Go
A Game Plan for the AI Boom
Ten years ago, AlphaGo trounced human competitors--and its legacy is still present in today's most advanced bots. Thore Graepel may have been the first human to be vanquished by a superintelligence. In 2015, on his first day as a researcher at Google DeepMind, he was challenged to play against the earliest iteration of AlphaGo--a computer program developed by DeepMind that would prove so effective at the ancient-Chinese game of (or Go, as it is commonly known in the West) that it changed how humans play it, and then upended the field of AI itself. When Graepel faced it, AlphaGo was just a "baby" project, as he put it to me, and he was an accomplished amateur player. But it still took him down.
The Good Robot podcast: what makes a drone "good"? with Beryl Pong
The Good Robot podcast: what makes a drone "good"? Hosted by Eleanor Drage and Kerry McInerney, The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. What makes a drone "good"? In this episode, we talk to Beryl Pong, UKRI Future Leaders Fellow at the University of Cambridge, where she leads the Centre for Drones and Culture. Beryl reflects on what it means to think about drones as "good" or "ethical" technologies and how it can be assessed through its socio-political context.
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Robot Dogs Are on Going on Patrol at the 2026 World Cup in Mexico
The Mexican city of Guadalupe, which will host portions of the 2026 World Cup, recently showed off four new robot dogs that will help provide security during matches at BBVA Stadium. The K9-X "robodogs" will help officers patrol during the 2026 World Cup this summer. Authorities in Mexico's Guadalupe, Nuevo León, this week unveiled four robot dogs that will be part of the security devices at BBVA Stadium, one of the three Mexican venues of the 2026 World Cup . The robot dogs are not armed, but each unit incorporates video cameras, night vision, and communication systems that are used to issue warnings or instructions. Its function is to deter illegal activity, detect unusual behavior, identify suspicious objects, control crowds, and immediately alert law enforcement when the system deems necessary. Robot dogs operate semi-autonomously: They do not make decisions or execute movements on their own.
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I've Changed My Mind: Robots Adapting to Changing Human Goals during Collaboration
Ghose, Debasmita, Gitelson, Oz, Jin, Ryan, Abawe, Grace, Vazquez, Marynel, Scassellati, Brian
I've Changed My Mind: Robots Adapting to Changing Human Goals during Collaboration Abstract --For effective human-robot collaboration, a robot must align its actions with human goals, even as they change mid-task. Prior approaches often assume fixed goals, reducing goal prediction to a one-time inference. However, in real-world scenarios, humans frequently shift goals, making it challenging for robots to adapt without explicit communication. We propose a method for detecting goal changes by tracking multiple candidate action sequences and verifying their plausibility against a policy bank. Upon detecting a change, the robot refines its belief in relevant past actions and constructs Receding Horizon Planning (RHP) trees to actively select actions that assist the human while encouraging Differentiating Actions to reveal their updated goal. We evaluate our approach in a collaborative cooking environment with up to 30 unique recipes and compare it to three comparable human goal prediction algorithms. Our method outperforms all baselines, quickly converging to the correct goal after a switch, reducing task completion time and improving collaboration efficiency. N real-world scenarios, humans often change their goals in response to evolving circumstances, new information, or spontaneous decisions. Previous work often addresses changing human goals by relying on explicit communication [1], [2], [3]. While effective, relying on communication assumes humans can and will communicate with the robot, which is often impractical due to physical, situational, or cognitive constraints [4], [5], [6], [7], [8].
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What makes a quantum computer good?
What makes a quantum computer good? Claims that one quantum computer is better than another rest on terms like quantum advantage or quantum supremacy, fault-tolerance or qubits with better coherence - what does it all mean? Eleven years ago, I was just getting a start on my PhD in theoretical physics, and to be honest with you I never thought about quantum computers, or writing about them, at all. Meanwhile, staff were hard at work putting together the world's first " Quantum computer buyer's guide " (we've always been ahead of the curve). Looking through it reveals what a different time it was - John Martinis at University of California, Santa Barbara got a shout out for working on an array of only nine qubits, and just last week he was awarded the Nobel Prize in Physics .
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Diverse Randomized Agents Vote to Win
We investigate the power of voting among diverse, randomized software agents. With teams of computer Go agents in mind, we develop a novel theoretical model of two-stage noisy voting that builds on recent work in machine learning. This model allows us to reason about a collection of agents with different biases (determined by the first-stage noise models), which, furthermore, apply randomized algorithms to evaluate alternatives and produce votes (captured by the second-stage noise models). We analytically demonstrate that a uniform team, consisting of multiple instances of any single agent, must make a significant number of mistakes, whereas a diverse team converges to perfection as the number of agents grows. Our experiments, which pit teams of computer Go agents against strong agents, provide evidence for the effectiveness of voting when agents are diverse.
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Fostering Robots: A Governance-First Conceptual Framework for Domestic, Curriculum-Based Trajectory Collection
Pablo-Marti, Federico, Fernandez, Carlos Mir
We propose a conceptual, empirically testable framework for Robot Fostering, -a curriculum-driven, governance-first approach to domestic robot deployments, emphasizing long-term, curated interaction trajectories. We formalize trajectory quality with quantifiable metrics and evaluation protocols aligned with EU-grade governance standards, delineating a low-resource empirical roadmap to enable rigorous validation through future pilot studies.
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This AI-Powered Robot Keeps Going Even if You Attack It With a Chainsaw
A single AI model trained to control numerous robotic bodies can operate unfamiliar hardware and adapt eerily well to serious injuries. A four-legged robot that keeps crawling even after all four of its legs have been hacked off with a chainsaw is the stuff of nightmares for most people. For Deepak Pathak, cofounder and CEO of the startup Skild AI, the dystopian feat of adaptation is an encouraging sign of a new, more general kind of robotic intelligence. "This is something we call an omni-bodied brain," Pathak tells me. His startup developed the generalist artificial intelligence algorithm to address a key challenge with advancing robotics: "Any robot, any task, one brain.
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Breaking encryption with a quantum computer just got 20 times easier
Quantum computers could crack a common data encryption technique once they have a million qubits, or quantum bits. While this is still well beyond the capabilities of existing quantum computers, this new estimate is 20 times lower than previously thought, suggesting the day encryption is cracked is closer than we think.
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