The news is a blow for Thinking Machines Lab. Two narratives are already emerging about what happened. Thinking Machines cofounders Barret Zoph and Luke Metz are leaving the fledgling AI lab and rejoining OpenAI, the ChatGPT-maker announced on Thursday. OpenAI's CEO of applications, Fidji Simo, shared the news in a memo to staff Thursday afternoon. The news was first reported on X by technology reporter Kylie Robison, who wrote that Zoph was fired for "unethical conduct."

Outcome-driven reinforcement learning has advanced reasoning in large language models (LLMs), but prevailing tool-augmented approaches train a single, monolithic policy that interleaves thoughts and tool calls under full context; this scales poorly with long horizons and diverse tools and generalizes weakly to new scenarios. Agentic systems offer a promising alternative by decomposing work across specialized modules, yet most remain training-free or rely on offline training decoupled from the live dynamics of multi-turn interaction. We introduce AgentFlow, a trainable, in-the-flow agentic framework that coordinates four modules (planner, executor, verifier, generator) through an evolving memory and directly optimizes its planner inside the multi-turn loop. To train on-policy in live environments, we propose Flow-based Group Refined Policy Optimization (Flow-GRPO), which tackles long-horizon, sparse-reward credit assignment by converting multi-turn optimization into a sequence of tractable single-turn policy updates. It broadcasts a single, verifiable trajectory-level outcome to every turn to align local planner decisions with global success and stabilizes learning with group-normalized advantages. Across ten benchmarks, AgentFlow with a 7B-scale backbone outperforms top-performing baselines with average accuracy gains of 14.9% on search, 14.0% on agentic, 14.5% on mathematical, and 4.1% on scientific tasks, even surpassing larger proprietary models like GPT-4o. Further analyses confirm the benefits of in-the-flow optimization, showing improved planning, enhanced tool-calling reliability, and positive scaling with model size and reasoning turns.

This is the latest confirmation that the "great man" theory of history continues to thrive in Silicon Valley. As such, it joins a genre that includes Walter Isaacson's twin tomes on Steve Jobs and Elon Musk, Brad Stone's book on Jeff Bezos, Michael Becraft's on Bill Gates, Max Chafkin's on Peter Thiel and Michael Lewis's on Sam Bankman-Fried. Notable characteristics of the genre include a tendency towards founder worship, discreet hagiography and a Whiggish interpretation of the life under examination. The great man under Witt's microscope is the co-founder and chief executive of Nvidia, a chip design company that went from being a small but plucky purveyor of graphics processing units (GPUs) for computer gaming to its current position as the third most valuable company in the world. Two things drove this astonishing transition.

Consciousness is commonly tied to being alive; a trait that allows one to be self-aware of themselves and their place in the world. However, whether or not consciousness is tied to our conventional definition of what it means to be alive is now a topic of discussion amongst roboticists and philosophers. A key difference, according to some academic circles, is that consciousness is considered to be multi-dimensional, while at the same time, artificial and human consciousness may in fact be more closely related than we think. According to renowned Australian robotics philosopher David Chalmers, consciousness should be analyzed from an object's point of view of experience. As quoted in his 1995 paper on defining consciousness, he wrote: "A subject is conscious when she feels visual experiences, bodily sensations, mental images, emotions."

Many histories of AI start with Homer and his description of how the crippled, blacksmith god Hephaestus fashioned for himself self-propelled tripods on wheels and "golden" assistants, "in appearance like living young women" who "from the immortal gods learned how to do things." I prefer to stay as close as possible to the notion of "artificial intelligence" in the sense of intelligent humans actually creating, not just imagining, tools, mechanisms, and concepts for assisting our cognitive processes or automating (and imitating) them. UNITED STATES - CIRCA 1943: Machine's Can't Think (Photo by Buyenlarge/Getty Images) In 1308, Catalan poet and theologian Ramon Llull completed Ars generalis ultima (The Ultimate General Art), further perfecting his method of using paper-based mechanical means to create new knowledge from combinations of concepts. Llull devised a system of thought that he wanted to impart to others to assist them in theological debates, among other intellectual pursuits. He wanted to create a universal language using a logical combination of terms.

I still remember walking past the tabletop game store in the mall when I was a kid. I used to think, "that looks really interesting, but everyone would think I'm a nerd if I started playing it." Admittedly, I am most definitely a nerd, and proud of it. But only recently have I begun diving into the world of tabletop games like Dungeons & Dragons (otherwise known as D&D). The poster (left), from one of the many Dungeons & Dragons-themed films of recent decades, gives some sense of the genre.

In the recent podcast, "Can We Upload Ourselves to a Computer and Live Forever?", Walter Bradley Center director Robert J. Marks and computer scientist Selmer Bringsjord discuss whether we could achieve immortality by uploading our minds to computers. The year 2029 is the consistent date I've predicted, when an artificial intelligence will pass a valid Turing test -- achieving human levels of intelligence. "I have also set the date 2045 for singularity -- which is when humans will multiply our effective intelligence a billion fold, by merging with the intelligence we have created. Indeed, when Kurzweil (left) became a director of engineering at Google in 2012, he not only mainstreamed the basic idea but he "heralded, for many, a symbolic merger between transhumanist philosophy and the clout of major technological enterprise." (The Guardian, 2017). Beyond the Valley, the project gets more ambitious. In a recent piece at Gizmodo, Toronto-based writer George Dvorsky advocates uploading our minds to supercomputers somewhere in the universe, a proposal he calls Distributed Humanity: "Entire civilizations could live on a single supercomputer, enabling the existence of potentially trillions upon trillions of individuals, each of them a single brain emulation.

This should show you just how bad anti-Islam arguments are. Unlike many internet Islamophobes, Holland is a PhD historian & this is the best argument he has. Which is just speculation & is easily refuted just like that.pic.twitter.com/C8GNaW35eC

The greater use of artificial intelligence (AI) and autonomous systems by the militaries of the world has the potential to affect deterrence strategies and escalation dynamics in crises and conflicts. Up until now, deterrence has involved humans trying to dissuade other humans from taking particular courses of action. What happens when the thinking and decision processes involved are no longer purely human? How might dynamics change when decisions and actions can be taken at machine speeds? How might AI and autonomy affect the ways that countries have developed to signal one another about the potential use of force?

Smart cities, search engines, autonomous vehicles: The pairing of massive data sets and self-learning algorithms is transforming the world around us in ways that are not always easy to grasp. The strange ways computers "think" are hidden within opaque proprietary code. It has been called the "end of theory." There is a danger, says Paola Sturla, Lecturer in Landscape Architecture at the Harvard Graduate School of Design, that human agency will be nudged out of the picture. Sturla, who is trained as an architect and landscape architect, has called on designers to renew the tradition of humanism.