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The most popular blog posts about ai & machine learning on Hacker News. 105 posts.
Nature has now released that AlphaFold 2 paper , after eight long months of waiting. The main text reports more or less what we have known for nearly a year, with some added tidbits, although it is accompanied by a painstaking description of the architecture in the supplementary information . Perhaps more importantly…
SUMMARY Mountain Dew's Super Bowl LV ad challenged viewers to count the exact number of bottles in the commercial for a $1 million prize, and this post builds an object detection model to assist with that count. The 30-second video was sampled at three frames per second in Roboflow to produce 92 annotated training…
Disclaimer: this post is an opinion piece based on the experience and opinions derived from attending the CASP14 conference as a doctoral student researching protein modelling. When provided, quotes have been extracted from my notes of the event, and while I hope to have captured them as accurately as possible, I…
By training Atlas to maneuver its way through complex parkour courses, our engineers push the humanoid robot to its limits.
To enable speech recognition technology for many more languages spoken around the globe, Facebook AI is releasing wav2vec Unsupervised, a new method to train models with no supervision whatsoever. Wav2vec Unsupervised rivals the performance of the best supervised systems from just a few years ago.
Andrew Gelman, a statistics professor at Columbia, and Aki Vehtari, a computer science professor at Finland’s Aalto University, recently published a list of the most important statistical ideas in the last 50 years. Here, they break it down in easy-to-understand terms.
Modern AI systems approach tasks like recognising objects in images and predicting the 3D structure of proteins as a diligent student would prepare for an exam. By training on many example problems, they minimise their mistakes over time until they achieve success. But this is a solitary endeavour and only one of the…
Recently, we translated the predictive power of machine learning (ML) into $1.7 million a year in infrastructure cost savings by optimizing how Dropbox generates and caches document previews. Machine learning at Dropbox already powers commonly-used features such as search , file and folder suggestions , and OCR in…
We are excited to announce the release of PyTorch 1.10. This release is composed of over 3,400 commits since 1.9, made by 426 contributors. We want to sincerely thank our...
Photos are among the most common types of files in Dropbox, but searching for them by filename is even less productive than it is for text-based files. When you're looking for that photo from a picnic a few years ago, you surely don't remember that the filename set by your camera was 2017-07-04 12.37.54.jpg .
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Language, and its role in demonstrating and facilitating comprehension - or intelligence - is a fundamental part of being human. It gives people the ability to communicate thoughts and concepts, express ideas, create memories, and build mutual understanding. These are foundational parts of social intelligence. It’s…
How can we build machines with human-level intelligence? There’s a limit to how far the field of AI can go with supervised learning alone. Here's why self-supervised learning is one of the most promising ways to make significant progress in AI.
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Learn how you can leverage Python and Pandas from directly inside PostgreSQL to build your own recommendation engine.
Cutting-edge cyber security research from NCC Group. Find public reports, technical advisories, analyses, & other novel insights from our global experts.
Details were disclosed at the company’s 5th Annual Samsung Foundry Forum
NVIDIA data scientists took three of the top spots in a brain tumor segmentation challenge validation phase at the prestigious MICCAI 2021.
GauGAN2, the latest version of NVIDIA Research’s wildly popular AI painting demo, allows anyone to create photorealistic masterpieces.
GROUND TRUTH is an inside look at the development and deployment of self-driving technology, from the simulation labs to city streets.
People + AI Research (PAIR) is a multidisciplinary team at Google that explores the human side of AI.
We’ve discovered neurons in CLIP that respond to the same concept whether presented literally, symbolically, or conceptually. This may explain CLIP’s accuracy in classifying surprising visual renditions of concepts, and is also an important step toward understanding the associations and biases that CLIP and similar…
