AI & Machine Learning News Hub

Shipping huggingface_hub every week with AI, open tools, and a human in the loop 10h ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parameters 20h ago A Blog post by PaddlePaddle on Hugging Face We got local models to triage the OpenClaw repo for FREE!* 1d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. MosaicLeaks: Can your research agent keep a secret? 4d ago A Blog post by ServiceNow on Hugging Face Beyond LoRA: Can you beat the most popular fine-tuning technique? 5d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. Is it agentic enough? Benchmarking open models on your own tooling 5d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. MolmoMotion: Language-guided 3D motion forecasting 5d ago A Blog post by Ai2 on Hugging Face From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot 5d ago A Blog post by Amazon on Hugging Face GLM-5.2: Built for Long-Horizon Tasks 6d ago A Blog post by Z.ai on Hugging Face Agentic Resource Discovery: Let agents search 6d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. Profiling in PyTorch (Part 2): From nn.Linear to a Fused MLP 12d ago How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces 13d ago Migrating Your GitHub CI to Hugging Face Jobs 14d ago The Open Source Community is backing OpenEnv for Agentic RL 15d ago Nemotron 3.5 Content Safety: Customizable Multimodal Safety for Global Enterprise AI 18d ago Designing the hf CLI as an agent-optimized way to work with the Hub 19d ago Direct Preference Optimization Beyond Chatbots 19d ago Adding MCP Tools to Reachy Mini 20d ago Holo3.1: Fast & Local Computer Use Agents 20d ago Introducing Mellum2: A 12B Mixture-of-Experts Model by JetBrains 21d ago

Lobachevsky’s integral formula 14h ago Queens on a prime order board 1d ago All pieces on a 6 by 5 board 2d ago Formalizing a ring theorem with Lean 4 and Claude 5d ago Partial fraction decomposition 6d ago Three examples suffice 6d ago Testing pentagonal numbers 7d ago Quaternion Rotations, Claude, and Lean 7d ago Writing Prolog with ChatGPT 7d ago RSA munitions T-shirt 9d ago Solving a chess puzzle with Claude and Prolog 11d ago Formally proving a calculation with Claude and Lean 12d ago Pulling on a thread 12d ago Aitken acceleration before Aitken 15d ago The Laplace limit 15d ago A crank formula for π 15d ago From Kepler to Bessel 16d ago Mr. Bessel’s eponymous functions 17d ago The Latin of Linux 18d ago Integrating smooth periodic functions 18d ago

Encoding Categorical Data for Outlier Detection 17h ago How to Use Claude Code in Your Browser 19h ago When RAG Users Ask Vague Questions: Clarify Once, Learn the Default 20h ago Neural Networks, Explained for Beginners: Start Here If They’ve Confused You 22h ago Tool Calling, Explained: How AI Agents Decide What to Do Next 1d ago Reconstructing the Table of Contents a PDF Forgot to Ship, So RAG Can Scope by Section 1d ago What Are the Possibilities to Build Date Tables in Self-Service Environments? 1d ago 7 Crucial Barriers Between Data Teams and Self-Healing Data Architecture 2d ago Making a PDF’s Images Searchable for RAG, Without Paying to Read Them All 2d ago Materialized Lake Views in Microsoft Fabric: When Your Medallion Fits in a SELECT Statement 2d ago Python 3.14 and its New JIT Compiler 3d ago Building a Custom GStreamer Plugin for NVIDIA DeepStream 3d ago I Tried to Schedule My ETL Pipeline. Here’s What I Didn’t Expect. 3d ago Parse Scanned PDFs for RAG with EasyOCR: Free OCR Gives You Words, Not a Document 3d ago GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step Would Stop Bouncing Off the GPU 3d ago Structured Outputs with LLMs: JSON Mode, Function Calling, and When to Use Each 4d ago How Powerful is Claude Fable (Mythos) 5 for Coding? 4d ago Proteins: A Mosaic Pattern to Rule Them All? 4d ago Dispatching the Parsed RAG Question: Chunk Strategy, Model Tier, Activations, Audit 4d ago The Power and Pitfalls of Vector-Based Image Search 4d ago

