What if we’re wrong?
I’ll quote the very wise Spider-Man (or more accurately, Uncle Ben): “With great power comes great responsibility.”
Medical RAG Research with txtai
txtai is an all-in-one AI framework for semantic search, LLM orchestration and language model... Tagged with ai, llm, rag, vectordatabase.
UI/UX - 大規模な CSS への対応
大規模なスタイルセットを記述する場合、CSS では限界があります。そこで登場するのが、CSS プリプロセッサ と呼ばれるツールです。その中でも代表的なのが SCSS (サス、Sassy CSS)... Tagged with vue, webdev, design, css.
CyberGuard AI
CyberGuardian: Building Autonomous Multi-Agent Cybersecurity Defense with Google Cloud's...
Unframe Launches Synergy
Now generally available, Synergy correlates and explains data across IT Ops systems for real-time clarity, faster resolution, and measurable efficiency without rip-and-replace Unfr...
How to add a curve to a moment-ratio diagram
I have previously written about the moment-ratio diagram as a graphical tool for modeling univariate distributions and also as a tool for examining the distribution of the skewness...
THAMES for mixtures, a reply from the authors
[Here is a reply to my comments on THAMES sent by the first author of the paper, Martin Metodiev. The above replica of the cover of Rivers of London is obviously unrelated with the...
Minimize squared relative error
How to choose an estimate that minimizes the squared relative errors to each of the data points. The "relative" requirement is what makes this interesting.
自由と統制:変化しながらもガバナンスを担保するための唯一無二のデータ分析プラットフォームとは
競争に勝つためのData & AI プラットフォームに完成はない 「ガウディとサグラダ・ファミリアに学ぶデータ分析基盤アーキテクチャのための原則」で考察したように、変化し続ける市場や消費者、経済環境において、企業・組織が意志決定する対象やその内容は刻々と変化していきます。また、よりよい意志決定のためのData & AI活用のためのテクノロジーも日々変化してい...
Seriously, What Is ‘Superintelligence’?
In this episode of “Uncanny Valley,” we talk about Meta’s recent investment in Scale AI and its move to build a superintelligence AI research lab. So we ask: What is superintellige...
R Package Quality: Validation and beyond!
As is often the case, it’s pretty easy to talk about “good” R packages. We can even wave our hands and talk about packages following “software standards” or “best practices”. But w...
Update on the AWS DeepRacer Student Portal
Starting July 14, 2025, the AWS DeepRacer Student Portal will enter a maintenance phase where new registrations will be disabled. Until September 15, 2025, existing users will reta...
Deleting vs Replacing Names
When deidentifying sensitive data, is it better to remove names or to replace them with randomly generated names?
SAS: The workhorse of the AI era
SAS is the AI era’s quiet workhorse – powering trusted, scalable systems where reliability, compliance and results matter most.
Futureverse – Ten-Year Anniversary
The future package turns ten years old today. I released version 0.6.0 to CRAN on June 19, 2015, just days before I presented the package and sharing my visions at useR! 2016. I ha...
The Crunchbase Tech Layoffs Tracker
Tech layoffs: At least 95,000 workers at U.S.-based tech companies were laid off in mass job cuts in 2024 and the cuts have continued into 2025.
Accelerate threat modeling with generative AI
In this post, we explore how generative AI can revolutionize threat modeling practices by automating vulnerability identification, generating comprehensive attack scenarios, and pr...
This AI Model Never Stops Learning
Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves its...
Oh Leave it Out
Sometimes we want to repeatedly do things with all but one row of a data frame, where we systematically drop each row in turn and do the thing. For example, jacknife cross-validati...
Typesetting Sha and Bitcoin
In LaTeX, how to insert the Russian letter Sha (Ш, U+0248) and the currency symbol for Bitcoin (₿, U+20BF).
Shiny in Production 2025: Full Length Talks
We are pleased to announce the full line-up for this year’s Shiny in Production conference! The conference includes nine full-length talks (25 minutes each) and a lightning talk se...
Unpacking the bias of large language models
MIT researchers discovered the underlying cause of position bias, a phenomenon that causes large language models to overemphasize the beginning or end of a document or conversation...
Unpacking the bias of large language models
MIT researchers discovered the underlying cause of position bias, a phenomenon that causes large language models to overemphasize the beginning or end of a document or conversation...
