Loading…

AI & Machine Learning News Hub

Research, releases, and applied work in AI & ML

What's New

Top 5 Across All Sources

  1. Smoothed polygons

    John D. Cook · 1h ago

  2. The Joy of Typing

    Towards Data Science · 1h ago

  3. Notes from inside China's AI labs

    Interconnects AI · 2h ago

  4. Give Your AI Unlimited Updated Context

    Towards Data Science · 3h ago
Latest
John D. CookSmoothed polygonsTowards Data ScienceThe Joy of TypingInterconnects AINotes from inside China's AI labsTowards Data ScienceGive Your AI Unlimited Updated ContextTowards Data ScienceHow Major Reasoning Models Converge to the Same “Brain” as They Model Reality Increasingly BetterTowards Data ScienceI Rewrote a Real Data Workflow in Polars. Pandas Didn’t Stand a Chance.John D. CookTriangular analog of the squircleHugging Face - BlogvLLM V0 to V1: Correctness Before Corrections in RLTowards Data ScienceWhen the Uncertainty Is Bigger Than the Shock: Scenario Modelling for English Local ElectionsJohn D. CookUnified config filesTowards Data ScienceBeyond Lists: Using Python Deque for Real-Time Sliding WindowsTowards Data ScienceTimer-XL: A Long-Context Foundation Model for Time-Series ForecastingTowards Data ScienceWhy I Don’t Trust LLMs to Decide When the Weather ChangedTowards Data ScienceDeconstruct Any Metric with a Few Simple ‘What’ QuestionsJohn D. CookThe mythology of category theoryHugging Face - BlogAdding Benchmaxxer Repellant to the Open ASR LeaderboardJohn D. CookChanging one character in a PDFTowards Data ScienceDiscrete Time-To-Event Modeling – Predicting When Something Will HappenTowards Data ScienceHow to Make Claude Code Validate its own WorkTowards Data ScienceRAG Hallucinates — I Built a Self-Healing Layer That Fixes It in Real TimeJohn D. CookSmoothed polygonsTowards Data ScienceThe Joy of TypingInterconnects AINotes from inside China's AI labsTowards Data ScienceGive Your AI Unlimited Updated ContextTowards Data ScienceHow Major Reasoning Models Converge to the Same “Brain” as They Model Reality Increasingly BetterTowards Data ScienceI Rewrote a Real Data Workflow in Polars. Pandas Didn’t Stand a Chance.John D. CookTriangular analog of the squircleHugging Face - BlogvLLM V0 to V1: Correctness Before Corrections in RLTowards Data ScienceWhen the Uncertainty Is Bigger Than the Shock: Scenario Modelling for English Local ElectionsJohn D. CookUnified config filesTowards Data ScienceBeyond Lists: Using Python Deque for Real-Time Sliding WindowsTowards Data ScienceTimer-XL: A Long-Context Foundation Model for Time-Series ForecastingTowards Data ScienceWhy I Don’t Trust LLMs to Decide When the Weather ChangedTowards Data ScienceDeconstruct Any Metric with a Few Simple ‘What’ QuestionsJohn D. CookThe mythology of category theoryHugging Face - BlogAdding Benchmaxxer Repellant to the Open ASR LeaderboardJohn D. CookChanging one character in a PDFTowards Data ScienceDiscrete Time-To-Event Modeling – Predicting When Something Will HappenTowards Data ScienceHow to Make Claude Code Validate its own WorkTowards Data ScienceRAG Hallucinates — I Built a Self-Healing Layer That Fixes It in Real Time

By Source

Feeds organized so you can skim by site.

