1441
Delimiters won’t save you from prompt injection
Prompt injection remains an unsolved problem. The best we can do at the moment, disappointingly, is to raise awareness of the issue. As I pointed out last week, “if you …
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 3,091 posts.
1442
Here be monsters: What do you still need to know when agents do the work?
AI agents write code faster than anyone can read it. What engineers still need: fundamentals, breadth, and the willingness to dive in when it breaks.
1443
Peer Programming with LLMs, for Senior+ Engineers
This article contains a collection of resources for senior (or staff+) engineers exploring the use of LLM for collaborative programming.
1444
LLMs Are Complicated Now
Back in 2022 and 2023 there were two big branches of machine learning happening at Meta1. The LLM work that led to Llama was a clean, smooth stack of repeated Transformer modules; the recommendatio…
1445
1446
Creating Shazam in Java (2010)
A couple of days ago I encountered this article: How Shazam WorksThis got me interested in how a program like Shazam works… And more importantly, how hard is...
1447
The Illustrated GPT-2: Visualizing Transformer Language Models (2019)
Discussions: Hacker News (64 points, 3 comments), Reddit r/MachineLearning (219 points, 18 comments) Translations: Simplified Chinese, French, Korean, Russian, Turkish This year, we saw a dazzling application of machine learning. The OpenAI GPT-2 exhibited impressive ability of writing coherent and passionate essays…
1448
ChatGPT's Chess Elo is 1400
It shouldn’t be surprising that ChatGPT can play chess.
1449
Where does next-token prediction leave us?
Your favourite ROP gadget
1450
Anti-AI fonts are useless and harmful
Trying to obfuscate the web is a bad, pointless idea
1451
OpenAI DevDay 2024 live blog
I’m at OpenAI DevDay in San Francisco, and I’m trying something new: a live blog, where this entry will be updated with new notes during the event. See OpenAI DevDay: …
1452
GPT-3 tries pickup lines
Once upon a time I decided to train a neural net to generate pickup lines. Once I started collecting the training data I began to regret it when I saw how awful the existing lines were. Turns out I needn’t have worried. The neural net I used was so small and clueless that
1453
Vāgdhenu: A Sanskrit Chanting TTS System
A vṛtta (meter) aware śloka-to-chant system for Sanskrit. Try the live demo, hear sample chants, read the paper.
1454
Meaningful Nonsense: How I generate sentences
I’m coding a system in JavaScript that generates sentences of “meaningful nonsense”. Here are some examples.
1455
1456
Notes on OpenAI o3-mini
OpenAI’s o3-mini is out today. As with other o-series models it’s a slightly difficult one to evaluate—we now need to decide if a prompt is best run using GPT-4o, o1, …
1457
1458
1459
1460
The Agentic AI Handbook: Production-Ready Patterns
A comprehensive guide to 113 production-informed patterns for building reliable AI agents.
1461
Stuff we figured out about AI in 2023
2023 was the breakthrough year for Large Language Models (LLMs). I think it’s OK to call these AI—they’re the latest and (currently) most interesting development in the academic field of …
1462
Sam Altman's pants are on fire
Even for him, his latest whopper is something
1463
I had ChatGPT write a Decemberists song and recorded it
And I recorded it. Here's "Sailor's Song."
1464
Demystifying GPU compute architectures
Getting 'low level' with Nvidia and AMD GPUs
1465
What mathematicians should know about the Lean Theorem Prover: reliability & AI
[This is a guest post by Thomas Hales. This blog post was initially written in a different file format and converted using AI. — T.] Mathematicians have been weighing in on what they value ab…
1466
Score matching with Langevin Sampling: a new contender to GANs
Last year, Yang Song, a graduate student at Stanford, showed an entirely new way of generating data based on denoising score matching with Annealed Langevin sampling (DSM-ALS). The paper showed tha…
1467
Data is the only moat
How different adoption models drive better applications
1468
Deep Learning 101
Deep learning has become something of a buzzword in recent years with the explosion of 'big data', 'data science', and their derivatives mentioned in the media. Justifiably, deep learning approaches have recently blown other state-of-the-art machine learning methods out of the water for standardized problems such as…
1469
Hamiltonian Monte Carlo explained
Understanding an effective way of sampling from complex distributions with 3d-demonstrations
1470
We accidentally solved robotics by watching 1M hours of YouTube
the existential crisis we all share imagine this: you've just spent $640 billion training the chonkiest language model known to humanity (lol) and decide...