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учебники для 7 класса скачать для электронной книги, Surge AI Led by Edwin Chen Surpasses Scale AI With $1B 2024 , A look at Scale AI rival Surge AI, which raised no outside , How Surge AI Is Already Outpacing Rival Scale AI - Inc.com, Surge AI: The Bootstrapped Data-Labeling Powerhouse Quietly , The Little-Known Startup That Has Surged Past Scale AI , Surge AI's Meteoric Rise: How This Startup Surpassed Scale AI , How Surge AI hit $1B revenue with a 121 person team in 2024..
Andrej Karpathy / @karpathy: Nice - my AI startup school talk is now up! Chapters: 0:00 Imo fair to say that software is changing quite fundamentally again. LLMs are a new kind of computer, and you program them *in English*. Hence I think they are well deserving of a major version upgrade in terms ofGreg Isenberg / @gregisenberg: andrej karpathy just gave the CLEAREST vision i've seen of where software is headed and how to win in 90 days in the age of AI TLDR; LLMs are the new OS, english is the new code, and software is starting to use software my full notes below: [image]Andrej Karpathy / @karpathy: Part 2 of this mystery. Spotted on reddit. In my test not 100% reproducible but still quite reproducible. 🤔 [image]@learn2vibe: Notes on Andrej Karpathy's latest talk at the Y Combinator event. If you are builder, I recommend watching the video. [image]Andrej Karpathy / @karpathy: Some of the links: - My slides as keynote: https://drive.google.com/... - Software 2.0 blog post from 2017 https://karpathy.medium.com/ ... - How LLMs flip the script on technology diffusion https://karpathy.bearblog.dev/ ... - Vibe coding MenuGen (retrospective) https://karpathy.bearblog.dev/ ...Ben Lang / @benln: Andrej Karpathy on how software is changing: [image]Rakesh Agrawal / @rakeshsfnyc: 💯 especially if you go outside domains where AI is overfitted. Eg coding.Jared Friedman / @snowmaker: Thought provoking points from @karpathy at AI Startup School today. Made me see LLMs in a whole new light. [image]Garry Tan / @garrytan: By popular demand we rushed this so you could have it ASAP Big ups @karpathy Legend talk by a true legend of AIHimanshu / @himanshustwts: high signals software 4.0 would've goals as primitives. this karpathy talk is so well articulated as always. [image]Victor / @victor_explore: Andrej Karpathy says that when state-of-the-art LLMs go down, “it's actually kind of like an intelligence brownout in the world. The planet just gets dumber the more reliance we have on these models, which already is like really dramatic.” [video]Drew Breunig / @dbreunig: The only point on this @karpathy slide I'd push back here is custom GUI, and then only gently. When building agents there are nearly infinite edge cases you're going to hit and have to squash with context control and tools. At some point, it's wise to let a human drive. [image]Luther Lowe / @lutherlowe: “2025-2035 is the *decade* of agents.” -@karpathy at @ycombinator AI Startup School [image]Mckay Wrigley / @mckaywrigley: Drop everything you're doing right now and watch Andrej Karpathy's talk from YC startup school. “Software in the era of AI” It's unbelievable. [image]Aadit Sheth / @aaditsh: Andrej Karpathy literally shows how to build apps by prompting in 30 mins [video]Kadir / @kdrnp: Andrej Karpathy just broke down how software is changing fast. It hasn't really evolved in 70 years. Now it's shifted twice in under five. My 30-second summary from his AI Startup School keynote: [image]@vitrupo: Andrej Karpathy says don't go full Iron Man robot — not yet. Today's AI is too fallible. The better product is the suit: fast feedback, partial autonomy, human in the loop. But build for the dial. It doesn't fly itself until it does. [video]Atharva / @atharvaraykar: I was seeing @karpathy's Software 3.0 talk, as one should. Surreal to see him recommend my writing to make a point on AI-assisted coding “Is that me on TV??” moment [image]Haider / @slow_developer: Andrej Karpathy says self-driving felt imminent back in 2013 — but 12 years later, full autonomy still isn't here “there's still a lot of human in the loop” he warns against hype: 2025 is not the year of agents; this is the decade of agents [video]Aaron Levie / @levie: Nailing the right AI Agent UX right now is critical. Requiring too much human interventions won't deliver enough value. Handing off all the work without user validation doesn't quite work yet. Build UX patterns that live in the middle, but that can evolve to full autonomy.