Density Sort
JD
John D. Cook
1h ago · 20 items
Smoothed polygons 1h ago Triangular analog of the squircle 22h ago Unified config files 1d ago The mythology of category theory 1d ago Changing one character in a PDF 1d ago The shape of a guitar pick 3d ago Approximating even functions by powers of cosine 6d ago Three ways to differentiate ReLU 7d ago Turning a trick into a technique 8d ago Circular arc approximation 9d ago
20 loaded
TD
Towards Data Science
1h ago · 20 items
The Joy of Typing 1h ago Give Your AI Unlimited Updated Context 3h ago How Major Reasoning Models Converge to the Same “Brain” as They Model Reality Increasingly Better 4h ago I Rewrote a Real Data Workflow in Polars. Pandas Didn’t Stand a Chance. 6h ago When the Uncertainty Is Bigger Than the Shock: Scenario Modelling for English Local Elections 1d ago Beyond Lists: Using Python Deque for Real-Time Sliding Windows 1d ago Timer-XL: A Long-Context Foundation Model for Time-Series Forecasting 1d ago Why I Don’t Trust LLMs to Decide When the Weather Changed 1d ago Deconstruct Any Metric with a Few Simple ‘What’ Questions 1d ago Discrete Time-To-Event Modeling – Predicting When Something Will Happen 2d ago
20 loaded
IA
Interconnects AI
2h ago · 20 items
Notes from inside China's AI labs 2h ago The distillation panic 3d ago Reading today's open-closed performance gap 16d ago My bets on open models, mid-2026 21d ago What I’ve been building: ATOM Report, post-training course, finishing my book, and ongoing research 22d ago The inevitable need for an open model consortium 26d ago Claude Mythos and misguided open-weight fearmongering 27d ago Gemma 4 and what makes an open model succeed 34d ago Latest open artifacts (#20): New orgs! New types of models! With Nemotron Super, Sarvam, Cohere Transcribe, & others 38d ago Lossy self-improvement 45d ago
20 loaded
HF
Hugging Face - Blog
23h ago · 20 items
vLLM V0 to V1: Correctness Before Corrections in RL 23h ago A Blog post by ServiceNow-AI on Hugging Face Adding Benchmaxxer Repellant to the Open ASR Leaderboard 1d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. Granite 4.1 LLMs: How They’re Built 8d ago A Blog post by IBM Granite on Hugging Face DeepInfra on Hugging Face Inference Providers 🔥 8d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. Introducing NVIDIA Nemotron 3 Nano Omni: Long-Context Multimodal Intelligence for Documents, Audio and Video Agents 9d ago A Blog post by NVIDIA on Hugging Face How to build scalable web apps with OpenAI's Privacy Filter 10d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. DeepSeek-V4: a million-token context that agents can actually use 13d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. How to Use Transformers.js in a Chrome Extension 14d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science. QIMMA قِمّة ⛰: A Quality-First Arabic LLM Leaderboard 16d ago A Blog post by Technology Innovation Institute on Hugging Face AI and the Future of Cybersecurity: Why Openness Matters 16d ago We’re on a journey to advance and democratize artificial intelligence through open source and open science.
20 loaded
EY
Eugene Yan
4d ago · 20 items
How to Work and Compound with AI 4d ago 2025 Year in Review 144d ago Product Evals in Three Simple Steps 165d ago Advice for New Principal Tech ICs (i.e., Notes to Myself) 200d ago Training an LLM-RecSys Hybrid for Steerable Recs with Semantic IDs 235d ago Evaluating Long-Context Question & Answer Systems 319d ago AI Engineer 2025 - Improving RecSys & Search with LLM techniques 337d ago Exceptional Leadership: Some Qualities, Behaviors, and Styles 354d ago Building News Agents for Daily News Recaps with MCP, Q, and tmux 368d ago An LLM-as-Judge Won't Save The Product—Fixing Your Process Will 382d ago
20 loaded
OU
One Useful Thing
13d ago · 20 items
Sign of the future: GPT-5.5 13d ago Claude Dispatch and the Power of Interfaces 36d ago The Shape of the Thing 56d ago A Guide to Which AI to Use in the Agentic Era 78d ago Management as AI superpower 100d ago Claude Code and What Comes Next 119d ago The Shape of AI: Jaggedness, Bottlenecks and Salients 138d ago Three Years from GPT-3 to Gemini 3 170d ago Giving your AI a Job Interview 176d ago An Opinionated Guide to Using AI Right Now 199d ago
20 loaded
NB
Claude for Legal Teams: Contract Review, Compliance and Due Diligence 16d 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 21d 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 27d 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 27d 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 29d 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? 35d 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 45d 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 54d 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? 56d 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. 57d ago We benchmarked GPT-5.4, Gemini 3.1 Pro, Claude Opus, Sonnet, and 12 others on 3 Open OCR Benchmarks
15 loaded
AO
Ahead of AI
19d ago · 20 items
