The quality of machine translation has increased remarkably over the past years, to the degree that it was found to be indistinguishable from professional human translation in a number of empirical investigations. We reassess Hassan et al.'s 2018 investigation into Chinese to English news translation, showing that the finding of human-machine parity was owed to weaknesses in the evaluation design--which is currently considered best practice in the field. We show that the professional human translations contained significantly fewer errors, and that perceived quality in human evaluation depends on the choice of raters, the availability of linguistic context, and the creation of reference translations. Our results call for revisiting current best practices to assess strong machine translation systems in general and human-machine parity in particular, for which we offer a set of recommendations based on our empirical findings.

Having participated and contributed to many programs on big data, artificial intelligence and health, I realize that yes, medicines and vaccines are needed to treat the COVID-19 virus, but big data analytics can also be mustered into service to prevent the spread of the insidious pandemic that now grips the world. This isn't just a hypothesis by an analytics professor who has spent two decades in the analytics and machine learning area, but it is actually being proven in Taiwan, an island nation that is in close proximity to mainland China, where the virus was first reported in the city of Wuhan. As of the week of March 16, Taiwan reported about 100 detected cases of COVID-19. Taiwan is about as close to the epicenter of this outbreak as any place can get. There is a lot of travel from the Wuhan area to places in Taiwan.

An audio version of this Medium article is available on Spotify and Apple Podcasts. The coronoavirus of 2019 (COVID-19) is being solved with Artificial Intelligence and Data Science. Global researchers are partnering on scientific breakthroughs to rapidly deploy and test new vaccines, to determine hotspots of the disease growth, and to recommend strategies with the World Health Organization for disease quarantine and prevention. Since the December 2019 outbreak of the #coronavirus (COVD-19) in China, I have been closely watching the news and listening to speeches about the deadly virus. There is panic everywhere with people wearing masks and others locked in their houses all day to avoid contracting the virus.

Researchers from the University of Chicago's Oriental Institute and the Department of Computer Science have collaborated to design an AI that can help decode tablets from ancient civilizations. According to Phys.org, the AI is called DeepScribe and was trained on over 6,000 annotated images pulled from the Persepolis Fortification Archive, when it is complete the AI model will be able to interpret unanalyzed tablets, making studying ancient documents easier. Experts who study ancient documents, like the researchers who are studying the documents created during the Achaemenid Empire in Persia, need to translate ancient documents by hand, a long process that is prone to errors. Researchers have been using computers to assist in interpreting ancient documents since the 1990s, but the computer programs that were used were of limited help. The complex cuneiform characters, as well as the three-dimensional shape of the tablets, put a cap on how useful the computer programs could be.

Russian researchers from the Moscow Institute of Physics and Technology, Valiev Institute of Physics and Technology, and ITMO University have created a neural network that learned to predict the behavior of a quantum system by "looking" at its network structure. The neural network autonomously finds solutions that are well-adapted toward quantum advantage demonstrations. This will aid researchers in developing new efficient quantum computers. The findings are reported in the New Journal of Physics. A wide range of problems in modern science are solved through quantum mechanical calculations.

There are plenty of tools and point solutions that address bits and pieces of the challenge of delivering artificial intelligence (AI) and Internet of things (IoT) applications. C3.ai's focus is on delivering an end-to-end platform for developing, deploying and running these applications in production at scale. Whether customers use every aspect of the C3.ai platform or not, big enterprise-scale companies seem to be attracted by that promise of quickly developing and running innovative, data-driven applications at scale. There was plenty of evidence of that fact at C3.ai's February 25-27 Transform conference in San Francisco, where customers including Bank of America, Shell, 3M and Engie detailed their deployments. C3.ai's cloud-first platform is comprehensive, addressing the needs of developers, data engineers and data scientists, and the operational teams challenged with bringing applications into production at scale.

If you're not concerned about the potential legal liability from using AI, then you're not paying attention. That's the message from Andrew Burt, one of the founders of BNH.ai, a boutique law firm that's dedicated to advising clients on the legal pitfalls of embracing AI. BNH.ai has been up and running for just over a month. But today is its official launch day for the Washington D.C. law firm, which was co-founded by Burt, the chief legal counsel for Immuta, and Patrick Hall, the head of product for H2O.ai. Both will continue in their existing roles at Immuta and H2O while growing their new law firm.

According to a report in the UK's Charged Retail, Alibaba is offering up its cloud based artificial intelligence technology to medical personnel around …

The new coronavirus is now officially a pandemic, and researchers are speeding to discover, test and deploy a vaccine. Some are hoping that breakthrough biotechnology and artificial intelligence can get us there faster. Much of the funding and development of a COVID-19 vaccine is likely to happen privately. The $8 billion coronavirus funding bill passed by the U.S. government includes just $800 million for the National Institutes of Health, where official U.S. vaccine research and development happens, but which is chronically underfunded. I asked Michael Greeley, co-founder and general partner with biotech investment fund Flare Capital in Boston, what uses AI could have in dealing with coronavirus.

Over the past decade, fintech firms have set out to reinvent banking and financial services. One major market trend is the growth of the neobank, a new type of bank that is 100% digital. Instead of using physical branch networks, neobanks service customers using software and applications, allowing customers to transact on their mobile devices and providing accounts with much lower fees and more features. This trend to digitizing banking and the exchange of value is a natural progression of the information revolution to embrace digital. Fintech is an exciting market that continues to grow.