Recent content on Hugo Penedones
Some inductive biases encode beliefs about the data: bets that certain hand-crafted features matter, that certain regularities hold. These can be wrong. But some encode theorems about the target function. These cannot be wrong. Rotational equivariance in molecular simulation is one of them. This post is about why encoding a provably correct theorem into a neural network is harder than it sounds.…
I just got Llama 3.2 1B running at 60 tokens/sec on my nucbox mini PC’s NPU (Neural Processing Unit) (AMD Ryzen AI 9 HX 370) under Ubuntu Linux — something that, as far as I can tell, hasn’t been publicly demonstrated before. The problem AMD shipped the XDNA2 NPU in Ryzen AI processors (Strix Point, Strix Halo, Kraken Point) with up to 50 TOPS of AI compute. On Windows, tools like…
Everyone’s talking about LLMs, but it is already pretty clear what the next big wave will be: AI for the physical world. AI that understands intuitive physics, not only the mechanics of large rigid bodies, which is fundamental for Robotics and autonomous driving, but also AI that understands fluid dynamics, thermodynamics, electromagnetism, plasmas, and even the quantum physics that governs…
Arriving at the Portuguese encounter “Ciência 2025”, for a roundtable discussion on AI for Science and how Inductiva.AI is contributing with a platform that makes numerical simulation and physics datasets generation really easy and affordable. At Nova School of Business and Economics . Here is a 1 min flash interview I gave at the event, sharing my thoughts on the role of AI and…
Machine Learning Summer School coming up! Inductiva.AI , in collaboration with the Universidade do Porto and the support of the AptWind doctoral network, is hosting a 5-day programme where we will dive into the state-of-the-art Machine Learning techniques and their impact across different scientific fields. The primary focus will be on Computational Fluid Dynamics (CFD), but it will also explore…
🇵🇹 DeepMinders Joao Carreira and Zita Marinho, with ex-DeepMinders Wang Ling and Hugo Penedones at AIHub / Unicorn Factory Lisboa in Lisbon.
I was invited as the keynote speaker at the Dia da Investigação (Research Day) organised by the Faculdade de Medicina da Universidade de Lisboa , held at the Auditório Professor David Ferreira (A52), Edifício Egas Moniz, at 13h. The talk was titled “AI meets Scientific Computing: Transforming Biology and Medicine” and covered the intersection of artificial intelligence, scientific…
Hoje as 17:30 na Faculdade de Ciências da Universidade do Porto (FCUP), uma palestra sobre as contribuições da área de Machine Learning nos prémios Nobel de 2024. Apareçam! :) (Today at 17:30 at the Faculty of Sciences of the University of Porto, a talk about the contributions of Machine Learning to the 2024 Nobel Prizes. Come join!)
“If there were many databases as good as the PDB, I would say, yes, this [prize] probably is just the first of many, but it is kind of a unique database in biology” - David Baker (Nobel prize in Chemistry). Agreed. That’s why in most other problems in science and engineering, we will need to generate high quality synthetic data using numerical simulators where the rules of…
Congrats Demis Hassabis and John Jumper! :) 😃 Nobel Prize in Chemistry 2024 winners David Baker, Demis Hassabis and John Jumper. Illustration: Niklas Elmehed / Nobel Prize Outreach The Royal Swedish Academy of Sciences awarded the 2024 Nobel Prize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M.…
Steve Crossan’s article Engineering for Science asks: “Why did AlphaFold happen at DeepMind rather than (for example) the Broad Institute ? It wasn’t data. Everyone had access to exactly the same data. It wasn’t compute. The compute budget for AlphaFold1 was well within the budget of an academic project. The real reason was that we treated it as an engineering problem as much as a…
