Artificial Intelligence

Artificial Intelligence has come a long way since the success of DeepMind over Go world champion Lee Sedol in 2016; the world is beginning to change according to the new possibilities afforded by AI. From the robust predictive abilities of OpenAI's ChatGPT - where the AI chatbot can be used for all sorts of purposes, from creating scripts (including malware) to writing academic essays - to AI image generators that are so good that they can win Sony world photography awards, the complexity and capabilities of AI algorithms are growing at a startlingly fast pace.

Materials informatics is the application of data-driven methods, including machine learning techniques, to the field of materials science. This important part of the digital transformation toolbox for the materials industry has wide-ranging benefits, but the ability to enhance the sustainability of materials and their manufacturing processes could be the most impactful of these.

6G is the next generation of wireless technology that promises to go beyond mobile communication and revolutionize how people interact with the world around them. According to IDTechEx's latest 6G research, 6G could be with us in 2028 at the earliest.

Autonomous mobility is the key value proposition for many robots. Thanks to the successes of self-driving systems in commercial vehicles from companies like Tesla and John Deere. Autonomous driving has gained significant momentum across the robotics industry.

With an increasing demand for automation in the 21st century, robots have had rapid and unprecedented growth across many industries, including logistics, warehousing, manufacturing, and food delivery.

The materials industry is sometimes described as conservative, but digital transformation is well underway in the sector. Materials informatics - the application of data-centric approaches, including machine learning, to materials R&D - has the potential to be the most impactful arm of this process.

The Road to More Intelligent Robots? Sensors are crucial for the value proposition behind many intelligent robotic systems. With the increasing demand for robots to handle complicated tasks, the growing adoption of robots, and the decreasing costs of sensors, the market for sensors in robotics is rapidly growing. It is expected to exceed US$80 billion by 2043. This fast growth and the substantial market size are partially driven by the growth of robots in the next two decades as a whole, but also expects sensors to capture an increasing proportion of the total value in robotic systems.

Robots, by definition, are machines with autonomy. Over the past several years, robots have gained significant momentum in a variety of industries, such as logistics and delivery, manufacturing, cleaning and disinfection, and daily services.

Collaborative robots, also commonly known as cobots, refer to robots that work side-by-side with human operators. Unlike industrial robots that are separated from human operators, cobots share the same working space as humans. As a relatively new definition, cooperative robots sound like collaborative robots but represents a different nature of the operation.

Lidar, which refers to light detection and ranging, is a technology that has been adopted in various applications such as mapping, surveying, military, archaeology, agriculture, geology, industry, etc.