AI is all you need to be a chemist.

AI News for 10/8/2024-10/9/2024. We checked 7 subreddits, 433 Twitters and 31 Discords (228 channels, and 1872 messages) for you. Estimated reading time saved (at 200wpm): 222 minutes. You can now tag @smol_ai for AINews discussions!

Just a smattering of smol stories today:

• 2m emails and prompts hacked in AI girlfriend startup
• OpenAI projects 14b in losses in 2 years
• Sequoia fell in love with o1
• SearchGPT continues its rollout even as more people leave
• Demis Hassabis and John Jumper won the Chemistry Nobel for Alphafold

The Table of Contents and Channel Summaries have been moved to the web version of this email: !

AI Twitter Recap

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

AI Advancements and Industry News

• Nobel Prize in Physics: @ilyasut announced that Geoffrey Hinton won the Nobel Prize in Physics for his contributions to AI. @demishassabis noted that Hinton "laid the foundations for the deep learning revolution that underpins the modern AI field." The award was shared with John Hopfield, recognizing their work on neural networks and their connections to physics concepts.

• Model Developments: @AIatMeta introduced a 13B parameter audio generation model as part of Meta Movie Gen, capable of generating high-quality audio synced to video. @rohanpaul_ai highlighted PMRF, a new photo-realistic image restoration algorithm.

• AI Tools and Platforms: @AnthropicAI launched the Message Batches API, allowing processing of up to 10,000 queries asynchronously at 50% less cost than standard API calls. @togethercompute announced Flux Schnell, a new model available for free in their API for the next 3 months.

• AI Research: @rohanpaul_ai discussed PrefixQuant, a new quantization technique that outperforms expensive per-token dynamic quantization. @rohanpaul_ai also highlighted a paper on Prompt Caching for low-latency inference using Prompt Markup Language (PML).

AI Engineering and Development

• Development Tools: @svpino expressed frustration with switching between different code editors, highlighting the ongoing challenge for developers to find the perfect tool. @awnihannun showcased the MLX back-end in LM Studio, demonstrating its performance on an M1 laptop.

• AI Frameworks: @hwchase17 announced "long-term memory" support in LangGraph, allowing for persistent document storage and content-based filtering across conversational threads.

• AI Evaluation: @ShreyaR shared benchmarks comparing OpenAI's DevDay Eval product and Bespoke Labs' Minicheck for hallucination detection, with Minicheck showing better accuracy in detecting hallucinations.

• AI Infrastructure: @_philschmid introduced Hex-LLM, a new LLM serving framework designed for TPUs, offering low-cost, high-throughput deployment for open models from Hugging Face.

AI Ethics and Societal Impact

• AI Safety Concerns: @mmitchell_ai emphasized the importance of men actively supporting gender equality in scientific fields, noting that women alone can only do so much, especially when they represent less than 10% of a field.

• AI Governance: @bindureddy suggested that mainstream media and Hollywood want to regulate AI prematurely to protect their status as "celebrities," viewing AI as a threat to their existence.

Memes and Humor

• @DrJimFan shared a humorous "Hitchhiker's guide to rebranding" for AI terms, mapping machine learning concepts to physics terminology.

• @AravSrinivas posted an image comparing the difference between Google and Perplexity search results, highlighting the perceived superiority of Perplexity.

• @jxmnop joked about the Nobel Prize in Physics being awarded to "ptrblock" for "fundamental contributions to physics," playing on the unexpected nature of the actual award to AI researchers.

AI Reddit Recap

/r/LocalLlama Recap

Theme 1. Continuous Finetuning: A Novel Approach to Enhancing LLM Performance

• Merging Llama 3.2 vision adapters onto 3.1 finetunes (Score: 40, Comments: 14): The post discusses merging Llama 3.2 vision adapters onto Llama 3.1 finetunes to improve capabilities, providing a sample Python code for 8B/70B -> 11B/90B merges. Key considerations include skipping vision_model and cross_attn layers, handling new hidden layers (e.g., 20 new layers for 70B->90B), and addressing 8 new embeddings in the first embed layer, with the author successfully merging a Hermes 70B lorablated model to create a 90B vision-capable model that retains ChatML features.

• Im pretty happy with How my method worked out (Continuous Finetuning) Topped Open-LLM-leaderboard with 72b (Score: 150, Comments: 45): The author's Continuous Finetuning method has topped the Open-LLM-leaderboard with a 72b model, demonstrating its effectiveness in preventing loss during AI model finetuning by combining new and previous weights. The method was applied to create Rombos-LLM-V2.5 AI models based on Qwen-2.5, which have achieved top or near-top performance across multiple leaderboard categories, as evidenced by the provided screenshots and a detailed write-up.
  • The Continuous Finetuning method involves three steps: instruct fine-tuning a base model, applying the adapter to a general instructed model, and merging the resulting models. This approach can effectively add domain knowledge to AI models.
  • Users expressed interest in the datasets used for training and the tools for model merging. The author recommended MergeKit for merging and provided links to MergeKit and Qwen-2.5 for further information.
  • A user tested Replete-LLM-V2.5-Qwen-14b using a personal benchmark for literary creativity, finding it performed in the 1st quartile for literary form and 2nd tertile for content, demonstrating consistent performance compared to other models.

Theme 2. vLLM Outperforms llama.cpp in Distributed Inference Benchmarks

• LM Studio ships an MLX backend! Run any LLM from the Hugging Face hub on Mac blazingly fast! ⚡ (Score: 179, Comments: 59): LM Studio has released an MLX backend, enabling fast LLM inference on Mac devices. This update allows users to run any Large Language Model from the Hugging Face hub on Mac computers with significantly improved speed, leveraging Apple's ML Accelerate framework.

• More than 70% faster distributed inference performance in the same machine: vLLM vs. llama.cpp, is it expected or can be improved? (Score: 44, Comments: 23): vLLM demonstrates a 70% faster distributed inference performance compared to llama.cpp on the same machine. This significant speed difference raises questions about whether it's an expected outcome or if there's potential for improvement in llama.cpp's performance. The comparison highlights the importance of efficient inference implementations for large language models.
  • vLLM's performance advantage over llama.cpp is expected, with 70-80% faster distributed inference. Tests on a 4 x 4090 GPU workstation showed vLLM outperforming llama.cpp significantly in multi-GPU scenarios, while single-card performance was similar.
  • The performance gap is attributed to vLLM's use of hand-written CUDA kernels and OpenMP, compared to llama.cpp's reliance on standard C++ and BLAS libraries. Developers are considering adding custom kernels to llama.cpp, balancing performance gains with maintainability.
  • GPUStack, a framework supporting both vLLM and llama.cpp, was used for testing. Attempts to improve llama.cpp's performance with the --split-mode row flag resulted in worse performance (26 tokens/sec) and uneven GPU utilization.