That feeling when Schmidhuber cites your (not well known) RL paper! 😝 Our 2019 NeurIPS paper “Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates” didn’t catch much attention, but it actually addresses a very fundamental problem in Deep Reinforcement Learning: how can you trust Temporal Difference updates, when you are not in a…
Forecasted the future 2 days ahead, not bad! Without inside info, despite having worked at DeepMind in the past. :) Two days ago I gave a talk at the Math department of Faculdade de Ciências e Tecnologia da Universidade NOVA de Lisboa, where in the last slide I made a prediction: In 2024 we would see a breakthrough in LLMs for Math and it would probably involve: merging search with LLMs, much like…
Prediction: training data from molecular dynamics simulations will be key. This is a reaction to the VentureBeat article “AI-driven drug discovery is poised to boom in 2024” . Background story: I was part of the initial AlphaFold team at DeepMind, back in early 2016. We knew that ideally we would train a deep neural network end-to-end on a large dataset of mappings (amino-acid sequence…
I tend to agree with Blaise Aguera y Arcas and Peter Norvig, who argue in their Noema Magazine article “Artificial General Intelligence Is Already Here” that today’s most advanced AI models should already be recognised as the first true examples of AGI. Their key insight: AI systems used to perform better than humans on some specific narrow tasks (e.g. chess). But they…
Congrats to my ex-colleagues from the AlphaFold project. It all started with a small internal Hackathon, and several months of hard work to just get near the state-of-the-art… Impressive how successful it has become! 🧬 🚀 “Never underestimate the power of a small group of committed people to change the world. In fact, it is the only thing that ever has.” - Margaret Mead
Talvez não seja óbvio, mas ser capaz de prever a próxima palavra, pode ir muito além de identificar correlações estatísticas superficiais: imaginem um romance policial em que após centenas de páginas com detalhes intrincados sobre todas as personagens, o detetive diz “o culpado é …”. O ChatGPT, criado pela OpenAI, é baseado numa grande rede neuronal artificial treinada…
Computation is at the heart of what we do. We write computer programs for running simulations of physical systems, training Machine Learning models, automating tasks or simply testing new ideas. In this blog post we share the programming principles that we try to follow to make fast progress on our goals, while maintaining high standards on the quality of our code. Principles: Tracer Bullets…
Our Nature paper describing AlphaFold is finally out. :) You can read it at: https://rdcu.be/b0mtx #nature #proteins #structureprediction #deepmind #alphafold #deeplearning AlphaFold: Using AI for scientific discovery
Our paper was accepted at NeurIPS 2019. Yay! :) We use ensembles of neural networks to get (per-state) uncertainty estimates and dynamically switch between Temporal-Difference and Monte Carlo estimates. Now you can do more accurate on-policy evaluation from logs. #reinforcementlearning #neurips Work done in collaboration with Carlos Riquelme, Damien Vincent, Hartmut Maennel, Timothy Mann, Andre…
I recently made public more of my programming projects from the past. My github profile now includes: luacnn - Convolutional Neural Network for hand digit recognition using Torch7 and Lua. metrics - a Torch7 package to compute some metrics, such as area under ROC. lakeml - some Machine Learning algorithms implemented in C++, e.g. AdaBoost, K-means, EM for (diagonal) Gaussian Mixture Models.…
It turns out that there are several very high profile Portuguese researchers in the field of Machine Learning, even though they all seem to live and work abroad. Here are, to the best of my knowledge, the most cited ones, including their current affiliation and the total citations according to Google Scholar (as of Sept. 2015): Fernando Pereira (Google, USA) citations: 32496 Pedro Domingos…
