patience is all you need.

AI News for 1/13/2025-1/14/2025. We checked 7 subreddits, 433 Twitters and 32 Discords (219 channels, and 2161 messages) for you. Estimated reading time saved (at 200wpm): 256 minutes. You can now tag @smol_ai for AINews discussions!

ChatGPT Tasks launched. Cursor raised a B. Sakana announced a beautiful improvement over LoRAs with only minor performance improvement. Hailuo dropped a giant 456B MoE similar to Deepseek v3.

Nothing we'd give title story feature to, but nice incremental progress.

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.

Model Releases and Updates

• Ollama Model Enhancements: @ollama announced the inclusion of Cohere's R7B, the smallest model in their Command R series, optimized for RAG and tool use tasks. Additionally, @ollama released Ollama v0.5.5, featuring multiple quality of life updates and a transition to a new engine. The upcoming 2025 Ollama meetup in San Francisco was highlighted by @ollama, attracting significant interest with 31,592 impressions.

• Together AI and OpenBMB Models: @togethercompute introduced Llama 3.3 70B, a multimodal model available for free on Together AI, boasting improved reasoning and math capabilities. Concurrently, @OpenBMB released the MiniCPM-o 2.6, an 8B parameter multimodal model that outperforms GPT-4V on visual tasks.

• Process Reward Models and Qwen Developments: @_philschmid shared insights into Process Reward Models (PRM), emphasizing their role in enhancing LLM reasoning. The Qwen team also unveiled their Qwen2.5-Math-PRM models, demonstrating superior performance in mathematical reasoning.

• LangChain and Codestral Updates: @LangChainAI released a beta version of tasks, allowing ChatGPT to handle future tasks like reminders and summaries. Codestral 25.01 by @dchaplot achieved joint #1 on LMSys Copilot Arena, showcasing significant performance improvements over previous versions.

AI Features and Tools

• OpenAI Task Rollout: @OpenAI announced the rollout of Tasks, a feature enabling users to schedule actions for ChatGPT such as weekly news briefings and personalized workouts. This feature is currently in beta for Plus, Pro, and Teams users and will eventually be available to all ChatGPT accounts.

• Ambient Agents and Email Assistants: @LangChainAI introduced an open-source email assistant agent, part of their new "ambient agents" paradigm. These agents are always active, handling tasks like email triage and drafting responses, enhancing productivity without traditional UX interfaces.

• AI Software Engineering Advancements: @bindureddy discussed the rapid maturation of AI software engineers, highlighting their capabilities in codebase analysis, test case generation, and security infrastructure, predicting that AI will match SWE capabilities within the next 18 months.

AI Research and Papers

• LLM Scaling Laws: @cwolferesearch delved into LLM scaling laws, explaining the power law relationships between compute, model size, and dataset size. The research emphasizes that while test loss decreases with scaling, the improvements plateau, challenging the notion of exponential AI advancements.

• GANs Revival: @TheTuringPost reported on the revival of GANs through the paper "The GAN Is Dead; Long Live the GAN! A Modern GAN Baseline," highlighting the R3GAN architecture and its superior performance over some diffusion models on benchmarks like FFHQ and CIFAR-10.

• Multimodal RAG and VideoRAG: @TheTuringPost introduced VideoRAG, an extension of multimodal RAG that retrieves videos in real-time, utilizing both visual and textual data to enhance response accuracy.

• Tensor Product Attention: @iScienceLuvr presented the "Tensor Product Attention (TPA)" mechanism, which reduces inference-time cache size by 10x and outperforms previous attention methods like MHA and GQA in performance benchmarks.

AI Community and Events

• Ollama Meetup and Community Engagement: @ollama promoted the 2025 Ollama meetup in San Francisco, fostering community engagement among AI enthusiasts. Additionally, @gdb and others encouraged community participation through joining initiatives and hiring announcements.

• LangChain AI Meetup: @LangChainAI organized an evening meetup in San Francisco featuring a fireside chat with industry leaders like @hwchase17 and Bihan Jiang, focusing on deploying production-ready AI agents.

• Hiring Announcements: Multiple tweets, including those from @WaveFormsAI and @LTIatCMU, shared job openings for software engineers and research positions in areas like multimodal LLMs, full-stack development, and AI safety.

AI Industry News and Policy

• AI Policy and Economic Impact: @gdb released an Economic Blueprint outlining policy proposals for optimizing AI benefits, enhancing national security, and driving economic growth in the U.S.. Concurrently, @NandoDF advocated for the removal of non-compete clauses in the UK to boost AI competitiveness.

• AI Workforce Transformation: @DeepLearningAI highlighted the emergence of AI Engineers and Consultants as top jobs on the rise due to AI's transformative impact across industries, underscoring the importance of gaining expertise in this field.

• China vs. US AI Competition: @teortaxesTex and others discussed the intensifying AI competition between China and the U.S., emphasizing geopolitical implications and the race for AI dominance.

• Data Center Revenue Projections: @teortaxesTex projected data center revenue for FY2026 at $236 billion, marking a 28% increase over market consensus, indicating the growing infrastructure investments in AI.

Memes/Humor

• Coding and Daily Reminders: @hkproj shared a daily reminder to eat veggies and code triton kernels, blending health tips with coding humor.

• AI and Personal Life Jokes: @teortaxesTex humorously remarked on a model's consciousness, joking about the need for better epistemology in examining AI capabilities.

• Developer Memes: @nearcyan posted a "two space" meme, resonating with developers' in-jokes about coding standards.

• Humorous Takes on AI Agents: @bindureddy joked about AI agents taking over work tasks, pondering if working would become obsolete.

• General Tech Humor: @saranormous quipped about reading readiness for having kids, intertwining life advice with humorous skepticism.