LLMOps Virtual Summit, May 2025
Catch up on every session from LLMOps Virtual Summit, with sessions from the likes of Google, Unicef, Capital One, Linkedin and more...
Post-Bayesianism? Let’s try it!
A recent seminar introduced me to a new kind of statistical inference called post-Bayesianism. It has its own website, seminar series, Youtube videos and, most importantly, a cool ...
AI Aims to Bring Order to the Law
A team of Stanford University researchers has developed an LLM system to cut through bureaucratic red tape. The LLM—dubbed the System for Statutory Research…
Key Rival Lends ChatGPT a Hand
A new piece in The New York confirms that AI-generated writing -- along with similar AI creation tools -- is now the 'it' app.
Book Review: Essential Graph RAG
Coming from a background of Knowledge Graph (KG) backed Medical Search, I don't need to be convinced about the importance of manually curate...
Hebrew Gematria in R
Gematria is a Greek word for the practice of assigning numerical values to letters. In Hebrew it has been used to interpret Jewish texts, particularly the Bible, by attempting to d...
📦 {alone} v0.6 is now available
Alone: Australia season 3 has finished and has been added to the {alone} R package 👍 Season 3 was awesome. […] The post 📦 {alone} v0.6 is now available appeared first on Dan Oehm |...
R Shiny App for DOE Analysis
Apps Team: This app is develpoed by a team of five members as listed below: Muhammad Riaz Jerry Joel Abdul Muqtadir Ahmed Amgad Alkhiaty Mustafa Hamed App Intrduction: This app all...
Inroads to personalized AI trip planning
Researchers from MIT and the MIT-IBM Watson AI Lab developed a framework that combines a large language model and a satisfiability modulo theories (SMT) solver to create complete a...
Inroads to personalized AI trip planning
Researchers from MIT and the MIT-IBM Watson AI Lab developed a framework that combines a large language model and a satisfiability modulo theories (SMT) solver to create complete a...
Melding data, systems, and society
“Data, Systems, and Society: Harnessing AI for Societal Good,” a book by MIT Professor Munther Dahleh, details the creation of the MIT Institute for Data, Systems and Society, a un...
Melding data, systems, and society
“Data, Systems, and Society: Harnessing AI for Societal Good,” a book by MIT Professor Munther Dahleh, details the creation of the MIT Institute for Data, Systems and Society, a un...
How we really judge AI
A new study finds people are more likely to approve of the use of AI in situations where its abilities are perceived as superior to humans’ and where personalization isn’t necessar...
Golden powers revisited
Powers of the golden ratio are nearly integers. This post explains why. Also, these integers are the sum of two Fibonacci numbers.
Internet Power
A talk given at the Yale Jackson School of Global Affairs arguing that 21st century institutions need to understand how to accrue and wield their own power on the Internet.
Naively computing sine
Suppose you need to write software to compute the sine function. You were told in a calculus class that this is done using Taylor series—it's not, but that's another story—and so y...
Golden ratio base numbers
Positional number systems typically have a integer base, but irrational and even complex bases are possible. The golden ratio was the first irrational base.
A closer look inside AI Mode
AI Mode is our most powerful AI search, which we’re rolling out to everyone in the U.S. Here’s how we brought it to life (and to your fingertips).
Binomial number system
The binomial number system represents numbers as (a, b, c) where every number is the sum C(a, 1) + C(b, 2) + C(c, 3).
Iterated logarithm
The iterated logarithm comes up occasionally in the analysis of algorithms. It's also useful for giving a compact way to describe unimaginably large numbers.
False witnesses
On average, big composite numbers have a lot of false witnesses that suggest they're prime.
How to make AI work in QA
AI has radically changed Quality Assurance, breaking old inefficient ways of test automation, promising huge leaps in speed and the ability to test things we otherwise couldn't eas...
At Your Service
Aprimo has rolled-out an army of new AI agents specially designed to aid in every step of the content creation process.
Gardener’s ellipse
Gardener's method for drawing an ellipse and how it could be useful in computer graphics
An anomaly detection framework anyone can use
MIT PhD candidate Sarah Alnegheimish’s research interests reside at the intersection of machine learning and systems engineering. Her objective: to make machine learning systems mo...