My Workflow for Understanding LLM Architectures 19d ago Components of A Coding Agent 33d ago A Visual Guide to Attention Variants in Modern LLMs 46d ago A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026 71d ago Categories of Inference-Time Scaling for Improved LLM Reasoning 103d ago The State Of LLMs 2025: Progress, Problems, and Predictions 128d ago LLM Research Papers: The 2025 List (July to December) 128d ago From DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL Updates 155d ago Beyond Standard LLMs 184d ago Understanding the 4 Main Approaches to LLM Evaluation (From Scratch) 214d ago
20 loaded
AW
AI Weirdness
36d ago · 15 items
Get working on your April Fools Eiffel Tower 36d 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 36d ago AI Weirdness: the strange side of machine learning When a chatbot runs your store 138d 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 139d ago AI Weirdness: the strange side of machine learning Tiny neural net Halloween costumes are the best 191d 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 191d ago AI Weirdness: the strange side of machine learning Halloween costumes by tiny neural net 202d 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 202d ago AI Weirdness: the strange side of machine learning Botober 2025: Terrible recipes from a tiny neural net 218d 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 218d ago AI Weirdness: the strange side of machine learning
15 loaded
DB
Damian Bogunowicz - dtransposed
76d ago · 10 items
Running Log: Trail du Mont Agel 76d ago Engineering, Robotics, AI, Technology I Completed The David Goggins Challenge And Asked My Garmin How I Did 820d ago Engineering, Robotics, AI, Technology A Video Game that Pays: Lessons Learned from Working Remotely 917d ago Engineering, Robotics, AI, Technology Deep Dive into NeRF (Neural Radiance Fields) 1370d ago Engineering, Robotics, AI, Technology Learning by Doing - the DeFi Quest (Part 2 out of 2) 1595d ago Engineering, Robotics, AI, Technology Learning by Doing - the DeFi Quest (Part 1 out of 2) 1608d ago Engineering, Robotics, AI, Technology So You Want to Study Computer Science (in Europe)? 1832d ago Engineering, Robotics, AI, Technology Mixed Martial Maths - Simple Reasoning Tools For Complex Phenomena 1858d ago Engineering, Robotics, AI, Technology Notes - Prisoners of Geography (Tim Marshall) 1950d ago Engineering, Robotics, AI, Technology Robotic Assembly Using Deep Reinforcement Learning 2024d ago Engineering, Robotics, AI, Technology
AK
Andrej Karpathy blog
84d ago · 10 items
microgpt 84d ago Musings of a Computer Scientist. Deep Neural Nets: 33 years ago and 33 years from now 1515d ago Musings of a Computer Scientist. A from-scratch tour of Bitcoin in Python 1781d ago Musings of a Computer Scientist. Short Story on AI: Forward Pass 1867d ago Musings of a Computer Scientist. Biohacking Lite 2156d ago Musings of a Computer Scientist. A Recipe for Training Neural Networks 2569d ago Musings of a Computer Scientist. (started posting on Medium instead) 3029d ago Musings of a Computer Scientist. A Survival Guide to a PhD 3529d ago Musings of a Computer Scientist. Deep Reinforcement Learning: Pong from Pixels 3628d ago Musings of a Computer Scientist. Short Story on AI: A Cognitive Discontinuity. 3827d ago Musings of a Computer Scientist.
SR
Salmon Run
94d ago · 20 items
Book Review: Software Engineering for Data Scientists 94d 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 116d 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 131d 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 206d 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 229d 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 312d 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 325d 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 491d 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 514d 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 578d ago Retrieval Augmented Generation (RAG) has become a popular approach to harness LLMs for question answering using your own corpus of data. Typ...
20 loaded
DS
David Stutz
214d ago · 10 items
RAISE 2025 panel statement on aligning AI to clinical values 214d 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 458d 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 476d 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 486d 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 541d 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 543d 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 668d 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 725d 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... Documenting your PhD — Keeping Track of Meetings, Experiments and Decisions 731d ago A PhD can be a difficult endeavour. While becoming an expert in tackling a specific problems, it is easy to lose track of things: Have I read this paper before? What was the paper saying? Why did we decide to change course? Why am I running... On NeurIPS’ High School Paper Track 752d ago The decision to have a separate High School Project Track at NeurIPS 2024 has sparked quite some controversy, with many prominent AI researchers debating pros and cons and personal opinions, primarily on X/Twitter. Initially, I ignored this...
