If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
It has penetrated almost every industry and is helping them become innovative, develop authentic tools, and build strategies towards a sustainable future. Researchers are eagerly exploring new use cases of artificial intelligence that have the power to radically transform societies around us. But as we develop intelligence artificially, will be there a room for this AI to rewire us as humans? Artificial intelligence has come a long way since its inception. We are at the brink of a massive change where world leaders are constantly discussing whether AI will take over the world and start controlling us.
Valuations are relatively straightforward yet still involved exercises when similar properties in terms of hedonic variables[i] (also called comparables) transacted in the market close to the valuation date. In the absence of reliable comparable transactions, the possible value of a piece of real estate (be it residential or commercial) needs to be assessed using a valuation method. From back-of-the envelope cap rate models, transparent discounted cash-flow spreadsheets to sophisticated econometric models, any reliable valuation stands to benefit from accurate forecasts of expected levels of cash-flows and discount rates. The buying or selling decision is further influenced by the perceived current state of the real estate cycle but also the projected direction of the cycle. Predicting rents requires a good understanding of demand and supply forces at work in the space market, construction and how its financed, the evolution of the natural vacancy rate and possible migration flows of both firms and workers, among the more prominent determinants.
In a 1967 McKinsey Quarterly article, "The manager and the moron," Peter Drucker noted that "the computer makes no decisions; it only carries out orders. It's a total moron, and therein lies its strength. It forces us to think, to set the criteria. The stupider the tool, the brighter the master has to be--and this is the dumbest tool we have ever had."1 1.Peter Drucker, "The manager and the moron," McKinsey Quarterly, 1967. After years of promise and hype, machine learning has at last hit the vertical part of the exponential curve.
You've likely already encountered artificial intelligence several times today. But for most people, the term AI still conjures images of The Terminator. We don't need to worry about hulking armed robots terrorizing American cities, but there are serious ethical and societal issues we must confront quickly -- because the next wave of computing power is coming, with the potential to dramatically alter -- and improve -- the human experience. Full disclosure: I am general counsel and chair of the AI Ethics Working Group at a company that is bringing AI to processor technology in trillions of devices to make them smarter and more trustworthy. Enabled by high-speed wireless capacity and rapid advances in machine learning, new applications for artificial intelligence are created every day.
When science and technology meet social and economic systems, you tend to see something akin to what the late Stephen Jay Gould called "punctuated equilibrium" in his description of evolutionary biology. Something that has been stable for a long period is suddenly disrupted radically--and then settles into a new equilibrium.1 1.See Stephen Jay Gould, Punctuated Equilibrium, Cambridge, MA: Harvard University Press, 2007. Gould pointed out that fossil records show that species change does not advance gradually but often massively and disruptively. After the mass extinctions that have occurred several times across evolutionary eras, a minority of species survived and the voids in the ecosystem rapidly filled with massive speciation. Gould's theory addresses the discontinuity in fossil records that puzzled Charles Darwin.
Hollywood has been embracing digital technology and computational algorithms in order to movies for a while now, using CGI to de-age actors and enhance shots in other ways. Just recently, one Hollywood company announced its intention to use AI to analyze movie data and assist in making a decision regarding greenlighting projects. As reported by The Hollywood Reporter, the AI firm will be providing Warner Bros. a program intended to simplify aspects of distribution and give projections regarding pricing and possible profit. The system developed for Warner Bros. will utilize big data to guide decision-making during the greenlight phase of a project. The system can reportedly return analyses regarding star power for a given region and even predict how much money a film is likely to make in theaters and through other distribution methods.
Researchers at Purdue University have developed a new deep learning algorithm, called DOVE, that can improve modelling of proteins and help create new drugs. The human body contains over 20,000 different types of proteins, which interact with each other to enable life as we know it. Currently, protein docking models have been developed to estimate how two proteins will interact, yet it is challenging to score whether or not the predicted docking estimate is correct. The Purdue researchers developed a new computational method to address this challenge. DOVE, short for Docking decoy selection with Voxel-based deep neural nEtwork, first scans protein-protein interfaces of a proposed protein docking configuration using a 3D voxel, while considering the atomic interactions and energetic contributions.
The LegalOps Highlight is a bi-weekly blog series that features relevant news, market trends and legal technology updates from the legal ecosystem. The content is curated from legal and business trade publications, consulting and analyst firms, and Onit SimpleLegal partners, customers and subject matter experts. Be sure to subscribe to our blog and follow SimpleLegal and #LegalOpsHighlight on LinkedIn and Twitter for updates! Corporate Counsel magazine reporters spoke to several general counsel about what they say will impact their work and the legal industry. From outside counsel merging with other law firms to the use of artificial intelligence to keep down legal department costs, this article outlines some of the trends in-house counsel may find themselves dealing with in the new year.
In the last couple of years, the retail industry has been considerably impacted because of technologies like Artificial Intelligence and Machine Learning. Especially, the companies that rely on online sales are integrating Machine Learning resources to increase sales and reduce costs. If we go by the books, Machine Learning can be defined as the scientific study of algorithms and statistical models to perform specific tasks by making use of patterns and inference. And interestingly, Artificial Intelligence and Machine Learning goes hand in hand because Machine Learning is considered as a subset of Artificial Intelligence. It's easier said than done to determine which of the industries have altered the most under the influence of Machine Learning and Artificial Intelligence technologies, but the retail sector is definitely one of them.