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According to the European Patent Office, for the first time in more than a decade, digital technologies have taken the lead in patent applications filed. Among the top technical fields digital communication (+19.6%) and computer technology (+10.2%) saw the steepest growth. The report, published on the 12th March 2020, notes that one driving factor for growth was the increase in patent applications related to artificial intelligence (AI), especially in the areas of machine learning and pattern recognition, image data processing and generation, and data retrieval.
Partner Mike Jennings, Patent Attorney and AI expert, reflects on this growth:
“AA Thornton handles large numbers of computer-implemented inventions and the EPO’s 12 March report reflects what we have seen – a proliferation of applications of AI and computer simulation and modelling that is helping to accelerate innovation in many industries. AA Thornton attorneys are ready to support clients’ protection strategies for AI and computer simulation in all industries, building on vast experience helping our computing clients to protect the technologies that have enabled this rapid growth, while also protecting major advances in quantum computing that will help to achieve the full potential of AI.”
Artificial Intelligence is finding its way into every industry indeed, and is driving innovation faster than ever before. Our industry leads share their views on how AI is impacting their respecting sectors of focus:
“Medical technology- related applications were the second highest in 2019 with 13,833 in total, after digital communications applications. What is interesting to note is that, in the medical devices field, the use of AI to process medical data is already leading to significant changes in the way patients are monitored, triaged, diagnosed and treated. AI is helping with the management of chronic diseases such as diabetes by processing data gathered from dedicated sensors or apps used by patients so that treatment can be automated and/or optimised. AI is being used in medical imaging to process medical images, such as scans or X-rays, where it can improve the clarity of images and help to speed analysis of the image content which can mean less radiation exposure for patients, and a more rapid diagnosis. Using AI to process data generated via the Internet of Things to monitor patient compliance with a prescribed treatment protocol in order to improve outcomes is also leading to developments of new types of medical devices, or the addition of sensors to existing device types. The emerging robotic surgery field is also likely to have a significant role for AI in due course.”
“As retail continues the shift from bricks and mortar to digital spaces, AI is playing a bigger and more important role in customer experience and content personalisation. AI is able to aggregate and analyse browsing and sales metrics and generate truly valuable customer insights. Those insights in turn allow retailers to create a personalised experience for each customer which drives both engagement and ultimately conversion. AI is also playing a role in image processing and therefore search – users provide an image a product and the AI returns suggestions of the same or similar products – Amazon’s Stylesnap is a well-publicised example of this but other retailers such as M&S, boohoo and ASOS are all offering visual search options to their digital customers.”
“The use of AI in the pharma and biotech industry has redefined how drug developers develop new drugs and clinical data. Previously, in the pharma field AI was mainly used for biochemical modelling, bioinformatics, and testing toxicity. However, in recent times many big pharmaceutical companies and start-ups are now investing substantially in AI for analysing oncology therapeutics, identifying drug targets, designing new drugs, developing better biomarkers and for selecting correct patients for clinical trials. A popular use of AI in the pharma industry is for finding new uses for existing drugs, since this leads to accelerated process of developing medicine. AI’s ability to analyse high volumes of data at a very high speed, machine learning and deep learning assist in new drug discovery, disease diagnosis, clinical trial, and personalized treatment of patients based on the patient data. More recently, AI is also being used for risk prediction to identify clinical, operational and financial risks for healthcare organizations, and for assisting in accurate and efficient reporting in pharma marketing. As the focus is shifting to AI, it would not be surprising to see more new applications of AI in the pharma sector in the future.”
“AI has a key role to play in the automotive industry. The most well-known use of AI in the industry is in autonomous vehicles where AI systems can monitor and control the vehicle in real time. Most modern vehicles have advanced driver assistance systems (ADAS) that use AI to monitor sensors in the vehicle and respond to any dangers or hazards by, for example, alerting a driver or carrying out corrective action such as emergency braking. More advanced autonomous vehicles can control the majority of the driving task that would normally be carried out by a human. Such vehicles are already being used for transporting of passengers. Automotive companies are also using AI for prototyping (machine learning in their product deployment), modelling and simulation (testing of vehicles), connectivity (vehicles autonomously communicating with each other and infrastructure), quality control (checking quality in manufacturing processes and predicting faults in processes or vehicles) as well as many other uses. It is clear that these are exciting times in the automotive industry with companies racing to develop new technology that makes use of AI.”
If you have any questions about AI and how it is affecting your industry, please do not hesitate to contact us. You can also find a lot of content on our AI hub, in particular our series of articles on AI in IP as part of our March Focus on AI.
Category: Latest Insights, News | Author: Alex Bone, Mike Jennings, Sarah Neil, Nikesh Patel, Leonita Paulraj | Published: | Read more
