The Bank of England is using its new fintech accelerator to work with startups on developing proof-of-concepts (POCs) in data analytics, information security and distributed ledgers. Launched in June, the accelerator is designed to boost the BofE's practical experience with fintech, with firms invited to apply to work with it on POCs that address challenges unique to the central bank. Speaking at Web Summit in Lisbon this week, BofE COO Charlotte Hogg invited new applications and gave an update on the project, revealing that the bank is working with BMLL Technologies on a POC that uses a machine learning platform, applied to historic limit order book data, to spot anomalies and facilitate the use of new tools in analytical capabilities. A second POC, with Enforcd, uses an analytic platform designed specifically to share public information on regulatory enforcement action. Meanwhile, two firms - Anomali and ThreatConnect - are working on technologies to collect, correlate, categorise and integrate cyber security intelligence data.
This article is a part of an evolving theme. Here, I explain the basics of Deep Learning and how Deep learning algorithms could apply to IoT and Smart city domains. Specifically, as I discuss below, I am interested in complementing Deep learning algorithms using IoT datasets. I elaborate these ideas in the Data Science for Internet of Things program which enables you to work towards being a Data Scientist for the Internet of Things (modelled on the course I teach at Oxford University and UPM – Madrid).
Facebook has built a simple-looking video tool to show off a sophisticated use of artificial intelligence on cell phones. During an event at its office fb in Menlo Park, Calif., last Friday afternoon, Facebook CTO Mike Schroepfer showed off software that takes a live Facebook video feed from a cell phone and converts the image in real time into a selection of artistic styles, such as that of Van Gogh. It might sound like a simple filter, but usually an algorithm of this nature would need to send that type of information back to a server in a data center to process the pixels on more powerful machines. The Facebook crew crafted a less power-hungry and computing-intensive deep learning system they call "Caffe2Go," that uses the computing power in a cell phone. Facebook's Schroepfer showed the algorithm and other applications of artificial intelligence at the Web Summit conference in Lisbon, Portugal on Tuesday.
The ROCSAFE Project (Remotely Operated CBRNe Scene Assessment & Forensic Examination) has recently been funded by the European Union's Horizon 2020 programme. Led by Dr Michael Madden in NUI Galway, it will make advances in autonomous robotics, probabilistic reasoning, intelligent decision support, and miniaturised sensors, all of which will work together to gather forensic evidence in the event of a chemical, biological, radiation/nuclear or explosive (CBRNe) incident. ROCSAFE's overall goal is to fundamentally change how CBRNe events are assessed, and ensure the safety of crime scene investigators, by reducing the need for them to enter dangerous scenes to gather evidence. There are 13 partners in total involved in the project across Ireland, Italy, Portugal, Spain and Germany, along with a further group of advisory board members. There is more information at http://www.nuigalway.ie/remoteforensics/.