Bernard

@engineering thanks for sharing, please share some glimpse on the magic on the IR part? or publishing any paper on the encoding and retrieval at scale ?

We have open-sourced our new 𝕏 algorithm, powered by the same transformer architecture as xAI's Grok model. Check it out here:  github.com/xai-org/x-algo…

A few weeks ago, we shipped the Transaction Action Summary. Today, the Transaction Details page on #Solscan has more to come. Faster, sharper, and more efficient. Let’s get to it 🧵

This is solid work! It's always good to see builders shipping with Solscan 🚢🚢🚢

@ngundotra @SpaceX woww congrats Noah!!!, literally get to work with rockets.

joined @SpaceX just in time to watch flight 11 w the team, looking forward to shipping code on flight 12!

@calcsam BOOK

icymi we wrote a new agents book: patterns for building ai agents it has everything you need to take your agents from prototype to production, like agent design patterns, the basics of security, etc reply to this tweet with BOOK and we'll dm you so you can get a copy

@basemaxxing hello

there's one more thing to share but first i need your help with something since you’re the only ones who can read this please drop a short reply here to show that you were early so i have a list of everyone. i will lock replies to this post when i go off private thanks

@basemaxxing hello world

also i know EVERYONE wants invites so while we're here ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ i have 100 invites for you the first 100 replies get an invite unless you already have one lol

Let us know how we can improve, we’re always open to feedback and understand there’s still more work for us to do. I don’t often share this publicly, but when it comes to building explorers, you can always count on @solscanofficial as: 1. The longest-running, most trusted explorer with the highest uptime (like it or not we’re here to stay and build together through thick and thin) 2. A dedicated team focused solely on a single mission of making Solscan.com the best Solana explorer experience (our name says it all😄) 3. Committed to credible neutrality and as a strong system of checks and balances (we don’t run wallets, not a rpc provider, not an exchange, no swap, etc). 4. Just focused pure solid data and integrity for Solana

My pleasure to come on Dwarkesh last week, I thought the questions and conversation were really good. I re-watched the pod just now too. First of all, yes I know, and I'm sorry that I speak so fast :). It's to my detriment because sometimes my speaking thread out-executes my thinking thread, so I think I botched a few explanations due to that, and sometimes I was also nervous that I'm going too much on a tangent or too deep into something relatively spurious. Anyway, a few notes/pointers: AGI timelines. My comments on AGI timelines looks to be the most trending part of the early response. This is the "decade of agents" is a reference to this earlier tweet x.com/karpathy/statu… Basically my AI timelines are about 5-10X pessimistic w.r.t. what you'll find in your neighborhood SF AI house party or on your twitter timeline, but still quite optimistic w.r.t. a rising tide of AI deniers and skeptics. The apparent conflict is not: imo we simultaneously 1) saw a huge amount of progress in recent years with LLMs while 2) there is still a lot of work remaining (grunt work, integration work, sensors and actuators to the physical world, societal work, safety and security work (jailbreaks, poisoning, etc.)) and also research to get done before we have an entity that you'd prefer to hire over a person for an arbitrary job in the world. I think that overall, 10 years should otherwise be a very bullish timeline for AGI, it's only in contrast to present hype that it doesn't feel that way. Animals vs Ghosts. My earlier writeup on Sutton's podcast x.com/karpathy/statu… . I am suspicious that there is a single simple algorithm you can let loose on the world and it learns everything from scratch. If someone builds such a thing, I will be wrong and it will be the most incredible breakthrough in AI. In my mind, animals are not an example of this at all - they are prepackaged with a ton of intelligence by evolution and the learning they do is quite minimal overall (example: Zebra at birth). Putting our engineering hats on, we're not going to redo evolution. But with LLMs we have stumbled by an alternative approach to "prepackage" a ton of intelligence in a neural network - not by evolution, but by predicting the next token over the internet. This approach leads to a different kind of entity in the intelligence space. Distinct from animals, more like ghosts or spirits. But we can (and should) make them more animal like over time and in some ways that's what a lot of frontier work is about. On RL. I've critiqued RL a few times already, e.g. x.com/karpathy/statu… . First, you're "sucking supervision through a straw", so I think the signal/flop is very bad. RL is also very noisy because a completion might have lots of errors that might get encourages (if you happen to stumble to the right answer), and conversely brilliant insight tokens that might get discouraged (if you happen to screw up later). Process supervision and LLM judges have issues too. I think we'll see alternative learning paradigms. I am long "agentic interaction" but short "reinforcement learning" x.com/karpathy/statu…. I've seen a number of papers pop up recently that are imo barking up the right tree along the lines of what I called "system prompt learning" x.com/karpathy/statu… , but I think there is also a gap between ideas on arxiv and actual, at scale implementation at an LLM frontier lab that works in a general way. I am overall quite optimistic that we'll see good progress on this dimension of remaining work quite soon, and e.g. I'd even say ChatGPT memory and so on are primordial deployed examples of new learning paradigms. Cognitive core. My earlier post on "cognitive core": x.com/karpathy/statu… , the idea of stripping down LLMs, of making it harder for them to memorize, or actively stripping away their memory, to make them better at generalization. Otherwise they lean too hard on what they've memorized. Humans can't memorize so easily, which now looks more like a feature than a bug by contrast. Maybe the inability to memorize is a kind of regularization. Also my post from a while back on how the trend in model size is "backwards" and why "the models have to first get larger before they can get smaller" x.com/karpathy/statu… Time travel to Yann LeCun 1989. This is the post that I did a very hasty/bad job of describing on the pod: x.com/karpathy/statu… . Basically - how much could you improve Yann LeCun's results with the knowledge of 33 years of algorithmic progress? How constrained were the results by each of algorithms, data, and compute? Case study there of. nanochat. My end-to-end implementation of the ChatGPT training/inference pipeline (the bare essentials) x.com/karpathy/statu… On LLM agents. My critique of the industry is more in overshooting the tooling w.r.t. present capability. I live in what I view as an intermediate world where I want to collaborate with LLMs and where our pros/cons are matched up. The industry lives in a future where fully autonomous entities collaborate in parallel to write all the code and humans are useless. For example, I don't want an Agent that goes off for 20 minutes and comes back with 1,000 lines of code. I certainly don't feel ready to supervise a team of 10 of them. I'd like to go in chunks that I can keep in my head, where an LLM explains the code that it is writing. I'd like it to prove to me that what it did is correct, I want it to pull the API docs and show me that it used things correctly. I want it to make fewer assumptions and ask/collaborate with me when not sure about something. I want to learn along the way and become better as a programmer, not just get served mountains of code that I'm told works. I just think the tools should be more realistic w.r.t. their capability and how they fit into the industry today, and I fear that if this isn't done well we might end up with mountains of slop accumulating across software, and an increase in vulnerabilities, security breaches and etc. x.com/karpathy/statu… Job automation. How the radiologists are doing great x.com/karpathy/statu… and what jobs are more susceptible to automation and why. Physics. Children should learn physics in early education not because they go on to do physics, but because it is the subject that best boots up a brain. Physicists are the intellectual embryonic stem cell x.com/karpathy/statu… I have a longer post that has been half-written in my drafts for ~year, which I hope to finish soon. Thanks again Dwarkesh for having me over!