GLM-5.2 is the step change for open agents 19h ago Banning Open Source AI Would Be A Mistake 3d ago State of the blog, mid-2026 5d ago Frontier post-training recipe review with Finbarr Timbers 6d ago Welcome to the AGI era of AI governance 8d ago Claude Fable 5 and new AI safety fables 13d ago Farewell Ai2 20d ago Open and closed models are on different exponentials 21d ago Some ideas for what comes next, May 2026 27d ago Latest open artifacts (#21): Open model bonanza! Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, GLM-5.1 & others. On CAISI's V4 assessment. 37d ago How open model ecosystems compound 41d ago Notes from inside China's AI labs 46d ago The distillation panic 49d ago Reading today's open-closed performance gap 63d ago My bets on open models, mid-2026 68d ago What I’ve been building: ATOM Report, post-training course, finishing my book, and ongoing research 69d ago The inevitable need for an open model consortium 72d ago Claude Mythos and misguided open-weight fearmongering 74d ago Gemma 4 and what makes an open model succeed 80d ago Latest open artifacts (#20): New orgs! New types of models! With Nemotron Super, Sarvam, Cohere Transcribe, & others 84d ago

Patterns for Building Cybersecurity Evals 2d ago Using LLMs to Secure Source Code 27d ago How to Work and Compound with AI 51d ago 2025 Year in Review 191d ago Product Evals in Three Simple Steps 212d ago Advice for New Principal Tech ICs (i.e., Notes to Myself) 247d ago Training an LLM-RecSys Hybrid for Steerable Recs with Semantic IDs 282d ago Evaluating Long-Context Question & Answer Systems 366d ago AI Engineer 2025 - Improving RecSys & Search with LLM techniques 384d ago Exceptional Leadership: Some Qualities, Behaviors, and Styles 401d ago Building News Agents for Daily News Recaps with MCP, Q, and tmux 415d ago An LLM-as-Judge Won't Save The Product—Fixing Your Process Will 429d ago Frequently Asked Questions about My Writing Process 450d ago NVIDIA GTC 2025 - Building LLM-Powered Applications 462d ago Improving Recommendation Systems & Search in the Age of LLMs 464d ago Building AI Reading Club: Features & Behind the Scenes 527d ago 2024 Year in Review 548d ago Seemingly Paradoxical Rules of Writing 569d ago How to Run a Weekly Paper Club (and Build a Learning Community) 576d ago My Minimal MacBook Pro Setup Guide 583d ago

Domain-Specific AI Should Focus on Workflows Rather Than Modeling 8d ago I spent the past few years working on AI for health. Starting with custom multimodal encoders, post-training, and sophisticated multi-agent architecturs, I now see modeling work becoming less and less important for domain-specific applicati... AI Evaluation is Becoming an Exciting Standalone Discipline 37d ago Having worked on robustness problems during my PhD, I see many of the characteristics appearing in the evaluation of LLMs and AI systems. Adversarial attacks such as jailbreaks are becoming more relevant, edge cases finally become relevant,... RAISE 2025 Panel Statement on Aligning AI to Clinical Values 261d ago Recently, I attended the Responsible AI for Social and Ethical Healthcare 2025 “2.0” Symposium organized by, among others, Harvard Medical School. The symposium featured various panels on topics surrounding generative AI, in particular mult... Some Lessons on Reviews and Rebuttals 505d ago Writing and responding to reviews is the bread and butter of any academic and especially in AI research, PhD students are confronted with both rather early compared to other displicines. Unfortunately, I found that drafting reviews and rebu... Thoughts on Watermarking AI-Generated Content 523d ago Watermarking AI-generated content has the potential to address various problems that generative AI threatens to aggravate — misinformation, impersonation, copyright infringement, web pollution, etc. However, it is also controversial with ma... Thoughts and Lessons for Planning Rater Studies in AI 532d ago With the goal of deploying generative AI systems, rater studies are becoming increasingly common and important. This means more and more researchers and engineers face the challenge of actually planning and conducting rater studies for AI s... Open-Sourcing Relabeled MedQA and Dermatology DDx Datasets 587d ago Dealing with rater disagreement is becoming more important in AI, especially for LLMs and in specialized domains such as health. In the past year, I helped open source two datasets allowing to study rater disagreement in the health domain: ... Thinking About Research Ideas vs. Technology 589d ago In this article, I want to share some thoughts on the difference between research ideas and technology, particularly in machine learning. This distinction is have been contemplating since starting my PhD. After joining Google DeepMind and b... The Importance of Effectively Experimenting in an AI PhD 714d ago Engineering and running experiments are a key component of most PhDs in AI. While there are plenty of more theoretical topics that are often limited to smaller scale experimentation, the trend has definitely been to scale up models, dataset... FAQ for our Monte Carlo Conformal Prediction 771d ago Over the past months, I have given several talks about Monte Carlo conformal prediction and the problem of calibrating with uncertain ground truth, for example, stemming from annotator disagreement. Each time, the audience had great questio...