AI Reddit Recap

/r/LocalLlama Recap

Theme 1. Qwen's Math Process Reward Models and Innovations

• Qwen released a 72B and a 7B process reward models (PRM) on their recent math models (Score: 145, Comments: 16): Qwen has released two new Process Reward Models (PRM), the Qwen2.5-Math-PRM-7B and Qwen2.5-Math-PRM-72B, designed to enhance mathematical reasoning in Large Language Models (LLMs) by identifying and correcting intermediate errors. These models demonstrate strong performance in Best-of-N (BoN) evaluations and excel in error identification on ProcessBench, as detailed in their paper titled The Lessons of Developing Process Reward Models in Mathematical Reasoning (arXiv:2501.07301).
  • Qwen2.5-Math-PRM-72B is primarily useful for academic purposes and training other models by providing feedback on reasoning quality and intermediate steps, rather than for typical text generation tasks. Zealousideal-Cut590 emphasizes the need for Process Reward Models (PRMs) in non-mathematical domains like programming, legal, and medical tasks to optimize test time compute.
  • -p-e-w- discusses the increasing challenge of keeping up with the rapid release of new models, predicting that even unlimited internet connections may soon be insufficient. Useful44723 suggests that Hugging Face should offer torrent links as an alternative download method to manage the high volume of data.
  • The rapid pace of model releases is highlighted, with -p-e-w- noting the occurrence of multiple substantial new releases per week, leading to potential saturation of download queues. Caffeine_Monster and Threatening-Silence- comment on the adequacy of current internet speeds and the potential for future limitations.

• MiniCPM-o 2.6: An 8B size, GPT-4o level Omni Model runs on device (Score: 158, Comments: 29): MiniCPM-o 2.6 is an 8 billion parameter model claimed to achieve GPT-4o level performance. It is designed to run on local devices, enhancing accessibility and usability for various applications.
  • Discussions highlight skepticism about MiniCPM-o 2.6's claim of achieving GPT-4o level performance, with users arguing that despite its accessibility and local running capability, it does not match GPT-4 in benchmarks or capabilities. AaronFeng47 and Aaaaaaaaaeeeee express doubts about its performance, suggesting it is not at par with GPT-4o and noting the technical challenges of running it on-device, requiring a device with ≥12GB memory.
  • Users debate the validity of claims that smaller models can surpass larger ones like GPT-4, with MoffKalast and Radiant_Dog1937 discussing how smaller models, such as Gemma 2 9B and Gemini 1.5 Flash 8B, rank high on the Hugging Face leaderboard but may not match GPT-4's comprehensive capabilities. They argue that while small models perform well in specific tasks, they cannot match the knowledge and application abilities of much larger models due to physical limitations in parameter capacity.
  • Many_SuchCases shares links to MiniCPM-o 2.6 on Hugging Face, raising questions about its inference engine compatibility, while discussions also touch on the MMMU score of MiniCPM-o 2.6, which is 50.4 compared to 69.2 for GPT-4o, indicating a significant

Theme 2. MiniMax-Text-01: MoE and Long Context Capabilities

• MiniMax-Text-01 - A powerful new MoE language model with 456B total parameters (45.9 billion activated) (Score: 93, Comments: 48): MiniMax-Text-01 is a new Mixture-of-Experts (MoE) language model with 456 billion total parameters, of which 45.9 billion are activated per token. It uses a hybrid architecture combining Lightning Attention, Softmax Attention, and MoE, with advanced parallel strategies like Linear Attention Sequence Parallelism Plus (LASP+) and Expert Tensor Parallel (ETP), allowing it to handle up to 4 million tokens during inference.
  • Hardware Requirements and Running Locally: Running MiniMax-Text-01 requires a significant amount of RAM, with suggestions ranging from 96GB for basic operations to 384/470GB for more practical use. Despite its size, the Mixture-of-Experts (MoE) architecture may allow for more manageable local execution by offloading active experts to a GPU, akin to deepseek v3.
  • Licensing and Accessibility: The model's restrictive license has raised concerns, particularly its limitations on using outputs to improve other models and its distribution requirements. Despite these restrictions, it remains open for commercial use, though some users question enforceability, drawing parallels with Apache 2.0 for military applications.
  • Performance and Capabilities: The model's ability to handle up to 4 million tokens is highlighted as a significant achievement in open-source long-context processing. Its hybrid of linear and softmax attention layers, alongside advanced parallel strategies, is noted for potentially reducing context requirements and enhancing retrieval and extrapolation capabilities compared to models relying solely on softmax attention.

Theme 3. Inspiration from LLMs Driving New Open Source Initiatives

• Today I start my very own org 100% devoted to open-source - and it's all thanks to LLMs (Score: 141, Comments: 44): The post author, with a background in biology, has founded a new organization fully dedicated to open-source projects, attributing this achievement to the influence of Large Language Models (LLMs) and the supportive community at r/LocalLlama. They express gratitude to the community and highlight the importance of the open-source ecosystem in enabling their transition from biology to this new venture.
  • Bootstrapping and Financial Challenges: Several commenters, including KnightCodin and mark-lord, discussed the challenges and benefits of bootstrapping a business. Mark-lord emphasized reducing living costs to manage finances effectively without investor pressure, sharing a personal journey of overcoming imposter syndrome and financial hurdles.
  • Community Support and Encouragement: The community expressed strong support and encouragement for the author's venture, with users like Silent-Wolverine-421 and NowThatHappened offering congratulations. The sentiment of "This is the way" was echoed by multiple commenters, highlighting a shared ethos of pursuing independent, open-source projects.
  • Advice and Tools: Mark-lord shared practical advice for those transitioning into AI, recommending tools like Claude 3.5 for various tasks and suggesting using Cursor for unlimited requests. They invited further discussion and networking through direct messages, reflecting a willingness to support others in similar journeys.

• Why are they releasing open source models for free? (Score: 283, Comments: 166): Open source AI models are being released for free despite the costs involved because they can drive community collaboration and accelerate innovation. The incentive for companies or developers to release these models includes gaining reputation, encouraging widespread adoption, and potentially stimulating improvements that can benefit the original creators.
  • Discussions highlight that open source AI models help companies like Meta and Google secure market dominance by making their models widely used standards, which reduces costs and attracts talent. The strategy is compared to Google's Android and Microsoft's GitHub, emphasizing the long-term benefits of community engagement and mindshare over direct revenue from the models themselves.
  • Several comments argue that releasing these models for free can disrupt competitors and create barriers to entry for new players. This can be seen as a "scorched earth" strategy, where the goal is to saturate the market with free resources, making it difficult for others to monetize similar offerings, as discussed in the context of Meta's LLaMA and GitHub Copilot.
  • Commenters also note that the "open source" label is sometimes misleading, as many models are only open weights without full retraining capabilities. This partial openness allows companies to benefit from community feedback and innovation, while still maintaining control over their proprietary technologies and strategic advantages.

