Wednesday 7 June 2023 - AI capabilities and why these matter; The link between AI and semiconductor manufacture; Reasons for government funding initiatives into shoring up domestic semiconductor supply chain capabilities; Outlook, both with regards to the effectiveness of these campaigns, as well as the global semiconductor supply chain and AI chips until 2033.

With the high inflation, increasing labor costs, labor shortage, energy crisis, and hybrid working, the manufacturing industry experienced significant turmoil in 2022. Although some of these have started to get eased, 2023 is still expected to be a challenging year for the manufacturing industry.

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.

Materials informatics (MI) involves using data-centric approaches, including AI and machine learning, to assist scientists and engineers in materials R&D.

A floor that can feel when you fall, a warmth that wanders from room to room with you; could the house of the future take care of you?

With the innovation of lidar beam steering technologies, continuous lidar cost reduction, as well as the progress of Advanced Driving Assistance System (ADAS) and Autonomous vehicles (AV), lidars are embracing their potential $8.4 billion-dollar market by 2033.

Where does 5G stand three years after its first commercialization in 2019? Let's start with the frequency band. We know that the sub-6 GHz (3.5 - 7 GHz) and millimeter wave (mmWave, >24 GHz) bands are the two new bands among the spectrum covered in 5G. Despite the hype surrounding mmWave, according to IDTechEx's "5G Market 2023-2033: Technology, Trends, Forecasts, Players" report, 53% of 5G commercial/pre-commercial services are actually based on sub-6 GHz, with mmWave accounting only for less than 10% of the market.

In 20 years, IDTechEx predicts electric cars will generate 76% of all e-transport revenues. Due to their scale, car markets create the largest opportunities for players in the electric vehicle supply chain, from advanced materials through to battery packs, power electronics, and electric motors.

Due to the labor shortage and decreasing costs of hardware, using robots to serve people has gained significant momentum over the past decade, with Tesla unveiling their humanoid robot "Optimus" at the electric vehicle maker's "AI Day" event last week.

Wednesday 12 October 2022 - IDTechEx forecasts the DNA sequencing market to exceed US$12 billion by 2033. This webinar will explore the growing DNA sequencing industry and evaluate the potential future of the market.