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A Guide to Synthesizing Adversarial Examples
Synthesizing adversarial examples for neural networks is surprisingly easy.
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 6,335 posts.
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The Math Required for Machine Learning
For the past year, I’ve been working on implementing well known model architectures and building web applications, so I have a fair amount…
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State-of-the-Art Image Generation Models
I have aggregated some of the SotA image generative models released recently, with short summaries, visualizations and comments. The overall development is summarized, and the future trends are spe…
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Hidet: A Deep Learning Compiler for Efficient Model Serving
Hidet is a powerful deep learning compiler that simplifies the process of implementing high-performing deep learning operators on modern accelerators (e.g., NVIDIA GPUs). With the new feature of torch.compile(...) in PyTorch 2.0, integrating...
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Experimenting with WebAssembly and Computer Vision
This past summer, four students at a coding bootcamp in Los Angeles began experimenting with WebAssembly. The result, after six weeks of exploration, was WebSight: a real-time face detection demo ...
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Creating a Starcraft AI – Part 22: Caveat Implementor
First part of this series | Previous | Next |Index In the latter part of the last episode, I outlined two problems I want to solve next. The first is to weigh in the direction of my target when fin…
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Shrinking Machine Learning Models for Offline Use
Get the latest news and features about smart home, Alexa Built-in, and Alexa Gadgets.
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ChatGPT's image generator can be manipulated to produce violent, sexual content
Mindgard reveals how ChatGPT's image generation safety filters can be bypassed with minor prompt adjustments, producing graphic violent and sexual content without users directly asking for it. Here's what was found, and why it matters.
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Why Is Claude Turning into an a**Hole?
Let's hope this trend reverses
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The vibe coder's career path is doomed
Let me get one thing out of the way immediately: LLMs are helpful. This isn't about whether LLMs can write code. They can. It's about why vibe coding might be the worst career investment you'll make.
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Planning for AGI and Beyond
Our mission is to ensure that artificial general intelligence—AI systems that are generally smarter than humans—benefits all of humanity.
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LLM-generated code must not be committed without prior written approval by core
If you are not sure if the code you plan to commit is acceptable (e. g. when taking code that was submitted with a problem report), ask a developer who is familiar with that part of the system for review. If you're new to the Project, check with your sponsor.
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Figma's woes compound with Claude Design
Figma's reliance on non-designer seats made it uniquely exposed to AI. Claude Design's launch deepens the problem.
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Case study: Creative math – How AI fakes proofs
Many AI enthusiasts debate whether Large Language Models actually "reason." My research indicates that a reasoning process does indeed occur, but its goal is different than we assume.
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DSLs Enable Reliable Use of LLMs
Why Domain-Specific Languages and good abstractions make LLM code generation reliable and reviewable.
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AI coding and the peanut butter and jelly problem
Why clear communication—not clever prompts—is your real AI superpower
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2023: The Year of AI
Explore the significant AI advancements, impactful partnerships, and legal debates that defined 2023.
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Baby Steps into Genetic Programming
While my final ranking in the Google AI Contest was disappointing ( 280th ), it was a very educational experience and was totally offset by Gábor Melis' dominating win using Common Lisp as well.
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I Taught My 8yo Subduction Zones with NotebookLM
Principal AI Architect. Creator of open-strix, a harness for building agent teams. Writing about AI architecture, stateful agents, and what happens when you give AI memory.
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AI’s compute fragmentation: what matrix multiplication teaches us
AI is powered by a virtuous circle of data, algorithms (“models”), and compute. Growth in one pushes needs in the others and can grossly affect the developer experience on aspects like usability and performance. Today, we have more data and more AI model research than ever before, but compute isn’t scaling at the same…
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Visual Reasoning Is Coming Soon
From silly cat costumes to world-changing innovations, OpenAI's latest release marks the beginning of something extraordinary. The fascinating world of visual reasoning is emerging, where AI models will soon think in pictures and solve complex spatial puzzles, transforming how machines understand and interact with the…
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Optimizing Tool Selection for LLM Workflows with Differentiable Programming
How local, learnable routers can reduce token overhead, lower costs, and bring structure back to agentic workflows.
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Backpropogation Is Just Steepest Descent with Automatic Differentiation (2013)
Preface The intended audience of this article is someone who knows something about Machine Learning and Artifical Neural Networks (ANNs) in particular and who recalls that fitting an ANN required a…
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Training Deep Networks with Data Parallelism in Jax
Misha Laskin personal website. Includes a blog and projects focused on artifical intelligence.
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Making sure AI serves people and knowledge stays human
Today we’re sharing a human rights impact assessment on AI/ML to help Wikimedia understand effects on human rights.