Building networks of data science talent
Through partnerships with organizations like BREIT in Peru, the MIT Institute for Data, Systems, and Society is upskilling hundreds of learners around the world in data science and...
A Kernel of Truth
A haunting modern parable about truth, distortion, and destruction—how one kernel of truth can grow into a fire that burns the world.
Learning how to predict rare kinds of failures
MIT researchers are developing algorithms to predict failures when automation meets the real world in areas like air traffic scheduling. They combine sparse data about a rare failu...
The sweet taste of a new idea
MIT professor and behavioral economist Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.
Hey There, Good Lookin’
ChatGPT is now able to auto-format the research it does for you into beautifully presentable, downloadable, .PDFs.
AIAI Silicon Valley, 2025
Catch up on every session from the AIAI Silicon Valley with sessions across 3 co-located summit featuring the likes of Anthropic, Open AI, Meta and many more.
Evaluating RAG Pipelines
Evaluating a RAG pipeline means assessing its behavior across three dimensions: performance, cost, latency.
De Minimis Is Fading, and AI Is Your Lifeline
The flood of full customs entries has started, and AI is the only way for customs brokers to keep up. It handles the prep work, so your team can focus on what only brokers can do. ...
Gone Fishin’
RobotWritersAI.com is playing hooky. We'll be back May 5, 2025 with fresh news and analysis on the latest in AI-generated writing.
Why We Think
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...
What’s wrong with data-based decision-making?
Why data-based decision-making sometimes fails? Learn from real-world examples and discover practical steps to avoid common pitfalls in data interpretation, processing, and applica...
Introducing Gemini 2.5 Flash
Gemini 2.5 Flash, is now in preview, offering improved reasoning while prioritizing speed and cost efficiency for developers.
#465 – Robert Rodriguez: Sin City, Desperado, El Mariachi, Alita, and Filmmaking
Robert Rodriguez is a legendary filmmaker and creator of Sin City, El Mariachi, Desperado, Spy Kids, Machete, From Dusk Till Dawn, Alita: Battle Angel, The Faculty, and his newest ...
The enterprise path to agentic AI
Feeling the pressure to adopt agentic AI? Learn how to scale safely through the evolving stages and avoid costly mistakes along the way.
Taking a responsible path to AGI
We’re exploring the frontiers of AGI, prioritizing technical safety, proactive risk assessment, and collaboration with the AI community.
Moving To Substack
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 Illustr...
Building Resilient Data Infrastructure
We know it's possible to build new data infrastructure, but we urgently need to figure out how to do so sustainably and ethically. Join us at CNG Conference and at Fed Geo Day as w...
Staying Sane in an Insane World
Staying sane is a daily practice. Discover seven practical strategies to stay sane, reclaim your clarity, and strengthen your resilience amid uncertainty.
#459 – DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, and AI Megaclusters
Dylan Patel is the founder of SemiAnalysis, a research & analysis company specializing in semiconductors, GPUs, CPUs, and AI hardware. Nathan Lambert is a research scientist at the...
Some Lessons on Reviews and Rebuttals
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 displi...
Minecraft with object impermanence
I generally am uninterested in generative AI that's too close to the real thing. But every once in a while there's a modern AI thing that's so glitchy and broken that it's strangel...
Thoughts on Watermarking AI-Generated Content
Watermarking AI-generated content has the potential to address various problems that generative AI threatens to aggravate — misinformation, impersonation, copyright infringement, w...
AI Safety Index Released
The Future of Life Institute has released its first safety scorecard of leading AI companies, finding many are not addressing safety concerns while some have taken small initial st...
Trip Report - PyData Global 2024
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...
Reward Hacking in Reinforcement Learning
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 completin...
Foundations of diffusion networks
Diffusion networks As there’s a lot of recent developments around image generation and diffusion models in general, I took a deep dive in the fundamentals of...
Build Your Own OCR Engine for Wingdings
Discover how OCR technology transforms text recognition, from handwritten notes to custom fonts like Wingdings. Learn about cutting-edge models and create tailored OCR solutions fo...
Max Tegmark on AGI Manhattan Project
A new report for Congress recommends that the US start a "Manhattan Project" to build Artificial General Intelligence. To do so would be a suicide race.
Thinking About Research Ideas vs. Technology
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 contemplatin...