Theme 4. RTX Titan Ada 48GB: Unveiling New GPU Potentials

• RTX Titan Ada 48GB Prototype (Score: 52, Comments: 13): The RTX Titan Ada 48GB is speculated to be more appealing than the 5090, with a potential price of $3k. It features all 144 SMs enabled, double the performance in mixed precision training, and possibly the transformer engine from the L40, unlike the 4090. Despite slower memory bandwidth, it offers 48GB memory, 300W TDP, and a GFLOPS/W of 1223.88, making it efficient for setups with multiple cards. More details here.
  • Memory Bandwidth Concerns: The discussion highlights concerns about the bandwidth drop being "brutal" at less than half, but some users argue that 904GB/s does not feel slow, emphasizing the importance of memory bandwidth relative to memory capacity used per token.
  • Pricing and Market Appeal: There is skepticism about the card's pricing strategy, with a suggestion that selling at a loss for $500 would be more appealing. However, the digits at 273GB/s are seen as a drawback for potential buyers who prioritize prompt processing.
  • Prototype and Features: The card is identified as an old prototype, resembling an L40 with ECC disabled and using GDDR6 and PCIe 4.0. It was rumored a year ago alongside the 4090 Ti, and recent GPU-Z screenshots lend some credibility to its existence.

Other AI Subreddit Recap

/r/Singularity, /r/Oobabooga, /r/MachineLearning, /r/OpenAI, /r/ClaudeAI, /r/StableDiffusion, /r/ChatGPT

Theme 1. AGI: Marketing Hype or Genuine Innovation?

• Are we actually far from AGI and this is all marketing? (Score: 161, Comments: 260): The post questions whether AGI is currently achievable or if claims about it are merely marketing tactics. The author suggests that despite the transformative impact of Transformers, a genuine leap toward AGI might require a breakthrough in neuroscience or cognitive science to develop a new architecture that complements existing technologies.
  • AGI Definition and Skepticism: Many commenters, including insightful_monkey and Deltanightingale, debate the definition of AGI, suggesting that while current AI models like o3 show advanced capabilities in specific domains, they lack the general problem-solving and autonomous reasoning skills that characterize true AGI. The consensus is that the current state of AI is far from achieving AGI, with some like PatrickOBTC highlighting that much of the AGI discourse is marketing-driven.
  • Technological and Financial Constraints: Discussions emphasize the technological and financial hurdles in achieving AGI, with vertigo235 and Deltanightingale noting the high costs and slow speeds associated with existing AI models. JonnyRocks points out that OpenAI's definition of AGI is tied to business goals, such as reaching $100 billion in revenue, rather than true technological milestones, indicating a financial motive behind AGI claims.
  • Progress and Future Outlook: While some, like ZillionBucks, remain optimistic about the future of AGI, many others are skeptical, with TheInfiniteUniverse_ and Economy-Bid-7005 suggesting that while models like o3 perform well in specific areas, they lack crucial elements such as recursive learning. The release of o3-mini and o3-Full is anticipated, but

AI Discord Recap

A summary of Summaries of Summaries by o1-preview-2024-09-12

Theme 1. New AI Models: Codestral, MiniMax-01, and DeepSeek V3

• Codestral Model Debuts with 256k Context: The new Codestral model is now free on the Mistral API, boasting a massive 256k context window and described by users as "stupid fast and good". It's expected to significantly speed up extensive code generation tasks.
• MiniMax-01 Launches Open-Source Models with 4M Tokens: MiniMax-01, including MiniMax-Text-01 and MiniMax-VL-01, can handle up to 4 million tokens, surpassing existing models by 20–32 times. Pricing is set at $0.2 per million input tokens and $1.1 per million output tokens, with a free trial available on Hailuo AI.
• DeepSeek V3 Outperforms Claude in Coding Tasks: Users report that DeepSeek V3 surpasses Claude in code generation and reasoning, though running it locally requires substantial resources—around 380GB of RAM and multiple GPUs. It's praised for its "impeccable reasoning" on complex tasks.

Theme 2. AI Tools and IDEs: Performance Hiccups and User Innovations

• Cursor IDE Faces Slowdowns and User Workarounds: Users experience significant slow requests and downtime with Cursor IDE, likening the bug reporting process to a "kindergarten". While monitoring Anthropic's Status, some developers created scripts using Beyond Compare to manage code snapshots due to Cursor's issues.
• Codeium's Windsurf Woes and the Quest for Clarity: Participants grapple with AI-generated code mistakes leading to development loops in Windsurf. Emphasizing the use of detailed .windsurfrules files, they seek better-structured approaches to refine outputs, referencing Codeium Docs.
• LM Studio Users Compare Qwen 2.5 and QwQ Models: Testing between Qwen 2.5 32B Instruct and QwQ reveals that Qwen provides better code generation with fewer verbose answers. Users recommend models with GGUF encodings for optimal performance on consumer hardware, as noted in local LLM recommendations.

Theme 3. Advancements in AI Features: From Task Scheduling to Ambient Agents

• ChatGPT Introduces Task Scheduling Feature: On January 14, 2025, ChatGPT rolled out a new Task Scheduling feature for Plus, Team, and Pro users. This allows for setting one-time and recurring reminders, aiming to reposition ChatGPT as a proactive AI agent.
• Ambient Agents Automate Email Management: A new AI email assistant autonomously triages and drafts emails, reducing inbox overload. Detailed in Harrison Chase's announcement, it represents a move towards less obtrusive AI assistance requiring minimal supervision.
• Hyper-Connections Proposed to Improve Neural Networks: Researchers introduce Hyper-Connections as an alternative to residual connections, addressing challenges like gradient vanishing. Early experiments show they meet or exceed existing methods, potentially enhancing both language and vision models.

Theme 4. AI Infrastructure: GPU Access and Support Challenges

• Thunder Compute Offers Affordable Cloud GPUs: Thunder Compute launches with A100 instances at $0.92/hr plus $20/month free credit during beta. With an easy CLI (pip install tnr), it simplifies GPU workflows, aiming to make high-performance computing more accessible.
• Unsloth AI Limited to NVIDIA GPUs, AMD Users Left Waiting: Users discover that Unsloth currently supports only one NVIDIA GPU, causing confusion and frustration among those hoping for AMD support. Reference to SHARK-AI’s AMD optimization guide highlights the community's interest in broader GPU compatibility.
• OpenRouter Users Face Rate-Limiting Issues with Models: High demand leads to rate-limiting hurdles, especially with models like DeepSeek V3. While OpenRouter invites providers to integrate models via support@openrouter.ai, users express frustration over performance bottlenecks.

