Uber AI in 2019: Advancing Mobility with Artificial Intelligence


Zoubin Ghahramani is Chief Scientist of Uber and a world leader in the field of machine learning, significantly advancing the state-of-the-art in algorithms that can learn from data. He is known in particular for fundamental contributions to probabilistic modeling and Bayesian approaches to machine learning systems and AI. Zoubin also maintains his roles as Professor of Information Engineering at the University of Cambridge and Deputy Director of the Leverhulme Centre for the Future of Intelligence. He was one of the founding directors of the Alan Turing Institute (the UK's national institute for Data Science and AI), and is a Fellow of St John's College Cambridge and of the Royal Society.

Tiny antennae that record how bees navigate may help perfect steering for driverless cars and drones

Daily Mail - Science & tech

They are not just cute and stripy, but devastatingly efficient when it comes to locating the best pollen-rich flowers. As a result, the humble bee is at the centre of a £4.8 million project to create drones and driverless cars. In a unusual experiment, scientists painstakingly stuck tiny radar transponders to hundreds of bumblebees and honey bees, to track them as they flew. Bees are famous in the animal world for their intelligence, even directing each other to delicious flowers using a'waggle dance'. To harness their navigational skills, researchers used radar to track bees' precise flight path as they buzzed over farmland in Hertfordshire Carefully avoiding painful stings, the researchers have also put bees in virtual reality chambers, then watched how their brains works as they navigate.

AI Shortcuts Speed Simulations Billions of Times


University of Oxford scientists led research that used artificial intelligence to generate accurate machine learning emulator algorithms for accelerating simulations billions of times, for all scientific disciplines. Researchers led by the University of Oxford in the U.K. used artificial intelligence to generate accurate machine learning emulator algorithms for accelerating simulations billions of times, for all scientific disciplines. The neural network-based emulators absorb the inputs and outputs of a full simulation, seeking patterns and learning to guess what the model would do with new inputs while avoiding the need to run the full simulation many times. The Deep Emulator Network Search (DENSE) method randomly inserts computation layers between network inputs and outputs and trains the system with the limited data, so added layers that improve performance are more likely to end up in future variations. DENSE-produced emulators for 10 simulations in physics, astronomy, geology, and climate science were 100,000 to 2 billion times faster than the models with the addition of specialized graphical processing chips--and were highly accurate.

7 AI Research Labs in Europe Leading the Data Science Community


In the past, we've highlighted some West Coast AI research labs that we think are doing some really incredible work. Now, in an attempt to look past the dominating presence of Silicon Valley, we're turning our focus overseas and taking a closer look at some of the cutting-edge Europe AI research labs. Founded in 2015, the Alan Turing Institute is a fairly new research lab with a unique structure. Located within the British Library in London, it's a national institute comprised of 13 universities and the UK Engineering and Physical Science Research Council. This structure creates an environment that promotes collaborate across disciplines.

Machine learning in UK finance - hype or reality?


UK financial firms are increasingly using machine learning to help run their businesses, and are exploring ever more sophisticated techniques. Such innovation can improve financial services, but authorities must remain on top of the risks. Computer programmes can, with limited human intervention, recognise patterns from data and automatically make decisions. This is called machine learning (ML). Two thirds of UK banks, insurers and other financial services firms that we surveyed are already using ML to help run their businesses (Chart A).

AI in Health and Care Award launches in the UK - EMR Industry


Innovators in England are now able to submit their applications for a new AI in Health and Care Award launched by health secretary Matt Hancock to speed up testing, evaluation and adoption of the "most promising" AI technologies for healthcare. The initiative will see £140 million be made available during the next three years, with a call for applications running twice a year. Initially, the award will focus on four areas: screening, diagnosis, clinical decision support and system efficiency. Run by the Accelerated Access Collaborative, NHSX and the National Institute for Health Research, it forms part of the £250m announcement made in August to support the creation of an AI Lab for the health service. "Too many good ideas in the NHS never make it past the pilot stage," Hancock said in a speech at the Parliament & Healthtech conference in London on Tuesday.

Financial Services Are Being Shaped by Artificial Intelligence


Artificial intelligence (AI) is in the process of transforming a variety of models in the global financial services industry, a global survey jointly conducted by the Cambridge Centre for Alternative Finance (CCAF) at the University of Cambridge Judge Business School and the World Economic Forum suggests. The study, supported by EY and Invesco, demonstrates that AI is changing how financial institutions generate and utilize insights from data, which in turn propels new forms of business model innovation, reshapes competitive environments and workforces, engenders new risk dynamics and poses novel challenges to firms and policy-makers alike. The survey, which gleaned responses from 151 financial institutions, including both incumbent firms and FinTechs hailing from more than 30 countries, confirms AI as a crucial business driver across the industry in the short term. Notably, AI adopters do not appear to have specific modi operandi for implementing AI; instead, 64% expect to become mass adopters within two years, proving the growing potential of AI to stimulate innovation and growth across a wide range of business functions. FinTechs and incumbents alike are moving from mainly using AI to reduce costs to utilizing its capabilities for revenue generation, albeit pursuing different AI strategies to achieve this.

How artificial intelligence could change London


Computers are scanning London's roads, with a 98% accuracy rate in identifying vehicles and people. And they are are learning all the time.

Fintech workforce to expand 19% by 2030 thanks to AI, Cambridge University predicts


Using data collected in a global survey during 2019, the report analysed a sample of 151 fintechs and incumbents across 33 countries to paint a rich picture of how artificial technology is being developed and deployed within the financial services sector. While 77% of respondents noted that they expect AI to become an essential business driver across the financial services industry in the near term, the report found that the way incumbents and fintechs are leveraging AI technologies differ in a number of ways. A higher share of fintechs tend to be creating AI-based products and services, employing autonomous decision-making systems, and relying on cloud-based systems. Whereas incumbents appear to focus on "harnessing AI to improve existing products. This might explain why AI appears to have a higher positive impact on fintechs' profitability."

Nissan completes U.K.'s longest and most complex driverless car trip

The Japan Times

CRANFIELD, ENGLAND – A Nissan car has completed a 370-kilometer journey autonomously in the U.K., the longest and most complex such trip in the country as carmakers race to develop the driverless technologies set to revolutionize travel. The U.K. has been wooing developers of autonomous vehicles, hoping to grab a slice of an industry it estimates could be worth around £900 billion (¥128 trillion) worldwide in 2035. Aided by eight laser scanners, seven cameras and a radar located around the vehicle along with six electronic control units in the trunk, the electric Leaf vehicle made the journey alongside conventional motorists on country lanes and motorways. The journey began at the Japanese carmaker's European technical center in Cranfield, southern England, and ended at its Sunderland factory in the northeast. It included roads with no or minimal markings, junctions and roundabouts, using advanced positioning technology.