Today we look atBritish Prime Minister Theresa May’s plantofocus onemerging technologies. She announced in a press release that the “modern Industrial Strategy is a critical part of our plan for post-Brexit Britain”. The Prime Minister set down ten strategic pillars for this industrial strategy, with the first one on the list being “investing in science, research, and innovation”.
The green paper sets out technologies which the government will support through its new Industrial Strategy Challenge Fund, including AI, smart technologies, and 5g mobile network technology. These technologies will benefit from the £4.7 billion funding increase to R&D, a bigger increase than in any Parliament since 1979.
If you would like to express your opinion on this new plan, please visit the government website and speak your mind.
The British government is placing cutting edge technology, such as AI, front and centre in its new post-Brexit industrial strategy. In their press release, they have outlined 10 key strategic pillars and the first on the list is “investing in science, research, and innovation”.
To that end, they are increasing research and development funding by £4.7 billion in order to focus on developing technology. Check outBritish Prime Minister Theresa May’s speechat Davos for how she thinks the UK should move forward after they have left the EU.
Jeremy Waite, Evangelist at IBM, employed IBM Watson
to analyse President Donald Trump‘s inaugural address in comparison with Obama‘s. The analysis used four APIs: 1) speech-to-text, 2) sentiment analysis, 3) tone analyser, and 4) personality insights. Watson found Trump to be “analytical, excitable, and can be perceived as critical” and gave him a 7% higher ‘trust’ score than Obama. Although Watson produced a thorough report, there is a concern that the data is not robust enough. A study comparing all of the speeches (and tweets) of Trump compared with those of Obama would be a much more meaningful and fruitful endeavour.
The market for AI technologies is flourishing. Beyond the hype and the heightened media attention, the numerous startups and the internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises. A Narrative Science survey found last year that 38% of enterprises are already using AI, growing to 62% by 2018.
Based on analysis conducted by Forrester, Forbes lists the 10 hottest AI technologies: 1) natural language generation, 2) speech recognition, 3) virtual agents, 4) machine learning platforms, 5) AI-optimized hardware, 6) decision management, 7) deep learning platforms, 8) biometrics, 9) robotic process automation, 10) text analytics and NLP.
Alstom is investing €14 million, and thus taking a minority stake, in EasyMile, an innovative start-up company developing the EZ10 electric driverless shuttle. The investment forms part of the start-up’s ongoing capital increase. In parallel, Alstom and EasyMile have signed a commercial partnership agreement aiming at joining their forces to provide integrated solutions for urban transportation. Alstom will be present at EasyMile’s board.
In the last few years, conservationists and others have turned to big data to get the big picture on environmental degradation. Big data, in this case, comes in various forms, from satellite images to global trade databases to social media postings.
An ongoing project is using big data analytics to test whether it’s feasible to use posts from social media to gauge the health of ecosystems when combined with other data sets. Specifically, researchers at the Griffith Institute for Tourism are trying to monitor environmental conditions at the Great Barrier Reef in real time using tweets from Twitter, in addition to meteorological data, tourism statistics, water quality reports, and coral cover, among other variables using sentiment analysis to extract the relevant ecological information.
Two medical specialists at the Austin Health’s Liver Transplant Unit in Melbourne, Australia developed an algorithm that matches potential liver donor with patients. The specialists said that they modelled the algorithm from the dating site, eHarmony, hoping to make the process faster which will, eventually, save more lives.
Bob Jones, director of the liver transplant unit, and Lawrence Lau said that they used 25 different features of donors and recipients and plug them into the algorithm to create faster and better outcome. Those features include the basic information, such as sex, age, and blood type, as well as certain characteristics the donors have. After that, they used the machine learning algorithm to assess the results of 75 patients who have undergone transplants. The algorithm is 84 percent accurate compared to the traditional method of matching donors and recipients which is only 68 percent.
POSB, one of Singapore’s oldest banks and part of the DBS Banking Group, has launched an online virtual assistant, POSB digibank Virtual Assistant. It is powered by the KAI conversational bot/AI platform from a New York-based fintech start-up, Kasisto. POSB’s chatbot is available on Facebook Messenger and can answer questions relating to account balances, utility bill payments and fund transfer requests. It will also be rolled out to the WhatsApp and WeChat messaging platforms.
Selling more than 10 million credit card-sized computers, Raspberry Pi is the most successful British computer ever. Now it could be about to get even more powerful. Google is working to bring its AI, machine learning and other developer tools to the small computer, Pi’s creators have said. “Google is going to arrive in style in 2017,” a blog post on the Raspberry Pi website says. “The tech titan has exciting plans for the Raspberry Pi community, with a range of AI and machine learning services ready to roll.”
Mark Zuckerberg and Priscilla Chan’s $45 billion philanthropy organization is making its first acquisition in order to make it easier for scientists to search, read and tie together more than 26 million science research papers. The Chan Zuckerberg Initiative is acquiring Meta, an AI-powered research search engine startup, and will make its tool free to all in a few months after enhancing the product. Meta could help scientists find the latest papers related to their own projects, while assisting funding organizations to collaborate with researchers and identify high-potential areas for investment or impact.
Jukedeck is one of a growing number of companies using AI to compose music. Their computers tap tools like artificial neural networks, modeled on the brain, that allow the machines to learn by doing, rather as a child does. So far, at least, these businesses do not seem to be causing much anxiety among musicians. “We see our system as still in its infancy; it’s only learnt a certain amount about music,” founder Patrick Stobbs said, although he quickly hinted how he hoped Jukedeck’s music could advance: “There’s no rule of physics that says computers can’t get as good as a human.”
This week, optimization platform Amplero is announcing an enhancement to its platform that employs machine learning to power influencer marketing for brands whose customers commonly form networks of users.
Called Influencer Optimization, the new approach identifies users with substantial networks of contacts, and then uses machine intelligence to make the least offer that would generate the biggest ripple. What distinguishes Amplero’s approach, Chief Product Officer Matt Fleckenstein said, is that the machine learning is continually testing the lowest offer that will deliver results, as well as figuring out the targeted customer’s network of influence.