Artificial intelligence is a 15 billion dollar industry and growing. With more than 2, 600 companies developing intelligent technology, the value of AI is expected to rise to more than 70 billion by 2020. For designers, that represents a major business opportunity. But AI is also a challenge requiring every strength and skill they've learned and many they haven't. They will have to understand sociology, psychology, and biology.

NFL coaching great Buddy Ryan, who passed away Tuesday at the age of 82, didn't have difficulty finding the spotlight wherever he went. From the New York Jets when they became the first AFL team to win a Super Bowl in 1968, to the Super Bears of 1985 to his last stop as the head man of the Arizona Cardinals in 1994-95, Ryan had a common theme -- "You got a winner in town." One of the best fits for that boisterous personality was his stop as head coach of the Philadelphia Eagles from 1986 to 1990. He was brash, but his teams backed up his words. He made fun of the rich owner, Norman Braman -- "that guy in France" -- who spent a lot of time overseas, and connected with the blue-collar town.

Almost all algorithmic assistants that utilize unsupervised machine learning have several skill sets based on modern data science. They can baseline normal behavior by accurately modeling time series data (any series of data with a time stamp on it – usually log data from servers, devices, endpoints, and applications); they can identify data points that are anomalous or "outliers;" and they can score the level of anomalousness of these outliers. Generally, you'll hear this set of skills packaged up under the term "machine learning anomaly detection."

Blaise Agüera y Arcas, principal scientist at Google, works with deep neural networks for machine perception and distributed learning. In this captivating demo, he shows how neural nets trained to recognize images can be run in reverse, to generate them. The results: spectacular, hallucinatory collages (and poems!) that defy categorization. "Perception and creativity are very intimately connected," Agüera y Arcas says. "Any creature, any being that is able to do perceptual acts is also able to create."

For the time being, countless decisions still require human engagement. Awash in data, executives dream of a time when the Jetson utopia finally manifests -- and they find themselves sipping coffee and cashing checks while machines slave away for them, uncovering unexpected business insights and learning optimal ways to manage organizations. Despite improvements in cognitive technologies, that dream managerial scenario is still far from reality. Decisions that executives face don't necessarily fit into defined problems well suited for automation. At least for the time being, countless decisions still require human engagement.

Artificial intelligence, or AI, is all around us today–and it's often invisible as we go about our daily lives.

Digital channels have become an easy way for citizens to connect with their local governments.

The most important players in this new world are the "digital assistants:" Siri, Alexa, Cortana, Facebook M, Google Assistant, and a handful of third-party players. These, say their makers, will be our computing familiars, the programs that we'll spend most of our time talking to. They'll be accessible on different platforms (phones, watches, cars, home hubs) but keep tabs on our personal data, schedules, and location, across an entire network. And thanks to machine learning, they'll understand human speech better than any computers before, able to grok context and slang, and, eventually, emotion and intent. Assistants like this will offer us ambient computing.

Unlike systemically delivered immunotherapies that can produce serious side effects, ImmunoPulse IL-12 is proving to be generally well tolerated and safe across multiple treatment cycles in clinical trials. DNA-based IL-12 is administered directly into the tumor using an applicator that delivers quick electric pulses to increase the permeability of cell membranes. This produces a localized immune response and educates fighter immune cells to recognize and attack cancer throughout the body, without attacking healthy cells.

Jean-Philip Poulin was feeling "joyful" and "excited" when I interviewed him recently in Montreal. I know this because he showed me his real-time emotion metrics during our conversation, which were being parsed by a machine-learning algorithm that uses heart-rate data transmitted from his Microsoft Band 2 fitness tracker. Poulin is the COO of Sensaura, a Montreal-based software startup that proposes to bridge the gap between consumer wearables and affective computing. If its founders are as successful as they believe they will be, their product will hasten the inevitable future of emotionally intelligent machines: video games will know when you're bored, advertisers will know when you're swayed, and mental health professionals will know when you need a check-in. So far, progress in affective computing has depended on facial recognition software, which reads people's emotions pretty much the same way that people do: by looking at their faces for cues.