What it feels like to work with Mythos 13d ago Co-Existence and the End of Co-Intelligence 18d ago Choosing to Stay Human 27d ago Sign of the future: GPT-5.5 60d ago Claude Dispatch and the Power of Interfaces 83d ago The Shape of the Thing 102d ago A Guide to Which AI to Use in the Agentic Era 125d ago Management as AI superpower 146d ago Claude Code and What Comes Next 166d ago The Shape of AI: Jaggedness, Bottlenecks and Salients 184d ago Three Years from GPT-3 to Gemini 3 216d ago Giving your AI a Job Interview 223d ago An Opinionated Guide to Using AI Right Now 246d ago Real AI Agents and Real Work 266d ago On Working with Wizards 284d ago Mass Intelligence 298d ago GPT-5: It Just Does Stuff 319d ago The Bitter Lesson versus The Garbage Can 329d ago Against "Brain Damage" 350d ago Using AI Right Now: A Quick Guide 364d ago

LLM Research Papers: The 2026 List (January to May) 16d ago Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention 37d ago My Workflow for Understanding LLM Architectures 65d ago Components of A Coding Agent 79d ago A Visual Guide to Attention Variants in Modern LLMs 92d ago A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026 117d ago Categories of Inference-Time Scaling for Improved LLM Reasoning 149d ago The State Of LLMs 2025: Progress, Problems, and Predictions 174d ago LLM Research Papers: The 2025 List (July to December) 174d ago From DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL Updates 201d ago Beyond Standard LLMs 230d ago Understanding the 4 Main Approaches to LLM Evaluation (From Scratch) 260d ago Understanding and Implementing Qwen3 From Scratch 289d ago From GPT-2 to gpt-oss: Analyzing the Architectural Advances 317d ago The Big LLM Architecture Comparison 338d ago LLM Research Papers: The 2025 List (January to June) 356d ago Understanding and Coding the KV Cache in LLMs from Scratch 370d ago Coding LLMs from the Ground Up: A Complete Course 408d ago The State of Reinforcement Learning for LLM Reasoning 429d ago First Look at Reasoning From Scratch: Chapter 1 450d ago

