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Interconnects (Nathan Lambert) ▷ #memes (5 messages):

• Trump account

• Trump's Account Still Bad: A user posted a link to what is presumably former President Donald Trump's account on a social media platform, mentioning that it is good for building understanding of AI, even when the AI is still in its early stages.
• ****:

Link mentioned: Tweet from Donald J. Trump (@realDonaldTrump): no description found

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Modular (Mojo 🔥) ▷ #general (73 messages🔥🔥):

• Mojo Networking
• Mojo vs Go
• Mojo vs Rust
• Mojo's Future
• Mojo's Branding

• Mojo's Future: Focus on MAX: Mojo's focus is currently on MAX, a platform for accelerated compute, rather than focusing solely on networking.
  • This decision is backed by solid arguments, as MAX has a larger impact in the compute space than the network space.
• MAX's Capabilities & Use Cases: MAX is a library for controlling hardware beyond the CPU, including GPUs, DPUs, and potentially even custom NICs.
  • It can be used for tasks like high performance networking, web servers, and implementing TCP/IP protocol clients and servers.
• Mojo's Package Management: The Mojo team is considering how to best manage packages, with a preference for smaller, modular packages.
  • They're currently focused on delivering key features like GPU support before exploring options for splitting packages into smaller units.
• MAX's Role in Matrix Multiplication: MAX aims to provide a single implementation for matrix multiplication that can be compiled to the optimal sequence of instructions for different hardware platforms.
  • This involves using MLIR to represent the high-level operation and then selecting optimized kernels based on the available hardware.
• Mojo's Branding & Identity: Mojo is established as a programming language, but the entire platform needs a brand, which is MAX - the Modular Accelerated Xecution Platform.
  • MAX will encompass various components, including GPUs, graph API, and other features, and will continue to evolve as new capabilities are developed.

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Modular (Mojo 🔥) ▷ #mojo (18 messages🔥):

• Mojo Community Meetings
• Mojo String optimizations
• Mojo String Unicode support
• Mojo String implementation
• Small String Optimization

• Mojo Community Meetings #6 Recording Available: The recording for the latest Mojo Community Meeting is now available on YouTube, covering topics such as small buffer and string optimizations, DuckDB bindings in Mojo, and MAX.
  • The recording can be accessed at https://youtu.be/6huytcgQgk8.
• Radical String Approach in Mojo: A member shared their implementation of a Mojo String with small string optimizations and Unicode support using field space stealing and a Unicode codepoint index.
  • The code, available at https://gist.github.com/mzaks/78f7d38f63fb234dadb1dae11f2ee3ae, is a proof of concept that demonstrates the manageable complexity of the approach, with the Unicode codepoint index being more challenging than the small string optimization.
• Mojo String's Future: Decoupling from List: The current Mojo String implementation is a wrapper around a List data structure, making small string optimization difficult.
  • A member suggests that the standard library String will need to decouple itself from List to implement the field space stealing technique.

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Modular (Mojo 🔥) ▷ #max (1 messages):

• MAX real-time safety
• C API for MAX
• Real-time audio applications
• Onnxruntime and libtorch limitations

• Is MAX real-time safe?: A member inquired about the real-time safety of the MAX engine, specifically in the context of real-time audio applications.
  • They highlighted the current limitations of other frameworks like onnxruntime and libtorch, which require non-ideal background thread inference and lock-free queuing due to their lack of real-time safety.
• C API for MAX usage: The member is currently using C++ frameworks for model deployment, but they are interested in using the MAX engine if it is real-time safe.
  • Since there is no C++ API available for MAX yet, they plan to use the C API for integration.

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LlamaIndex ▷ #blog (2 messages):

• LlamaIndex Workflows
• RAG system
• Azure AI Search
• Azure OpenAI
• Citation Query Engine

• LlamaIndex Workflows for RAG Systems: LlamaIndex's new Workflows enable the creation of robust Retrieval-Augmented Generation (RAG) systems integrated with Azure services.
  • This workflow involves implementing custom data connectors for Azure AI Search and Azure OpenAI.
• Re-building the Citation Query Engine with Workflows: A video from @ravithejads demonstrates the re-building of the Citation Query Engine using workflows.
  • It covers techniques for chunking and citing retrieved text, creating responses that show their sources, and using workflows and events for citation-enhanced retrieval.

