Mira Murati Wants Her AI to'Keep Humans in the Loop' The Thinking Machines Lab founder and former CTO of OpenAI tells WIRED she isn't interested in automating people out of jobs. Instead, she's building AI that can collaborate. Mira Murati still wants to build AI superintelligence. But the ex-CTO of OpenAI sees human intelligence as a critical part of the equation. At a time of rising worry over AI eliminating jobs and increasing the power of few big companies, Murati's startup, Thinking Machines Lab, offers a radically different vision of the technology.

PCWorld reports that Thinking Machines, founded by ex-OpenAI executive Mira Murati, has developed new AI voice interaction models that enable real-time conversations with interruptions and visual cue recognition. The technology uses a dual-AI system with a fast interaction model and background model for complex tasks, employing a multi-stream, micro-turn approach. This advancement could transform AI voice chat from current CB radio-style turn-taking into natural human-like conversations, though the technology remains in research phase. Voice chatting with today's AI can feel as stilted as an old-school CB radio exchange, where you're forced to take turns as you talk. "Hey ChatGPT, let's talk about the movies!

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.

Sixty-five years ago, Arthur Samuel went on TV to show the world how the IBM 701 plays checkers. He was interviewed on a live morning news program, sitting remotely at the 701, with Will Rogers Jr. at the TV studio, together with a checkers expert who played with the computer for about an hour. Three years later, in 1959, Samuel published "Some Studies in Machine Learning Using the Game of Checkers," in the IBM Journal of Research and Development, coining the term "machine learning." He defined it as the "programming of a digital computer to behave in a way which, if done by human beings or animals, would be described as involving the process of learning." A few months after Samuel's TV appearance, ten computer scientists convened in Dartmouth, NH, for the first-ever workshop on artificial intelligence, defined a year earlier by John McCarthy in the proposal for the workshop as "making a machine behave in ways that would be called intelligent if a human were so behaving."

A few months after Samuel's TV appearance, ten computer scientists convened in Dartmouth, NH, for the first-ever workshop on artificial intelligence, …

Sixty-five years ago, Arthur Samuel went on TV to show the world how the IBM 701 plays checkers. He was interviewed on a live morning news program, sitting remotely at the 701, with Will Rogers Jr. at the TV studio, together with a checkers expert who played with the computer for about an hour. Three years later, in 1959, Samuel published "Some Studies in Machine Learning Using the Game of Checkers," in the IBM Journal of Research and Development, coining the term "machine learning." He defined it as the "programming of a digital computer to behave in a way which, if done by human beings or animals, would be described as involving the process of learning." On February 24, 1956, Arthur Samuel's Checkers program, which was developed for play on the IBM 701, ... [ ] was demonstrated to the public on television A few months after Samuel's TV appearance, ten computer scientists convened in Dartmouth, NH, for the first-ever workshop on artificial intelligence, defined a year earlier by John McCarthy in the proposal for the workshop as "making a machine behave in ways that would be called intelligent if a human were so behaving."

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.