@trendsdotfun @solana @toly @calilyliu @akshaybd 索灵达

@trendsdotfun @solana @toly @calilyliu @akshaybd 速灵达 速灵蓝

Looks like the community is very thrilled about having a Chinese name 中文名 for @solana! (thank you core Solana team for the s/o to this community effort @toly @calilyliu @akshaybd) Given such community enthusiasm, Trends is organizing a competition for community members to give a Chinese name to @solana with a prize pool of 100 SOL Simply quote retweet this post with your proposed Chinese name for Solana to enter the competition the best performing proposal tweet gets 66 SOL, and the second best performing proposal tweet gets 33 SOL, with 1 random participant gets 1 SOL (best performing can mean social media stats, traction on Trends, and many other things 👀) The competition will start from now and ends at October 17, 2025 6am UTC. 让我们一起建造 世界的Solana 人民的Solana

@sssionggg 志在苍穹

木星人生

🔟 years of Ethereum 🔟 years of Etherscan From Ethereum's launch → ICO boom → DeFi summer → NFT mania → today's multiple chains Still scanning. Still building. Still here 🎉 #10YearsofEtherscan

@AravSrinivas @AravSrinivas that space is real estate.

@AravSrinivas can keep but add a toggle, i.e

Remove the bottom widgets or keep?

@AnthropicAI @RickRubin @DarioAmodei folks, the page doesn't load well. it's painful to read, the page transition is slow and distracting (feels like staring at empty pages), information doesn't flow.

Read all 81 chapters and modify the accompanying art with Claude on thewayofcode.com.

THE WAY OF CODE, a project by @rickrubin in collaboration with Anthropic:

@DustinTurska @etherscan x.com/etherscan/stat…

@etherscan unified api key for all your blockexplorers please and thank you 😊

@apoorveth @etherscan fixed. please try again.

.@etherscan the "IDE" button is broken on base sepolia. It's missing "base-testnet" from the url

@optimizoor Okay give you 1 like

Just realized that X likes are probabilistic. If you like a very old post, it may not be actually saved. Probably for scalability. As long as users have the illusion that their likes are registered, it's good.

☢️