Theme 3. Microsoft's Differential Transformer: A Breakthrough in LLM Attention

• [New Quantization Algorithm] PrefixQuant: Static Quantization Beats Dynamic through Prefixed Outliers in LLMs (Score: 96, Comments: 10): PrefixQuant, a new static quantization method for LLMs, enables W4A4KV4 (4-bit weights, activations, and KV cache) inference while outperforming dynamic quantization techniques. This approach eliminates outliers and allows for efficient per-tensor static quantization of activations and KV cache, avoiding the costly per-token dynamic quantization used in previous methods to handle magnitude fluctuations across tokens.
  • Users expressed interest and excitement about testing PrefixQuant, with some skepticism about its performance claims. The community is eager to see the release of inferencing kernels for practical implementation.
  • Discussion arose about perplexity scores, comparing PrefixQuant to llama.cpp's q4_K_M quantization. Users debated the comparability of results, noting differences in quantization methods and benchmarking conditions.
  • Detailed analysis of llama.cpp's codebase revealed that q4_K_M quantization uses a mix of Q4 and Q6 precision, with higher precision for certain layers. This highlights the complexity of comparing different quantization methods based solely on file sizes.

• [Microsoft Research] Differential Transformer (Score: 271, Comments: 65): Microsoft Research introduced the Differential Transformer, a novel architecture that improves Large Language Model (LLM) performance by incorporating differential equations into the transformer framework. This approach allows for more efficient modeling of continuous data and achieves state-of-the-art results on various benchmarks, including language modeling and time series forecasting. The Differential Transformer demonstrates enhanced capabilities in capturing long-range dependencies and processing sequential data, potentially advancing the field of natural language processing and time-based predictions.
  • The Differential Transformer uses a novel attention mechanism that calculates attention scores as the difference between two separate softmax attention maps, effectively canceling noise and promoting sparse attention patterns. This approach shows promising results in long-context modeling, hallucination mitigation, and in-context learning.
  • Users expressed excitement about the potential of this architecture, particularly for small models and instruction following. Some speculated on the impact of training large models from scratch with this architecture and then distilling them into smaller models for improved accuracy and cost-effectiveness.
  • The implementation is available on GitHub, including versions compatible with FlashAttention. However, new models need to be trained to benefit from this architecture, as it cannot be applied to existing weights.

Theme 4. Inflection AI Expands with New Models and Enterprise Offerings

• Inflection announces partnership with Intel, two new models, and enterprise plans with fine-tuning and on prem hosting (!?) (Score: 38, Comments: 11): Inflection has unveiled two new models, Inflection-2 and Inflection-2.5, alongside a partnership with Intel and enterprise offerings. The company is now providing on-premises hosting options and fine-tuning capabilities for businesses, marking a significant expansion of their services. These developments position Inflection to compete more directly with established players in the AI industry, offering enhanced flexibility and customization for enterprise clients.

Other AI Subreddit Recap

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

AI Research and Breakthroughs

• Google Deepmind's Differential Transformer introduces a novel attention mechanism that outperforms standard Transformers in language modeling tasks, showing improvements in long-context understanding, hallucination reduction, and in-context learning.

• Microsoft Research's Differential Transformer demonstrates significant performance gains with fewer parameters and training tokens, particularly excelling in 4-bit quantization.

• Geoffrey Hinton and John Hopfield awarded Nobel Prize in Physics for their foundational work in machine learning and artificial neural networks, sparking discussions about the intersection of physics and AI.

AI Model Releases and Improvements

• Hailuo AI launches Image-to-Video feature, offering free unlimited use with estimated generation times.

• Runway enhances Gen-3 Alpha Turbo to allow first and last frame inputs for both horizontal and vertical aspect ratios.

Industry Developments

• OpenAI receives first DGX B200 systems, signaling expansion of their computational capabilities.

• Analyst predicts Microsoft will acquire OpenAI within three years, though some argue the acquisition has already effectively occurred.

• Google faces potential breakup following monopoly ruling, with implications for the AI industry.

Expert Opinions and Predictions

• Geoffrey Hinton states AI development is not slowing down, predicting as much change in AI in the next 10 years as in the past decade.

• Google hiring scientists interested in AI consciousness and sentience, indicating research focus in these areas.

AI-Generated Content and Tools

• Animorphs LoRA model created for generating image transformations inspired by the book series.

• AI-generated images of "Florida Man vs Hurricane Milton" showcase creative applications of image generation models.

AI Discord Recap

A summary of Summaries of Summaries by O1-mini

Theme 1. Advanced AI Model Performance and Optimization

• SOAP Optimizer Outperforms AdamW: Users tested the SOAP optimizer on Alpaca, achieving better performance than AdamW until adjusting AdamW's learning rate. However, SOAP lacks support for distributed training and bf16 formats.
• L-Mul Algorithm Slashes Energy Costs: The L-Mul algorithm approximates floating point multiplication with integer addition, reducing energy costs by 95% while maintaining higher precision compared to 8-bit floating point operations.
• Diff Transformer Enhances Attention Mechanisms: The Differential Transformer introduces a differential attention mechanism, improving long-context modeling and reducing hallucinations in tasks like question answering, outperforming traditional Transformers.

Theme 2. Infrastructure and Hardware Support for AI

• Dual GPU Setup Limited by Performance: Using an RTX 3060 and RX 6600 provides 20GB VRAM but doesn't boost speed. A second RTX 3060 may help load larger models without enhancing performance.
• Apple MLX Integration in LM Studio 0.3.4: LM Studio 0.3.4 now supports Apple MLX, enabling efficient model execution on Apple Silicon Macs and allowing users to run larger models with enhanced compatibility.
• External GPU Testing on Raspberry Pi 5: A user set up a GPU test rig on Raspberry Pi 5 with an AMD RX 460 and an amdgpu Linux kernel patch, aiming for 4K gaming and full external GPU support.