SAP Sapphire 2026: The Complete Breakdown 32d ago All 25 announcements from Orlando, what's actually shipping vs. what's marketing — and what it means for the document and data foundation of the autonomous enterprise. SAP's Sapphire 2026 in Orlando was the most AI-dense keynote in the comp... Claude for Legal Teams: Contract Review, Compliance and Due Diligence 62d ago See how the Claude legal plugin helps in-house legal teams with contract review, compliance scanning, due diligence, obligations tracking, and drafting. Vibe Coding Best Practices: 5 Claude Code Habits for Better Agentic Coding 67d ago Learn 5 practical vibe coding best practices for Claude Code and coding agents: CLAUDE.md, planning, review agents, safer prompts, and diff review. AI Benchmarks Explained: GPQA, SWE-bench, Chatbot Arena and What They Actually Measure 73d ago Learn what MMLU, GPQA Diamond, SWE-bench, HealthBench, and Chatbot Arena actually measure, and how labs game benchmark scores. Why AI-Native IDP Platforms Outperform ABBYY and Kofax in Modern Document Workflows 74d ago Evaluating IDP vendors? Compare Nanonets vs ABBYY and Kofax across architecture, operating model, and TCO to see why AI-native wins for IDP. Why You Hit Claude Limits So Fast: AI Token Limits Explained 76d ago Learn what AI tokens are, why Claude hits limits fast, and how to cut waste from context windows, history, files, tools, and reasoning. Did Google's TurboQuant Actually Solve AI Memory Crunch? 81d ago Google’s TurboQuant promises 6x KV-cache compression. Here’s what it means for AI memory, HBM demand, and the broader memory crunch. Claude for Finance Teams: Investment Banking, DCF Models, Reconciliation & Variance Analysis 91d ago See how finance teams use Claude for one-pagers, CIMs, comps, DCF models, reconciliations, and variance commentary, plus key human checks. AI Agent Hacks McKinsey: 5 Situations When You Should Not Deploy Agents 100d ago McKinsey hacked in 2 hours. 5 situations where AI agents will fail. Production permissions, regulated data, legacy systems—check before deploy. Are OpenAI and Google intentionally downgrading their models? 103d ago Yes, OpenAI and Google degrade their models. OpenAI admitted silent updates after denying it. Gemini redirects models. With full evidence. We ran 16 AI Models on 9,000+ Real Documents. Here's What We Found. 103d ago AI Arms Race Has Real Numbers: Pentagon vs China 2026 109d ago Stop Paying for AI You Don't Use: The Case for Fine-Tuned Models 112d ago Claude's Role in Capturing Nicolás Maduro 124d ago Claude vs Open AI: Real Fight Is Business Model 131d ago

Get working on your April Fools Eiffel Tower 82d ago Elevator Surprise: Place a tiny camera in the elevator, and when someone gets in, snap a photo saying, "Welcome to Space Station!" Or build a miniature model of the Eiffel Tower next to it for a dramatic effect. Tower of Pancakes: Create a ... Bonus: More April Fools pranks from Eiffel Tower Llama 82d ago AI Weirdness: the strange side of machine learning When a chatbot runs your store 185d ago You may have heard of people hooking up chatbots to controls that do real things. The controls might run internet searches, run commands to open and read documents and spreadsheets, or even edit or delete entire databases. Whether this soun... Bonus: Incorrect Christmas Carols 186d ago AI Weirdness: the strange side of machine learning Tiny neural net Halloween costumes are the best 237d ago I've been experimenting with getting a tiny circa-2015 recurrent neural network to generate Halloween costumes. Running on a single cat hair-covered laptop, char-rnn has no internet training, but learns from scratch to imitate the data I gi... More tiny neural net costumes 237d ago AI Weirdness: the strange side of machine learning Halloween costumes by tiny neural net 248d ago I've recently been experimenting with one of my favorite old-school neural networks, a tiny program that runs on my laptop and knows only about the data I give it. Without internet training, char-rnn doesn't have outside references to draw ... Bonus: more halloween costumes from tiny neural net 248d ago AI Weirdness: the strange side of machine learning Botober 2025: Terrible recipes from a tiny neural net 265d ago After seeing generated text evolve from the days of tiny neural networks to today's ChatGPT-style large language models, I have to conclude: there's something special about the tiny guys. Maybe it's the way the tiny neural networks string t... Bonus: Char-rnn's jello creations 265d ago AI Weirdness: the strange side of machine learning ChatGPT will apologize for anything 318d ago Revised instructions for troubleshooting the warp confabulator 318d ago Minecraft with object impermanence 519d ago Bonus: In Which The Adventurer Attempts to Build a Website 519d ago Botober 2024 630d ago

