1411
Let's talk about AI and end-to-end encryption
Recently I came across a fantastic new paper by a group of NYU and Cornell researchers entitled “How to think about end-to-end encryption and AI.” I’m extremely grateful to see th…
New
The latest blog posts to take off on Hacker News. 3,091 posts.
1412
Test-driven development with an LLM for fun and profit
Welcome to the very first post in a new blog! Here I will discuss software development, SRE work, and other fun stuff. Sometimes an idea is just too good to pass up. I hope this blog will motivate me to turn sparks and little pieces into general knowledge in writing the words down. The other day I was discussing Tabby…
1413
Nepenthes is a tarpit to catch AI web crawlers
Making web crawlers eat shit since 2023
1414
Generate audiobooks from E-books with Kokoro-82M
A guide on how to convert .epub e-books into high-quality audiobooks narrated by neural text-to-speech
1415
Don't use cosine similarity carelessly
Cosine similarity - the duct tape of AI. Convenient but often misused. Let's find out how to use it better.
1416
AI founders will learn the bitter lesson
Historically, general approaches always win in AI. Founders in AI application space now repeat the mistakes of AI researchers.
1417
How we used GPT-4o for image detection with 350 similar illustrations
The Attic is a running catalog of Olup's side projects, sketches, and weekend rabbit holes.
1418
How outdated information hides in LLM token generation probabilities
Random tech notes
1419
Entropy of a Large Language Model output
Large language models like ChatGPT & Claude have become ubiquitous in today’s world. I visited a friend for the New years eve and was impressed by how ChatGPT was being extensively used within the family. The friend’s little kid is going to grow up in a world, where turning to large language models (LLM) for quick…
1420
Common misconceptions about the complexity in robotics vs. AI (2024)
Common misconceptions about the complexity in robotics vs AI
1421
How I program with LLMs
This document is a summary of my personal experiences using generative models while programming over the past year. It has not been a passive process. I have intentionally sought ways to use LLMs while programming to learn about them. The result has been that I now regularly use LLMs while working and I consider their…
1422
LLMs and Code Optimization
Dave Andersen's (new) blog
1423
1424
A messy experiment that changed how I think about AI code analysis
A messy experiment that changed how we think about AI code analysis Last week, I watched our AI choke on a React codebase - again. As timeout errors flooded my terminal, something clicked. We’d been teaching AI to read code like a fresh bootcamp grad, not a senior developer. Here’s what I mean.
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1426
Using LLMs and Cursor to finish side projects
Struggling to finish side projects due to limited time? In my latest blog post, I share how I improved my productivity using AI tools like LLMs and Cursor IDE. Learn to refine specs, bootstrap code, and iterate effectively to rapidly build and deploy your projects—even with a busy schedule.
1427
Self driving 1993 Volvo with open pilot
Together with some friends, I decided earlier this year to particpate in the Carbage run 2025 Winter edition. This is a 6-day journey in winter all the way through Sweden to the polar circle, and back down to Helsinki in a group of roughly 400 cars. One small catch (you might have guessed it from the name): your car…
1428
The State of Generative Models
In the face of disruptive technologies, moats created by closed source are temporary. Even OpenAI’s closed source approach can’t prevent others from catching up. So we anchor our value in our team — our colleagues grow through this process, accumulate know-how, and form an organization and culture capable of…
1429
Can LLMs write better code if you keep asking them to “write better code”?
Most coders want AI to write code faster: I want AI to write FASTER CODE.
1430
Building a Knowledge System That Enhances Rather Than Replaces Thought
Preserving and augmenting human insight in an age of automated knowledge with Zettelgarden
1431
My 25-year adventure in AI and ML
This is the 25-year story of how I fell into the field of AI.
1432
Things we learned about LLMs in 2024
A lot has happened in the world of Large Language Models over the course of 2024. Here’s a review of things we figured out about the field in the past …
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1434
OpenAI’s board, paraphrased: ‘All we need is unimaginable sums of money’
OpenAI is to this decade’s generative-AI revolution what Netscape was to the 1990s’ internet revolution.
1435
How I run LLMs locally
I document how I run Large Language Models locally.
1436
Can LLMs accurately recall the Bible?
I've often found myself uneasy when LLMs (Large Language Models) are asked to quote the Bible. While they can provide insightful discussions about faith, their tendency to hallucinate responses raises concerns when dealing with scripture, which we regard as the inspired Word of God. To explore these concerns, I
1437
All You Need Is 4x 4090 GPUs to Train Your Own Model
How I built an ML rig for training LLMs locally, exploring hardware choices, setup tricks, and lessons learned along the way.
1438
Google's Results Are Infested, Open AI Is Using Their Playbook from the 2000s
Google search results are becoming annoying to use and Open AI is about to eat Google's lunch.
1439
Building AI Products–Part I: Back-End Architecture
In 2023, we launched an AI-powered Chief of Staff for engineering leaders—an assistant that unified information across team tools and tracked critical project developments. Within a year, we attrac...
1440
Short Message Compression Using LLMs
ts_sms works similarly to ts_zip . It uses a specific padding system compatible with arithmetic coding so that the message length does not need to be explicitly encoded.