Theme 5. AI in Code Development: Practices and Philosophies

• Developers Debate Testing Tensions: "Jesus Take the Wheel" Approach: Some programmers admit to minimal testing, humorously relying on "Jesus take the wheel" before pushing code changes. Others stress the importance of rigorous testing, especially in languages lacking compilation checks, to avoid risky deployments.
• Community Emphasizes Clear Guidelines for AI Code Collaboration: In tools like Windsurf, users highlight that detailed guidelines via .windsurfrules are crucial to reducing ambiguous AI responses. Sharing these rules and suggesting improvements via Codeium's Feature Requests fosters a proactive community seeking better AI interactions.
• Interest in AI for Real-Time Bug Fixing in Game Development: Users speculate about future video games shipping with real-time AI capable of patching bugs on the fly. They humorously imagine AI fixing older titles, viewing it as a step towards fully polished gaming experiences.

PART 1: High level Discord summaries

Codeium (Windsurf) Discord

• Windsurf Woes & Wins: Multiple participants confronted recurring AI-generated code mistakes, creating a 'loop of doom' in development, and sought better structured approaches to refine outputs, referencing Codeium Docs.
  • Some expressed that adopting specialized instructions, rather than broad prompts, significantly improves reliability and fosters a more proactive community discussion around Windsurf’s potential.
• Rules Rock with .windsurfrules: Users stressed that meticulously defined .windsurfrules guides help clarify project requirements and cut down on ambiguous AI responses during code collaboration.
  • Community members suggested sharing these rules and filing requests at Feature Requests | Codeium to accelerate the enhancement of Windsurf capabilities.
• Quantum TicTacToe Tantalizes Techies: A new Quantum Computing Assembly Language demonstration featuring ‘Quantum TicTacToe’ was showcased via a YouTube video.
  • Enthusiasts viewed this teaser as a spark for broader experimentation, hinting at the potential synergy between Windsurf's AI-driven code generation and quantum-oriented projects.

Unsloth AI (Daniel Han) Discord

• Unsloth GPU Support Collides with AMD Aspirations: Users discovered that Unsloth supports only one NVIDIA GPU at present, causing confusion about future AMD support and referencing SHARK-AI’s AMD optimization guide.
  • Community members saw no immediate fix, while some pinned hopes on specialized GPU forums to produce workable patches.
• Mistral's Codestral 2501 Sparks Licensing Buzz: Mistral revealed Codestral 2501 with an official announcement, but users lamented its restricted API-only release and commercial slant.
  • They questioned if enterprise licensing would limit open-source collaboration, fueling heated debate on model access.
• DeepSeek V3 Drops In For Local Testing: Several members managed to run DeepSeek V3 locally, reporting high VRAM and RAM consumption when pairing it with llama3.1 405B.
  • They traded performance tips, acknowledging slow speeds in minimal setups and the potential for heavy overhead in large-scale fine-tuning.
• Llama 3.1 Fine-Tuning Hits Bumps: A user struggled with absent validation loss metrics while fine-tuning Llama 3.1, even after adjusting dataset size and evaluation frequency.
  • They referenced Unsloth’s Gradient Accumulation fix blog post and attributed issues to tricky training loops for large language modeling.
• 4bit Format Sparks Size Debates: Some expressed enthusiasm for 4bit model saving, hoping to reduce memory usage and keep smaller GPUs relevant.
  • They cited Unsloth Notebooks for instructions, though concerns about model performance in compressed form persisted.

Cursor IDE Discord

• Cursor IDE's Cumbersome Performance: Discord participants flagged Cursor IDE for major slow requests, comparing it to a 'kindergarten' bug reporting scenario, as documented in the Cursor Community Forum.
  • They monitored Anthropic Status for possible interruptions but remained frustrated with the downtime that hurt coding productivity.
• Claude Outshines O1: Users discussed a preference for Claude over O1, noting that Claude excels at agent-mode tasks.
  • Developers cited O1's heavier resource demands, fueling debate over model performance in real-world usage.
• Batch Files for Code Snapshots: A dev created a script to produce numbered folders and use Beyond Compare for quick rollbacks on Cursor IDE mishaps.
  • They shared their GitHub profile, encouraging others to adopt the strategy to track code modifications effectively.
• Testing Tensions: 'Jesus Take the Wheel' Approach: Some developers confessed to minimal testing, jokingly letting 'Jesus take the wheel' before pushing code changes.
  • Others stressed rigorous checks in languages lacking built-in compilation, warning that headless deployment poses a risky but sometimes unavoidable trade-off.
• MCP Servers and Slow Requests: Community members anticipate MCP servers, suggesting they might improve the existing slowdown in Cursor.
  • Despite the wait times, many prefer the loose constraints of this system over stricter concurrency limits on other platforms.

LM Studio Discord

• Qwen 2.5 vs QwQ Showdown: One user tested Qwen 2.5 32B Instruct alongside QwQ, reporting better code generation and fewer wordy answers with Qwen, but mixed results still emerged.
  • Participants noted QwQ had occasional inconsistencies, and overall reactions favored Qwen for clearer coding suggestions.
• Local LLM Recs for Coders: A member shared a local LLM guide emphasizing GGUF encodings for consumer hardware.
  • Others pointed to bartowski/Sky-T1-32B-Preview-GGUF on Hugging Face, citing decent performance with carefully tuned quantizations.
• Game Dev Gains with Generative AI: Users speculated about future video games shipping with real-time AI that patches bugs on the fly, resulting in fewer crashes at launch.
  • They humorously imagined an emergent AI fix for older titles, describing it as a step closer to fully polished classics.
• Multi-GPU Mayhem: RTX 5090 vs 4090: Participants debated whether combining a 5090 with a 4090 could boost processing, although the older card might throttle performance.
  • They highlighted synchronization in layer-by-layer tasks, potentially causing idle time on the RTX 5090 while the slower GPU catches up.

