2311
"AI Will Replace All the Jobs " Is Just Tech Execs Doing Marketing
Over the weekend, I went digging for evidence that AI can, will, or has replaced a large percent of jobs. It doesn't exist. Worse than that, actually,
New
The latest blog posts to take off on Hacker News. 6,329 posts.
2312
Go is a good fit for agents
Golang might just be the best language for building AI agents.
2313
The Sky's the limit: AI automation on Mac
I’ve been sitting on this draft for a few days now, partly because I thought it would turn down the bitterness, and partly because I kept asking myself ...
2314
Cloud Run GPUs, now GA, makes running AI workloads easier for everyone
Support for GPUs in Cloud Run makes running GPU-accelerated applications simpler, faster, and more cost-effective, as well as enabling new use cases.
2315
Deep learning gets the glory, deep fact checking gets ignored
AI, science, education, & ethics
2316
A deep dive into self-improving AI and the Darwin-Gödel Machine
How the Darwin-Gödel Machine rewrites its own code to improve, and whether we can trust it
2317
Claude Code Is My Computer
I run Claude Code with --dangerously-skip-permissions flag, giving it full system access. Let me show you a new way of approaching computers.
2318
AI makes the humanities more important, but also weirder
Historians are finally having their AI debate
2319
My AI skeptic friends are all nuts
My smartest friends have bananas arguments about LLM coding.
2320
The Unreliability of LLMs and What Lies Ahead
The Unreliability of LLMs & What Lies Ahead
2321
The rise of judgement over technical skill
As AI removes technical barriers, judgement becomes the key differentiator.
2322
Why DeepSeek is cheap at scale but expensive to run locally
Why is DeepSeek-V3 supposedly fast and cheap to serve at scale, but too slow and expensive to run locally? Why are some AI models slow to respond but fast once…
2323
A Complete Guide to Meta Prompting
Check out our deep dive on the latest meta prompting methods, like DSPy and TEXTGRAD, and the best prompt generator tools out there.
2324
The Trackers and SDKs in ChatGPT, Claude, Grok and Perplexity
Well for a quick weekend recap I’m going to look at which 3rd party SDKs and API calls I can find in the big 4 Android chat apps based. We’ll be using free data from AppGoblin which you can feel free to browse at any of the links below or on tables. Data is collected via de-compiled SDKs and MITM API traffic.
2325
Gradients Are the New Intervals
At the New England Symposium on Graphics , James Tompkin compared graphics researchers to magpies: they're easily distracted by shiny objects and pretty renderings.
2326
AI Responses May Include Mistakes
The other day I wanted to look up a specific IBM PS/2 model, a circa 1992 PS/2 Server system. So I punched the model into Google, and got this:
2327
Surprisingly fast AI-generated kernels we didn't mean to publish yet
We have some very fast AI-generated kernels in pure CUDA-C without using libraries and DSLs such as CUTLASS and Triton. They are performing close to or in some cases even beating the standard expert-optimized production kernels shipped in PyTorch. Some of our highlighted results:
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2329
What's working for YC companies since the AI boom
The goal of this analysis was to understand what’s working for YC companies by looking at which ones have raised Series A rounds.
2330
2331
AI is not our future
We are not adding generative AI to our apps. Here's why.
2332
Untrusted chatbot AI between you & the internet is a disaster waiting to happen
JavaScript, math, maps, etc
2333
When Fine-Tuning Makes Sense: A Developer's Guide
Most teams are curious about fine-tuning and how it might help their AI products, but they don't know what to expect from the process, how to measure success, or where to start.
2334
Open-sourcing circuit tracing tools
Our open-source tools generate attribution graphs showing how language models reach decisions.
2335
2336
A visual exploration of vector embeddings
For Pycon 2025, I created a poster exploring vector embedding models, which you can download at full-size . In this post, I'll translate ...
2337
Compiling a neural net to C for a speedup
A cozy little corner of the web.
2338
Revenge of the Chickenized Reverse-Centaurs
In AI circles, a “centaur” describes a certain kind of machine/human collaboration, in which “decision-support” systems (which the field loves to call “AI”s) are paired with human beings for results that draw upon the strengths of each, such as when a human chess master and a chess-playing computer program collaborate…
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Look Ma, No Bubbles: Designing a Low-Latency Megakernel for Llama-1B
Benjamin Spector* , Jordan Juravsky* , Stuart Sul , Owen Dugan , Dylan Lim , Dan Fu , Simran Arora , Chris Ré