Running Log: Trail du Mont Agel 123d ago Engineering, Robotics, AI, Technology I Completed The David Goggins Challenge And Asked My Garmin How I Did 867d ago Engineering, Robotics, AI, Technology A Video Game that Pays: Lessons Learned from Working Remotely 964d ago Engineering, Robotics, AI, Technology Deep Dive into NeRF (Neural Radiance Fields) 1417d ago Engineering, Robotics, AI, Technology Learning by Doing - the DeFi Quest (Part 2 out of 2) 1642d ago Engineering, Robotics, AI, Technology Learning by Doing - the DeFi Quest (Part 1 out of 2) 1655d ago Engineering, Robotics, AI, Technology So You Want to Study Computer Science (in Europe)? 1879d ago Engineering, Robotics, AI, Technology Mixed Martial Maths - Simple Reasoning Tools For Complex Phenomena 1905d ago Engineering, Robotics, AI, Technology Notes - Prisoners of Geography (Tim Marshall) 1997d ago Engineering, Robotics, AI, Technology Robotic Assembly Using Deep Reinforcement Learning 2071d ago Engineering, Robotics, AI, Technology

microgpt 131d ago Musings of a Computer Scientist. Deep Neural Nets: 33 years ago and 33 years from now 1562d ago Musings of a Computer Scientist. A from-scratch tour of Bitcoin in Python 1828d ago Musings of a Computer Scientist. Short Story on AI: Forward Pass 1914d ago Musings of a Computer Scientist. Biohacking Lite 2203d ago Musings of a Computer Scientist. A Recipe for Training Neural Networks 2616d ago Musings of a Computer Scientist. (started posting on Medium instead) 3075d ago Musings of a Computer Scientist. A Survival Guide to a PhD 3575d ago Musings of a Computer Scientist. Deep Reinforcement Learning: Pong from Pixels 3674d ago Musings of a Computer Scientist. Short Story on AI: A Cognitive Discontinuity. 3873d ago Musings of a Computer Scientist.

Book Review: Software Engineering for Data Scientists 141d ago As a Software Engineer (backend Web Development then Search) turned Data Scientist, I was particularly interested in what the book Software ... Book Review: Transformers In Action 163d ago The Attention Is All You Need paper proposed the Transformer Architecrture as an improvement to the dominant encoder-decoder models of the ... Trip Report: PyData Global 2025 178d ago I attended PyData Global 2025 earlier this month. I had hoped to write this up earlier, but I've been busy, so only now getting the time Ch... Book Review: Time Series Forecasting using Foundation Models 253d ago As someone who primarily works in NLP and Search in the Health Domain, I don't have much use for Time Series. However, while exploring the F... Book Review: Statistics every Programmer Needs 275d ago I recently read Statistics every Programmer Needs by Gary Sutton. I am probably a good target audience for the book since I used to be a so... Book Review: Hands-On Artificial Intelligence for IoT 359d ago For those in similar professional circles as I am in, i.e. looking forward into the Generative AI space, yet with one foot pragmatically and... Book Review: Essential Graph RAG 372d ago Coming from a background of Knowledge Graph (KG) backed Medical Search, I don't need to be convinced about the importance of manually curate... Packaging ML Pipelines from Experiment to Deployment 538d ago As an ML Engineer, we are generally tasked with solving some business problem with technology. Typically it involves leveraging data assets ... Trip Report - PyData Global 2024 561d ago I attended PyData Global 2024 last week. Its a virtual conference, so I was able to attend it from the comfort of my home, although presenta... Using Knowledge Graphs to enhance Retrieval Augmented Generation 625d ago Retrieval Augmented Generation (RAG) has become a popular approach to harness LLMs for question answering using your own corpus of data. Typ... Experiments with Prompt Compression 693d ago Table Extraction from PDFs using Multimodal (Vision) LLMs 722d ago Book Report: Pandas Workout 729d ago Finetuning RAGAS Metrics using DSPy 765d ago Performance Analysis of Float vs Byte vs Binary Vectors on OpenSearch 769d ago KGC/HCLS 2024 Trip Report 776d ago Book Report: Machine Learning for Drug Discovery 821d ago Hierarchical (and other) Indexes using LlamaIndex for RAG Content Enrichment 827d ago Thoughts on using LangChain LCEL with Claude 849d ago Book Report: Allen B Downey's Probably Overthinking It 870d ago

