#Karpathy Autoresearch Github Programmd

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#Karpathy Autoresearch Github Programmd Reel by @cloudwithkarl - Andrej Karpathy just open-sourced autoresearch: a framework where AI agents don't just tune hyperparameters, they rewrite the entire training codebase
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@cloudwithkarl
Andrej Karpathy just open-sourced autoresearch: a framework where AI agents don't just tune hyperparameters, they rewrite the entire training codebase to improve model performance. I break down how it works in under 2 minutes. What's in this video? - How autoresearch goes beyond hyperparameter optimization by rewriting source code - The clever use of Git for experiment tracking and automatic rollback - A walkthrough of the 3-file, 630-line codebase - Why this combination of code-writing agents and systematic experimentation matters Timestamps 0:00 - Agents rewriting their own code 0:10 - Hyperparameter optimization vs. autoresearch 0:28 - How the agent proposes and evaluates changes 0:37 - Git-based experiment tracking 0:55 - The 3-file codebase walkthrough 1:14 - program.md: the agent's instructions 1:27 - The big picture: agents + experiments #Autoresearch #Gemini #AIAgents #MachineLearning #OpenSource
#Karpathy Autoresearch Github Programmd Reel by @mansispeaks_ (verified account) - Andrej Karpathy open-sourced a 630-line Python tool that lets an AI agent run hundreds of ML experiments overnight - and it found a bug he'd missed af
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@mansispeaks_
Andrej Karpathy open-sourced a 630-line Python tool that lets an AI agent run hundreds of ML experiments overnight — and it found a bug he’d missed after years of manual tuning. The catch: it only works in tightly constrained problems with clear metrics. Not replacing researchers, just the grunt work. Source: https://venturebeat.com/technology/andrej-karpathys-new-open-source-autoresearch-lets-you-run-hundreds-of-ai #AIResearch #Karpathy #MachineLearning #Autoresearch #OpenSource
#Karpathy Autoresearch Github Programmd Reel by @rafaeldevelops - Auto research can be used on your codebase also! What you think? #artificialintelligence #ai #llm #aiagents
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@rafaeldevelops
Auto research can be used on your codebase also! What you think? #artificialintelligence #ai #llm #aiagents
#Karpathy Autoresearch Github Programmd Reel by @interns.fun - If it's off-peak hours: I'll be prompting… $75k BTC btw👀 Auto Research is one of the newest ideas pushing the frontier of AI-assisted knowledge work
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@interns.fun
If it’s off-peak hours: I’ll be prompting… $75k BTC btw👀 Auto Research is one of the newest ideas pushing the frontier of AI-assisted knowledge work. Popularized by AI researcher Andrej Karpathy, the concept describes a system where AI models autonomously search the internet, read papers, analyze datasets, and continuously refine their understanding of a topic — essentially acting like a tireless research analyst. Instead of asking an AI for a single answer, Auto Research frameworks run iterative loops: gather information, evaluate sources, synthesize findings, then search again until the system builds a deeper, more reliable understanding. The idea reflects a broader shift in how people use AI tools. Rather than one-off prompts, developers are building research agents that can operate for hours — scraping data, summarizing academic literature, generating reports, and identifying new hypotheses. Karpathy has argued that this kind of automated research pipeline could dramatically accelerate fields like software development, science, and finance, where information synthesis is the main bottleneck. In many ways, Auto Research represents the next step beyond chatbots: AI that doesn’t just answer questions, but actively conducts research on your behalf
#Karpathy Autoresearch Github Programmd Reel by @techie0123 - Andrej Karpathy just dropped AUTORESEARCH 🔥 A tiny 630-line script that turns your single GPU into an NON-STOP AI researcher! 😱 Karpathy's Autorese
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@techie0123
Andrej Karpathy just dropped AUTORESEARCH 🔥 A tiny 630-line script that turns your single GPU into an NON-STOP AI researcher! 😱 Karpathy's Autoresearch = AI does ML research 24/7 on 1 GPU! Edits code → 5-min tests → better models overnight 11% faster training discovered automatically 🤯 github.com/karpathy/autoresearch AGI loading... 👀 #AI #Karpathy #aiexploration #artificialintelligence #nextgenaihub
#Karpathy Autoresearch Github Programmd Reel by @aickstudio - AI just crossed a line. 🤯 Andrej Karpathy's Auto Research shows how AI can test, improve, and rerun its own training code while you sleep. This is
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@aickstudio
AI just crossed a line. 🤯 Andrej Karpathy’s Auto Research shows how AI can test, improve, and rerun its own training code while you sleep. This is bigger than coding faster. It hints at a future where humans set the goal, and AI runs the research loop. If that happens, how does our role change? Comment “future” if you’d trust AI to do this. Link in bio for the full breakdown. #ai #machinelearning #andrejkarpathy
#Karpathy Autoresearch Github Programmd Reel by @its_xiao.zeng - Comment "RESEARCH" I'll send this to you. An AI just ran 100 experiments in a single night. No human touched it. And it found improvements that the g
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@its_xiao.zeng
Comment "RESEARCH" I'll send this to you. An AI just ran 100 experiments in a single night. No human touched it. And it found improvements that the guy who built it hadn't found himself. This is called autoresearch. Andrej Karpathy — the person who led AI at Tesla and co-founded OpenAI — released it for free this week. And I want to break this down for you because it's the clearest example of what people mean when they say "AI agent." So here's how it works — and I promise, no technical jargon. The entire thing is three files. Think of it like this. File one is the rulebook. It defines what the AI is not allowed to change, and it defines exactly how you measure success. One number. Did it go up or did it go down. That's it. File two is the workspace. This is the only thing the AI is allowed to touch. It's 630 lines of code that control how a small AI model gets trained. The agent can change anything in this file — the structure, the settings, the math — whatever it thinks might make the result better. File three is the job description. And this is the part that blew my mind. It's a plain English document — not code — where the human writes instructions like "try different approaches," "if something crashes, fix it and move on," and — this is a direct quote — "NEVER STOP. The human might be asleep." So you start it. You go to bed. And the AI reads its job description, makes one small change to the workspace, runs a 5-minute test, checks the score. If the score got better, it saves the change. If it didn't, it throws it away and goes back to where it started. Then it does it again. And again. Twelve experiments per hour. A hundred by morning. When Karpathy ran this himself, here's what happened. The AI tried about 700 changes. Out of those, roughly 20 actually improved the result — and they stacked on top of each other, shaving 11 percent off the total training time.