Introducing mall for R...and Python
We are proud to introduce the {mall} package. With {mall}, you can use a local LLM to run NLP operations across a data frame. (sentiment, summarization, translation, etc). {mall}...
Paris AI Safety Breakfast #3: Yoshua Bengio
The third of our 'AI Safety Breakfasts' event series, featuring Yoshua Bengio on the evolution of AI capabilities, loss-of-control scenarios, and proactive vs reactive defense.
Botober 2024
Back by popular demand, here are some AI-generated drawing prompts to use in this, the spooky month of October!
Longtime AI Weirdness readers may recognize some of these. That's b...
Panda vs. Eagle
FLI's Director of Policy on why the U.S. national interest is much better served by a cooperative than an adversarial strategy towards China.
Join the Most-Awaited Chatbot Conference
The conference features a range of events designed to enrich attendees’ understanding of the chatbot industry: With upcoming events already lined up, now is the time to get involve...
Demystifying AI in the Water Industry
Water industry professionals explored the intersection of artificial intelligence (AI) and machine learning (ML) during a pre-conference workshop in Ocean City, Maryland yesterday,...
Can AI agents learn to be good?
AI agents are different from AI assistants because they can initiate actions independently. Here we discuss the safety concerns involved with AI agents and what we are doing to mit...
Understanding the cp Command in Bash
The cp command in Bash is used to copy files and directories from one location to another.. “Understanding the cp Command in Bash” is published by Javascript Jeep🚙💨 in Becoming Hum...
Save up to $400 on Your Conference Tickets!
Whether you’re a returning attendee or new to our community, this is the perfect chance to experience the future of AI and chatbot technology at a discounted rate. Simply go to the...
Experiments with Prompt Compression
I recently came across Prompt Compression (in the context of Prompt Engineering on Large Language Models) on this short course on Prompt Com...
Extrinsic Hallucinations in LLMs
Hallucination in large language models usually refers to the model generating unfaithful, fabricated, inconsistent, or nonsensical content. As a term, hallucination has been somewh...
Book Report: Pandas Workout
Unlike many Data Scientists, I didn't automatically reach for Pandas when I needed to analyze data. I came upon this discipline (Data Scien...
An exercise in frustration
There's an anonymous facebook posting that's been making the rounds, in which a studio art director tried to hire AI prompters to make art, only to discover that they were complete...
Introducing Keras 3 for R
We are thrilled to introduce {keras3}, the next version of the Keras R package. {keras3} is a ground-up rebuild of {keras}, maintaining the beloved features of the original while r...
Finetuning RAGAS Metrics using DSPy
Last month, I decided to sign-up for the Google AI Hackathon , where Google provided access to their Gemini Large Language Model (LLM) and ...
FAQ for our Monte Carlo Conformal Prediction
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 annot...
KGC/HCLS 2024 Trip Report
I was at KGC (Knowledge Graph Conference) 2024 , which is happening May 6-10 at Cornell Tech . I was presenting (virtually) at their Health ...
Hidden 3D Pictures
Do you know those autostereograms with the hidden 3D pictures? Images like the Magic Eye pictures from the 1990s that look like noisy repeating patterns until you defocus your eyes...
Hidden sheep
AI Weirdness: the strange side of machine learning
On NeurIPS’ High School Paper Track
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...
Diffusion Models for Video Generation
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. T...
Chat with AI in RStudio
Interact with Github Copilot and OpenAI's GPT (ChatGPT) models directly in RStudio. The `chattr` Shiny add-in makes it easy for you to interact with these and other Large Language...
Shaped like information
Hey look, it's a guide to basic shapes!
Not only does it have the basic shapes like circle, tringle, hectanbie, and sqale, it also has some of the more advanced shapes like renstq...
Bonus: More shape shaped shapes
The image I shared in my main post isn't one of the more incorrect examples of DALL-E3 generated guides - it's actually one of the more correct ones.
Here's another generated imag...
Learn your farm animals with AI!
Hey kids! What sound does a woolly horse-sheep make?
The image above is what you get when you ask dalle-3 (via chatgpt) for some basic educational material: "Please generate an il...
DALL-E3 generates candy hearts
I've experimented a couple of times with generating candy heart messages using various kinds of machine learning algorithms. Originally, short messages were just about all the orig...