I have recently started working as a Research Engineer at Google DeepMind , in London. It’s very exciting to be surrounded by some of the best researchers in Machine Learning in the world, with such an ambitious mission statement and the right conditions to pursue it. I will be working in Deep Learning and Reinforcement Learning real world applications with positive impact in society. Go…
Yesterday I attended a talk organized by the London Machine Learning meetup group, where Yoshua Bengio was the invited speaker . Not surprisingly, there were about 200 people attending. Yoshua reinforced the idea that a lot of the success of learning algorithms for AI tasks comes from incorporating meaningful priors. These should be general enough to hold true in a wide range of applications, but…
I recently started playing with the torch library again. Torch7 is now a growing set of packages, managed by luarocks. I really like this approach because it forces torch contributors to make their code more modular and re-usable. So far, I have done a few very simple contributions to the torch ecosystem: Extended the matio package, which reads MAT files, to support structs, cell arrays and…
Ten years after my Summer internship at Microsoft as an undergraduate student, I had the opportunity to be back to the Redmond campus. This time the goal was to attend Microsoft Research’s techfest and participate in the Practice of Machine Learning conference. I can’t share much about what I saw there, but I must say I was impressed by the amount of great talks and cool demos. MSR is…
Nassim Nicholas Taleb (author, scholar, statistician, trader, philosopher, risk manager) Books: The Black Swan ), Antifragile: Things That Gain from Disorder Bret Victor (engineer, designer, inventor, dreamer): Talks: Inventing on Principle , The Future of Programming Essay: Learnable Programming Salvatore Sanfilippo (programmer, I mean rock-star programmer): Software: redis ( source code )
Soon I will be in Dublin, Ireland, attending one of the best conferences in Information Retrieval. Looking forward to hearing about the latest research and probably meeting some old friends. http://www.sigir2013.ie/
A couple of years ago, I was doing research involving Convolutional Neural Networks for object classification tasks (see here ). At that point, deep learning was an (re)emergent field, but it hadn’t achieved mainstream yet. Today, several factors are contributing to the increase of visibility: Announcements of great results in Kaggle competitions and commercial applications, such as…
Yesterday I attended to the Machine Learning Workshop at Idiap EPFL. It was a good opportunity to see old friends and colleagues, and listen about their latest research. In general, the quality of the talks was quite good, ranging from very theoretical machine learning (sparse coding, optimization, etc.) to commercial applications of computer vision. Somewhere in the middle of that spectrum, I…
Lately, I have been working with Deformable Models and I am surprised by how well they can work. Your browser does not support the video tag. In the video above I am using an Inverse Compositional Active Appearance Model, which was trained with images of myself. It’s specially tuned for my face, but I still find it quite impressive how well it can track my face in realtime! On the other…
I recently read an article from Y. Bengio and Y. LeCun named “Scaling Learning Algorithms to AI” . You can also find it as a book chapter in “Large-Scale Kernel Machines"L. Bottou, O. Chapelle, D. DeCoste, J. Weston (eds) MIT Press, 2007. In some aspects it is an “opinion paper” where the authors advocate for deep learning architectures and their vision of the Machine…
I recently added to my webpage a tutorial on how to use torch5 library to train a convolutional neural network for the task of handwritten digit recognition. Update (February 20, 2026): The code for this tutorial is now available at https://github.com/hpenedones/luacnn and uses torch7. This tutorial was reviewed by Claude Code as of 2026.
