ZUMATA, a Singapore-based hotel distribution and technology company, along with DHISCO, the world's leading hospitality distribution company headquartered in Dallas, Texas, today announced a reciprocal agreement aimed to increase each other's hotel inventory while accelerating their mutual geographic expansion of distribution. ZUMATA, through its extensive network of wholesale partners and channel managers will supplement DHISCO's inventory by providing over 500,000 instantly bookable hotel properties. For ZUMATA, DHISCO will facilitate distribution of this hotel inventory to its large customer base largely based in North America and other Western markets. "DHISCO has been an industry powerhouse for years, and yet their management is keenly focused on innovation," said ZUMATA CEO Josh Ziegler. "This partnership underscores their commitment to staying at ahead of their competition by embracing the latest technological advancements. For us, this partnership represents a significant opportunity for our partners to gain access to DHISCO's amazing distribution. Complementing inventory and distribution, our artificial intelligence, or AI, powered technology will add exciting new capabilities that can increase customer satisfaction while increasing performance and conversions for all of us."

In transaction banking, the focus on technological development has centred on the possibilities of blockchain technology. However, this has overshadowed the arrival of AI into transaction-banking platforms. AI and machine learning are helping to further reduce manual checks and processes. The first target for implementation is sanctions and compliance. As companies become increasingly international, irrespective of size, checking against sanctions has become an essential activity for more than just the MNCs. AI can learn through experience what can pass through the sanctions filter, and what compliance obligations need to be checked.

The amount of data being handled in chip design is growing significantly at each new node, prompting chipmakers to begin using some of the same concepts, technologies and algorithms used in data centers at companies such as Google, Facebook and GE. While the total data sizes in chip design are still relatively small compared with cloud operations--terabytes per year versus petabytes and exabytes--it's too much to sort through using existing equipment and approaches. "You can take many big data approaches to handle this, but there may be a business problem if you do," said Leon Stok, vice president of EDA at IBM. He said EDA doesn't have the kind of concentrated volume necessary to drive these kinds of techniques, and typically that problem is made worse because the data is often different between design and manufacturing. But for those working on designs, the amount has grown significantly at a time when extracting key data in various parts of the design flow is crucial.

Google's week consisted of bringing its TensorFlow machine learning software to iOS, seeing its Tango software added into the first consumer smartphones, and receiving a proposal by its DeepMind division to add a kill switch to artificial intelligence (AI) systems. The firm's AlphaGo AI is also scheduled to face the best Go player the world can offer in a match later this year. Google updated its TensorFlow machine learning software to run on iOS devices. The technology that powers AlphaGo was released to the open source community in November, but has now reached the hands of Apple developers who can build a neural network right into apps. Google's Tango software was revealed to be a key feature of Lenovo's new smartphones.

This piece was originally published on Medium in Imaginary Papers, an online publication of Arizona State University's Center for Science and the Imagination. Matt Scherer runs the Law and AI blog. Artificial intelligence (A.I.) systems are becoming increasingly ubiquitous in our economy and society, and are being designed with an ever-increasing ability to operate free of direct human supervision. Algorithmic trading systems account for a huge and still-growing share of stock market transactions, and autonomous vehicles with A.I. "drivers" are already being tested on the roads. Because they operate with less human supervision and control than earlier technologies, the rising prevalence of autonomous A.I. raises the question of how legal systems can ensure that victims receive compensation if (read: when) an A.I. system causes physical or economic harm during the course of its operations.

Ross has been built on IBM's cognitive computer Watson and is designed to read and understand language, formulate hypotheses when asked questions, conduct research, and generate responses in order to back up its conclusions. Ross also improves with age, as it learns from its experiences and gains knowledge with more interaction. "You ask your questions in plain English, as you would a colleague, and ROSS then reads through the entire body of law and returns a cited answer and topical readings from legislation, case law and secondary sources to get you up-to-speed quickly. In addition, ROSS monitors the law around the clock to notify you of new court decisions that can affect your case," ROSS website says. Ross will also serve as a time efficiency tool, as it will be capable of narrowing down results from a thousand answers to a handful of the most relevant answers and then translates them into an understandable language.

For eBay (EBAY), artificial intelligence could prove to be its salvation. The San Jose, Calif.-based e-commerce giant, which has been working to transform itself after spinning off PayPal Holdings (PYPL) last year, could reap some huge benefits if it can find out a way to effectively use AI, according to analysts. At the Code Conference earlier this month, eBay CEO Devin Wenig revealed that the company started getting very serious about using artificial intelligence last year, noting that e-commerce is essentially a data business and that AI may be more important for eBay than its peers due to the "breadth of [its] inventory." Wenig further explained that eBay plans to formulate a strategy focused on using data to predict what consumers might want and offering a wide selection of products. In fact, eBay aims to use algorithms over the next three to four years to better understand consumer intent and create an ecosystem involving social networks and messaging applications to allow for better targeting, R.W. Baird analyst Colin Sebastian wrote in a note earlier this month.

It's well known that we in the tech sector love our acronyms. We also like re-badging stuff.What was once ASP (application service provision) morphed into SaaS (software as a service) and then became part of the cloud computing eco-system. And so it is at the moment with AI (artificial intelligence). There have been a number of pronouncements recently, particularly from private practice firms, about their adoption of AI. But is the truth more weighted towards the "artificial" than the "intelligence"? That well-known convenient one-stop-shop of truth, Wikipedia, defines AI as "a machine acting as a rational agent that perceives its environment and takes actions which maximise its chance for success at an arbitrary goal".

The edtech trend on the tip of everyone's tongue at this year's EdtechXEurope event is artificial intelligence. By harnessing the power of AI and deep learning, educators can glean insights from the vast quantities of data hoovered up from their students. AI could also help lecturers make better decisions and could improve student retention rates, according to experts. "AI is a tool to make better sense of data," says Satya Nitta, director of education and cognitive sciences at IBM. The world's top online learning platforms are working with business schools such as Yale SOM and Duke Fuqua, and are offering advanced analytical tools to help them refine and enhance student learning.

Are the warnings we have heard, from no lesser figures than Bill Gates and Stephen Hawking, about artificial intelligence being a threat to the future of humanity, to be taken seriously? Will our children or grandchildren live in a world where walking, talking humanoid robots are difficult to tell apart from biological humans? There are those in the field, such as Ray Kurzweil, American writer and computer scientist, who believe that in just a few decades machine intelligence will be able to improve itself, independent from human help, to generate exponential improvements that are described as "the singularity" - a term borrowed from mathematics where it is used to describe a function that veers off to infinity.