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LlamaIndex ▷ #general (62 messages🔥🔥):

• GraphRAG Apps
• LlamaIndex Agent tool expectations
• LlamaIndex agent and chat history
• LlamaIndex embedding update
• LlamaIndex GraphRAG and Microsoft's implementation

• Production GraphRAG Apps: A member asked if any production GraphRAG apps exist, highlighting their interest in seeing how graphs are used in production to show references or additional context beyond just the LLM written answer.
  • They specifically mentioned their own app using a property graph and a RAG implementation for chat questions, aiming to combine the two and seeking inspiration from other projects.
• LlamaIndex Agent Tool Call Expectations: A user inquired about LlamaIndex Agent's expectations for tool calls within the astream_chat() function, particularly when receiving tools to use.
  • They were trying to determine the best approach: either detecting tool calls and buffering the response before sending it with the request.tools list, or continuing streaming tokens and sending the tools in the final response.
• LlamaIndex Agent and Chat History: A member sought guidance on feeding a list of messages to an OpenAIAgent, as the existing methods appear to only accept strings.
  • They explored the possibility of popping off the last message and submitting it as a string, but sought confirmation on the correct usage of the library and the appropriate approach for working with an Agent.
• LlamaIndex Embedding Update Best Practices: A user inquired about the best practice for updating embeddings when using an ingestion pipeline to create embeddings for a PDF article and store them in ChromaDB.
  • They specifically asked how to handle situations where the same file is processed twice, resulting in the insertion of another set of embeddings.
• LlamaIndex GraphRAG vs. Microsoft's Implementation: A member acknowledged the power of LlamaIndex's GraphRAG implementation but questioned whether it fully aligns with Microsoft's original implementation.
  • They were curious if any steps suggested by Microsoft's implementation were not implemented in LlamaIndex and specifically asked if local and global search were currently implemented.

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OpenAccess AI Collective (axolotl) ▷ #general (21 messages🔥):

• Mistral Large 2 training
• KTO Trainer
• TRL
• SmolLM models
• Lambda Clusters

• Mistral Large 2 - Training Progress: A member inquired about the training status of Mistral Large 2.
  • Another member responded that inputs are masked even in KTO.
• Understanding KTO Trainer: A member asked if KTO supports multi-turn or system prompts.
  • Another member provided a link to the KTO Trainer documentation on Hugging Face which explains the trainer's purpose and expected dataset format.
• KTO and SFT - A Comparison: The KTO Trainer is designed for aligning language models with binary feedback data (e.g., upvote/downvote).
  • Depending on the quality of the base model, SFT may not be necessary before KTO, unlike RLHF and DPO which always require it.
• SmolLM Models - Fine-tuning: A member expressed interest in fine-tuning the SmolLM 130m or 350m models.
  • No direct response was given but this conversation thread suggests a potential area of interest.
• Lambda Clusters - Usage: A member inquired if anyone has experience with using the clusters on the Lambda platform.
  • No specific responses were provided.

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OpenAccess AI Collective (axolotl) ▷ #general-help (2 messages):

• llama.cpp
• GGUF conversion

• Llama.cpp: GGUF Conversion: A user inquired about which repository is commonly used for converting models to GGUF format and quantizing them.
  • A reply suggested using llama.cpp and its associated commands, noting that the process is relatively straightforward.
• llama.cpp: GGUF Conversion: A user inquired about which repository is commonly used for converting models to GGUF format and quantizing them.
  • A reply suggested using llama.cpp and its associated commands, noting that the process is relatively straightforward.

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tinygrad (George Hotz) ▷ #general (9 messages🔥):

• Tinygrad Typechecking
• Compiler Book Recommendations
• Cuda.py Documentation
• ONNX Support in Tinygrad

• Tinygrad Typechecking Tested!: A member added a py.typed file to ensure type-checking of Tinygrad works as a package.
  • This fix was needed on their machine to ensure mypy functions properly with tinydreamer.
• Compiler Book Recommendations Requested: A member requested recommendations for a good book on compilers.
• Seeking Deeper Cuda.py Insights: A member asked for in-depth documentation or blogs specifically about the cuda.py file within Tinygrad.
• ONNX Integration for Tensor.py: A member expressed interest in adding ONNX support to the main Tinygrad repository, aiming to support the majority of ONNX features within tensor.py.

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tinygrad (George Hotz) ▷ #learn-tinygrad (10 messages🔥):

• Tinygrad vs Jax/Flux
• Tinygrad's CUDA/NV Issues
• Google's TPU dominance
• PyTorch vs Tinygrad Benchmarks

• Tinygrad's Competition With Jax/Flux: A member asked how Tinygrad could compete with Jax/Flux, noting that Jax appears extremely good.
  • Another member responded with their opinion that Jax is designed to push users towards renting Google's TPUs and fixing bugs for Google, while supporting other accelerators is merely for prototyping before migrating to Google's infrastructure.
• Tinygrad's NV Accelerator Issue: A user reported that their Tinygrad setup on Ubuntu 22.04 with CUDA installed showed NV as the accelerator, despite trying to use a 3060.
  • Another user clarified that NV is a lower-level CUDA and suggested setting the CUDA environment variable to 1 if the issue persists.
• PyTorch Outperforming Tinygrad in Benchmarks: A user asked why PyTorch still outperforms Tinygrad in certain benchmarks.
  • Another member suggested that model implementation might be the reason for the discrepancy.