Eleuther Discord

• Quantum Quirk in Eukaryotic Vaults: Researchers noted that eukaryotic cell vaults maintain coherence in noisy settings, fueling speculation about quantum computing uses.
  • Neoxah stayed tight-lipped on deeper specifics, hinting future expansions once the work reaches a formal release.
• Hyper-Connections Combat Residual Roadblocks: Researchers propose Hyper-Connections as an alternative to standard residual connections, citing gradient vanishing and representation collapse challenges, referencing this paper.
  • Preliminary tests show they meet or exceed existing methods, sparking optimism for expansions in both language and vision pipelines.
• Process Rewards & VinePPO Tweak LLM Reasoning: New Process Reward Models (PRMs) spotlight token-level checks to strengthen math skills in LLMs, as outlined in this study.
  • Conversations also explored VinePPO for chain-of-thought tasks, confirming it doesn't rely on explicit CoT examples to achieve consistent benefits in expansions like LATo.
• MLQA Arrives in Style: A new MLQA benchmark implementation appeared via pull request, adding multi-lingual QA coverage for the community, though an AST error awaits code review.
  • The submitter pointed out that lm-eval-harness includes majority voting, citing this config snippet to set repeated sampling.
• Llama 2's Quirky Config & Tokenizer Tales: Developers spotted large shifts in padded_vocab_size for Llama 2 (11008 vs 32768) between NeoX and HF, referencing this config detail.
  • They also observed HF uses silu over swiglu, which some see as a mismatch with earlier activation choices, all while encountering baffling dummy tokens in the build logs.

Stackblitz (Bolt.new) Discord

• Supabase Setup Surprises: Members noted that forking a Bolt project demanded new Supabase deployments each time, blocking reconnection to existing projects and disrupting normal workflows.
  • They compared it to Loveable’s reuse approach and hoped the development team would enable a simpler, more direct connection method.
• Perplexity Chatbot Brainstorm: A user proposed creating a perplexity-style chatbot by integrating a Hugging Face model into Bolt, sparking interest in open-source AI solutions.
  • Others suggested OpenAI’s API for quicker setup, but they also discussed the challenges of juggling different API services.

OpenRouter (Alex Atallah) Discord

• DeVries AI Launches Telegram LLM Hub: The new DeVries AI offers 200+ Large Language Models in Telegram for $24.99/month with free trials available.
  • Users can quickly switch between ChatGPT and Claude, and soon add image/video generation in a single Telegram interface.
• OpenRouter Provider Setup Gains Momentum: OpenRouter invited prospective providers to email support@openrouter.ai to integrate their models, fueling talk of creative usage.
  • One user joked about a provider that secretly uses OpenRouter, prompting comedic speculation on inadvertently building AGI.
• Deepseek V3 Slowness Sparks Concern: Users reported Deepseek V3 failing to respond 7 out of 10 times, pointing to overload causing sluggish replies.
  • Some suggested switching to Together AI endpoint for faster performance.
• MiniMax 456B Parameter Model Draws Attention: MiniMax introduced a model with 456 billion parameters, showing robust context handling despite not topping benchmarks.
  • Its efficient scale has piqued interest among developers exploring larger performance possibilities.

Stability.ai (Stable Diffusion) Discord

• Discord Bots or Not? Comical Conundrum: Members joked about suspicious newcomers who simply greet, suspecting Discord bots were lurking behind these one-line hellos.
  • Some proposed stricter sign-up steps, but worried it might discourage genuine participants.
• DEIS BETA Boldly Boosts Flux Sampling: Enthusiasts praised DEIS BETA for effectively guiding flux sampling in Stable Diffusion scenarios.
  • They also hunted for additional tools, aiming to improve sampling parameters across diverse tasks.
• Aesthetic Classifier Gains Curious Fans: A user sought datasets blending art styles with numeric ratings to build a solid aesthetic classifier.
  • Suggestions included leveraging ollama for streamlined prompting, hoping to unify subjective and objective scoring methods.
• FP8 vs FP16: Showdown of the Bits: Community members debated the merits of FP8 in newer GPUs versus more common FP16 in older devices.
  • They noted FP8's memory benefits but worried about accuracy trade-offs in high-detail Stable Diffusion jobs.
• Intel B580 Stumbles Seek Solutions: A contributor lamented posting hassles around Intel B580 benchmarks for Stable Diffusion due to subreddit restrictions.
  • Others advised contacting mods or exploring alternative forums to gather broader feedback and insights.

Interconnects (Nathan Lambert) Discord

• Qwen's PRM Gains Ground on Process Supervision: The new Qwen2.5-Math-PRM aced intermediate error detection in math tasks on ProcessBench, referencing a 72B model on Hugging Face that uses human-annotated data for stronger reasoning.
  • Developers cautioned that Monte Carlo synthetic approaches lag behind human methods, highlighting the need for careful evaluation.
• Claude Sonnet & MiniCPM-o Make Waves: Claude Sonnet 3.5 hit 62.2% on SWE-Bench Verified, trailing OpenAI's o3 at 71.7%, startling many who saw it as a previous-gen coding contender.
  • Meanwhile, MiniCPM-o 2.6 from OpenBMB, boasting an 8B-size Omni design, impressed with real-time bilingual audio capability, as shown on GitHub and Hugging Face.
• Higher Ed Chatbots & Stripe's Tax Trick: A talk for higher-ed CIOs spotlighted U-M GPT and Maizey, with the University of Michigan championing tailored AI offerings for diverse campus needs.
  • On the tax front, members praised Stripe's Non-Union One Stop Shop, letting outside businesses handle EU VAT in one swoop.
• Synthetic CoT & O1 Drama Bawl: Members found synthetic chain-of-thought training underwhelming, especially when it was just supervised fine-tuning with no RL.
  • They doubted the chances of O1 models, hinting that Big Molmo or Tulu-V might do a better job for vision tasks.
• Policy Punch: AI Blueprint & Datacenter Boom: An Economic Blueprint proposes harnessing AI for national security and growth, echoing repeated policy suggestions from OpenAI.
  • President Biden's executive order unlocks federal land for gigawatt-scale datacenters, mandating on-site clean energy to match capacity.

