271
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 402 posts.
272
Using GPT-4 to measure the passage of time in fiction
Large language models are valuable research assistants, especially when they refuse to follow instructions.
273
Replika AI: Your Money or Your Wife
Isn't there somebody you forgot to ask?
274
Role-playing with AI will be a powerful tool for writers and educators
Or, how well can GPT-4 simulate an acid trip in 1963?
275
Natural language is an unnatural interface
How can we use familiar design patterns to constrain the unwieldy state space of large language models?
276
Double Descent in Human Learning
The uncanny resemblance between double descent and a 50 year old theory from psychology
277
278
Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields
Neural Radiance Field training can be accelerated through the use of grid-based representations in NeRF's learned mapping from spatial coordinates to colors and volumetric density. However, these grid-based approaches lack an explicit understanding of scale and therefore often introduce aliasing, usually in the form…
279
AI is just someone else's intelligence
It’s been a long time since I’ve worked in the field of ML (or what some call AI), and we’ve come a long way from simple text classification to what’s being casually called generative AI today. While the technology has made many advances, the foundational concepts of machine learning have remained analogous over time…
280
Artificial intelligence just lost a leader
Plus a position-search announcement from NSF Roger Schank just passed away. Roger was a top leader of AI. I overlapped with him for my time at Yale. In 1974, he became a professor of computer scien…
281
282
283
GPT-4 is not getting worse
GPT-4 may have declined in some areas, but it hasn’t systematically done so. My tests were shit, and never proved much of anything.
284
Margaret Mead, technocracy, and the origins of AI's ideological divide
The anthropologist helped popularize both techno-optimism and the concept of existential risk
285
Our humble attempt at “how much data do you need to fine-tune”
Efficacy of OpenAI Fine-tuning API, Cost/Latency Considerations, Experiencing Catastrophic Forgetting, and...Getting Roasted by a Fine-tuned GPT-3.5
286
LLM tech comes to Wolfram Language
Wolfram's Version 13.3 includes a subsystem around LLMs plus new functionality in integrals, special functions, finite fields, computational geometry, live highlighting in visualizations, AR & VR deployment. See examples for those and dozens of other enhancements.
287
Let's Talk about ChatGPT with Code Interpreter and Microsoft Copilot
Let's talk about ChatGPT with Code Interpreter & Microsoft Copilot
288
Early Days of AI
Rather then view LLMs, Transformers, and diffusion models as part of a continuum with past "AI", it is worth thinking of this as an entirely new era and discontinuity from the past
289
The Prospect of an AI Winter
Texts on this and that.
290
Why I chose OpenAI over academia
Part 2 of a blog post about my time on the computer science job market in 2021-2022, in which I discuss my personal decision-making process between offers.
291
LLMs are good at playing you
Large language models seem just like humans, but some of this is in our heads.
292
ChatGPT has trouble giving an answer before explaining its reasoning
ChatGPT is a fancy auto-complete : what it does is finding the most likely continuation of text for the text it has already printed out (or as a reply for the prompt, when it is starting printing stuff out), according to the large corpus of text it has been trained with.
293
Hello, Perceptron: An introduction to artificial neural networks
Generative AI tools like ChatGPT and Midjournery are able to replicate (and often exceed) human-like performance on tasks like taking exams, generating text and making art.
294
Current architectural best practices for LLM applications
In this guide, I will share the standard architecture for data-informed language model applications and explain forthcoming improvements in knowledge retrieval.
295
SVD Image Compression
Singular Value Decomposition (SVD) is a fundamental concept in linear algebra, and it is particularly important in the field of machine learning for tasks such as dimensionality reduction, data compression, and noise reduction.
296
Demystifying Text Data with the Unstructured Python Library
In the world of data, textual data stands out as being particularly complex. It doesn’t fall into neat rows and columns like numerical data does. As a side project, I’m in the process of developing my own personal AI assistant. The objective is to use the data within my notes and documents to answer my questions. The…
297
Experimenting with LLMs to Research, Reflect, and Plan
Also, shortcomings in document retrieval and how to overcome them with search & recsys techniques.
298
C++ Neural Network in a Weekend (2020)
A blog about game engines, graphics, C++, and more.
299
Optimizing LLMs from a Dataset Perspective
Practical guide to improving LLM finetuning with better instruction datasets, covering data curation, prompt-output pairs, synthetic data, and experiment ideas.
300
And yet It Understands
In high-dimensional vector spaces, numerical optimization is omnipotent.