President & Co-Founder @OpenAI
Joined July 2010
- Tweets 4,815
- Following 65
- Followers 495,334
- Likes 1,386
It is amazing how much positive velocity is created by putting something, no matter how barebones, in front of users. Delivering something useful forces you to level up your thinking & execution, and your cherished ideas get quickly validated or disproven.
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One lesson from AI progress is it’s hard to predict the relative difficulties of various skills; one lesson from AI limitations is that humans are much more capable than we give ourselves credit for.
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Really special group of people at OpenAI. Trying not to grow too fast; easy to lose the feeling of talent density. That being said, we need more help to achieve the mission, so we're growing carefully & deliberately: openai.com/careers/
i know im not supposed to brag about openai, but the talent density at this scale (375 people) is 🤯 and i dont think has happened in the tech industry in recent memory
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Microsoft + OpenAI = amazing technology available safely & usefully to the world. So much to build as we pursue our mission of ensuring AGI benefits all of humanity:
In this next phase of our partnership with @OpenAI, we will deliver the best AI infrastructure, models, and toolchain for customers to safely and responsibly build and run their applications on Azure. blogs.microsoft.com/blog/202…
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This year is 80th birthday of the McCulloch-Pitts neuron. Remains the fundamental idea behind all neural networks. Such a simple mathematical model, yet has scaled to incredible results across many orders of magnitude of compute. Hard not to feel inspired. cs.cmu.edu/~./epxing/Class/1…
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Azure OpenAI Service is now generally available. Very nice milestone in making these models widely accessible:
ChatGPT is coming soon to the Azure OpenAI Service, which is now generally available, as we help customers apply the world’s most advanced AI models to their own business imperatives. azure.microsoft.com/en-us/bl…
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ChatGPT API coming soon — sign up for the waitlist:
We've learned a lot from the ChatGPT research preview and have been making important updates based on user feedback. ChatGPT will be coming to our API and Microsoft's Azure OpenAI Service soon.
Sign up for updates here: share.hsforms.com/1u4goaXwDR…
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Abstraction is the best & worst part of programming. Amazing abstractions give the power to easily build something great; bad abstractions mean not getting anything done. Worth waiting much later to get started, and then much more effort iterating on them, than most people think.
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Collaborative research on LLM misuse & mitigation. Like for any new technology, important to maximize the upsides and mitigate the downsides:
We're publishing a report, co-authored with @CSETGeorgetown and @stanfordio, analyzing how language models could be misused for disinformation and how to mitigate those risks. openai.com/blog/forecasting-…
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Working on a professional version of ChatGPT; will offer higher limits & faster performance. If interested, please join our waitlist here: forms.gle/LMmj7wpExKv7YcX29
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Fun application of ChatGPT!
You knew it was just a matter of time until we did this (extend the @MintMobile savings with @OpenAI, that is).
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Classic software wisdom is to focus on one problem at a time. However, I often find it more productive to focus on many interrelated problems. When you get stuck on one, you can do something productive on another one — and often unstick the original by noticing the connections.
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Amazing to see the energy of the OpenAI developer community. These models are starting to unlock real opportunity to build on top of them, whether for side projects, new products, or integrations into established services.
The OpenAI cookbook is the top trending repo on Github this month!
If you haven’t checked it out, it’s an incredible resource for getting started on the API — maintained by our team (and others!)
github.com/openai/openai-coo…
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Depends on how experimental the idea is. Usually you want to start with something you know will work, and then try out one new idea at a time, each time persisting until you understand the results you're seeing fully.
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Perhaps the single most important virtue in ML engineering is persistence. The ML engineering process is one of repeatedly checking & understanding every detail of the system, until it finally goes through a phase transition from "not working at all" to "working shockingly well".
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Wrong lesson from GPT paradigm — text is all you need. Other modalities will be incredibly stunning. Can feel it already from DALL-E, which can do something quite useful despite its nascent language ability.
Big takeaway from the GPT paradigm is that the world of text is a far more complete description of the human experience than almost anyone anticipated.
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