Pretty much every cinematic portrayal of artificial intelligence has been less than encouraging. HAL 9000 kills the crew members on the Discovery in 2001: A Space Odyssey, making us all a little bit afraid of handing the reins over to computers. Sonny kills his creator in I, Robot, increasing worldwide scepticism about the integration of humans and their smart robots. Even real life AI has given us pause. For example, when an IBM computer defeated Russian chess Grandmaster Garry Kasparov in the 1990s, it was definitely a cause for concern.

Here's What We Can Expect from Deep Learning in 2016 and Beyond Robots Need "Common Sense" A.I. to Work in Our Uncertain World

Artificial intelligence is making miracles happen. A group of researchers at Massachusetts Institute of Technology (MIT) recently developed an AI that predicts social interactions. The core algorithm of their research is able to predict whether a person will go for a hug, handshake, high-five, or kiss. Like every AI, this algorithm also needs some data to train itself. The researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) used television shows like "Desperate Housewives" and "The Office" to train the algorithm.

IBM Watson Services Artificial intelligence APIs related to language processing, speech processing, visual processing and data insights.

Sinequa provides a Cognitive Search & Analytics platform for Fortune Global 2000 companies and government agencies. Using advanced Natural Language Processing (NLP) and Machine Learning algorithms, the solution offers insights extracted from structured and unstructured data. Broad connectivity to on-premise, Cloud and Hadoop Big Data sources facilitates and accelerates enterprise-wide projects. Sinequa ES offers strong Natural Language Processing (NLP) capabilities and combines semantic analysis in 21 languages with statistical analysis, to extract relevant information from all databases data and unstructured data (text, image, video). Sinequa ES contains a set of scalable Machine Learning libraries, developed on Spark, to provide deep analytics of contents and user behavior, offering information with continually improving relevance to users in their work environments.

Popular search engines are great at finding answers for point-of-fact questions like the elevation of Mount Everest or current movies running at local theaters. They are not, however, very good at answering what-if or predictive questions--questions that depend on multiple variables, such as "What influences the stock market?" In many cases that shortcoming is not for lack of relevant data. Rather, what's missing are empirical models of complex processes that influence the behavior and impact of those data elements. In a world in which scientists, policymakers and others are awash in data, the inability to construct reliable models that can deliver insights from that raw information has become an acute limitation for planners.

A new startup has harnessed the power of artificial intelligence to digitize and automate accounting processes. The startup, Smacc, offers small to midsize companies a platform to track invoices, sales, costs, etc. It will gradually learn over time, said Smacc, so it becomes progressively better at automatically dealing with customers' data. Smacc has secured a 3.5 million round of angel investment capital. Techcrunch.com said its founders came up with the idea after finding that handling accounting was the most annoying part of managing another startup. Smacc joins other cloud-based accounting programs like Xero and Crunch Accounting, but said their high level of automation differentiates them.

Retired U.S. Air Force Col. Gene Lee (seated) is operating a simulator developed by Nick Ernest (standing left) for military training and research. Ernest, a University of Cincinnati graduate and Psibernetix president and CEO, is standing next to David Carroll of Psibernetix. Gene Lee has decades of experience as a fighter pilot and aerial combat instructor. The talent Lee, a retired U.S. Air Force colonel, has as a pilot allowed him to easily and consistently defeat other computer programs used in research and training. That was until he began working with a system developed by a University of Cincinnati doctoral graduate in collaboration with the Air Force Research Laboratory based at Wright-Patterson Air Force Base.

Chatbots for Facebook Messenger are in that awkward phase of development when they are mostly a proof of concept and a way to demonstrate potential. Most of the bots available today do not quite match the artificial intelligence you'll find in a Tesla or at Google. However, they are easily accessible through the Messenger app (you can see the latest chats at the top of the screen on your phone). Many are powerful and useful, including the new Yahoo Weather bot. They're about to improve radically this year (find out more about the latest developments this coming week at MobileBeat 2016) but, for now, here are a few unusual bots you can try.