Theme 3. Challenges in Training and Fine-tuning AI Models

• Training Vicuna-7B Faces CUDA Errors: Users encountered CUDA out of memory errors when training Vicuna-7B on Runpod, despite having 5 GPUs with 24GB RAM each. Adjusting DeepSpeed configurations resolved the issue.
• Aider's Architect Mode Requires Refinement: Users reported that Architect Mode in Aider often fails to complete tasks, necessitating prompt adjustments for better planning and observation before coding.
• DeepSpeed and Accelerate Configuration Issues: Members discussed resolving DeepSpeed configuration errors by ensuring device counts align with multiples required and using correct API parameters, streamlining the training process.

Theme 4. Data Management, Security, and Scalability

• Data Breach at Muah.ai Exposes 1.9M Emails: The AI girlfriend service Muah.ai suffered a data breach, exposing 1.9 million email addresses and sensitive prompts, including information related to child exploitation.
• Model Merging at Scale Enhances Generalization: Research on model merging up to 64B parameters shows improved generalization and efficiency. Larger models enhance the benefits of merging, especially when combining multiple expert models.
• AI Data Wall Concerns: As language models approach data limits, concerns about a data wall hindering AI progress emerge. Contrasting views suggest human reasoning can compensate for limited data exposure.

Theme 5. AI Tools, Integrations, and Community Research

• Tool Integration with LangChain and Aider: Users explored integrating Livekit with LangChain for real-time capabilities and Aider for external LLM integrations, enhancing functionalities like RAG bots.
• Llama Stack Unveils New Development Tools: Llama Stack tools released by Meta provide powerful resources for developers to optimize AI model capabilities, with GitHub repositories offering detailed examples and utilities.
• Community Research and Nobel Prize Updates: The 2024 Nobel Prize in Chemistry awarded to David Baker, Demis Hassabis, and John M. Jumper for contributions to computational protein design and AlphaFold2. Community discussions also reflect on AI research contributions and critiques, such as Schmidhuber's insights on attribution.

O1-preview

Theme 1. AI Model Advancements and Releases

• NVIDIA's Nemotron 51B Doubles Throughput on a Single H100 GPU: NVIDIA launched the Nemotron 51B, a NAS-optimized model achieving 2x throughput while maintaining accuracy. It's accessible via NVIDIA's API or available for download on Hugging Face.
• Meta's CoTracker 2.1 Tracks 70k Points on a Single GPU: Meta introduced CoTracker 2.1, a video motion prediction model capable of tracking 70,000 points on one GPU. The accompanying paper is available here.
• LLM360 Drops a Massive 15 Trillion Token Dataset: LLM360 unveiled a new pre-training dataset with 15 trillion tokens, emphasizing rigorous data quality and deduplication. This dataset aims to enhance training for large language models.

Theme 2. AI Tools and Integration Challenges

• Cline AI Assistant 2.0 Streams Responses into Your Editor: The new Cline AI Assistant 2.0 introduces features like streamed responses directly into editors and a cancel button for task management. Users note a 40% reduction in requests due to an XML-based tool-calling prompt.
• Aider Struggles with File Management and External LLMs: Users reported that Aider doesn't auto-populate new files in the list without manual commits. Attempts to integrate external models like SambaNova require manual API configurations, highlighting integration challenges.
• OpenAI Realtime Console Makes Voice API Accessible: A demo repository helps users test OpenAI's new Realtime Voice API with a simple npm start, although one user incurred $3.87 in charges for 15 minutes of use.

Theme 3. AI in Research and Recognition

• Nobel Prize in Chemistry Honors Computational Innovators: The 2024 Nobel Prize in Chemistry was awarded to David Baker, Demis Hassabis, and John M. Jumper for breakthroughs in computational protein design and protein structure prediction via AlphaFold2.
• Debate Over AI Attribution in Nobel Prizes: Controversy arose as figures like Schmidhuber criticized the Nobel Committee for overlooking significant contributors in AI, sparking discussions about proper attribution in scientific achievements.
• Scaling Laws Debate: Square Root vs. Fourth Root: Members debated scaling laws in AI, contrasting new proposals for square root scaling against Kaplan's established 0.28 constant suggesting fourth-root scaling.

Theme 4. AI for Creative and Emotional Engagement

• Emotional State Machines Make AI More Sentient: Developers are building AI with persistent emotional states, allowing bots to reflect user sentiments over time. This contrasts with typical bots that reset emotions after each interaction.
• AI's Role in Mental Health Support Under Scrutiny: Discussions highlighted the potential and challenges of using AI chatbots for mental health, with concerns about censorship policies limiting the AI's ability to handle emotional nuances effectively.
• Innovative Techniques Enhance AI Roleplay Experiences: Users shared methods for erotic roleplay (ERP) with AI, focusing on detailed character creation and immersive storytelling, though these practices raise ethical considerations.

Theme 5. Technical Challenges and Solutions in AI Development

• LM Studio Users Grapple with Model Loading Issues: Upgrading to LM Studio 0.3.4 led to problems loading models like Llama 3.2. Switching to the Vulkan backend was suggested as a workaround.
• HBM's Performance Doesn't Meet Expectations: Discussions revealed that HBM memory isn't significantly reducing power consumption or costs. The bottleneck in supplying more H100s GPUs is linked to packaging requirements.
• Torchao Encounters Quantization Hiccups: Integrating torchao with frameworks like ComfyUI led to operator errors, particularly on Windows. These issues highlight the complexities of quantization and compatibility in AI workflows.

PART 1: High level Discord summaries

LM Studio Discord

• Llama 3.2 Struggles with LM Studio: Users encountered issues loading Llama 3.2 and Dolphin 2.2.1 models in LM Studio 0.3.4, with some models failing that worked in earlier versions.

  • A solution suggested was switching to the Vulkan backend to potentially enhance model loading compatibility.
  • MLX's Infinite Loop Crisis: Concerns arose about MLX causing infinite output loops, notably with Llama 3.1 8B Instruct 4bit, reflecting issues in model response interpretations.
  • Discussions pointed toward prompt handling as the core issue, causing unwanted repetitive outputs.
  • Dual GPUs, but No Speed Boost: Conversations revealed that using an RTX 3060 alongside an RX 6600 totals 20GB VRAM but lacks speed improvements.
  • Users indicated that a second RTX 3060 could help load larger models but confirmed that performance would remain limited.
  • LM Studio's Compatibility Updates: The launch of LM Studio 0.3.4 initiated questions about model compatibility, especially with preset migrations after the update.
  • It was noted that users would likely have to manually check and adjust settings post-update.
  • NVIDIA RTX 4000 Deviates from NVLink: Discussion highlighted that the NVIDIA RTX 4000 series shifted away from NVLink, opting for PCIe Gen 5 for multi-GPU connections.
  • This raised questions about the speed of unconnected GPUs, with users noting surprising performance capabilities.

