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Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 789 posts.
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LLM discourse needs more nuance
With this write-up, I want to outline my current thinking around large language models like OpenAI's chatGPT.
724
Why are there no antitrust claims vs. GitHub Copilot, when there is a precedent?
Microsoft GitHub released CoPilot last year, a tool for generating code and auto-completion, that’s been trained on vast amount of open source code, notably all open source code hosted on Git…
725
ChatGPT is really good at roleplaying
ChatGPT is really good at roleplaying as strange and unusual characters with minimal prompting.
726
The A.I. business influencer guys must be stopped
Please let's stop predicting the future of A.I.
727
The idea maze for AI startups (2015)
programming, philosophy, history, internet, startups
728
The Full Story of Large Language Models and RLHF
Large Language Models have been in the limelight since the release of ChatGPT, with new models being announced seemingly every week. This guide walks through the essential ideas of how these models came to be.
729
Changing my relationship with GitHub Copilot
I've been using GitHub Copilot on personal projects since March. It's been an interesting experience, and one that I realized I have to change. Using Copilot nearly full time has had some positive and negative impacts on me, and it's time to take control of how I interact with it.
730
Q* Hypothesis: Enhancing Reasoning, Rewards, and Synthetic Data
Emergency special: The information we need to understand what Q* is was right in front of us, but the memes are more fun than reality.
731
Generative AI and The Future of Work
Unexpected ways generative AI will change how you work forever
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"Building Machines That Learn and Think Like People", 7 Years Later
In the post about GPT-4V, I mentioned the paper “Building Machines That Learn and Think Like People” (https://arxiv.org/abs/1604.00289) by Brenden Lake, Tomer Ullman, Joshua Tenenbaum, and Samuel Gershman.
734
ProfileGPT: An Example of AI Agents Collaboration Architecture
A dive into the architecture and design of ProfileGPT, an app that allows users to analyze their user's profile and personality as seen by ChatGPT to raise awareness about data usage.
735
Nvidia's CUDA Monopoly
CUDA (Compute Unified Device Architecture) is a closed-source low-level API that interfaces software with NVIDIA GPUs.
736
LeoLM: German-Language LLM Research
We proudly introduce LeoLM ( L inguistically E nhanced O pen L anguage M odel), the first comprehensive suite of German-language Foundation Language Models t…
737
The State of Serverless GPUs
Comprehensive guide to understand the Serverless GPU Inference landscape.
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English as the new programming language for Apache spark
Discover the English SDK for Apache Spark, making data analytics more accessible with simple English instructions powered by Generative AI.
740
The Neural Net Tank Urban Legend
AI folklore tells a story about a neural network trained to detect tanks which instead learned to detect time of day; investigating, this probably never happened.
741
Bayesian statistics and machine learning: How do they differ?
My colleagues and I are disagreeing on the differentiation between machine learning and Bayesian statistical approaches. I find them philosophically distinct, but there are some in our group who would like to lump them together as both examples of machine learning. I have been favoring a definition for Bayesian…
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Open Sourcing Cody – Sourcegraph's AI-enabled editor assistant
Cody, Sourcegraph's AI-enabled editor assistant, is now open source.
743
Gaussian explosion
Over the past month it seems like Gaussian Splatting (see my first post ) is experiencing a Cambrian Gaussian explosion of new research. The seminal paper came out in July 2023, and starting about mid-November, it feels like every day there’s a new paper or two coming out, related to Gaussian Splatting in some way…
744
Exploring Neural Graphics Primitives
Neural fields have quickly become an interesting and useful application of machine learning to computer graphics. The fundamental idea is quite straightforward: we can use neural models to represent all sorts of digital signals, including images, light fields, signed distance functions, and volumes.
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Try Bard and share your feedback
Bard is an early experiment from Google that lets you collaborate with generative AI. If you’re in the U.S. and U.K., you can sign up to try it.
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Generative AI's Act Two
One year ago, we published a hypothesis that generative AI would become a profound platform shift in technology. Then came the firestorm.
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Squawk bots: Can generative AI lead us to understanding animals?
The Earth Species Project is using large language models to develop tools to decipher animal communication.
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ChatGPT is laying you off
(In various voices)