Get live statistics and analysis of Mira Murati's profile on X / Twitter

OpenAI is nothing without its people

I shared the following note with the OpenAI team today.

I started Thinking Machines Lab alongside a remarkable team of scientists, engineers, and builders. We're building three things: - Helping people adapt AI systems to work for their specific needs - Developing strong foundations to build more capable AI systems - Fostering a culture of open science that helps the whole field understand and improve these systems Our goal is simple, advance AI by making it broadly useful and understandable through solid foundations, open science, and practical applications. https://t.co/y2Bbl6BKF9

💙

In just 5 days since launch, ChatGPT has reached over 1M users. Thank you for your feedback to help us improve the platform!

Thinking Machines Lab exists to empower humanity through advancing collaborative general intelligence. We're building multimodal AI that works with how you naturally interact with the world - through conversation, through sight, through the messy way we collaborate. We're excited that in the next couple months we’ll be able to share our first product, which will include a significant open source component and be useful for researchers and startups developing custom models. Soon, we’ll also share our best science to help the research community better understand frontier AI systems. To accelerate our progress, we’re happy to confirm that we’ve raised $2B led by a16z with participation from NVIDIA, Accel, ServiceNow, CISCO, AMD, Jane Street and more who share our mission. We’re always looking for extraordinary talent that learns by doing, turning research into useful things. We believe AI should serve as an extension of individual agency and, in the spirit of freedom, be distributed as widely and equitably as possible.  We hope this vision resonates with those who share our commitment to advancing the field. If so, join us. https://t.co/EaAKidpany

Today we launched Tinker. Tinker brings frontier tools to researchers, offering clean abstractions for writing experiments and training pipelines while handling distributed training complexity. It enables novel research, custom models, and solid baselines. Excited to see what people build.

🚢ing

At OpenAI, we’re working to advance scientific understanding to help improve human well-being. The AI tools we are building, like Sora, GPT-4o, DALL·E and ChatGPT, are impressive from a technical standpoint. But what really matters is how they’re starting to change the way we interact with information and ideas. A few years ago, in my essay "Language & Coding Creativity", I wrote about how these systems represent a big shift in our relationship with language and creativity. As we keep improving these tools, our mission stays the same: to make them helpful, safe, easy to use, and available to as many people as possible. We want to help reduce the obstacles that have traditionally kept people from expressing their unique ideas and perspectives. By carefully designing these technologies to collaborate with human creators, I think we can build wonderful tools to help artists have more control, be more innovative, and explore new frontiers of possibility. When we made DALL·E, we worked closely with artists, designers, and storytellers, trying to build a tool that fits into their creative process and helps bring their visions to life. Moving forward, I believe AI has the potential to democratize creativity on an unprecedented scale. A person’s creative potential should not be limited by their access to resources, education, or industry connections. AI tools could lower the barriers and allow anyone with an idea to create. At the same time, we must be honest and acknowledge that AI will automate certain tasks. Just like spreadsheets changed things for accountants and bookkeepers, AI tools can do things like writing online ads or making generic images and templates. But it's important to recognize the difference between temporary creative tasks and the kind that add lasting meaning and value to society. With AI tools taking on more repetitive or mechanistic aspects of the creative process, like generating SEO metadata, we can free up human creators to focus on higher-level creative thinking and choices. This lets artists stay in control of their vision and focus their energy on the most important parts of their work. To make sure these technologies are developed and used in a way that does the most good and the least harm, we work closely with red-teaming experts from early stages of research. We also use an iterative approach, gradually releasing tools and carefully studying how they impact the real world to guide future development. Protecting and strengthening the most valuable aspects of creativity is fundamental to our human experience.  Realizing the potential of AI is not guaranteed. It takes carefully building tools and using them responsibly, in close partnership with creators and communities they’re intended to benefit. This means putting strong safeguards in place, reducing harmful biases, and proactively dealing with potential negative effects. At OpenAI, this is at the core of how we work, and we’ve never wavered in our commitment to this as we've released new tools.

A big part of our mission at Thinking Machines is to improve people’s scientific understanding of AI and work with the broader research community. Introducing Connectionism today to share some of our scientific insights.

We’re sharing Sora, text-to-video model that creates min long insanely magical scenes

Today we rolled out OpenAI o1-preview and o1-mini to all ChatGPT Plus/Team users & Tier 5 developers in the API. o1 marks the start of a new era in AI, where models are trained to "think" before answering through a private chain of thought. The more time they take to think, the better they handle complex reasoning. We're no longer limited by pretraining paradigm; now, we can scale through inference compute, opening up new possibilities for capabilities and alignment. Chain-of-thought offers new opportunities for advances in safety and alignment research by making the model's reasoning transparent—allowing us to observe its thought process step by step—and enabling it to actively reason about safety rules, which makes it more resilient in unexpected or novel situations. Looking forward to seeing what you build, create, and discover.

OpenAI is nothing without its people

I shared the following note with the OpenAI team today.