Q&A with Mala Kumar, Our Newest Board Member
We are pleased to welcome Mala Kumar to our Board of Directors. In this Q&A profile, we talk with Mala about her career journey, joining our Board, and the intersections between te...
Thinking about High-Quality Human Data
[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...
Chocolates, labeled
So much of current AI-generated stuff is derivative sludge that I'm enjoying the pockets of weirdness where I find them. One of my favorite things right now: DALL-E3's attempts to ...
Unicorns, Show Ponies, and Gazelles
A few four-legged animal metaphors that explain how we’ve been building global data infrastructure to date and how we might do better in the future.
PyData Global 2023: Trip Report
I had the opportunity to present at PyData Global this year. It is a virtual conference that ran over 3 days in multiple tracks from Decemb...
Adversarial Attacks on LLMs
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 effo...
Hugging Face Integrations
Hugging Face rapidly became a very popular platform to build, share and collaborate on deep learning applications. We have worked on integrating the torch for R ecosystem with Hug...
STAC API 1.0.0 Released
The STAC API specification reached its 1.0.0 version. With this release, the spec is fully aligned with the OGC API - Features Version 1.0 standard.
LLM Powered Autonomous Agents
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 inspi...
Understanding LoRA with a minimal example
LoRA (Low Rank Adaptation) is a new technique for fine-tuning deep learning models that works by reducing the number of trainable parameters and enables efficient task switching. I...
GPT-2 from scratch with torch
Implementing a language model from scratch is, arguably, the best way to develop an accurate idea of how its engine works. Here, we use torch to code GPT-2, the immediate successor...
My Faculty Application Experience
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 ...
safetensors 0.1.0
Announcing safetensors, a new R package allowing for reading and writing files in the safetensors format.
We may finally crack Maths. But should we?
Automating mathematical theorem proving has been a long standing goal of artificial intelligence and indeed computer science. It's one of the areas I became very interested in rece...
torch 0.11.0
torch v0.11.0 is now on CRAN. This release features much-enhanced support for executing JIT operations. We also amended loading of model parameters, and added a few quality-of-life...
Say Hello to Radiant Earth
Announcing some changes to the Radiant Earth brand and our plans to serve our community moving forward.
Generative AI and AI Product Moats
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 th...
Group-equivariant neural networks with escnn
Escnn, built on PyTorch, is a library that, in the spirit of Geometric Deep Learning, provides a high-level interface to designing and training group-equivariant neural networks. T...
luz 0.4.0
luz v0.4.0 is now on CRAN. This release adds support for training models on ARM Mac GPUs, reduces the overhead of using luz, and makes it easier to checkpoint and resume failed run...
torch 0.10.0
torch v0.10.0 is now on CRAN. This version upgraded the underlying LibTorch to 1.13.1, and added support for Automatic Mixed Precision. As an experimental feature, we now also sup...
De-noising Diffusion with torch
Currently, in generative deep learning, no other approach seems to outperform the family of diffusion models. Would you like to try for yourself? If so, our torch implementation of...
Prompt Engineering
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 weig...
The Transformer Family Version 2.0
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 ...
AO, NAO, ENSO: A wavelet analysis example
El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO) are atmospheric phenomena of global impact that strongly affect people's lives. E...
Large Transformer Model Inference Optimization
[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 ...
Books Read in 2022
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...
Wavelet Transform - with torch
torch does not have built-in functionality to do wavelet analysis. But we can efficiently implement what we need, making use of the Fast Fourier Transform (FFT). This post is a ver...
The Illustrated Stable Diffusion
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 ...
Some Math behind Neural Tangent Kernel
Neural networks are well known to be over-parameterized and can often easily fit data with near-zero training loss with decent generalization performance on test dataset. Although ...
A Plea to End Harassment
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 ...
Generalized Visual Language Models
Processing images to generate text, such as image captioning and visual question-answering, has been studied for years. Traditionally such systems rely on an object detection netwo...
The Illustrated Retrieval Transformer
Discussion: Discussion Thread for comments, corrections, or any feedback.
Translations: Korean, Russian
Summary: The latest batch of language models can be much smaller yet ac...
Books Read in 2021
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 ...
What are Diffusion Models?
[Updated on 2021-09-19: Highly recommend this blog post on score-based generative modeling by Yang Song (author of several key papers in the references)].
[Updated on 2022-08-27: ...