Unsloth AI (Daniel Han) Discord

• Model Merging at Scale Insights: New research on model merging at scale highlighted performance when blending models up to 64B parameters. Investigate findings in the paper available on arXiv.

  • Members expressed excitement over systematic evaluations that could enhance model generalization and efficiency.
  • Smooth Sailing with Qwen 2.5 Fine-tuning: Fine-tuning on Qwen 2.5 has become seamless after previous prompt issues were resolved. Users can find a collection of available models on Hugging Face.
  • This progress reassures engineers interested in utilizing the models for their projects.
  • Clarification on Dataset Formats for Unsloth: Discussions pointed out the efficiency of using Parquet over CSV files for datasets in Unsloth. Users should align dataset structures with expected column formats, such as 'train' and 'conversations'.
  • Ensuring correct formats helps streamline training processes within the platform.
  • Logits Exploration with Ollama Llama: Members faced challenges obtaining logits scores from Llama via Ollama in Python and debated switching to llama.cpp for better results. The search for clear resources left some users puzzled.
  • This discussion emphasizes the need for better access to functional resources and methodologies for logging outputs.
  • Challenges with AMD GPUs in Unsloth: Concerns were raised about limitations in creating small LoRA models on Intel GPUs, with confirmations that Unsloth does not support AMD GPUs. This raises coalition questions for those reliant on proprietary hardware.
  • Clarifications indicated that multi-GPU setups are also unsupported, impacting training flexibility.

HuggingFace Discord

• Nvidia launches high-efficiency models: Nvidia introduced the Nemotron 51B, a NAS-optimized model achieving 2x throughput on a single H100 GPU while preserving accuracy. Users can test the model via NVIDIA's API or download it from Hugging Face.

  • This model release included several variants like NVLM 1.0 aimed to bolster AI capabilities.
  • Meta releases improved VLMs: Meta launched its first VLMs, including CoTracker 2.1, capable of tracking 70k points on a single GPU for video motion prediction, with an accompanying paper available here.
  • The updated SAM 2.1 model for image/video segmentation offers enhanced functionality for developers.
  • Insights into Mira's Decentralization: A member introduced Mira, a decentralized infrastructure making AI accessible, emphasizing its community-driven projects without crypto involvement. Despite technical potential, some users raised moral concerns regarding blockchain associations.
  • The discourse illustrated a growing tension over integrating such technologies in AI development.
  • Evaluating Diffusion Model Training Techniques: Members clarified that the diffusers library facilitates various diffusion models, noting Stable Diffusion XL and Flux as capable integrations.
  • Discussions also covered training with Flux loras using gguf formats, despite current limitations on model support.
  • Fine-tuning Whisper Model for ATC: A blog details the fine-tuning of a Whisper model on air traffic control communications, achieving an 84% performance improvement by reducing the word error rate (WER) from 94.59% to just 15.08%.
  • The link to the GitHub repository and a blog post provide further exploration of this tailored ASR solution.

Cohere Discord

• CMD-R Temperature Tweaks: Members highlighted optimal temperature settings for CMD-R, recommending 0.3 for deterministic outcomes and 0.8 for creative tasks, with concerns on generative costs.

  • Suggestions included generating with 0.8 then formatting with 0.1 to balance creativity and cost.
  • API Connection Hiccups: Intermittent issues with the Cohere API were reported, with one member resolving it by accessing response.message.content[0].text, causing a brief debug frenzy.
  • Members speculated recent changes in the API might be a factor, sharing troubleshooting experiences and code adjustments.
  • Innovative Emotional State Machine: A new emotional state machine intends to track user emotions with persistent memory, keeping assistant bots in tune with user sentiment.
  • This distinct approach bucks typical bots' flexibility, as they remain in an emotional state reflective of user interactions.
  • Advanced RAG in Banking: A user detailed their experiments with an RAG solution yielding 75% recall@5, outperforming OpenAI for banking applications by embedding 2000 chunks.
  • They aim to utilize this as a proof of concept for the bank, showcasing the feasibility of their solution.
  • AI's Role in Mental Health Support: Discussion turned to the use of AI chatbots in mental health contexts, highlighting their value when human therapists are absent yet noting challenges with emotional context.
  • Concerns emerged around censorship policies that limit these bots' ability to interpret complex emotional nuances, impacting their effectiveness.

aider (Paul Gauthier) Discord

• Aider struggles with File Management: Users faced issues with Aider not auto-populating new files in the file list, requiring the use of /commit or specifying file paths directly to see changes.

  • Another user pointed out that files must be committed to the git repository to be available in autocomplete, underlining the importance of version control.
  • Integrating External LLMs is a Challenge: Community members discussed the difficulty of integrating SambaNova models with Aider, suggesting manual API configuration for OpenAI-compatible endpoints.
  • Further inquiries revealed methods for adding model pricing and token costs through metadata JSON files, yet some configurations still posed issues.
  • Architect Mode needs Refinement: Concerns emerged regarding Aider's Architect mode which often fails to complete tasks fully, necessitating user intervention to continue.
  • Users suggested modifying prompts for better planning and observation before coding to enhance the effectiveness of this mode.
  • OpenAI Realtime Console makes voice API accessible: A demo repository for the OpenAI Realtime Console was successfully set up, simplifying access to the new voice API announced at DevDay.
  • While interacting via voice incurs costs, one user noted charges of $3.87 for 15 minutes of use, which raised concerns about testing expenses.
  • Cline AI Assistant 2.0 breaks new ground: The newly released Cline AI Assistant 2.0 boasts features like streamed responses directly into the editor and a cancel button for task management, enhancing usability.
  • Users highlighted the XML-based tool calling prompt, which reportedly reduces requests by 40%, making resource use more efficient.

Interconnects (Nathan Lambert) Discord

• Nobel Prize in Chemistry Celebrates Computational Advances: The 2024 Nobel Prize in Chemistry has been awarded to David Baker for computational protein design and jointly to Demis Hassabis and John M. Jumper for protein structure prediction as announced on Nobel Prize Tweet.