@ycombinator: Andrej Karpathy's (@karpathy) keynote yesterday at AI Startup School in San Francisco. [video]Rohan Paul / @rohanpaul_ai: Andrej Karpathy: Software Is Changing (Again) Key learning points from this brilliant lecture from yesterday. 🚀 The Shifting Software Map For 70 years code flowed in one style, then neural networks arrived and rewrote large patches of logic. Karpathy divides eras into [image]Deniz Birlikci / @denizbirlikci: 🧵 @karpathy dropped the most compelling lecture at the AI startup school :) Here's my notes summarized with Opus. Main thesis: We're not in the “year of agents” — we're in the DECADE of agents. Here's the historical arc that explains why... ==== The Software Evolution Story [image]Aish / @aish_caliperce: Andrej Karpathy explains why human-AI collaboration often fails: we've got the workflow backwards and the bottleneck wrong. He points out that when working with AI, there's a clear pattern. The AI generates solutions quickly while humans verify the output. The goal is making [video]Karthik Kalyanaraman / @karthikkalyan90: If anyone at GCP/AWS/Azure watched the latest Karpathy talk, it should be very clear to them that the highest impact immediate ROI work they can do is to make their docs LLM friendly. Like just do the work to write it from scratch, test it with the SOTA models and release it as aNiels Rogge / @nielsrogge: “Hugging Face is basically the equivalent of Github in the era of software 2.0” - Karpathy, 2025, colorized [image]Amit Goel / @amittwitr: Everyone's hyped about autonomous agents (which fail so often. don't complete the entire task. something breaks) But Andrej Karpathy makes a dead-simple point: we've got the loop backwards. Al is fast at generating. Humans are slow at verifying. So speed doesn't come fromTaarush Grover / @tagrtagr: In case you forget @karpathy's vocabulary that will run the next decade: - autonomy slider - vibe coding - agents as an iron man suit - his pop culture references - demo-to-product gap - semi-autonomous agents [video]Jeremy Howard / @jeremyphoward: Thank you @karpathy for the shout-out to llms.txt in your wonderful talk about software 3.0 https://www.youtube.com/... [image]Aish / @aish_caliperce: Andrej Karpathy explains why he thinks of LLMs as “people spirits.” He describes them as simulations of people. The technical machinery is a transformer neural network that processes text in chunks, applying equal computing power to each piece. The system learns by reading [video]Matthew Berman / @matthewberman: New @karpathy talk just dropped! AI, software 2.0, infra, LLM as an operating system, new coding paradigm, vibe coding, and so much more! [video]Alex Cheema / @alexocheema: .@karpathy shouted out my work on @exolabs at @ycombinator AI SUS! “we use LLMs similarly to mainframes in the '70s - compute is timeshared by having a slice in the batch dimension. models will compress over time, and with this we'll be able to run more on-device” [image]@kuluruvineeth: Karpathy take on building for LLMs than Humans (What SAAS Normally does) [video], Surge AI, a data labeling startup led by Edwin Chen, has surpassed Scale AI in revenue, generating over $1 billion in 2024 compared to Scale AI's $870 million. Unlike Scale AI, Surge AI has achieved this growth without raising any outside capital and has remained consistently profitable. This development highlights a.., A look at Scale AI rival Surge AI, which raised no outside capital, told staff it had $1B+ in 2024 revenue, vs. Scale's $870M, and has always been profitable — For years, data labeling existed in a tucked-away corner of Silicon Valley, a critical but unglamorous area of AI where companies ….
But as The Information reported on Thursday, competitor Surge AI has quietly surpassed Scale in revenue, pulling in $1 billion last year. Scale, in comparison, reportedly brought in $870, Discover how Surge AI, a human-centered, bootstrapped data-labeling startup, is outperforming rivals like Scale AI—while staying profitable, productive, and committed to ethical AI development., Artificial Intelligence The Little-Known Startup That Has Surged Past Scale AI—Without Any Investors After Meta Platforms’ Scale AI deal, data labeling is looking like Silicon Valley’s hot new interest. That’s an enormous opportunity for Edwin Chen's Surge AI., Clients of Scale AI, concerned about potential bias and conflicts of interest, are turning to alternatives like Surge AI. This shift highlights the importance of data sovereignty and unbiased data sources in AI development., Surge AI CEO Edwin Chen shares how Surge AI grew to $1B over the past 7 years. Surge AI has raised $25M. See more Surge AI data here., .