Enlarge / An image Ilya Sutskever tweeted with this OpenAI resignation announcement. From left to right: New OpenAI Chief Scientist Jakub Pachocki, President Greg Brockman, Sutskever, CEO Sam Altman, and CTO Mira Murati. (credit: Ilya Sutskever / X)

On Tuesday evening, OpenAI Chief Scientist Ilya Sutskever announced that he is leaving the company he co-founded, six months after he participated in the coup that temporarily ousted OpenAI CEO Sam Altman. Jan Leike, a fellow member of Sutskever's Superalignment team, is reportedly resigning with him.

"After almost a decade, I have made the decision to leave OpenAI," Sutskever tweeted. "The company’s trajectory has been nothing short of miraculous, and I’m confident that OpenAI will build AGI that is both safe and beneficial under the leadership of @sama, @gdb, @miramurati and now, under the excellent research leadership of @merettm. It was an honor and a privilege to have worked together, and I will miss everyone dearly."

Sutskever has been with the company since its founding in 2015 and is widely seen as one of the key engineers behind some of OpenAI's biggest technical breakthroughs. As a former OpenAI board member, he played a key role in the removal of Sam Altman as CEO in the shocking firing last November. While it later emerged that Altman's firing primarily stemmed from a power struggle with former board member Helen Toner, Sutskever sided with Toner and personally delivered the news to Altman that he was being fired on behalf of the board.

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On Monday, OpenAI employee William Fedus confirmed on X that a mysterious chart-topping AI chatbot known as "gpt-chatbot" that had been undergoing testing on LMSYS's Chatbot Arena and frustrating experts was, in fact, OpenAI's newly announced GPT-4o AI model. He also revealed that GPT-4o had topped the Chatbot Arena leaderboard, achieving the highest documented score ever.

"GPT-4o is our new state-of-the-art frontier model. We’ve been testing a version on the LMSys arena as im-also-a-good-gpt2-chatbot," Fedus tweeted.

Chatbot Arena is a website where visitors converse with two random AI language models side by side without knowing which model is which, then choose which model gives the best response. It's a perfect example of vibe-based AI benchmarking, as AI researcher Simon Willison calls it.

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On Monday, OpenAI debuted GPT-4o (o for "omni"), a major new AI model that can ostensibly converse using speech in real time, reading emotional cues and responding to visual input. It operates faster than OpenAI's previous best model, GPT-4 Turbo, and will be free for ChatGPT users and available as a service through API, rolling out over the next few weeks, OpenAI says.

OpenAI revealed the new audio conversation and vision comprehension capabilities in a YouTube livestream titled "OpenAI Spring Update," presented by OpenAI CTO Mira Murati and employees Mark Chen and Barret Zoph that included live demos of GPT-4o in action.

OpenAI claims that GPT-4o responds to audio inputs in about 320 milliseconds on average, which is similar to human response times in conversation, according to a 2009 study, and much shorter than the typical 2–3 second lag experienced with previous models. With GPT-4o, OpenAI says it trained a brand-new AI model end-to-end using text, vision, and audio in a way that all inputs and outputs "are processed by the same neural network."

Enlarge / Mustafa Suleyman, co-founder and chief executive officer of Inflection AI UK Ltd., during a town hall on day two of the World Economic Forum (WEF) in Davos, Switzerland, on Wednesday, Jan. 17, 2024. Suleyman joined Microsoft in March. (credit: Getty Images)

Microsoft is working on a new large-scale AI language model called MAI-1, which could potentially rival state-of-the-art models from Google, Anthropic, and OpenAI, according to a report by The Information. This marks the first time Microsoft has developed an in-house AI model of this magnitude since investing over $10 billion in OpenAI for the rights to reuse the startup's AI models. OpenAI's GPT-4 powers not only ChatGPT but also Microsoft Copilot.

The development of MAI-1 is being led by Mustafa Suleyman, the former Google AI leader who recently served as CEO of the AI startup Inflection before Microsoft acquired the majority of the startup's staff and intellectual property for $650 million in March. Although MAI-1 may build on techniques brought over by former Inflection staff, it is reportedly an entirely new large language model (LLM), as confirmed by two Microsoft employees familiar with the project.

With approximately 500 billion parameters, MAI-1 will be significantly larger than Microsoft's previous open source models (such as Phi-3, which we covered last month), requiring more computing power and training data. This reportedly places MAI-1 in a similar league as OpenAI's GPT-4, which is rumored to have over 1 trillion parameters (in a mixture-of-experts configuration) and well above smaller models like Meta and Mistral's 70 billion parameter models.

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On Thursday, renowned AI researcher Andrej Karpathy, formerly of OpenAI and Tesla, tweeted a lighthearted proposal that large language models (LLMs) like the one that runs ChatGPT could one day be modified to operate in or be transmitted to space, potentially to communicate with extraterrestrial life. He said the idea was "just for fun," but with his influential profile in the field, the idea may inspire others in the future.

Karpathy's bona fides in AI almost speak for themselves, receiving a PhD from Stanford under computer scientist Dr. Fei-Fei Li in 2015. He then became one of the founding members of OpenAI as a research scientist, then served as senior director of AI at Tesla between 2017 and 2022. In 2023, Karpathy rejoined OpenAI for a year, leaving this past February. He's posted several highly regarded tutorials covering AI concepts on YouTube, and whenever he talks about AI, people listen.

Most recently, Karpathy has been working on a project called "llm.c" that implements the training process for OpenAI's 2019 GPT-2 LLM in pure C, dramatically speeding up the process and demonstrating that working with LLMs doesn't necessarily require complex development environments. The project's streamlined approach and concise codebase sparked Karpathy's imagination.