Generative AI Summit LA, 2025
Catch up on every session from Generative AI Summit LA. with sessions from the likes of OpenAI, Waymo, DeepSeek and more.
What does the future hold for generative AI?
Hundreds of scientists, business leaders, faculty, and students shared the latest research and discussed the potential future course of generative AI advancements during the inaugu...
What does the future hold for generative AI?
Hundreds of scientists, business leaders, faculty, and students shared the latest research and discussed the potential future course of generative AI advancements during the inaugu...
1420 MHz
Pioneer, Voyager, and the Wow! signal. Communicating with extraterrestrials at 1420 MHz.
Intercropping with robots
Intercropping is an agricultural practice that can enhance soil quality, total yield and biodiversity. Modern advances in artificial intelligence and robotics are helping this trad...
Netskope Moves Higher In Nasdaq Debut
Shares of cybersecurity provider Netskope were up 28% in early first-day trading Thursday, indicating fairly robust investor enthusiasm for a new entrant in the space.
Day of the week centuries from now
Yesterday I wrote a post outlining mental math posts I'd written over the years. I don't write about mental math that often, but I've been writing for a long time, and so the posts...
AI Psychosis Is Rarely Psychosis at All
A wave of AI users presenting in states of psychological distress gave birth to an unofficial diagnostic label. Experts say it’s neither accurate nor needed, but concede that it’s ...
Mental math posts
Outline of mental math posts. Some basic things like divisibility rules, but also more advanced topics like computing logs or gamma functions.
Investing in America 2025
Google’s deep investments in American technical infrastructure, R&D and the workforce will help the U.S. continue to lead the world in AI.
Phoenician colonization
Figura de Astarté – Museo Arqueológico de Sevilla, Public domain, via Wikimedia Commons I was reading Phoenician colonization from its origin to the 7th century BC (Manzano-Aguglia...
Just Released: Warp 1.9
A Python framework for accelerated simulation, data generation and spatial computing. - Release v1.9.0 · NVIDIA/warp
Monero’s seed phrase words
How Monero's list of words for seed phrases differs from the list used in Bitcoin and other cryptocurrencies
Predicting the regulatory genome
Deep learning models have made impressive strides in decoding the regulatory genome, but key challenges remain unsolved. In this Comment, the authors overview the latest deep learn...
Regulatory genome annotation
Large-scale annotation efforts over the past two decades have identified regulatory regions and networks through functional genomics and evolutionary analyses. The challenge now wi...
How We Came To Know Earth
Climate science is the most significant scientific collaboration in history. This series from Quanta Magazine guides you through basic climate science — from quantum effects to anc...
The Ends of the Earth
Building an accurate model of Earth’s climate requires a lot of data. Photography reveals the extreme efforts scientists have undertaken to measure gases, glaciers, clouds and more...
The Climate Change Paradox
Earth’s climate is chaotic and volatile. Climate change is simple and predictable. How can both be true?
The Quantum Mechanics of Greenhouse Gases
Earth’s radiation can send some molecules spinning or vibrating, which is what makes them greenhouse gases. This infographic explains how relatively few heat-trapping molecules can...
Stirling numbers in SAS
In probability and statistics, special numbers are used to compute probabilities by counting the number of ways certain events can occur.
Introducing admiralneuro!
Introduction Neuroscience Extension Package for ADaM in R Asset Library • admiralneuro {admiralneuro} joins the family as the latest admiral {admiral} extension package. The packag...
Exploring {ggplot2}’s Geoms and Stats
Code library(tidyverse) library(patchwork) library(gt) # sysfonts::font_add_google(name = "fira code") # showtext::showtext_auto() knitr::opts_chunk$set(collapse = TRUE, comment = ...
wbstats is back on CRAN
If this post is useful to you I kindly ask a minimal donation on Buy Me a Coffee. It shall be used to continue my Open Source efforts. The full explanation is here: A Personal Mess...
I Vibe Coded an R Package
Learning Japanese means memorizing thousands of characters, some of which look nearly identical. I wanted a way to visualize which kanji are similar to each other, and for once the...
Random samples from a polygon
Algorithm for random sampling from a polygon. The polygon does not have to be regular, though things are easier if the polygon is convex.
A mental random number generator
A random number generator you can run in your head. It's adequate for some tasks, better than trying to make up a random sequence.
New symbols in Unicode 17
Some of the symbols added to Unicode in version 17: The new Saudi riyal symbol, equal sign with infinity on top, symbols for asteriods
Mandelbrot and Fat Tails
The Mandelbrot set is the set of complex numbers c such that iterations of f(z) = z² + c remain bounded. But how do you know an iteration will remain bounded? You know when it beco...
Bech32 encoding
What is Bech32 encoding? Where does the name come from? What are its advantages?
Hollywood Killer
A new piece in The New York confirms that AI-generated writing -- along with similar AI creation tools -- is now the 'it' app.
