Arun Krishnamurthy

@avilesrafa @mattpocockuk cool idea!

@mattpocockuk To upload our sessions and run real-time analysis on them. Goals: learn what works, track efficiency, track errors, and learn how to avoid them.

What do you use Claude Code's hooks for? So far, all I'm doing is using it to play a little 'ding' sound when I need to look at the terminal.

@mattpocockuk I’m currently working on a hook to grab used context & tokens to compaction into the context after every PostToolCall. I want to instruct it to write out notes for itself before compaction.

@HeyBilt I was told this but I never got any emails. This is hilariously bad service.

@arun279 Hey, please feel free to DM us with any questions. We're happy to help.

Trying to get a human to respond from @HeyBilt is a great way to waste time. Someone has hard coded “59 minutes” to the support service and it has no relationship to reality.

only one team in the entire premier league right now has more than 2 wins in the last 5. how common is that?

.@stevenbjohnson please consider making a @NotebookLM API! there are a lot of interesting use cases that can be unlocked with this.

New 3h31m video on YouTube: "Deep Dive into LLMs like ChatGPT" This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their "psychology", and how to get the best use them in practical applications. We cover all the major stages: 1. pretraining: data, tokenization, Transformer neural network I/O and internals, inference, GPT-2 training example, Llama 3.1 base inference examples 2. supervised finetuning: conversations data, "LLM Psychology": hallucinations, tool use, knowledge/working memory, knowledge of self, models need tokens to think, spelling, jagged intelligence 3. reinforcement learning: practice makes perfect, DeepSeek-R1, AlphaGo, RLHF. I designed this video for the "general audience" track of my videos, which I believe are accessible to most people, even without technical background. It should give you an intuitive understanding of the full training pipeline of LLMs like ChatGPT, with many examples along the way, and maybe some ways of thinking around current capabilities, where we are, and what's coming. (Also, I have one "Intro to LLMs" video already from ~year ago, but that is just a re-recording of a random talk, so I wanted to loop around and do a lot more comprehensive version of this topic. They can still be combined, as the talk goes a lot deeper into other topics, e.g. LLM OS and LLM Security) Hope it's fun & useful! youtube.com/watch?v=7xTGNN…

@robot the order 22509929 says it’s delivered but it’s not, i tried everything and emailed your support chat but i got no response.

@MKBHD how many charging cycles would this battery be rated for if it's charged 320W every time?

RealMe just showcased 320W charging in a smartphone... THREE HUNDRED TWENTY watts That charged a 4400mah phone from 1-100% in 4 minutes 22 seconds 😳 0-26% in 1 minute 0-50% in 2 minutes 0-100% in 4 minutes 30 seconds I am now unconvinced that this does not damage the phone

my favorite @LinusTech product!

camouflage @PlayStation

Can I just say I loooove Suno. Some of my favorites: Dog dog dog dog dog dog dog dog woof woof suno.com/song/1783c864-… Chemical elements suno.com/song/5f324463-… train_gpt2.c header (who did this lol) suno.com/song/2a210337-… Suno tutorial (in Suno!): suno.com/song/d960e84a-… Many others. So good. Anyone else favorites?

How to be as "smart" as Auto-Regressive LLMs: - memorize lots of problem statements together with recipes on how to solve them. - to solve a new problem, retrieve the recipe whose problem statement superficially matches the new problem. - apply the recipe blindly and declare victory. - do not use basic logic. - do not use common sense to check your solution. - do not use a mental model of the situation as a sanity check. - do not simulate the scenario in your mind using your world model. - when someone tells you your solution is wrong, reply "I'm sorry, you are right" and apply another irrelevant recipe. Knowledge accumulation is not a substitute for actual understanding.

Java developers, where are you?

new @PatrickRothfuss fan

Gemini 1.5 pro is STILL under hyped I uploaded an entire codebase directly from github, AND all of the issues (@vercel ai sdk,) Not only was it able to understand the entire codebase, it identified the most urgent issue, and IMPLEMENTED a fix. This changes everything

pointerArithmeticBeLike reddit.com/r/programmerhu…