The event took place yesterday at the New York Academy of Sciences, a building right next to the World Trade Center. The views from the 40th floor were breathtaking: The names of the participants in the room was no less impressive, (by no special order): Corinna Cortes (Google), Rob Schapire and David Blei (Princeton University), John Langford and Alex Smola (Yahoo), Yann LeCun (NYU), Sanjoy…
In the last few months (in which I haven’t posted in this blog) there were a few interesting web platforms related to Machine Learning poping-up, most notably: MLcomp.org - you can upload your datasets and/or your algorithms, and experiments will run automatically. Then you can see statistics related to classifier performances and computation times. It is intended to help researchers and…
Just a short link to an article of the New York Times about AI . In 1978, Dr. McCarthy wrote, “human-level A.I. might require 1.7 Einsteins, 2 Maxwells, 5 Faradays and .3 Manhattan Projects.” I think we probably have the genius scientists around, but not so sure about the 0.3 Manhattan Projects! Update: You might also want to read latest Shane Legg’s predictions about human level artificial…
Today I assisted to the first edition of TEDx Geneva. This was a locally-organized event following the same spirit of the original TED talks: “ideas worth spreading”. I think the program was really good, because in this region there are some many incredible organizations. He could listen to people from CERN, EPFL, the United Nations, the Red Cross and some independent Swiss adventurers…
I’m doing research in the fields of Machine Learning and Computer Vision, so each time we have an idea for a new algorithm, I have to write code, run experiments and compare results. I have realized that the experimental part is really the bottleneck, we have more ideas than we can test. For this reason, it’s critical to chose a good set of tools you can work with. This is a list of my…
My supervisor is leading a new European project called MASH, which stands for “Massive Sets of Heuristics”. There are open positions here in Switzerland, as well as in France, Germany and Czech Republic. The goal is to solve complex vision and goal planning problems in a collaborative way. It will be tested in 3D video games and also in a real robotic arm. Collaborators will submit…
I just quickly tried the new Gmail Labs feature “Got the wrong Bob”? and it actually works quite nicely! I put some email addresses of family members, followed by the address of an old professor, who has the same first name of one of my cousins, and… Gmail found it! :) It suggested right way to change to the correct person, based on context!The other new feature, called…
My good friend Miguel called my attention to a TED talk that you might also find interesting: Ken Robinson: Do schools kill creativity? Ken Robinson argues that “schools kill creativity”, because kids are not given the chance to discover their interests and talents. Since very soon, students get a negative reward for making mistakes, which makes them too risk averse. He goes further,…
Thoughts on Life This essay will be in beta version, longer than any Google product. Some assumptions I am an individual. I care about my life and happiness There are other entities around. To different degrees, animals, persons, robots (future) also have feelings and personal ambitions. I interact with them. They will influence my level of well-being. Happiness The really wise people realized…
In the past it happened that I didn’t publish some potentially interesting thoughts in this blog, just because they didn’t exactly fit the “about intelligence” topic. I’m fed up of this self-imposed censorship. In the future the scope will be broader.
I spend lots of time wondering about the best ways to be both more productive and happy. Curiously, I’m coming to the conclusion that this is exactly what I should not do. Being productive, like being happy, requires living the present moment, not thinking about it. If you want to complete a task, the best strategy is just doing it! You might start by setting up a plan, a sequence of smaller…
John Langford wrote a very interesting post on the failures of Artificial Intelligence research and why Machine Learning has been a safer bet. Read it here .
Google already has a tradition of April fool’s jokes : this year they are introducing an Artificial Intelligence brain! They describe the development process of their so called CADIE : Cognitive Autoheuristic Distributed-Intelligence Entity like this: “For several years now a small research group has been working on some challenging problems in the areas of neural networking, natural…
Today I tried out a great site to generate tag clouds, it is called wordle.net. I rendered some images just by copy-pasting the text from wikipedia about machine learning . The results were pretty cool and I guess one could print awesome t-shirts with them. What do you say? This one became officially my computer wallpaper:
The 2008 ACM Paris Kanellakis Theory and Practice Award was awarded to Corinna Cortes and Vladimir Vapnik “for the development of Support Vector Machines, a highly effective algorithm for classification and related machine learning problems”. It’s not the first time this award is given to Machine Learning people. In 2004 it was awarded to Yoav Freund and Robert Schapire…
If I had to explain what computer vision is all about, in just one snapshot, I would show you this: Computer Graphics algorithms go from the parameter space to the image space (rendering), computer vision algorithms do the opposite (inverse-rendering). Because of this, computer vision is basically a (very hard) problem of statistical inference. The common approach nowadays is to build a classifier…
This is an extremely geek picture! :) Let’s try to explain it: First of all, as many of you know, the gentleman in the picture is Prof. Vladimir Vapnik . He is famous for his fundamental contributions to the field of Statistical Learning Theory, such as the Empirical Risk Minimization (ERM) principle, VC-dimension and Support Vector Machines. Then we notice the sentence in the board: it…