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OpenInterpreter ▷ #general (12 messages🔥):

• Local LLMs
• Home Server Setup
• Umbrel
• TuringPi
• 01 Device

• Local LLMs: Not for the Faint of Heart: A user pointed out that running LLMs locally requires significant computational power.
• Home Cloud Setup for OI & 01: Another user shared their thoughts on using a home server setup for OpenInterpreter (OI) and 01.
• Umbrel: A Potential Home Server Solution: One user suggested using Umbrel as a possible solution for a home server setup.
• TuringPi: Another Home Server Option: A user mentioned TuringPi as an alternative hardware solution for a home server.
• Components of a Distributed Setup: A user provided a breakdown of the three key components in a distributed setup for LLMs, OI, and 01.

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OpenInterpreter ▷ #O1 (4 messages):

• Personalized Education
• AI Tutors
• Science Education

• Personalized AI Tutors for Kids: The idea is to give every kid a personalized AI tutor, which has been shown as highly effective if the tutor can relate to the individual child.
  • The goal is to allow the tutor to be adjusted to each child so they can learn concepts through familiar things in an emotionally reassuring way.
• Focus on Natural Sciences: The first field to address is fundamental principles of the natural sciences.

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OpenInterpreter ▷ #ai-content (1 messages):

8i8__papillon__8i8d1tyr: https://www.youtube.com/watch?v=gujAar8NZKo

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Alignment Lab AI ▷ #general (1 messages):

• Jala

• Jala: End-to-End Data Labeling: Jala is a new tool for automating text data labeling, aiming to reduce costs and time associated with manual labeling.
  • It leverages advanced AI technologies to ensure high accuracy and efficiency, supporting various text data types like CSV, JSON, TXT, and XML.
• Jala: Key Features: Jala offers features such as automated text data labeling, high accuracy and efficiency, support for diverse text data types, scalability for large datasets, and seamless integration with existing workflows.
  • It also provides a user interface for fine-tuning a wide variety of models.
• Jala: Industry Use Cases: Jala finds applications in various industries, including Natural Language Processing (NLP), Machine Learning and AI model training, data annotation for research and development, and automated content categorization.
  • It is ideal for businesses seeking to improve their data labeling processes.
• Join the Jala Waitlist: The Jala team invites interested users to join their waitlist to be among the first to experience the tool.
  • Sign up at https://heimdall-3jl.pages.dev/pages/jala to stay updated and get early access.

Link mentioned: Jala - Data Labeling Solution: no description found

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MLOps @Chipro ▷ #events (1 messages):

• AI Capabilities and Risks Demo-Jam Hackathon
• Pre-Hackathon Workshop
• AI safety
• AI risks and potential

• AI Capabilities and Risks Demo-Jam Hackathon: The AI Capabilities and Risks Demo-Jam Hackathon is happening in 7 days!
  • It's a great opportunity to showcase AI risks and potential, win $2,000 in prizes, and network with AI safety experts and enthusiasts.
• Pre-Hackathon Workshop: A pre-hackathon workshop is happening tomorrow, August 18th at 3 pm UTC.
  • Participants can meet judges and mentors, and get a head start on brewing ideas for the hackathon.
• Join the Discord: Join the Discord server to learn more about the hackathon and connect with other participants.
  • The link to the Discord server is https://discord.gg/A4GZ9UKb?event=1270997649260281968.

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AI21 Labs (Jamba) ▷ #general-chat (1 messages):

• AI21 FusionLabs plugin for bubble
• Conversation RAG
• AI21Labs models on bubble

• AI21 FusionLabs Plugin Progress: Development for the AI21 FusionLabs plugin for Bubble is moving forward smoothly.
  • The plugin will allow users to easily integrate AI21Labs models into their Bubble applications.
• Conversation RAG Rollout: A portal for trying out the newly released Conversation RAG will be rolled out soon.
  • This will allow users to test and experiment with the new features of Conversation RAG.
• AI21Labs Models on Bubble: Once the Conversation RAG portal is launched, a dev test link will be provided to see how AI21Labs models work on Bubble.
  • This will enable developers to explore the capabilities of AI21Labs models within the Bubble environment.

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