Why We Think 418d ago Special thanks to John Schulman for a lot of super valuable feedback and direct edits on this post. Test time compute (Graves et al. 2016, Ling, et al. 2017, Cobbe et al. 2021) and Chain-of-thought (CoT) (Wei et al. 2022, Nye et al. 2021), ... Reward Hacking in Reinforcement Learning 572d ago Reward hacking occurs when a reinforcement learning (RL) agent exploits flaws or ambiguities in the reward function to achieve high rewards, without genuinely learning or completing the intended task. Reward hacking exists because RL enviro... Extrinsic Hallucinations in LLMs 716d ago Hallucination in large language models usually refers to the model generating unfaithful, fabricated, inconsistent, or nonsensical content. As a term, hallucination has been somewhat generalized to cases when the model makes mistakes. Here,... Diffusion Models for Video Generation 802d ago Diffusion models have demonstrated strong results on image synthesis in past years. Now the research community has started working on a harder task—using it for video generation. The task itself is a superset of the image case, since an ima... Thinking about High-Quality Human Data 869d ago [Special thank you to Ian Kivlichan for many useful pointers (E.g. the 100+ year old Nature paper “Vox populi”) and nice feedback. 🙏 ] High-quality data is the fuel for modern data deep learning model training. Most of the task-specific lab... Adversarial Attacks on LLMs 972d ago The use of large language models in the real world has strongly accelerated by the launch of ChatGPT. We (including my team at OpenAI, shoutout to them) have invested a lot of effort to build default safe behavior into the model during the ... LLM Powered Autonomous Agents 1096d ago Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond genera... Prompt Engineering 1196d ago Prompt Engineering, also known as In-Context Prompting, refers to methods for how to communicate with LLM to steer its behavior for desired outcomes without updating the model weights. It is an empirical science and the effect of prompt eng... The Transformer Family Version 2.0 1243d ago Many new Transformer architecture improvements have been proposed since my last post on “The Transformer Family” about three years ago. Here I did a big refactoring and enrichment of that 2020 post — restructure the hierarchy of sections an... Large Transformer Model Inference Optimization 1259d ago [Updated on 2023-01-24: add a small section on Distillation.] Large transformer models are mainstream nowadays, creating SoTA results for a variety of tasks. They are powerful but very expensive to train and use. The extremely high inferenc... Some Math behind Neural Tangent Kernel 1383d ago Generalized Visual Language Models 1474d ago Learning with not Enough Data Part 3: Data Generation 1529d ago Learning with not Enough Data Part 2: Active Learning 1584d ago Learning with not Enough Data Part 1: Semi-Supervised Learning 1661d ago How to Train Really Large Models on Many GPUs? 1733d ago What are Diffusion Models? 1808d ago Contrastive Representation Learning 1849d ago Reducing Toxicity in Language Models 1920d ago Controllable Neural Text Generation 1998d ago

