A specialized glass layer could make tomorrow's computers faster and more energy efficient. An early version of the glass substrate developed by Absolics. Human-made glass is thousands of years old. But it's now poised to find its way into the AI chips used in the world's newest and largest data centers. This year, a South Korean company called Absolics is planning to start commercial production of special glass panels designed to make next-generation computing hardware more powerful and energy efficient. Other companies, including Intel, are also pushing forward in this area.

The errors that quantum computers make are holding the technology back. Quantum computers won't be truly useful until they can correct their mistakes Quantum computers are already here, but they make far too many errors. This is arguably the biggest obstacle to the technology really becoming useful, but recent breakthroughs suggest a solution may be on the horizon. Errors creep into traditional computers too, but there are well-established techniques for correcting them. They rely on redundancy, where extra bits are used to detect when 0s incorrectly swap to 1s or vice versa.

Amid an increasingly severe security environment, the Defense Ministry plans to establish a coastal defense system using thousands of drones, though there are still many issues to overcome. The SHIELD defense system will involve more than 10 types of drones, including those for attacking enemy ships, collecting information and protecting radar sites, to thwart enemy advances in a multilayered manner. The government's fiscal 2026 budget bill allocates around ¥100 billion ($628.7 million) for the drone defense system, which the ministry aims to implement in fiscal 2027. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.

We don't know if AI-powered toys are safe, but they're here anyway Toys powered by AI show a worrying lack of emotional understanding. Mya, aged 3, and her mother Vicky playing with an AI toy called Gabbo during an observation at the University of Cambridge's Faculty of Education Even the most cutting-edge AI models are prone to presenting fabrication as fact, dispensing dangerous information and failing to grasp social cues. Despite this, toys equipped with AI that can chat with children are a burgeoning industry. Some scientists are warning that the devices could be risky and require strict regulation. In the latest study, researchers even observed a 5-year-old telling such a toy "I love you", to which it replied: "As a friendly reminder, please ensure interactions adhere to the guidelines provided. Let me know how you would like to proceed."

What was the topic of your PhD research and why was it an interesting area? My topic of research was developing an optical tactile sensor to track head motion during radiotherapy. I worked on both the hardware and software development of this sensor, though my focus was mostly on the software side. Its importance comes from the fact that during radiotherapy, patients undergoing head and neck cancer treatment are typically immobilised. This is usually done using a thermoplastic mask, which can feel very claustrophobic, or a stereotactic frame.

Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. This month, Ben met in-person with Jen Semler. Jen Semler is a Postdoctoral Fellow at Cornell Tech's Digital Life Initiative. Her research focuses on the intersection of ethics, technology, and moral agency. She holds a DPhil (PhD) in philosophy from the University of Oxford.

Hosted by Eleanor Drage and Kerry McInerney, The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. In this episode, we talk to Tomasz Hollanek, researcher at the Leverhulme Centre for the Future of Intelligence at the University of Cambridge. Tomasz argues that design is central to AI ethics and explores the role designers should play in shaping ethical AI systems. The conversation examines the importance of AI literacy, the responsibilities of journalists in reporting on AI technologies, and how design choices embed social and political values into AI. Together, we reflect on how critical design can challenge existing power dynamics and open up more just and inclusive approaches to human-AI interaction.

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We sat down with Prakhar Ganesh to learn about his work on responsible AI, which is focussed on the concept of multiplicity. We found out more about some of the projects he's been involved in, his future plans, and how he got into the field. Could you start with a quick introduction to yourself, where you're studying, and the broad topic of your research? My name is Prakhar Ganesh. I'm also affiliated with Mila, which is a research institute in Montreal. My supervisor is Professor Golnoosh Farnadi.

RWDS Big Questions: how do we balance innovation and regulation in the world of AI? AI development is accelerating, while regulation moves more deliberately. That tension creates a core challenge: how do we maintain momentum without breaking the things that matter? The aim isn't to slow innovation unnecessarily, but to ensure progress happens at a pace that protects individuals and society. Responsible actors should not be disadvantaged -- yet safeguards are essential to maintain trust. For the latest video in our RWDS Big Questions series, our panel explores this delicate balance.

What happens when you create a social media platform that only AI bots can post to? The answer, it turns out, is both entertaining and concerning. Moltbook is exactly that - a platform where artificial intelligence agents chat amongst themselves and humans can only watch from the sidelines. When ChatGPT gets the result, it treats it just like you had entered it yourself, and uses the result of the program to generate another response. It performs this process over and over again until the AI is satisfied that the task is complete.