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.

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. Tanmay Ambadkar is researching the reward structure in reinforcement learning, with the goal of providing generalizable solutions that can provide robust guarantees and are easily deployable. We caught up with Tanmay to find out more about his research, and in particular, the constrained reinforcement learning framework he has been working on. Tell us a bit about your PhD - where are you studying, and what is the topic of your research? I am a 4th year PhD candidate at The Pennsylvania State University, PA, USA.

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We caught up with Oliver Chang whose research interests span deep reinforcement learning, autonomous vehicles, and explainable AI. We found out more about some of the projects he's worked on so far, what drew him to the field, and what future AI directions he's excited about. Could you give us a quick introduction to who you are, where you're studying, and the topic of your research? I'm specializing in reinforcement learning applied to autonomous vehicles and UAVs.

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.

Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we explore multi-agent systems and collective decision-making, dive into neurosymbolic Markov models, and find out how robots can acquire skills through interactions with the physical world. What if AI were designed not only to optimize choices for individuals, but to help groups reach decisions together? AIhub Ambassador Liliane-Caroline Demers interviewed Kate Larson whose research explores how AI can support collective decision-making. She reflected on what drew her into the field, why she sees AI playing a role in consensus and democratic processes, and why she believes multi-agent systems deserve more attention.

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 Maxime Meyer to chat about his current research, future plans, and how he found the doctoral consortium experience. Could you start with an introduction to yourself, where you're studying and the topic of your research? My research focuses on large language models. Which aspect of large language models are you looking at?

The potential for artificial intelligence to affect election results is a major public concern. Two new papers - with experiments conducted in four countries - demonstrate that chatbots powered by large language models (LLMs) are quite effective at political persuasion, moving opposition voters' preferences by 10 percentage points or more in many cases. The LLMs' persuasiveness comes not from being masters of psychological manipulation, but because they come up with so many claims supporting their arguments for candidates' policy positions. "LLMs can really move people's attitudes towards presidential candidates and policies, and they do it by providing many factual claims that support their side," said David Rand, a senior author on both papers. "But those claims aren't necessarily accurate - and even arguments built on accurate claims can still mislead by omission."

The dust coated the Alps and caused'blood rain' in England. In the light of the setting sun, the sky forms a veil of Saharan dust over the Wurmberg in Lower Saxony, Germany. Breakthroughs, discoveries, and DIY tips sent six days a week. The wild winds of winter typically bring snow in the Northern Hemisphere. But sometimes, they carry dust .

WIRED spoke with Nick Fox, Google's SVP of knowledge and information, about how AI is changing the company's advertising business. Google executives have insisted for months that the company has no immediate plans to put ads in Gemini. But in an interview with WIRED, Google's senior vice president of knowledge and information, Nick Fox, says the tech giant is "not ruling them out." "I would expect that the learnings that we get from ads in AI Mode would likely carry over to what we might want to do in the Gemini app down the road," says Fox. "It's an odd thing to say, but our research shows that users actually like ads within the context of Search. Over time, we'll figure out what makes sense in the Gemini app." Google has spent the past year racing to catch up with OpenAI in the AI chatbot market.

Yellowstone's ravens may memorize wolf hunting hotspots--to feast The birds will fly over 90 miles to dine where wolves have drawn blood. Breakthroughs, discoveries, and DIY tips sent six days a week. When wolves are on the hunt, a kill rarely goes unnoticed for long. In the elk-and deer-rich areas of northern Yellowstone National Park, ravens are often among the first scavengers to arrive on the scene, swooping down to feast on scraps left behind by the howling canines. Field biologists have long assumed that the birds simply follow wolves as they track and take down their prey.