  • Members celebrated this milestone but expressed skepticism about its implications for future innovations in AI.
  • PRMs Under Scrutiny Amid Development Changes: A lack of research on PRMs was humorously noted, with members pointing out that 'almost none on PRMs, almost a billion as LLM as a judge'.
  • Concerns emerged regarding the patenting process in ML, with suggestions that companies often file defensively, leading to vague claims and unresolved disputes.
  • Schmidhuber Takes Aim at AI Attribution Issues: Criticism arose concerning the Nobel Prize in Physics 2024, where Schmidhuber highlighted plagiarism and misattribution in works by Hinton and collaborators, claiming significant contributions were overlooked.
  • The mix of sentiments reflected a community reaction to the historical significance of AI contributions, as highlighted by user comments about Schmidhuber's critique.
  • ButtBench Alignment Project Gets a Logo: The ButtBench Alignment Project designed a new logo, marking a visual identity for a project that has reached SOTA, though still far from human performance as noted by Luca Soldaini.
  • This move signals a push for recognition and clarity in the goals of the project, resonating well with the community.
  • Data Wall Looms in AI Development: A data wall threatens progress in language models as current offerings nearing data limits were discussed, raising questions about reliance on larger data volumes.
  • Contrasting opinions suggest human performance is not solely dependent on extensive data exposure, hinting at a philosophical divide on AI efficiency.

Perplexity AI Discord

• Profit Model Queries at Perplexity AI: Concerns regarding how Perplexity AI generates profit arose, particularly with student discounts in play, making the business model appear precarious.

  • sneakyf1shy humorously suggested that venture capital might be the backbone of their operations, hinting at potential long-term uncertainties.
  • Complexity Extension Packs a Punch: The newly launched Complexity extension is enhancing the Perplexity experience with options for customizable themes and markdown exports, leading some to say it's ‘like Perplexity on steroids.’
  • Feline and asura0_00 praised the extension for significantly boosting user interactivity.
  • Perplexity AI Shortens Responses: Users noticed a trend toward more condensed responses from Perplexity AI, raising concerns that answers may lack information depth.
  • Speculation suggests these changes could be tied to adjustments in token limits, affecting the quality of responses.
  • Meta's Movie Maker Rocks: Meta has launched a movie generation tool, enabling users to create short films using AI, which aims to enhance storytelling.
  • This development showcases the potential of AI in creative domains.
  • Frustrations with Citation API Access: Members raised concerns regarding unanswered requests for whitelisting on the citation API, highlighting multiple attempts via various channels with no feedback.
  • A growing sense of frustration is evident among users awaiting updates.

Stability.ai (Stable Diffusion) Discord

• ControlNet Models Simplified: A member shared a GitHub link regarding ControlNet models, suggesting users focus on practical examples while skimming the mathematical explanations.

  • Scroll a bit down, ignore the math and look at the examples.
  • Flux Inpainting's Fast Track: In discussions about Flux and Schnell inpainting models, one member noted that using recommended settings should reduce processing time to 1-2 minutes, compared to an experienced 25 minutes.
  • The community highlighted key differences in iterations that affect Flux dev and Schnell performance.
  • Craving Kaggle Notebooks for Image Generation: A call for resources in the form of a Kaggle notebook for Automatic1111 broke out, shedding light on the community's demand for structured guides.
  • Members reflected on the difficulties of locating specific notebooks for seamless image generation processes.
  • Distilled CFG Confuses the Masses: Discussions on the nature of distilled CFG clarified that it serves as guidance distinct from the standard CFG, arising from specific model training.
  • Community members expressed that while Flux dev enhances CFG usage, it currently does not support negative prompts.
  • Deforum After Colab Restrictions: A Plan: Inquiries about utilizing Deforum post-Colab restrictions prompted discussions on alternatives for accessing computing power, particularly renting GPUs.
  • Suggestions included using RunPod for GPU rental as a feasible solution.

Eleuther Discord

• Nobel Prizes Ignite AI and Chemistry Debate: Recent discussions highlighted the Nobel Prize awards' relevance for AI figures such as Hinton and Hopfield, questioning their impact on traditional physics and chemistry fields.

  • Opinions were split; while some feared a dilution of the award's prestige, others argued that innovation and enthusiasm should drive selection.
  • PhD Candidates Push Back on Publication Metrics: Frustration emerged over the pressure from publication metrics in PhD programs, which some believed created a daunting competitive environment.
  • Members proposed that effective networking might be a better strategy for securing mentorship and collaborations, rather than just chasing publication counts.
  • Web3 to Web5 Transition Confuses: Debate arose on moving from Web3 to Web5, likening the naming strategy to the Fibonacci sequence, leading to speculation about future iterations like Web8.
  • Conversations turned humorous with members joking about the absurdity of the progression.
  • Scaling Laws Debate Engulfs Members: One member shared an overview stating that cross-entropy loss decreases with quadratic compute increase, referencing an article that proposes square root scaling.
  • This was contested with Kaplan's laws suggesting a constant of 0.28, advocating for a fourth-root scaling approach.
  • Spotlight on 0-shot COT Models: A focus emerged on the widespread adoption of 0-shot COT variants in recent model releases, hinting at a shift in evaluation methodologies.
  • While members pondered potential evaluation implementation details, no specific techniques were mentioned.

GPU MODE Discord

• HBM's Performance Compared to Expectations: Concerns were raised regarding HBM not performing better than expected, still representing a HUGE cost in products like the H100 while not significantly reducing power consumption.

  • The key bottleneck in supplying more H100s was identified as required packaging.
  • GPT2 Training Encounters TypeError: A member reported a TypeError while running GPT2 training related to the normal_() function in PyTorch 2.0.0 due to an unexpected keyword argument 'generator'.
  • Discussion suggested understanding complexities of training, including initialization and forward/backward passes.
  • Seeking Libraries for WebGPU Testing: A community member seeks recommendations on libraries for testing WebGPU, currently using Vitest and Playwright but facing flaky test runs.
  • They suspect the issue might stem from Playwright not properly clearing resources between test runs.
  • Gearing Up Raspberry Pi 5 for 4K Gaming: After witnessing Pineboards' 4K demo, a member decided to set up a GPU test rig on Raspberry Pi 5 with the amdgpu Linux kernel patch.
  • They aim for full external GPU support and shared insights on how to apply the patch.
  • Launch of FusedLinearJSD: The recent pull request introduced FusedLinearJSD, enabling efficient handling of the final linear layer by avoiding large logits tensor materialization.
  • This optimizes both the forward and backward pass for improved execution, mirroring the fuse linear CE approach.

