A new AI-based data "navigation" system is billed as the first analytics platform to use natural language processing to generate SQL queries from spoken requests. The result is a sort of virtual assistant for data analysts. Promethium, a data management startup based in Menlo Park, Calif., said this week its NLP-generated SQL queries can be used to assemble data across different systems and platforms. The navigation system is based on the company's AI and machine learning-driven contextual automation tool. The software can be used to locate data, then present it in form that is most useful to business analysts.

Is Kenya ready for five 5G network? With Asia and other continents of the world taking steps to become a global leader in 5G and the Advanced Intelligence (AI) technology, Kenya will be ranked one of the first East African countries to tap into this, with the completion of the Data Centre by Huawei in Konza Smart City. This would help to revolutionize several industries, including manufacturing, agriculture, transport, health sector, making factory automation, as well as communication between self-driving vehicles to regulate traffic. According to Ms Pamela Tutui, a director at Konza Technopolis Development Authority (KoTDA), Kenya is set to borrow ideas from a campus in China's Shenzhen City to lift Konza Smart City to a technology hub in Africa. "Smart cities is bringing solutions to a city that is not smart. Like in Nairobi what is stopping us from having street lights, from looking at our road networks and to go beyond just taxis and looking into our busing lanes," says Ann Theresse Jatta Ndong – Director UNESCO regional Eastern Africa.

For Rolls-Royce, the world's second largest manufacturer of aero engines and a company with a distinguished history of pioneering R&D, technology strategy is all about the play-off between optimising existing products and simultaneously leading the charge on developing the low carbon power systems of the future. "The most pressing issue is how to get the right balance between new technology-led opportunities and existing product evolution," says the firm's chief technology officer, Paul Stein. "People will still be buying gas turbines [conventional aero engines] for the next 40 or 50 years, so we have to make sure we keep those products competitive for the long term. But we also have to free up as many resources as we can for driving productivity and for investing in the new." Stein explains how technologies such as digitisation and AI are already paying big dividends in design and operational efficiency.

GE is experimenting with using bots as a way to more effectively implement its AI strategy. Deploying AI capabilities via bots, in essence, allows the company to apply traditional practices used for managing its human workforce to technology. These include practices like onboarding, training, rating and creating a culture around the AI bots. The company has even taken to naming the bots, said Vivek Thakral, director of artificial intelligence at GE. About 50 different bots, with names like Greg, Olive and Max, have been created by Thakral's team to do particular tasks that existing workers are having trouble keeping up with.

The second AI HW Summit took place in the heart of Silicon Valley on September 17-18, with nearly fifty speakers presenting to over 500 attendees (almost twice the size of last year's inaugural audience). While I cannot possibly cover all the interesting companies on display in a short blog, there are a few observations I'd like to share. Computer architecture legend John Hennessy, Chairman of Alphabet and former President of Stanford University, set the stage for the event by describing how historical semiconductor trends, including the untimely demise of Moore's Law and Dennard scaling, led to the demand and opportunity for "Domain-Specific Architectures." This "DSA" concept applies not only to novel hardware designs but to the new software architecture of deep neural networks. The challenge is to create and train massive neural networks and then optimize those networks to run efficiently on a DSA, be it a CPU, GPU, TPU, ASIC, FPGA or ACAP, for "inference" processing of new input data.

Mitul Tiwari expertise lies in building data-driven products using AI, machine learning, and big data technologies. Previously, he was head of People You May Know and Growth Relevance at LinkedIn, where he led technical innovations in large-scale social recommender systems. Prior to that, he worked at Kosmix (now Walmart Labs) on web-scale document and query categorization, and its applications. He earned his PhD in Computer Science from the University of Texas at Austin and his undergraduate degree from the Indian Institute of Technology, Bombay. He has also co-authored more than 20 publications in top conferences such as KDD, WWW, RecSys, VLDB, SIGIR, CIKM, and SPAA.

Robots can diagnose heart problems in as little as four seconds, tests have shown, as a review of artificial intelligence (AI) found machines are now as good at spotting illness as doctors. Analysing a patient's heart function on a cardiac MRI scan currently takes doctors around 13 minutes. But a new trial by University College London (UCL) showed an AI programme could read the scans in a fraction of the time with equal accuracy. There are approximately 150,000 such scans performed in the UK each year, and researchers estimate that fully utilising AI to read them could save 54 clinician-days at each cardiac centre per year. It is hoped that AI - where computer systems are able to learn from data to identify new patterns with minimal human intervention - will transform medicine by helping doctors spot diseases such heart disease and cancer quicker and earlier.

The adoption of AI could take a toll on women's employment, over the next ten years, says a recent report by McKinsey global institute McKinsey Global Institute report "The future of women at work: Transitions in the age of automation, published earlier this year says the adoption of AI could take a toll on women's employment. It has found that the world's ten economies, – Canada, France, Germany, Japan, the U.K., the U.S., China, India, Mexico, and South America- that collectively contribute over 60% of GDP of the world, will be severely affected by AI adoption, especially for women's employment. The report says, "an average of 20% of women working today (107 million) could find their jobs displaced by 2030. That's compared with 21% of men (163 million) in the same period". As she spoke about the research at MIT Technology Review's EmTech MIT conference at the MIT Media Lab, Krishnan said that almost 90% of the jobs that are repetitive can be automated, in about 10% of occupations.

"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.