LL
Lil'Log
371d ago · 20 items
Why We Think 371d 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 525d 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 669d 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 755d 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 822d 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 925d 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 1049d 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 1149d 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 1196d 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 1213d 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...
20 loaded
DA
Datumbox
376d ago · 20 items
VernamVeil: A Fresh Take on Function-Based Encryption 376d ago The journey of Modernizing TorchVision – Memoirs of a TorchVision developer – 3 1447d ago A sneak peek at TorchVision v0.11 – Memoirs of a TorchVision developer – 2 1670d ago New Blog series – Memoirs of a TorchVision developer 1720d ago How to take S3 backups with DejaDup on Ubuntu 20.10 2026d ago Datumbox Machine Learning Framework v0.8.2 released 2100d ago How to get around Dropbox’s symlink limitations on Linux 2266d ago The Batch Normalization layer of Keras is broken 2941d ago 5 tips for multi-GPU training with Keras 3028d ago Ubuntu 17.10: a last minute review 3132d ago
20 loaded
JA
Jay Alammar
407d ago · 10 items
Moving To Substack 407d 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 1094d 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 1222d 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 1311d 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 1522d 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 1585d 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 1829d 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 1934d 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 1967d 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 2110d 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...
CH
Chip Huyen
476d ago · 10 items
Common pitfalls when building generative AI applications 476d ago Agents 485d ago Building A Generative AI Platform 651d ago Measuring personal growth 750d ago What I learned from looking at 900 most popular open source AI tools 784d ago Predictive Human Preference: From Model Ranking to Model Routing 799d ago Generation configurations: temperature, top-k, top-p, and test time compute 842d ago Multimodality and Large Multimodal Models (LMMs) 940d ago Open challenges in LLM research 995d ago Generative AI Strategy 1065d ago
SS
Seita's Place
1056d ago · 10 items
My Faculty Application Experience 1056d 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 1222d 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 1227d ago The airplanes on display at the CoRL 2022 banquet. The 2022 Robotics: Science and Systems Conference 1243d 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 1373d ago A photo I took while at ICRA 2022 in Philadelphia. This is the Two New Papers: Learning to Fling and Singulate Fabrics 1379d ago The system for our IROS 2022 paper on singulating layers of cloth with tactile sensing. A Plea to End Harassment 1391d 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 1475d ago This is a regularly updated post, last updated April 21, 2026. I Stand with Ukraine 1532d ago I stand with Ukraine and firmly oppose Vladimir Putin’s invasion. Books Read in 2021 1587d 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 ...
MI
ML in Production
1460d ago · 10 items
Driving Experimentation Forward through a Working Group (Experimentation Program Series: Guide 03) 1460d 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) 1496d 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) 1509d ago An introduction to building an effective experimentation program at your company. Lessons Learned from Writing Online 1552d ago Where I share my story writing MLinProduction and key metrics from building my audience and monetization. Newsletter #087 1983d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #086 1991d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #085 1997d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #084 2004d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #083 2011d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems. Newsletter #082 2018d ago Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems.
SB
Software 2.0 3098d 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 3262d 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 3269d 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 3317d 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 3341d 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. 3396d 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 3425d 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 3826d 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 …

No matching sources found.