Latent Space Discord

• ChatGPT's Scheduling Surge: On January 14, 2025, ChatGPT unveiled a new Task Scheduling feature that handles one-time and recurring reminders, as detailed in The Verge report, initially rolling out to Plus, Team, and Pro users.
  • This move aims to recast ChatGPT as a more proactive AI agent, enabling tasks like daily weather updates or news alerts, as mentioned in TechCrunch.
• Cursor's Series B Grab: Cursor announced a Series B funding round co-led by a16z, showcasing strong investor confidence in advanced coding tools and AI-powered dev platforms, with more context in Sarah Wang's tweet.
  • This injection of capital highlights growing enthusiasm for AI-assisted development and sets the stage for further improvements in Cursor's tooling ecosystem.
• Ambient Agents Automate Email: A new AI email assistant autonomously triages and drafts emails, with the concept behind such 'ambient agents' detailed in a blog post and further discussed in Harrison Chase's tweet.
  • This approach promises to reduce email overload by handling routine tasks behind the scenes, letting users focus on higher-level decisions and minimal direct supervision.
• Claude's Rate-Limiting Roadblock: Users reported rate-limiting hurdles with the Claude model Sonnet 3.6 on Cursor, with forum chatter blaming high traffic that exceeds Anthropic’s GPU availability.
  • Developers shared that Cursor is Anthropic's largest customer, intensifying the demand for more robust GPU provisioning.
• Magnetar's Compute-for-Equity Maneuver: Magnetar, a hedge fund, offers compute resources to AI startups in exchange for equity, as covered in a recent podcast and through collaboration with Coreweave.
  • This strategy aims to lessen the funding logjam for emerging AI ventures, underscoring the significance of infrastructure access in fueling next-generation AI developments.

Notebook LM Discord Discord

• Google's $10 Audio Overviews Survey: The Google team introduced a 5-minute screener form to gather feedback on Audio Overviews, awarding a $10 gift code upon completion.
  • They require participants to be at least 18, aiming to shape future NotebookLM updates based on user insights.
• Akash, a New Site for AI-Generated Podcasts: One user showcased Akash as a convenient site for uploading and sharing AI-generated podcasts, removing complicated permission steps.
  • They provided examples of distributing NotebookLM-based content, describing it as 'a simpler approach.'
• Podcast Duration Dilemmas: Community members debated how to restrict podcast length for NotebookLM, citing a Reddit link for attempted solutions.
  • Others discussed direct audio transcription, suggesting a built-in feature instead of uploading files as sources.
• Paid NotebookLM's Quest for Public Sharing: Questions arose about the paid NotebookLM version offering fully public access, without manual permissions for each user.
  • Some members noted only organization-wide sharing works now, inspiring calls for more open publication.
• NoCode RAG Brainstorm for PDFs: A user raised the idea of using NoCode methods to retrieve answers from PDFs in Google Drive, tying it to NotebookLM's retrieval workflows.
  • Participants recognized the complexity of integrating that approach, hoping for deeper support in upcoming iterations.

Perplexity AI Discord

• Perplexity Pro’s Topsy-Turvy Reception: Users raised concerns about redeemed reward codes failing on Pro features, limited effectiveness for coding help, and friction in activating Pro search seamlessly. Some applauded its research benefits but criticized UI changes, pointing to Ublock Origin for blocking ads and unwanted content.
  • Members asked if Pro search could be accessed via API, but official replies confirmed it’s unavailable, frustrating workflows. Others worried about private content not appearing on Google and losing access to previously uploaded documents.
• Coding Assistant Oversteps Boundaries: A coding assistant repeatedly insisted on disclaimers and partial code confirmations despite explicit user directives. This caused friction and dissatisfaction with the assistant’s unresponsive design.
  • Community members suggested more adaptive conversation flows to reduce repetitive disclaimers. Some viewed the behavior as unnecessary friction that complicated development tasks.
• TikTok Tussles with Extra Oversight: Chinese officials weighed possible guidelines around TikTok, focusing on content moderation and user privacy, according to this article. They highlighted increasing concern over data handling and regulatory action.
  • Observers expect more scrutiny from government entities with possible global consequences. Users remain uncertain when or how these rules will be fully imposed.
• German Summary Request Sparks Translation Talk: A user asked for a German-language summary of data referenced in this discussion. They stressed the importance of localized coverage.
  • Some questioned how Perplexity manages multilingual queries at scale. Others viewed it as an interesting test for cross-lingual AI knowledge sharing.

Nous Research AI Discord

• DeepSeek Dethrones Claude: DeepSeek v3 overshadowed Claude in coding tasks, even though Anthropic keeps adjusting Claude's post-training approach.
  • Members shared a fist-pump GIF and appreciated Claude's human-like style, hinting it might stay a user favorite.
• Private Data vs Open Source Face-Off: Participants debated whether open source can match proprietary training sets, with some suggesting government data hubs to even the field.
  • They argued that dataset quality outshines mere quantity, fueling skepticism about fully synthetic corpora.
• Gemini Grabs Data with Ease: Gemini earned praise for data extraction, overshadowing 4o-mini and Llama-8B in accuracy.
  • Participants proposed Jina for specialized text conversion, referencing programmatic methods to ensure precise results.
• Spotlight on Attention Alternatives: A new paper promises methods beyond standard attention, fueling speculation.
  • The group labeled this the month of attention alternatives, expecting more robust approaches in upcoming releases.

aider (Paul Gauthier) Discord

• DeepSeek v3 demands big memory: Contributors reported that effectively running DeepSeek v3 requires about 380GB of RAM, multiple GPU cards, and recommended checking the official Hugging Face repo.
  • They compared it to smaller options like Qwen, noting the trade-offs in performance when hardware resources are limited.
• Qwen runs locally with fewer resources: Members recommended Qwen as a smaller open-source alternative for local usage, highlighting its lower resource requirements compared to bigger models like DeepSeek v3.
  • They indicated it offers balanced performance and avoids heavy memory overhead, although no benchmark data was explicitly shared.
• Gemini excels at user story creation: Discussion suggested the Gemini model as an effective open-source tool for generating user stories tailored to specific requirements.
  • Participants praised its specialized capabilities for narrative tasks but did not provide explicit metrics or links to confirm these claims.