VernamVeil: A Fresh Take on Function-Based Encryption 422d ago The journey of Modernizing TorchVision – Memoirs of a TorchVision developer – 3 1493d ago A sneak peek at TorchVision v0.11 – Memoirs of a TorchVision developer – 2 1716d ago New Blog series – Memoirs of a TorchVision developer 1766d ago How to take S3 backups with DejaDup on Ubuntu 20.10 2073d ago Datumbox Machine Learning Framework v0.8.2 released 2147d ago How to get around Dropbox’s symlink limitations on Linux 2312d ago The Batch Normalization layer of Keras is broken 2988d ago 5 tips for multi-GPU training with Keras 3074d ago Ubuntu 17.10: a last minute review 3179d ago Datumbox Machine Learning Framework v0.8.1 released 3217d ago Drilling into Spark’s ALS Recommendation algorithm 3404d ago Getting the GPU usage of NVIDIA cards with the Linux dstat tool 3418d ago Datumbox Machine Learning Framework version 0.8.0 released 3446d ago Datumbox Machine Learning Framework 0.7.0 Released 3747d ago Datumbox Machine Learning Framework 0.6.1 Released 3824d ago Datumbox Machine Learning Framework 0.6.0 Released 4068d ago How to install and use the Datumbox Machine Learning Framework 4243d ago New open-source Machine Learning Framework written in Java 4264d ago Clustering with Dirichlet Process Mixture Model in Java 4369d ago

Moving To Substack 454d ago I’m freezing this blog and starting to post on my Substack instead. The authoring experience is much more convenient for me there. Please follow me there, and check out The Illustrated DeepSeek R-1 if you haven’t yet. And check out our How ... Generative AI and AI Product Moats 1141d ago Here are eight observations I’ve shared recently on the Cohere blog and videos that go over them.: Article: What’s the big deal with Generative AI? Is it the future or the present? Article: AI is Eating The World Remaking Old Computer Graphics With AI Image Generation 1269d ago Can AI Image generation tools make re-imagined, higher-resolution versions of old video game graphics? Over the last few days, I used AI image generation to reproduce one of my childhood nightmares. I wrestled with Stable Diffusion, Dall-E ... The Illustrated Stable Diffusion 1358d ago Translations: Chinese, Vietnamese. (V2 Nov 2022: Updated images for more precise description of forward diffusion. A few more images in this version) AI image generation is the most recent AI capability blowing people’s minds (mine included... Applying massive language models in the real world with Cohere 1569d ago A little less than a year ago, I joined the awesome Cohere team. The company trains massive language models (both GPT-like and BERT-like) and offers them as an API (which also supports finetuning). Its founders include Google Brain alums in... The Illustrated Retrieval Transformer 1632d ago Discussion: Discussion Thread for comments, corrections, or any feedback. Translations: Korean, Russian Summary: The latest batch of language models can be much smaller yet achieve GPT-3 like performance by being able to query a database or... Explainable AI Cheat Sheet 1876d ago Introducing the Explainable AI Cheat Sheet, your high-level guide to the set of tools and methods that helps humans understand AI/ML models and their predictions. I introduce the cheat sheet in this brief video: Finding the Words to Say: Hidden State Visualizations for Language Models 1981d ago By visualizing the hidden state between a model's layers, we can get some clues as to the model's Interfaces for Explaining Transformer Language Models 2014d ago Interfaces for exploring transformer language models by looking at input saliency and neuron activation. Explorable #1: Input saliency of a list of countries generated by a language model Tap or hover over the output tokens: Explorable #2: ... How GPT3 Works - Visualizations and Animations 2157d ago Discussions: Hacker News (397 points, 97 comments), Reddit r/MachineLearning (247 points, 27 comments) Translations: German, Korean, Chinese (Simplified), Russian, Turkish The tech world is abuzz with GPT3 hype. Massive language models (lik...

Common pitfalls when building generative AI applications 523d ago Agents 532d ago Building A Generative AI Platform 698d ago Measuring personal growth 797d ago What I learned from looking at 900 most popular open source AI tools 831d ago Predictive Human Preference: From Model Ranking to Model Routing 846d ago Generation configurations: temperature, top-k, top-p, and test time compute 889d ago Multimodality and Large Multimodal Models (LMMs) 987d ago Open challenges in LLM research 1042d ago Generative AI Strategy 1112d ago

