A panel of industry experts gathered at RSA 2018 in San Francisco to explore the role that machine learning and artificial intelligence is playing in the current cyber landscape. After opening the discussion by asking the panel to each give their own definition of what machine learning is, Ira asked the speakers to define what types of applications are most appropriate for the use of machine learning and AI. Hillard: The places where it is most mature is around speech and image processing, and also around fraud detection. "The technology should be an enabler to solving a problem but sometimes it gets lost in what's being accomplished." Friedrichs: Most people have woken up to the fact that machine learning and AI are not the panacea that marketing tells us they are, but they can add to the feature set of a product.
The key to getting better at deep learning (or most fields in life) is practice. Each of these problem has it's own unique nuance and approach. But where can you get this data? A lot of research papers you see these days use proprietary datasets that are usually not released to the general public. This becomes a problem, if you want to learn and apply your newly acquired skills.
A British agritech start-up has won a prestigious Horizontal Innovation Award from the IET and the High Value Manufacturing Catapult (HVMC) to help develop'Harry', the company's drilling and planting robot. Small Robot Company, based in Shropshire, harnesses the power and precision of robots and Artificial Intelligence (AI) to improve the way that food is produced. The £50,000 funded research award will look to develop'Harry' from concept through to in-field prototype. Addressing key challenges around the use of robotics in agriculture, the development of'Harry's' punch planting mechanism will be supported by the Manufacturing Technology Centre, one of seven centres of excellence which make up the High Value Manufacturing Catapult (HVM Catapult), which is sponsored by Innovate UK. The technology is built on 15 years of robotics research by Professor Simon Blackmore, the world's leading expert on precision farming at Harper Adams University.
Neural networks (NNs) and deep learning (DL) currently provide the best solutions to many problems in image recognition, speech recognition, natural language processing, control and precision health. NN and DL make the artificial intelligence (AI) much closer to human thinking modes. However, there are many open problems related to DL in NN, e.g.: convergence, learning efficiency, optimality, multi-dimensional learning, on-line adaptation. This requires to create new algorithms and analysis methods. Practical applications both require and stimulate this development.
There's no question artificial intelligence and machine learning technologies are enabling important discoveries in healthcare, but there can be a bit of a disconnect among the various stakeholders using them. A panel discussion at the upcoming CNS Summit in Boca Raton, Fla. presents a rare opportunity to bring the parties together and foster collaboration.