The science of human touch - and why it's so hard to replicate in robots Robots now see the world with an ease that once belonged only to science fiction. They can recognise objects, navigate cluttered spaces and sort thousands of parcels an hour. But ask a robot to touch something gently, safely or meaningfully, and the limits appear instantly. As a researcher in soft robotics working on artificial skin and sensorised bodies, I've found that trying to give robots a sense of touch forces us to confront just how astonishingly sophisticated human touch really is. My work began with the seemingly simple question of how robots might sense the world through their bodies.

Why we should be skeptical of the hasty global push to test 15-year-olds' AI literacy in 2029 If 2022 was the year OpenAI knocked our world off course with the launch of ChatGPT, 2025 will be remembered for the frenzied embrace of AI as the solution to everything. And, yes, this includes teaching and schoolwork. In today's breakneck AI innovation race, the Organization for Economic Co-operation and Development (OECD), along with the European Commission, have called for the development of unified AI literacy strategies in kindergarten to Grade 12 education. They have done this through an AI Literacy Framework developed with Code.org, and a range of experts in computational thinking, neuroscience, AI, educational technology and innovation -- and with "valuable insights" from the "TeachAI community ." The "TeachAI community" refers to a larger umbrella project providing web resources targeting teachers, education leaders and "solution providers" .

How does AI affect how we learn? When OpenAI released " study mode " in July 2025, the company touted ChatGPT's educational benefits. "When ChatGPT is prompted to teach or tutor, it can significantly improve academic performance," the company's vice president of education told reporters at the product's launch. But any dedicated teacher would be right to wonder: Is this just marketing, or does scholarly research really support such claims? While generative AI tools are moving into classrooms at lightning speed, robust research on the question at hand hasn't moved nearly as fast.

Mars rovers serve as scientists' eyes and ears from millions of miles away - here are the tools Perseverance used to spot a potential sign of ancient life NASA's search for evidence of past life on Mars just produced an exciting update. On Sept. 10, 2025, a team of scientists published a paper detailing the Perseverance rover's investigation of a distinctive rock outcrop called Bright Angel on the edge of Mars' Jezero Crater . This outcrop is notable for its light-toned rocks with striking mineral nodules and multicolored, leopard print-like splotches. By combining data from five scientific instruments, the team determined that these nodules formed through processes that could have involved microorganisms. While this finding is not direct evidence of life, it's a compelling discovery that planetary scientists hope to look into more closely.

In 1770, after Captain Cook's Endeavour struck the Great Barrier Reef and was held up for repairs, botanists Joseph Banks and Daniel Solander collected hundreds of plants. One of those pressed plants is among 170,000 specimens in the herbarium at the University of Melbourne. Worldwide, more than 395 million specimens are housed in herbaria. Together they comprise an unparalleled record of Earth's plant and fungal life over time. We wanted to find a better, faster way to tap into this wealth of information.

With his flowing locks, long beard, and worn robes, Jesus is one of the most instantly recognisable figures in the Western world. So it comes as no surprise that his face is also regularly spotted in inanimate objects. This is due to'face pareidolia' - a common brain phenomenon in which a person sees faces in random images or patterns. 'Sometimes we see faces that aren't really there,' explained Robin Kramer, Senior Lecturer in the School of Psychology, at University of Lincoln, in an article for The Conversation. 'You may be looking at the front of a car or a burnt piece of toast when you notice a face-like pattern. 'This is called face pareidolia and is a mistake made by the brain's face detection system.'

LLM-as-a-Judge is a framework that uses an LLM (large language model) to evaluate the quality of natural language text - typically text that is also generated by an LLM. This framework holds great promise due to its relative low-cost, ease of use, and strong correlations with human stylistic preferences. However, LLM Judges have been shown to exhibit biases that can distort their judgments. We evaluate how well LLM Judges can grade whether a given response to a conversational question is correct, an ability crucial to soundly estimating the overall response quality. To do so, we create and publicly release a human-annotated dataset with labels of correctness for 1,200 LLM responses. We source questions from a combination of existing datasets and a novel, challenging benchmark (BFF-Bench) created for this analysis. We demonstrate a strong connection between an LLM's ability to correctly answer a question and grade responses to that question. Although aggregate level statistics might imply a judge has high agreement with human annotators, it will struggle on the subset of questions it could not answer. To address this issue, we recommend a simple solution: provide the judge with a correct, human-written reference answer. We perform an in-depth analysis on how reference quality can affect the performance of an LLM Judge. We show that providing a weaker judge (e.g. Qwen 2.5 7B) with higher quality references reaches better agreement with human annotators than a stronger judge (e.g. GPT-4o) with synthetic references.

It's been hard recently to think about anything other than the wars and humanitarian crises raging around the world. Climate change has left its mark in what was almost certainly the hottest year in human history--there were unprecedented heat waves, intensified forest fires, torrential rain, and floods like those in Libya that caused devastation after two dams burst. But this has not stopped scientists, innovators, and decisionmakers from working on solutions to our biggest societal challenges--with success. Here is a collection of uplifting news to come out of 2023. In an instant, millions of volts can damage buildings, spark fires, and harm people--unless the lightning can be redirected.

Check out all the on-demand sessions from the Intelligent Security Summit here. We may be living in the golden age of information, but finding the right information is still a pain in the neck. To tackle this challenge, my team and I at Amazon Alexa are building what will believe is the next-generation user interface that will redefine how we interact with technology and find information. We spend hours every day hunched over phones and laptops. We open and close and reopen apps. And we click through an endless sea of blue links every time we search the web.

ChatGPT is a prototype artificial intelligence chatbot developed by OpenAI which specializes in dialogue. The chatbot is a large language model fine-tuned with both supervised and reinforcement learning techniques. It is based on OpenAI's GPT-3.5 model, an improved version of GPT-3. ChatGPT was launched on November 30, 2022 and has garnered attention for its detailed responses and articulate answers. I wanted to see what chatGPT has to say about the metaverse.