My Faculty Application Experience 1103d ago I spent roughly a year preparing, and then interviewing, for tenure-trackfaculty positions. My job search is finally done, and I am joining theUniversity of ... Books Read in 2022 1269d ago At the end of every year I have a tradition where I write summaries of thebooks that I read throughout the year. Unfortunately this year wasexceptionally bus... Conference on Robot Learning 2022 1273d ago The airplanes on display at the CoRL 2022 banquet. The 2022 Robotics: Science and Systems Conference 1289d ago A photo I took while at RSS 2022 in New York City, on the dinner cruise arranged by the conference. The (In-Person) ICRA 2022 Conference in Philadelphia 1419d ago A photo I took while at ICRA 2022 in Philadelphia. This is the Two New Papers: Learning to Fling and Singulate Fabrics 1425d ago The system for our IROS 2022 paper on singulating layers of cloth with tactile sensing. A Plea to End Harassment 1437d ago Scott Aaronson is a professor of computer science at UT Austin, where hisresearch area is in theoretical computer science. However, he may be more wellknown ... My Paper Reviewing Load 1521d ago This is a regularly updated post, last updated June 13, 2026. I Stand with Ukraine 1578d ago I stand with Ukraine and firmly oppose Vladimir Putin’s invasion. Books Read in 2021 1634d ago At the end of every year I have a tradition where I write summaries of thebooks that I read throughout the year. Here’s the following post with the roughset ...

Driving Experimentation Forward through a Working Group (Experimentation Program Series: Guide 03) 1506d ago We describe how diverse stakeholders can drive experimentation forward through the formation of a working group and what role data science plays. What is an Experimentation program and Who is Involved? (Experimentation Program Series: Guide 02) 1542d ago We define what an experimentation program is and discuss which stakeholder groups should participate in order to drive experimentation forward. Building An Effective Experimentation Program (Experimentation Program Series: Guide 01) 1555d ago An introduction to building an effective experimentation program at your company. Lessons Learned from Writing Online 1598d ago Where I share my story writing MLinProduction and key metrics from building my audience and monetization. Newsletter #087 2029d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #086 2037d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #085 2043d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #084 2050d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #083 2057d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #082 2064d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems.

Efficient multi-lingual language model fine-tuning 2478d ago Introducing state of the art text classification with universal language models 2961d ago

Software 2.0 3145d ago Software 2.0 I sometimes see people refer to neural networks as just “another tool in your machine learning toolbox”. They have some pros and cons, they work here or there, and sometimes you can … AlphaGo, in context 3309d ago AlphaGo, in context Update Oct 18, 2017: AlphaGo Zero was announced. This post refers to the previous version. 95% of it still applies. I had a chance to talk to several people about the recent … ICML accepted papers institution stats 3316d ago ICML accepted papers institution stats The accepted papers at ICML have been published. ICML is a top Machine Learning conference, and one of the most relevant to Deep Learning, although NIPS has a … A Peek at Trends in Machine Learning 3363d ago A Peek at Trends in Machine Learning Have you looked at Google Trends? It’s pretty cool — you enter some keywords and see how Google Searches of that term vary through time. I thought — hey, I … ICLR 2017 vs arxiv-sanity 3388d ago ICLR 2017 vs arxiv-sanity I thought it would be fun to cross-reference the ICLR 2017 (a popular Deep Learning conference) decisions (which fall into 4 categories: oral, poster, workshop, reject) with … Virtual Reality: still not quite there, again. 3443d ago Virtual Reality: still not quite there, again. The first time I tried out Virtual Reality was a while ago — somewhere in the late 1990's. I was quite young so my memory is a bit hazy, but I … Yes you should understand backprop 3472d ago Yes you should understand backprop When we offered CS231n (Deep Learning class) at Stanford, we intentionally designed the programming assignments to include explicit calculations involved in … CS183c Assignment #3 3873d ago CS183c Assignment #3 The last few weeks we heard from several excellent guests, including Selina Tobaccowala from Survey Monkey, Patrick Collison from Stripe, Nirav Tolia from Nextdoor, Shishir …