Contrastive Representation Learning
The goal of contrastive representation learning is to learn such an embedding space in which similar sample pairs stay close to each other while dissimilar ones are far apart. Con...
Explainable AI Cheat Sheet
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 t...
On Information Theoretic Bounds for SGD
Few days ago we had a talk by Gergely Neu, who presented his recent work:
* Gergely Neu Information-Theoretic Generalization Bounds for Stochastic
Gradient Descent [https://ar...
Weight Banding
Weights in the final layer of common visual models appear as horizontal bands. We investigate how and why.
Branch Specialization
When a neural network layer is divided into multiple branches, neurons self-organize into coherent groupings.
Reducing Toxicity in Language Models
Large pretrained language models are trained over a sizable collection of online data. They unavoidably acquire certain toxic behavior and biases from the Internet. Pretrained lan...
Visualizing Weights
We present techniques for visualizing, contextualizing, and understanding neural network weights.
Curve Circuits
Reverse engineering the curve detection algorithm from InceptionV1 and reimplementing it from scratch.
Controllable Neural Text Generation
[Updated on 2021-02-01: Updated to version 2.0 with several work added and many typos fixed.]
[Updated on 2021-05-26: Add P-tuning and Prompt Tuning in the “prompt design” sectio...
Newsletter #087
Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems.
Newsletter #086
Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems.
Some Intuition on the Neural Tangent Kernel
Neural tangent kernels are a useful tool for understanding neural network
training and implicit regularization in gradient descent. But it's not the
easiest concept to wrap your he...
Understanding RL Vision
With diverse environments, we can analyze, diagnose and edit deep reinforcement learning models using attribution.
Newsletter #085
Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems.
Notes on Causally Correct Partial Models
I recently encountered this cool paper in a reading group presentation:
* Rezende et al (2020) Rezende Causally Correct Partial Models for
Reinforcement Learning [https://arxi...
Newsletter #084
Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems.
Newsletter #083
Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems.
Newsletter #082
Weekly newsletter dedicated to sharing resources for building and operating production machine learning systems.
So long, and thanks for all the fish
All good things must come to an end, including this podcast. This is the last episode we plan to release, and it doesn’t cover data science—it’s mostly reminiscing, thanking our wo...
A Data Science Take on Open Policing Data
A few weeks ago, we put out a call for data scientists interested in issues of race and racism, or people studying how those topics can be studied with data science methods, should...
The Data Science Open Source Ecosystem
Open source software is ubiquitous throughout data science, and enables the work of nearly every data scientist in some way or another. Open source projects, however, are dispropor...
Rock the ROC Curve
This is a re-release of an episode that first ran on January 29, 2017. This week: everybody's favorite WWII-era classifier metric! But it's not just for winning wars, it's...
Curve Detectors
Part one of a three part deep dive into the curve neuron family.
Criminology and data science
This episode features Zach Drake, a working data scientist and PhD candidate in the Criminology, Law and Society program at George Mason University. Zach specializes in bringing da...
Convolutional neural networks
This is a re-release of an episode that originally aired on April 1, 2018 If you've done image recognition or computer vision tasks with a neural network, you've probably used a...
Stein's Paradox
This is a re-release of an episode that was originally released on February 26, 2017. When you're estimating something about some object that's a member of a larger group of simi...
Causal Trees
What do you get when you combine the causal inference needs of econometrics with the data-driven methodology of machine learning? Usually these two don’t go well together (deriving...
The Grammar of Graphics
You may not realize it consciously, but beautiful visualizations have rules. The rules are often implict and manifest themselves as expectations about how the data is summarized, p...
Gaussian Processes
It’s pretty common to fit a function to a dataset when you’re a data scientist. But in many cases, it’s not clear what kind of function might be most appropriate—linear? quadratic?...
Putting machine learning into a database
Most data scientists bounce back and forth regularly between doing analysis in databases using SQL and building and deploying machine learning pipelines in R or python. But if we t...
The work-from-home episode
Many of us have the privilege of working from home right now, in an effort to keep ourselves and our family safe and slow the transmission of covid-19. But working from home is an ...
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 ca...
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 AlphaG...
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 longer DL tradition a...
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 happen to have this arxi...
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 the nu...
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 remember a research-lab-like room ful...
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 backpropagation on the ...
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 Mehrotr...