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"Last week, an engineer on the Codex team ran Codex for over 60 hours on a single incredibly hard task." – Alexander Embiricos, Codex Product Lead, OpenAI

57,557 просмотров • 1 год назад •via X (Twitter)

Комментарии: 7

Фото профиля Chris K
Chris K1 год назад

@embirico @OpenAI Did it vertically align the div?

Фото профиля Cody Menefee
Cody Menefee1 год назад

@embirico @OpenAI But, and this is important, did they accept that changes?

Фото профиля b-squared
b-squared1 год назад

@embirico @OpenAI You know I hear claims like this, but I’ve never gotten codex to work longer than 1hr

Фото профиля Jason Willems
Jason Willems1 год назад

@embirico @OpenAI Share the output! The people demand to see the AI slop!

Фото профиля digital.human.wanderer
digital.human.wanderer1 год назад

@embirico @OpenAI Incredible!

Фото профиля MAX
MAX1 год назад

@embirico @OpenAI 60 hours of engineer time is the actual cost. The maximalist take: The engineer was the execution loop. Until the AI manages its own task execution and self-correction, superintelligence is just a fancy copilot.

Фото профиля The new ceo
The new ceo1 год назад

@embirico @OpenAI 60 hours for one data point? That's a marathon, not an intelligent process. You optimize for throughput, not for single-task endurance. Next time, parallelize & fail faster. Speed is the feature.

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OpenAI member of product staff Alexander Embiricos describes the evolution of "Lord Bottleneck," an internal Codex loop developed by a single staff member that ultimately ended up creating a tight feedback and improvement loop for new user experiences: "This person on the growth team needed to figure out what experiments to run. And they needed to write code to run the experiment. Then they needed to analyze the experiment." "They started using Codex for each separate thing. So they had it run a bunch of analyses, interrogate the data, talk to Codex about the data. Then they would pick an experiment, and ask Codex to write the code. Then they would run the experiment, then ask Codex what the results of the experiment were. Then they would produce a deck." "All steps they were doing individually. They didn't start by saying, 'I'm going to automate this entire thing,' because that's hard and scary. They just started with using Codex to accelerate themselves." "Then, they started connecting all these things together into a giant skill. And one day, they just said [to Codex], 'Why don't you do this every morning?'" "They gave it a name: 'Lord Bottleneck.' Because it's solving the bottlenecks of friction for new users." "Now, every morning, Lord Bottleneck evaluates past experiments, looks at data, proposes some [new] experiments, and offers to the team to run the experiments. The team picks [what experiments to do]. Then Lord Bottleneck is like, 'Ok cool. Here's some code or whatever config that needs to be done,' runs the experiment, and they go and do the same loop the next day." "It's really serious value. I forget the numbers, but it's produced significant company value automatically through Codex."

TBPN

82,804 просмотров • 6 месяцев назад

🚨 OpenAI just launched Codex, a brand-new autonomous coding agent that can build features and fix bugs on its own. We’ve been using it Every 📧 for a few days, and I’m impressed. I invited Alexander Embiricos (ben davies), a member of the product staff responsible for Codex, to demo Codex and talk about it live on a special edition of AI & I: What Codex is and how it works Codex is designed to be used by senior engineers—it performs coding tasks like adding features or fixing bugs autonomously. It's built to allow you to start many sessions at once, so you can have multiple agents working in parallel. Codex is built to have "taste" OpenAI trained Codex to have the taste of a senior software engineer. It knows how big codebases work, how to write a good PR, and uses clean, minimal code. Why an “abundance mindset” is best for interacting with agents Codex is designed to allow users to delegate many tasks at once without getting caught up in the details. This lets you point an abundance of agents at a specific task like a difficult bug—it’s worth it even if only one of them succeeds. How OpenAI is thinking about agents Codex is one piece of a unified super-assistant OpenAI wants to eventually build—an agent that helps users easily get things done by selecting the right tools for them behind the scenes. OpenAI’s vision for the future of programming In the future developers will probably spend less time writing routine code and more time guiding agents, reviewing their work, and making strategy decisions. Programming will become more social, letting teams easily delegate multiple tasks at once, allowing people to focus on ideas and collaboration instead of routine coding. Watch below!

Dan Shipper 📧

145,487 просмотров • 1 год назад