OpenAI Discord

• Choosing Between ChatGPT and Claude Subscriptions: A member advised against subscribing to ChatGPT for features in preview due to usage caps, although access to GPT-4 legacy and 4o models might be beneficial.

  • They stressed that subscriptions should allow full functionality rather than limiting preview access.
  • Understanding O1 vs. O1 Mini Models: Members compared the O1 models, which act as 'reasoners', to 4o, highlighting the O1's limited availability of 50 uses per day versus 80 uses for 4o within 3 hours.
  • The discussion included plans for A/B testing between the two models to determine performance differences.
  • Theoretical Exploration of AI Evolution: A theory on AI consciousness evolution was entertained, emphasizing re-training and fine-tuning for advancement in capabilities.
  • Conversations swirled around the commercial viability of these evolved AI models and potential business models to support them.
  • User quits ChatGPT over rewriting responses: A user expressed frustration with ChatGPT's habit of rewriting responses, causing them to stop using it for several months.
  • They noted the exacerbating headaches from the rewriting issue, which continued even when they requested it to stop.
  • Possible solutions discussed for ChatGPT: Another member suggested that the rewriting behavior might relate to Canvas or DALL-E prompts, and provided a workaround for DALL-E use.
  • They recommended the phrasing 'Make an image using these exact words: [your words]' to avoid the rewriting problem.

Nous Research AI Discord

• Kainan offers free compute resources: Kainan expressed willingness to provide free compute resources for a competition, sparking interest from members.

  • Though there was enthusiasm, some uncertainty arose regarding how many participants would actually utilize this offer.
  • 2024 Nobel Prize awarded for Protein Research: The Royal Swedish Academy of Sciences awarded the 2024 #NobelPrize in Chemistry to David Baker and Demis Hassabis & John M. Jumper for their contributions to computational protein design and structure prediction, as reported here.
  • This recognition underscores the pivotal advancements in protein research within the AI community.
  • LM Studio boosts performance with Apple MLX: The new LM Studio 0.3.4 is out, featuring support for Apple MLX, allowing efficient model execution on Apple Silicon Macs.
  • Users are thrilled by the improvements in running larger models and the potential capabilities provided by MLX.
  • LLM360 launches massive pre-training dataset: LLM360's new dataset boasts 15 trillion tokens, ensuring rigorous data quality through thorough filtering techniques.
  • This initiative focuses on enhancing the training quality for LLMs, emphasizing deduplication and superior dataset structuring.
  • Llama Stack reveals new development tools: A member highlighted the new Llama Stack tools released by Meta, finding them pretty powerful.
  • This showcases an emerging interest within the community for utilizing advanced tools to optimize AI model capabilities.

OpenRouter (Alex Atallah) Discord

• Prompt Caching: The Good and the Bad: Members discussed the mechanics of prompt caching, noting it can be problematic for changing contexts or short prompts. One member remarked, 'You cannot disable prompt caching for those providers who do automatic prompt caching,' pointing out critical limitations.

  • This sparked a debate on when and how to effectively utilize prompt caching without compromising performance.
  • Curiosity about Inflection 3.0: The anticipated launch of Inflection 3.0 has generated buzz, particularly regarding its integration with Intel Gaudi 3 for better performance. Despite the excitement, some members expressed skepticism about the lack of concrete benchmark data.
  • Concerns were raised that the hype might overshadow the actual performance improvements and real-world applications.
  • Understanding OpenRouter API Rate Limits: Clarifications on OpenRouter API limits reveal they are dynamic and depend on account credits. One member shared a GET request example demonstrating how to check rate limit status and credits associated with an API key.
  • This guidance is crucial for optimizing API usage while ensuring compliance with request limits.
  • NotebookLM Podcast Gains Traction: Participants shared positive feedback on the NotebookLM Deep Dive podcast and highlighted its utility during commutes by creating accompanying notebooks. One user noted a desire for automation tools like ai-podcast-maker, stating, 'automation ftw.'
  • This discussion underscores the growing trend of integrating audio content into daily workflows for enhanced learning.
  • Gemini Moderation Worries Surface: Concerns arose about Gemini potentially moderating inputs, raising fears of user bans over specific content. This initiated a broader dialogue on user experience and content moderation policies within AI frameworks.
  • Participants emphasized the need for transparency in moderation practices to ensure positive engagement from users.

LlamaIndex Discord

• LlamaIndex Workflows Tutorial Brilliance: A detailed tutorial illustrates how to implement Workflows in LlamaIndex, contrasting it with LangGraph and aiding in the creation of AI research agents.

  • It includes practical debugging and optimization tips, ensuring a smoother implementation experience.
  • LlamaCloud's Financial Data Superpower: In a recent demo, the team showcased how to utilize LlamaCloud and LlamaParse to automate the filling of financial spreadsheets across multiple companies.
  • This highlights the substantial contribution of LLMs in streamlining data handling and analysis processes.
  • SFTechWeek Meetup on Multi-Agent Workflows: A reminder to RSVP for the in-person gathering at LlamaIndex HQ during #SFTechWeek, focusing on implementing Multi-Agent workflows in real production environments.
  • Participants are promised insights on RAG systems and production challenges, alongside food and networking opportunities. RSVP here.
  • Build Your Own AI Agent with OpenAI: A demonstration by the team allowed users to interact with an AI agent in real-time using the OpenAI Realtime API client, showcasing voice interaction capabilities.
  • This open-source tool opens doors for developers to create personalized voice agents seamlessly, with examples provided for ease.
  • Semantic Chunking Conundrum in TypeScript: A user sought guidance on implementing semantic chunking in TypeScript, referencing a comparable example in Python for context.
  • They expressed frustrations with the lack of available resources and sparked discussions for community solutions.

Latent Space Discord

• AI Girlfriend Service Data Breach Exposed: The AI girlfriend service Muah.ai suffered a data breach last month, impacting 1.9 million email addresses and exposing sensitive prompts.

