Feature Stores: A Hierarchy of Needs
Access, serving, integrity, convenience, autopilot; use what you need.| eugeneyan.com
The first thing to know is that I don’t call it AI. When those of us in the humanities talk about “AI in education” what we almost always mean is “chat interfaces to large language modules.” There are many other kinds of machine-learning endeavors but they’re not immediately relevant to most of us. And anyway, whether they’re “intelligent” is up for debate. So the word I’ll use here is “chatbot,” and the question is: What’s my policy? What do I think about your using...| The Homebound Symphony
NetChoice is a massive coalition of internet companies — look who’s in it — that is throwing enormous resources to block any law or proposed law in any and every state that requires age verification for access to websites. Given the technical challenges that make reliable age-verification schemes difficult if not impossible, I might have sympathy for the NetChoice companies if they weren’t who they are. (Oh the moral dilemma: thinking that laws are probably unconstitutional and yet wi...| The Homebound Symphony
Introduction: Why “Kubernetes AI” Dominates 2025 Search Rankings If you’ve been following cloud computing trends in 2025, you’ve probably noticed one term consistently topping search results: Kubernetes AI. This isn’t just a passing fad—it represents the most significant shift in container orchestration since Kubernetes itself revolutionized cloud-native development. According to multiple industry reports and trend […]| Collabnix
Freddie de Boer noted that Yascha Mounck strives to explain The Peculiar Persistence of the AI Denialists — and I want to note what has happened to Mounck’s key term, “denialism.” It originated of course in the debate over climate change: it was and is used to describe people who deny that the climate is changing, and instead insist that everything is what it has always been and that any apparent warming is merely ordinary variation in weather. The point of the phrase is that we have ...| The Homebound Symphony
...| The Homebound Symphony
Access, serving, integrity, convenience, autopilot; use what you need.| eugeneyan.com
Tensorflow is a machine learning library that lets you create all kinds of neural networks....| DEV Community
Whether you’re generating slop or code, underneath it’s the same shoggoth with a smiley face.| adactio.com
Play nice in the enterprise development sandbox with this one simple trick.| Port 1433
Background| hillman.dev
Patrick Hoefler| Blog
Recently, Machine Learning (ML) has emerged as a powerful tool within cryospheric sciences, offering innovative and effective solutions for observing, modelling and understanding the frozen regions of the Earth. From learning snowfall patterns and predicting avalanche dynamics to speeding up the process of modelling ice sheets, ML has transformed cryospheric sciences and bears many opportunities for future research. Case study: Sea ice As an example, let’s consider how ML can help us observ...| Cryospheric Sciences
Self-hosted sabotage as a form of collective action.| adactio.com
A quick look into the biology and machine learning behind DeepMind's new AlphaFold| daleonai.com
Wandering in a lifelong journey seeking after truth| Mostafa Samir's Blog
Wandering in a lifelong journey seeking after truth| Mostafa Samir's Blog
Wandering in a lifelong journey seeking after truth| Mostafa Samir's Blog
Scribd offers a variety of publisher and user-uploaded content to our users and while the publisher content is rich in metadata, user-uploaded content typically is not. Documents uploaded by the users have varied subjects and content types which can make it challenging to link them together. One way to connect content can be through a taxonomy - an important type of structured information widely used in various domains. In this series, we have already shared how we identify document types and...| Scribd Technology
Extracting metadata from our documents is an important part of our discovery and recommendation pipeline, but discerning useful and relevant details from text-heavy user-uploaded documents can be challenging. This is part 2 in a series of blog posts describing a multi-component machine learning system the Applied Research team built to extract metadata from our documents in order to enrich downstream discovery models. In this post, we present the challenges and limitations the team faced when...| Scribd Technology
User-uploaded documents have been a core component of Scribd’s business from the very beginning, understanding what is actually in the document corpus unlocks exciting new opportunities for discovery and recommendation. With Scribd anybody can upload and share documents, analogous to YouTube and videos. Over the years, our document corpus has become larger and more diverse which has made understanding it an ever-increasing challenge. Over the past year one of the missions of the Applied Res...| Scribd Technology
Everything you wanted to know about AI on Google Cloud, and much more| daleonai.com
GPU ML on Intel Arc| hillman.dev
