The Association for the Advancement of Artificial Intelligence's 2025 Spring Symposium Series was held in Dubai, UAE, May 20-May 22, 2025. There were four symposia in the spring program: AI-Driven Resilience: Building Robust, Adaptive Technologies for a Dynamic World, AI in Business: Intelligent Transformation and Management and Context-Awareness in Cyber-Physical Systems. The AI for Resilient Communities symposium explores the intersection of artificial intelligence, resilience, and adaptive technologies, highlighting AI's transformative role in helping communities navigate environmental, economic, and social uncertainties. As societies face escalating challenges--from climate crises to shifting economic landscapes--the need for resilient, adaptive systems has never been more critical. This symposium is designed to foster innovation and dialogue around creating robust communities that can withstand and adapt to crises, evolving into stronger and more resilient entities over time.

It sounds like a scenario straight out of a sci-fi movie. But researchers at Heriot-Watt University in Edinburgh have developed a new light detection system that can recognise human faces and objects from more than half a mile away – even at night or through smoke or fog. Scientists say the ground-breaking research could be a'step change' for security and defence and has the potential to'make identification significantly easier'. Using pulses of laser light to measure the distances to objects, the system can construct'high-resolution 3D images' of faces and other surfaces from as far away as ten football pitches in both daylight and darkness. Dr Aongus McCarthy, an optical scientist and research fellow at Heriot-Watt's Institute of Photonics and Quantum Sciences, said: 'If someone is standing behind camouflage netting, this system has the potential to determine whether they are on their mobile phone, holding something, or just standing there idle.'

From 325 metres away, your eyes can probably distinguish a person's head from their body – and not much else. But a new laser-based device can create a three-dimensional model of their face. Aongus McCarthy at Heriot-Watt University in Scotland and his colleagues built a device that can create detailed three-dimensional images, including ridges and indentations as small as 1 millimetre, from hundreds of metres away. It uses an imaging technique called lidar, emitting pulses of laser light that collide with objects then reflect back into the device. Based on how long each pulse takes to return, lidar can determine an object's shape.

A humanoid robot described as the most advanced in the world will be showcased in Scotland. The National Robotarium, the UK's centre for robotics and artificial intelligence (AI) based at Heriot-Watt University in partnership with The University of Edinburgh, has purchased the robot, named Ameca, from Engineered Arts. Ameca is described as able'to interact with people in a natural and engaging way', and facial expressions include'playful' and'pondering'. The acquisition is a bid to'demystify complex technologies and foster a greater understanding of the potential benefits of robotics', and AI. The robot has embedded microphones, cameras, facial recognition software and articulated motorised components.

An impressive array of robots serves as a fitting backdrop for Stewart Miller, the CEO of the new National Robotarium, in a large and mostly empty space in a swish new building on the campus of Heriot-Watt University on the outskirts of Edinburgh. Launched in September in partnership with Edinburgh University, the center aims to bolster the UK's artificial intelligence (AI) and robotics sector, which Miller believes is lagging behind the major players. "We're rich in research in AI," he explains, "but where we tend to stumble – not just with AI, but with other technology as well – is when we try to take it out of the research setting and apply it. That's why we've been set up." In the weeks and months ahead this large, sparse space will fill up as it welcomes various tenant start-up AI and robotics firms and takes them under its wing.

Metal-organic frameworks (MOFs) are a class of materials that contain nano-sized pores. These pores give MOFs record-breaking internal surface areas, which make them extremely versatile for a number of applications: separating petrochemicals and gases, mimicking DNA, producing hydrogen, and removing heavy metals, fluoride anions, and even gold from water are just a few examples. MOFs are the focus of Professor Berend Smit's research at EPFL School of Basic Sciences, where his group employs machine learning in the discovery, design, and even categorization of the ever-increasing MOFs that currently flood chemical databases. In a new study, Smit and his colleagues have developed a machine-learning model that predicts the heat capacity of MOFs. "This is about very classical thermodynamics," says Smit. "How much energy is needed to heat up a material by one degree? Until now, all engineering calculations have assumed that all MOFs have the same heat capacity, for the simple reason that there is hardly any data available."

The National Robotarium, hosted by Heriot-Watt University in Edinburgh, has unveiled an AI-powered telepresence robotic solution for remote health consultations. Using the solution, health practitioners would be able to assess a person's physical and cognitive health from anywhere in the world. Patients could access specialists no matter whether they're based in the UK, India, the US, or anywhere else. "It was fascinating to visit the National Robotarium and see first-hand how virtual teleportation technology could revolutionise healthcare and assisted living. Backed by £21 million UK Government City Region Deal funding, this cutting-edge research centre is a world leader for robotics and AI, bringing jobs and investment to the area."

An artificial intelligence (AI) companion for people with dementia is being developed in research involving the University of Strathclyde. The technology will aid memory recollection, boost confidence and combat depression in people living with Alzheimer's Disease and other types of dementia. Memory loss in people with Alzheimer's Disease occurs in reverse chronological order, with pockets of long-term memory remaining accessible even as the disease progresses. While most current rehabilitative care methods focus on physical aids and repetitive reminding techniques, the new project, named AMPER (Agent-based Memory Prosthesis to Encourage Reminiscing) will take an AI-driven, user-centred approach and will focus on personalised storytelling to help bring a patient's memories back to the surface. The research team is led at Heriot-Watt University and the National Robotarium, a partnership between Heriot-Watt University and the University of Edinburgh.

Researchers at the National Robotarium, hosted by Heriot-Watt University and the University of Edinburgh, are developing an artificial intelligence (AI) companion that will aid memory recollection, boost confidence and combat depression in people living with Alzheimer's disease and other types of dementia. The idea for the ground-breaking'Agent-based Memory Prosthesis to Encourage Reminiscing' (AMPER) project originated from Dr. Mei Yii Lim, a co-investigator of the project and an experienced memory modelling researcher. Memory loss in people with Alzheimer's disease occurs in reverse chronological order, with pockets of long-term memory remaining accessible even as the disease progresses. While most current rehabilitative care methods focus on physical aids and repetitive reminding techniques, AMPER's AI-driven user-centred approach will focus on personalised storytelling to help bring a patient's memories back to the surface. Dr. Lim explains "AMPER will explore the potential for AI to help access an individual's personal memories residing in the still viable regions of the brain by creating natural, relatable stories. These will be tailored to their unique life experiences, age, social context and changing needs to encourage reminiscing."

Energy communities will play a key role in building the more decentralized, less carbon-intensive, and fairer energy systems of the future. Such communities enable local prosumers (consumers with own generation and storage) to generate, store and trade energy with each other--using locally owned assets, such as wind turbines, rooftop solar panels and batteries. In turn, this enables the community to use more locally generated renewable generation and shifts the market power from large utility companies to individual prosumers. Energy community projects often involve jointly-owned assets such as community-owned wind turbines or shared battery storage. Yet, this raises the question of how these assets should be controlled--often in real-time, and how the energy outputs jointly-owned assets should be shared fairly among community members, given not all members have the same size, energy needs or demand profiles.