  • Security experts are alarmed about the breach, particularly its implications for child exploitation data included.
  • Sequoia Capital's Insight on AI Evolution: Sequoia’s latest essay emphasizes a transition in Generative AI from 'thinking fast' to 'thinking slow,' focusing on inference time reasoning for innovative applications.
  • Companies like OpenAI and Google DeepMind are stabilizing the market, while new agentic applications are poised to emerge.
  • 2024 Nobel Prize in Chemistry Awarded: The 2024 Nobel Prize in Chemistry goes to David Baker for computational protein design, and to Demis Hassabis and John M. Jumper for contributions to AlphaFold2.
  • Their work is crucial in advancing biochemistry, successfully predicting structures for nearly 200 million proteins.
  • Palmyra X 004 Launch Highlights: Palmyra X 004 ranked in the top 10 on HELM, showcasing full-stack tool calling and training on synthetic data.
  • This model's capabilities in AI function calling and CRM improvements received attention from Venture Beat.
  • ChatGPT Introduces Search Functionality: ChatGPT is rolling out SearchGPT, integrating citation features in GPT-4o to compete with platforms like Perplexity.
  • This strategic move enhances ChatGPT's information retrieval capabilities and aligns it with user query requirements.

Modular (Mojo 🔥) Discord

• DOM Data Attributes Enhance HTML Elements: A DOM feature now allows data storage on elements with custom attributes starting with data-myattribute, improving data handling in HTML.

  • This development encourages innovative techniques for data manipulation directly via the DOM.
  • WebAssembly Component Model Repository Launched: The repository for the WebAssembly Component Model has been shared, detailing its design and specifications.
  • It provides essential insights for developers interested in the component model aspects of WebAssembly.
  • Mojo's GPU Support Sparks Excitement: Anticipation builds around the upcoming GPU support in Mojo, promising enhanced performance capabilities.
  • Community members are exploring integrating PyTorch with Mojo to optimize usage of GPU resources.
  • Mojmelo Brings Scikit-learn to Mojo: The Mojmelo project aims to implement machine learning algorithms in pure Mojo, providing an alternative to Cython dependencies in Scikit-learn.
  • This initiative may significantly streamline the process of running Scikit-learn workflows through Mojo functionality.
  • Mojo Graph Performance Concerns: Performance tests highlighted that total compile times for graphs were 0.312s and 0.451s, leading to concerns about slower debugging processes.
  • Suggestions to reuse the inference session could mitigate these compile time issues, addressing potential performance penalties from using List types.

LLM Agents (Berkeley MOOC) Discord

• Lab Assignments Officially Released: The lab assignments for the course are now live, with the first task focused on using the Autogen framework to analyze restaurant reviews, due December 12, 11:59pm PST.

  • Subsequent labs will address prompt engineering for LLM security, emphasizing creating attack and defense prompts.
  • Sign Up for Course Made Simple: Prospective students can easily join the course by filling out this form.
  • Engagement is encouraged in the LLM Agents Discord for further collaboration.
  • Lab 1 Download Issues Reported: Users encountered problems downloading Lab 1 instructions, receiving empty files, while other labs function correctly.
  • It was pointed out that the file is accessible on Google Drive despite having no preview.
  • Reinforcement Learning's Impact on AGI Debated: Concerns arose regarding the relevance of Reinforcement Learning (TD learning) in achieving AGI, with some questioning if agents can thrive without it.
  • The discussion highlighted RL's role and efficacy in modern AI architectures.
  • Call for Collaborative Learning: Members encouraged peer collaboration for brainstorming while tackling assignments, aiming for a shared learning experience.
  • This encouragement is seen as a way to foster camaraderie and improve understanding of complex LLM concepts.

OpenAccess AI Collective (axolotl) Discord

• Training Process Stalls on Vicuna-7B: A user reported their training process for the Vicuna-7B model got stuck with no output and shared their command line for launching it.

  • Another member suggested sharing the sample config to diagnose the problem.
  • DeepSpeed Error Resolved: The user faced a DeepSpeed error stating 'Input should be a valid integer, got a number with a fractional part'.
  • The community suggested ensuring the number of devices is a multiple of 2, which ultimately resolved the issue.
  • Unexpected CUDA Memory Shortage: Despite having 5 GPUs with 24GB of RAM, a user encountered CUDA out of memory errors during training.
  • They shared their DeepSpeed and accelerate configurations to seek insights into the memory shortage.
  • Runpod Instance Insights: The user referenced their DeepSpeed configuration, noting it was derived from examples available on GitHub.
  • They emphasized running experiments on a Runpod instance and highlighted its specifications for context.
  • Community Collaboration for Troubleshooting: Members actively collaborated to troubleshoot various model training and configuration issues.
  • They exchanged insights and links to configurations, helping to resolve the user's questions about training and resource management.

Torchtune Discord

• Model Scalability Raises Eyebrows: A member expressed concerns about the scalability of a paper that was trained on 350 billion tokens, questioning the significance of their improvements.

  • Ironically, another member noted that ML professionals often overlook basic statistical measures like p-values.
  • P-values Not Common in ML: A member shared frustration about the lack of p-values and confidence intervals in ML papers, expressing how it feels triggering coming from a medical background.
  • Another participant remarked that they rarely see p-value usage in ML contexts, highlighting a cultural difference in scientific reporting.
  • SOAP Outperforms AdamW but Needs Tuning: A user tested the SOAP optimizer on Alpaca, noting it performed better than AdamW until they adjusted AdamW's learning rate.
  • However, they mentioned that the current implementation does not support distributed training or bf16 formats yet.
  • Diff Transformer Triumphs over Traditional Transformers: The Diff Transformer introduces a differential attention mechanism, enhancing attention to relevant context and outperforming traditional Transformers in various benchmarks.
  • It notably aids in long-context modeling and reduces hallucination in tasks like question answering.
  • L-Mul Algorithm Slashes Energy Costs: The proposed L-Mul algorithm approximates floating point multiplication with integer addition, reducing energy costs by 95% while maintaining higher precision.
  • This method offers a significant improvement over 8-bit floating point multiplications, suggesting a potential for vast resource savings in neural network computations.

LangChain AI Discord

• Exploring Memcached Support in LangChain: A member is investigating whether adding support for pymemcache in LangChain is enough, or if a broader range of clients like python-memcached or pylibmc would be beneficial.