#Karpathy Autoresearch Github Programmd Reel by @ajaydeep.dev - Automating Discovery: Inside Karpathy's Autoresearch Imagine a researcher that never sleeps, an autonomous engine designed to accelerate scientific d
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@ajaydeep.dev
Automating Discovery: Inside Karpathy's Autoresearch Imagine a researcher that never sleeps, an autonomous engine designed to accelerate scientific discovery. This is the core of Andrej Karpathy’s autoresearch project. explore here : https://github.com/karpathy/autoresearch
#Karpathy Autoresearch Github Programmd Reel by @v.i.s.h.ai (verified account) - Comment "ML" for the link Andrej Karpathy launched Auto research an open source project
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@v.i.s.h.ai
Comment “ML” for the link Andrej Karpathy launched Auto research an open source project
#Karpathy Autoresearch Github Programmd Reel by @future.is.ai - Andrej Karpathy, a founding member of OpenAI and former Tesla AI Director, believes that mastery in the AI era still demands the classic "10,000-hour
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@future.is.ai
Andrej Karpathy, a founding member of OpenAI and former Tesla AI Director, believes that mastery in the AI era still demands the classic "10,000-hour rule" of deliberate practice. Speaking on the Lex Fridman Podcast, he argued that beginners often waste time agonizing over which specific language or framework to learn, when they should instead focus on the sheer volume of their work. Karpathy asserts that there is a level of determinism to expertise; if you pick any technical domain and put in the hours of coding and debugging, you will inevitably become an expert through the "march of nines" in quality. However, as of early 2026, Karpathy warns that the nature of these 10,000 hours is changing from manual syntax to "agentic orchestration." He recently admitted to feeling a sense of "atrophy" in his own coding skills as AI agents take over the bulk of implementation, shifting his role toward reviewing and guiding automated workflows. For beginners, this means the goal is no longer just learning to type code, but learning to deeply understand the underlying systems so they can effectively supervise the "stochastic and fallible" AI agents that now do the heavy lifting. Is becoming an AI "orchestrator" as satisfying as being a builder? Follow @future.is.ai #fyp #life #ai
#Karpathy Autoresearch Github Programmd Reel by @pp.xtudio (verified account) - An OpenAI cofounder just built an AI that improves itself. When Elon Musk warned about the coming AI singularity, most people ignored it. But somethi
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@pp.xtudio
An OpenAI cofounder just built an AI that improves itself. When Elon Musk warned about the coming AI singularity, most people ignored it. But something interesting just happened. Andrej Karpathy, former OpenAI cofounder, revealed an experimental system called Autoresearch. It’s an AI agent that runs machine learning experiments completely on its own. Give it a single GPU, leave it overnight, and it can run around 100 experiments without human help. In just two days, the system ran 650 experiments and discovered 20 improvements. It even reduced the “Time to GPT-2” training metric from 2.02 hours to 1.80 hours — an 11% efficiency gain on code Karpathy believed was already optimized. Here’s how it works 👇 The agent modifies the training code, runs a quick experiment, checks if performance improves, keeps the change if it works, and discards it if it doesn’t. Then it repeats this loop again and again. In other words, AI is starting to automate the research process itself. It’s still a small prototype — not the singularity yet — but it might be one of the earliest glimpses of self-improving AI systems. #AI #MachineLearning #TechNews
#Karpathy Autoresearch Github Programmd Reel by @youdontdoge - Andrej Karpathy just dropped "Autoresearch" - a script that ran 700 AI experiments overnight and improved a model by 11% on its own. We're not at the
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@youdontdoge
Andrej Karpathy just dropped "Autoresearch" — a script that ran 700 AI experiments overnight and improved a model by 11% on its own. We're not at the end of human potential. We're at the beginning of human + AI leverage. Anyone with a laptop and a good idea can now compete with billion-dollar labs. This is what abundance looks like. The tools are here. Use them. 🙌 #AI #Karpathy #Autoresearch #MachineLearning #Abundance #FutureOfWork #AITools #Tech

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