The Definitive Guide to Data Parsing
A complete guide to modern data parsing. Covers the latest AI technologies (VLMs, RAG), types of parsing, and a blueprint for implementation in 2025.
AI and machine learning for engineering design
In MIT course 2.155/156 (AI and Machine Learning for Engineering Design), students use tools and techniques from artificial intelligence and machine learning for mechanical enginee...
AI and machine learning for engineering design
In MIT course 2.155/156 (AI and Machine Learning for Engineering Design), students use tools and techniques from artificial intelligence and machine learning for mechanical enginee...
A greener way to 3D print stronger stuff
The “SustainaPrint” software and hardware toolkit from MIT CSAIL strengthens only the weakest parts of eco-friendly objects. It analyzes a model to predict stress areas, supporting...
A greener way to 3D print stronger stuff
The “SustainaPrint” software and hardware toolkit from MIT CSAIL strengthens only the weakest parts of eco-friendly objects. It analyzes a model to predict stress areas, supporting...
Bringing in ChatGPT for Email
A new piece in The New York confirms that AI-generated writing -- along with similar AI creation tools -- is now the 'it' app.
mall 0.2.0
The mall 0.2.0 update for R and Python introduces support for external LLM providers like OpenAI and Gemini. This version also features parallel processing for R users, the abili...
AIOps Virtual Summit, July 2025
Catch up on every session from AIOps Virtual Summit, with sessions from the likes of NBCUniversal, United States Federal Government, Amazon and more...
Ranking GPT-5 against LLMs
AI benchmarks have created a false impression about how to evaluate AI models: test AI for complex questions that several humans can’t answer. Even if AI does well, they conclude t...
A tech debt fighting champion for developers
Technical debt occurs when best practices are ignored as IT solutions are built. In a survey of 500+ IT pros conducted by CompTIA, approximately three-quarters said technical debt ...
ChatGPT will apologize for anything
ChatGPT will apologize for anything - even advice it definitely didn't give, and stuff it definitely didn't do. It very much regrets its recommendation that we hire a giraffe as CE...
Self-adaptive reasoning for science
Microsoft is pioneering a vision for a self-adapting AI system that can adapt to the dynamic nature of scientific discovery, promoting deeper, more refined reasoning in complex sci...
Genie 3: A new frontier for world models
Today we are announcing Genie 3, a general purpose world model that can generate an unprecedented diversity of interactive environments. Given a text prompt, Genie 3 can generate d...
Try Deep Think in the Gemini app
Deep Think utilizes extended, parallel thinking and novel reinforcement learning techniques for significantly improved problem-solving.
How graph thinking empowers agentic AI
Agentic AI systems are designed to adapt to new situations without requiring constant human intervention. These systems can provide tremendous benefits within many industries such ...
FinOps and the need for straight talk
FinOps is about bringing together leaders in business, technology, finance, and engineering to gain a clear understanding of, and better control over, cloud spend (and associated e...
A new way to edit or generate images
MIT and Meta researchers discover that special kinds of neural networks called encoders or “tokenizers” can do much more than previously realized, leading to a new way to edit or g...
Why good data doesn’t guarantee good decisions
It’s easy to assume that more data—or cleaner dashboards—will automatically lead to better decisions. But after working in product analytics at MAANG and top fintech companies, I’v...
Elon Musk’s New AI: Number One
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...
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.
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.
Evaluating RAG Pipelines
Evaluating a RAG pipeline means assessing its behavior across three dimensions: performance, cost, latency.
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...
#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 ...
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.
Injecting Domain Expertise Into Your AI System
Domain experts can help you connect the dots between the technicalities of an AI system and its real-life usage and value. Thus, they should be key stakeholders and co-creators of ...
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...
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...
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}...
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...
Join the Most-Awaited Chatbot Conference
Join the Most-Awaited Chatbot Conference 🚀 What to Expect The conference features a range of events designed to enrich attendees’ understanding of the chatbot industry: Expert Keyn...
Demystifying AI in the Water Industry
Demystifying AI in the Water Industry Water industry professionals explored the intersection of artificial intelligence (AI) and machine learning (ML) during a pre-conference works...
Understanding the cp Command in Bash
Understanding the cp Command in Bash The cp command in Bash is used to copy files and directories from one location to another. Copy Command Syntax and Explanation The basic syntax...
Save up to $400 on Your Conference Tickets!
Save up to $400 on Your Conference Tickets! For the next two weeks, you can save up to $400 on Tickets to the Chatbot Conference 2024. Whether you’re a returning attendee or new to...
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...
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.
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...
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...
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...
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
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 som...
AlphaGo, in context
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 abo...
ICML accepted papers institution stats
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, al...
A Peek at Trends in Machine Learning
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 thou...
ICLR 2017 vs arxiv-sanity
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, wor...
Virtual Reality: still not quite there, again.
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 ha...
Yes you should understand backprop
Yes you should understand backprop When we offered CS231n (Deep Learning class) at Stanford, we intentionally designed the programming assignments to include explicit calculations ...
CS183c Assignment #3
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 Next...