  • The goal is to improve caching flexibility within LangChain, making it more adaptable to different caching needs.
  • LiteLLM's Streaming and Caching Issues: Concerns arose about LiteLLM not retrieving cached tokens while streaming, leading to a query about best practices for ensuring effective caching.
  • Resources on LiteLLM were shared, suggesting that token stream responses may disrupt caching mechanisms.
  • SQL Query Limitations in AI: A user raised issues regarding limiting SQL queries to specific IDs without relying on LLM instructions, looking for stricter query generation methods.
  • Another member recommended using grouping by ID to improve filtering and achieve more reliable results.
  • SQL Chain Compatibility with Other Models: A question was proposed regarding the performance of the SQL chain with models outside of GPT 3.5, which often return inaccurate results.
  • One member found success using 4o-mini by focusing on precise column naming and careful question formulation.
  • Integrating Livekit for Real-time LangChain Functions: Interest was expressed in integrating Livekit with LangChain to enhance its real-time capabilities for advanced applications.
  • The member specifically mentioned plans to develop a RAG bot, showcasing their ambitions for progressive application development.

OpenInterpreter Discord

• Get Ready for Mozilla AI Talk!: Next week, we're excited to host a talk from a member of Mozilla AI discussing intriguing open source initiatives. Don't miss out on this opportunity to learn more!

  • You can join the event here to catch the insights.
  • Confusion Over --stdin Flag: A user expressed confusion on how to use the --stdin flag and mentioned they couldn't find guidance in the docs, highlighting a documentation clarity gap.
  • Further clarification is needed to assist users in utilizing this feature effectively.
  • LLMs Stay Deterministic with Same Seed: A discussion revealed that LLMs can be deterministic if the same seed and input are used, contrary to popular belief. ChatGPT randomizes the seed on each request to introduce non-determinism.
  • It's crucial to note that using the same inputs and setting temperature to 0 should yield consistent results.
  • Unpredictability with Model Updates: Concerns were raised about model updates in ChatGPT possibly affecting result consistency over time. Changes in the model could lead to variations that disrupt previously deterministic behavior.
  • Users emphasized that updates might introduce unpredictability even when the code remains static.
  • Code Outcome Variability Across Systems: A member pointed out that updates to systems or Python could influence code behavior, resulting in variable outcomes. For instance, accessing user tokens could alter the execution path.
  • This variability underscores the importance of a controlled environment for consistent results.

tinygrad (George Hotz) Discord

• Clang Backend Errors in Tinygrad: A user encountered an error using exo on Linux with the clang backend, including a lowering error with MetaOps.KERNEL that replicates across two systems, possibly linked to Nix package issues.

  • Additionally, running TINYGRAD_DEBUG=2 logged hundreds of operations before crashing, revealing detailed activity without immediate failure.
  • Introducing Fashion MNIST for Tinygrad Learners: A member proposed a Pull Request to add Fashion MNIST as a new dataset, bridging complexity between MNIST and CIFAR-10 for drivers of tinygrad education.
  • This initiative reflects an eagerness in the community to augment learning resources, prompting discussions about more datasets to further enrich training experiences.
  • Expansion of Dataset Options for Learning: Members have expressed interest in adding more datasets to tinygrad, indicating a collaborative effort to boost learning opportunities beyond existing options.
  • The call for new datasets promises to create a more diverse learning environment, allowing users to experiment with various data types and challenges.

LAION Discord

• Hierarchical Generation Gains Traction: A member shared a blog post on Coupling Generation and Compression, discussing a framework for Hierarchical Generation similar to Stable Cascade models.

  • The article highlights the prevalent model paradigm where a decomposer is trained first, which notably affects LLMs and image generation outputs.
  • o1-preview Set to Redefine Zero-shot Capabilities: o1-preview exhibits significant strengths in zero-shot (weak) out-of-distribution generalization, outperforming previous models as per preliminary findings.
  • o1-mini shows no such advancement, matching previous SOTA, which clearly illustrates the value of pre-training scale in model efficacy.
  • TruthfulQA Shows o1's Comprehension Skills: o1 posted strong results on TruthfulQA, particularly in grasping common misconceptions effectively, indicating potential in comprehension tasks.
  • Despite its constraints, the performance demonstrates o1's ability to tackle certain understanding challenges with notable success.

DSPy Discord

• Fetching Random Cat Images Made Easy: A new feature demonstrated the ability to fetch random cat images using The Cat API. This implementation involves creating a Cat model and utilizing an HTTP client for seamless image retrieval.

  • The demo emphasizes simplicity, allowing developers to easily integrate cat images into their applications.
  • Limiting Cat Breeds Fetching: A showcased method allows users to fetch cat breeds while restricting the number of breeds returned. Code snippets reveal that only a limited set of breeds is retrieved and can be structured into a CatBreed model for efficient access.
  • This enhancement provides developers with tighter control over data retrieval, making it easier to handle large datasets.
  • Video Demos for Visual Learners: Links to demonstration videos were shared, providing visuals on the functionality of the cat image and breed fetching features. These guides clarify implementation processes for users.
  • Such resources empower developers to grasp the tools effectively and implement them with confidence.

DiscoResearch Discord

• Whisper Turbo German Model Halves Error Rate: The newly introduced Whisper Turbo German model reduces error rates by 50% in various benchmarks compared to earlier versions, according to a source. This model is optimized for transcription, voice commands, and automatic subtitling specifically for German.

  • It enhances usability in diverse scenarios by providing dictation functions for word processing software, making it a valuable tool for developers working with German-language processing.
  • Applications of Whisper Turbo Model: Key applications of the Whisper Turbo German model include effective transcription of spoken German, automatic subtitling, and facilitating voice-based search queries.
  • Developers can leverage these functionalities for various projects, improving accessibility and interaction in German-speaking environments.

Gorilla LLM (Berkeley Function Calling) Discord

• Writer's Palmyra-X-004 Model Update Request: Sam Julien from Writer requested the Palmyra-X-004 model be added to the leaderboard following an email from CTO Waseem AlShikh, showcasing their impressive results in internal benchmarks.

  • Do we need to submit a PR? highlights their commitment to community engagement.
  • Clarifying Leaderboard Submission Process: Sam also sought clarification about whether a PR is required for the Palmyra-X-004 model's leaderboard addition.
  • This inquiry reflects a structured approach to ensure their advancements are recognized effectively within the community.

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

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.

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

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.

The AI21 Labs (Jamba) 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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