GPU MODE Discord

• MiniMax's 4M Token Triumph: MiniMax-01, including MiniMax-Text-01 and MiniMax-VL-01, launched open-source and can handle up to 4M tokens, far surpassing existing models by 20–32 times (paper).
  • Their pricing is $0.2 per million input tokens and $1.1 per million output tokens, with a free trial on Hailuo AI, prompting excitement around next-gen AI agent tooling.
• Thunder Compute's Cloudy Bargain: A co-founder announced Thunder Compute, offering A100 instances at $0.92/hr plus $20/month free credit during beta.
  • They highlighted an easy CLI (pip install tnr) for fast instance setup, simplifying GPU workflows and requesting user feedback.
• Kaiko & Prior Labs Seeking Model Builders: Kaiko AI is hiring Senior ML Platform Engineers and Data Engineers in Amsterdam and Zurich, focusing on Foundation Models for cancer treatments, with no visa sponsorship (ML Engineer posting).
  • Meanwhile, Prior Labs is building Foundation Models for tabular data, time series, and databases, citing a Nature article that underlines broad impacts in healthcare and finance.
• TorchAO Tinkers with int8: Community members confirmed int8_weight_only uses a fused dequant-and-matmul approach optimized by torch.compile.
  • They demonstrated how to export these quantized models via torch.export or ONNX, emphasizing compatibility with TorchScript for performance gains.
• DeepSeek 2.5 Delivers: Members applauded DeepSeek 2.5 for “impeccable reasoning” on a shared task, illustrating notably advanced logic.
  • They shared an image for verification, showcasing strong results and drawing curiosity about the model’s broader capabilities.

OpenAI Discord

• Codestral Catapults 256k Context: The new codestral model, free on the Mistral API with 256k context, is described as “stupid fast and good" by those testing its efficiency.
  • Users anticipate significant speed benefits for extensive code generation, citing its large context window and ease of deployment.
• ChatGPT 4o Canvas Confusion: Members questioned if ChatGPT 4o with Canvas is just the older model from September or a newly released variant, given OpenAI's ambiguous rollout.
  • Some observed that their previous 4o canvas conversations reverted to 4o mini, fueling further speculation about system updates.
• AI Misalignment Sparks Chatter: A YouTube video on AI misalignment grabbed attention, showcasing animated scenarios of potential risks.
  • Questions arose around the video's relevance, prompting viewers to explore how it aligns with broader concerns about advanced AI systems.
• PDF is Not an API: Contributors in prompt-engineering and api-discussions sought better data formats than PDF, advocating for JSON, YAML, or plain text.
  • One user joked that PDFs are not an API, echoing collective frustration with unwieldy document conversions for AI tasks.
• Language Simplification for Non-Natives: A new de-GPTing prompt helps rephrase text to omit rare words while preserving essential technical terms.
  • Users shared a custom technique in the OpenAI Playground to cut repetitive references, aiming for clarity in responses.

Cohere Discord

• Konkani Coordination & Linguistic Preservation: In Cohere discussions, a user spotlighted Konkani spoken by 2.5 million people in Goa, with developer Reuben Fernandes seeking professional collaboration to boost acceptance of his language-preservation project.
  • He plans to create an AI model that converses in Konkani, emphasizing that no existing systems adequately handle the language, which stirred curiosity among participants.
• Rerank Fine-Tuning Pricing Puzzles: Members questioned Rerank FT costs missing from Cohere pricing, prompting references to official docs for clarification.
  • They shared FAQ links and suggested these resources might shed light on specialized policies, revealing a push for clearer cost structures.
• Cohere's 128k Context Limit Dig: Participants clarified a 128k tokens capacity (around 42,000 words) that spans all interactions, emphasizing it's more than just single-chat memory.
  • Discussion contrasted long-term vs short-term memory, with usage-rate constraints outlined in the Cohere documentation rather than based on token length.
• Alice in Wonderland Bot Banter: The Cmd R Bot denied any link between corvo and escrivaninha, but an Alice in Wonderland reference suggested a hidden linguistic twist.
  • Its Cohere documentation search turned up empty, underscoring gaps in addressing cultural or literary angles.

Modular (Mojo 🔥) Discord

• Mojo's Async Aspirations: Owen posted two pull requests and pull request #3946 for structured async and effect handlers in Mojo, stressing the need for standardizing exceptions like oom and divbyzero.
  • Attendees debated multiple executor designs, suggesting that a basic API layer is crucial before branching into advanced concurrency.
• Zed Zoom: The Mojo Extension Marches On: A developer created a dedicated Mojo in Zed extension that overcame stdlib path detection issues and offered improved LSP functionalities.
  • Others swapped suggestions to refine autocompletion, with some highlighting the extension's potential for broader Mojo adoption.
• Mojodojo's Int8 Hitch: A user encountered a conversion error converting Int8 to String in Mojodojo, citing partial code from the docs.
  • Community members shared references to String struct docs and Parameterization concepts to address the mismatch.
• Meet & Stream: Quick Refresh: A participant missed part of a meeting due to a class conflict but thanked others for an update that kept them in sync.
  • They shared a YouTube video as a helpful resource for anyone unable to catch the full conversation.

tinygrad (George Hotz) Discord

• Tiny corp’s $5M leap for accessible compute: A blog post revealed that tiny corp raised $5M to accelerate their push toward chip development for advanced computing.
  • The founder highlighted the massive gap between 20 PFLOPS of human brain compute and current HPC costs, sparking discussions on bridging public access to bigger compute.
• Tinygrad’s role in tackling hardware gaps: Members discussed the purpose of tinygrad, focusing on its capacity to handle GPU and CPU backends with minimal overhead.
  • They noted that familiarity with LLVM aids in understanding how tinygrad orchestrates lower-level operations, informed by a distributed systems viewpoint.
• Stacking Tensors hits recursion snag: Users ran into a RecursionError when stacking over 6,000 tensors and then calling .numpy().
  • They reduced to 1,000 tensors and bypassed the stacking limit, with suggestions to chunk operations to avoid internal recursion depth issues.
• Dimension confusion triggers errors: A user discovered an IndexError caused by calling transpose() on a 1D tensor in tinygrad.
  • Others explained that specifying dimension parameters is critical for safe operations, highlighting the importance of dimension-awareness with tensor attributes.