At OpenAI, we’re working to advance scientific understanding to help improve human well-being. The AI tools we are building, like Sora, GPT-4o, DALL·E and ChatGPT, are impressive from a technical standpoint. But what really matters is how they’re starting to change the way we interact with information and ideas. A few years ago, in my essay "Language & Coding Creativity", I wrote about how these systems represent a big shift in our relationship with language and creativity. As we keep improving these tools, our mission stays the same: to make them helpful, safe, easy to use, and available to as many people as possible. We want to help reduce the obstacles that have traditionally kept people from expressing their unique ideas and perspectives. By carefully designing these technologies to collaborate with human creators, I think we can build wonderful tools to help artists have more control, be more innovative, and explore new frontiers of possibility. When we made DALL·E, we worked closely with artists, designers, and storytellers, trying to build a tool that fits into their creative process and helps bring their visions to life. Moving forward, I believe AI has the potential to democratize creativity on an unprecedented scale. A person’s creative potential should not be limited by their access to resources, education, or industry connections. AI tools could lower the barriers and allow anyone with an idea to create. At the same time, we must be honest and acknowledge that AI will automate certain tasks. Just like spreadsheets changed things for accountants and bookkeepers, AI tools can do things like writing online ads or making generic images and templates. But it's important to recognize the difference between temporary creative tasks and the kind that add lasting meaning and value to society. With AI tools taking on more repetitive or mechanistic aspects of the creative process, like generating SEO metadata, we can free up human creators to focus on higher-level creative thinking and choices. This lets artists stay in control of their vision and focus their energy on the most important parts of their work. To make sure these technologies are developed and used in a way that does the most good and the least harm, we work closely with red-teaming experts from early stages of research. We also use an iterative approach, gradually releasing tools and carefully studying how they impact the real world to guide future development. Protecting and strengthening the most valuable aspects of creativity is fundamental to our human experience.  Realizing the potential of AI is not guaranteed. It takes carefully building tools and using them responsibly, in close partnership with creators and communities they’re intended to benefit. This means putting strong safeguards in place, reducing harmful biases, and proactively dealing with potential negative effects. At OpenAI, this is at the core of how we work, and we’ve never wavered in our commitment to this as we've released new tools.

I started Thinking Machines Lab alongside a remarkable team of scientists, engineers, and builders. We're building three things: - Helping people adapt AI systems to work for their specific needs - Developing strong foundations to build more capable AI systems - Fostering a culture of open science that helps the whole field understand and improve these systems Our goal is simple, advance AI by making it broadly useful and understandable through solid foundations, open science, and practical applications. https://t.co/y2Bbl6BKF9

Thinking Machines Lab exists to empower humanity through advancing collaborative general intelligence. We're building multimodal AI that works with how you naturally interact with the world - through conversation, through sight, through the messy way we collaborate. We're excited that in the next couple months we’ll be able to share our first product, which will include a significant open source component and be useful for researchers and startups developing custom models. Soon, we’ll also share our best science to help the research community better understand frontier AI systems. To accelerate our progress, we’re happy to confirm that we’ve raised $2B led by a16z with participation from NVIDIA, Accel, ServiceNow, CISCO, AMD, Jane Street and more who share our mission. We’re always looking for extraordinary talent that learns by doing, turning research into useful things. We believe AI should serve as an extension of individual agency and, in the spirit of freedom, be distributed as widely and equitably as possible.  We hope this vision resonates with those who share our commitment to advancing the field. If so, join us. https://t.co/EaAKidpany

ChatGPT app for iOS now in 🇦🇱🇭🇷🇫🇷🇩🇪🇮🇪🇯🇲🇰🇷🇳🇿🇳🇮🇳🇬🇬🇧 and more to come soon!

🚢ing

One year since GPT-4 deployment: From GPT-1 and 2 establishing the language model paradigm, through GPT-3's scaling predictions, to GPT-4 showing how complex systems emerge, mimicking nature’s unpredictable patterns from simple elements. An exploration from observation to deep,

We have parted ways with Barret Zoph. Soumith Chintala will be the new CTO of Thinking Machines. He is a brilliant and seasoned leader who has made important contributions to the AI field for over a decade, and he’s been a major contributor to our team. We could not be more excited to have him take on this new responsibility.

In just 5 days since launch, ChatGPT has reached over 1M users. Thank you for your feedback to help us improve the platform!

💙

All Plus and Team users in ChatGPT

Today we rolled out OpenAI o1-preview and o1-mini to all ChatGPT Plus/Team users & Tier 5 developers in the API. o1 marks the start of a new era in AI, where models are trained to "think" before answering through a private chain of thought. The more time they take to think, the better they handle complex reasoning. We're no longer limited by pretraining paradigm; now, we can scale through inference compute, opening up new possibilities for capabilities and alignment. Chain-of-thought offers new opportunities for advances in safety and alignment research by making the model's reasoning transparent—allowing us to observe its thought process step by step—and enabling it to actively reason about safety rules, which makes it more resilient in unexpected or novel situations. Looking forward to seeing what you build, create, and discover.