Torchtune Discord

• Scaling Sprints for Medical Mastery: Increasing inference time by 6%-11% on a small training set of 500 samples significantly boosted LLM performance in medical benchmarks, as presented in O1 Replication Journey -- Part 3: Inference-time Scaling for Medical Reasoning. Task complexity demanded extended reasoning chains, prompting the exclusion of in-house data to avoid confusion in logical deductions.
  • Nature Communications underscored gaps in model metacognition in Large Language Models lack essential metacognition for reliable medical reasoning, spotlighting the tension between extra computational cost and clinically robust outputs.
• O1 Jailbreak Jitters: Skeptics questioned the validity of jailbreaking O1 for new model training, criticizing existing benchmarks as disconnected from real-world needs.
  • Others demanded more thorough risk assessment, warning that careless jailbreaking practices erode trust in the resulting systems and necessitate rethinking the entire O1 approach.
• Healthcare's Automated Assessment Angst: Members argued that multiple-choice-based evaluations in healthcare constrain AI to pattern recognition and memory tasks, missing deeper clinical capabilities.
  • They called for more nuanced testing protocols to gauge how future AI might participate in actual diagnosis and treatment scenarios.
• Debunking Medical Testing Myths: A debate arose over equating multiple-choice exam success with genuine clinical skills, noting that real-world scrutiny by seasoned doctors goes beyond test scores.
  • Enthusiasts pushed for combining prompt-driven AI with hands-on expertise, aiming at more realistic assessments of a model's clinical competence.
• Redefining AI’s Future in Medicine: Participants stressed that AI should reshape established medical norms and training, rather than replace doctors, to advance patient care.
  • They urged designers to challenge outdated routines, envisioning balanced AI-human team efforts built around ethical safeguards and authentic clinical needs.

OpenInterpreter Discord

• Open Interpreter Gains Video Edge: After a user overcame issues installing Open Interpreter via pipx and brew, they confirmed it can handle commands for video editing.
  • They also noted Cmder performance glitches when Open Interpreter emits large outputs, leading to frequent screen clearing.
• Deepseek Model & Integration Insights: A user asked about the Deepseek model name and setting up the DEEPSEEK_API_KEY for clarity on usage.
  • They also inquired about integrating Deepseek into Open Interpreter, revealing interest in bridging both tools.

LLM Agents (Berkeley MOOC) Discord

• 2024 MOOC Spurs Nostalgia: One user recalled 2024 with strong admiration, describing the MOOC as a highlight of the year.
  • They shared excitement about rewatching Fall 2024 MOOC lectures and connecting with others who felt the same spark.
• MOOC Gains Traction Among Beginners: A newcomer asked about beginner friendliness after completing a prior machine learning class, seeking an easy transition.
  • Others responded that Fall 2024 MOOC lectures strike a balance between core concepts and advanced tips for upskilling.
• Fall 2024 Lectures Lay the Groundwork for Spring 2025: A member urged prospective learners to watch the Fall 2024 lectures to gain background knowledge for upcoming Spring 2025 modules.
  • They noted that the next session won't strictly require prior expertise, but a head start can't hurt.
• Certificate Release Calms Concerned Students: A user inquired about the Fall 2024 MOOC certificate, worried they'd miss the official award.
  • Another user confirmed that certificates will be released later this month, reducing everyone's anxiety about recognition.

Nomic.ai (GPT4All) Discord

• AMD edges closer to NPU integration in GPT4All: A question was raised about whether GPT4All would soon exploit NPU on AMD processors, hinting at future performance boosts.
  • A developer mentioned that AMD's software stack remains a constraint, but indicated that support would be promising once it is finalized.
• VPN solution for remote GPT4All usage: Participants recommended using a VPN or reverse proxy on the inference machine to allow GPT4All's interface to be reached from other devices.
  • They described it as a practical method for multi-device interactions without hardware complications.
• Hugging Face clarifies GPT4All model variations: A conversation highlighted the presence of multiple quantization variants such as codellama q4_0 on Hugging Face.
  • Placing the model files in a single folder apparently resolved confusion about using different versions.

LlamaIndex Discord

• Agent Aces the RAG Race with Weaviate: In a recent notebook by Tuana, an agent using Weaviate and LlamaIndex outperformed naive RAG in retrieving relevant data.
  • Community members credited the agent's approach to combining data sources for stronger coverage, spotlighting its decision-making capabilities.
• QAE Gains Custom Prompt Power: A user explored extra variables in QuestionsAnsweredExtractor using self.llm.apredict(), citing LlamaIndex advanced prompts documentation.
  • Another member shared how function mappings can feed dynamic variables, showing LlamaIndex can fluidly inject multiple data points into prompt templates.

LAION Discord

• Meta's JASCO Ignites Music Generation: The FAIR team of Meta AI introduced JASCO, a new music model trained in November 2024 that uses EnCodec for audio tokenization and handles chords, drums, and melody.
  • It comes in 400M and 1B variants with a flow-matching backbone and condition dropout, spurring excitement for flexible text-to-music generation.
• JASCO Paper Highlights Tech Foundations: A paper titled Joint Audio And Symbolic Conditioning for Temporally Controlled Text-To-Music Generation outlines JASCO's transformer-based architecture and features.
  • Engineers discuss its specialized audio and symbolic conditioning, noting potential for next-level musical composition and model sophistication.

DSPy Discord

• DSPy Ambient Agents, Still Missing Examples: A member asked how to configure an ambient agent using DSPy, requesting any code samples, but none surfaced in the chat.
  • Others echoed interest in real-world DSPy use cases, hoping for shared resources and experiences from fellow developers.
• DSPy Implementation Show-and-Tell: Another participant invited more DSPy demonstrations, highlighting any hands-on trials or partial prototypes for ambient agent scenarios.
  • They encouraged the community to share relevant details or open-source repos, aiming to spark growth in DSPy solutions.

MLOps @Chipro Discord

• AI in Healthcare & Finance Gains Speed: On January 16, 2025, from 4:00 pm to 5:30 pm IST, a global panel will discuss how AI impacts healthcare and finance, with registration at this link.
  • Organizers invited builders, operators, and owners of AI-enabled solutions to tackle cost optimization and data management, hoping to accelerate AI adoption in these sectors.
• Panel Eyes Real-World AI Deployments: The panel plans to emphasize operational details, including data interoperability, compliance, and real-time analytics in the healthcare and finance fields.
  • They stress cross-pollination between these sectors, anticipating new strategies for scaling machine learning models with minimal overhead.

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

The Gorilla LLM (Berkeley Function Calling) 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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