As Silicon Valley investors and tech giants continue to pour cash into burgeoning artificial intelligence technologies such as machine learning and chatbots, the relatively nascent A.I. industry is emerging as the latest mega-hot new ticket in town--the heir to online delivery apps, anything-hailing services, and virtual reality start-ups. But much like another buzz-worthy predecessor, Big Data, many A.I. cheerleaders and investment check signatories probably don't quite understand it. But in Silicon Valley, when has that ever stopped anyone? The obsession in the Valley with artificial intelligence is almost palpable. Just last week, Twitter announced its acquisition of London-based machine learning start-up Magic Pony Technology.

The biggest trend in technology right now is the race to make machine learning more sophisticated and as the experts say, "less stupid." Machine learning is the ability of computers to learn something without being explicitly programmed. Based on human neural learning, machine learning takes millions of examples and uses layers to build on itself to eventually interpret something without a human first identifying it. Machine learning is infiltrating every aspect of life. From machine translation, email spam filters, ATM check depositing, category filters for photos, emails and apps to facial recognition, machine learning is everywhere taking our basic human actions and instantly making sense of them through technology.

In the future, the US Air Force hopes to have armed drones flying in formation with human pilots, responding to their verbal and digital commands to fight the enemy and strike targets. That would require an artificial intelligence capable of interpreting commands and applying knowledge of combat tactics--something that is already being proven in a project funded by the Air Force Research Lab. ALPHA, an artificial intelligence trained by a retired Air Force expert in air combat, was originally developed as what amounts to ultimate video game AI--an autonomous simulated enemy for use in training fighter pilots. The AI is so good that it has consistently beaten human pilots in simulated air combat--even when heavily handicapped by simulated physics. And now AFRL is investigating using ALPHA as the AI for Unmanned Combat Aerial Vehicles (UCAVs) in the physical world, potentially flying missions alongside human pilots.

Towards making systems forget with machine unlearning.

Microsoft's acquisition of LinkedIn is the largest in giant's history and was hardly expectable[1]. Brilliant analysis of the deal may be found in multiple sources. However, one may suggest that the current narrative is too focused on immediate results and current opportunities rather than the future options for the software giant. A dive into one of the Bill Gates' favorite books may add valuable insights and explain the role of LinkedIn in the Microsoft's push into artificial intelligence (AI). However, the deal of that magnitude deserves to be considered from the perspective of the future.

Microsoft has a birthday present for Windows 10 users: more capabilities for its Cortana digital assistant and new ways to ditch passwords. The company is also changing the notices it sends to users of previous versions, following complaints that it was too aggressive in pushing them to get the free Windows 10 upgrade. Microsoft's "Anniversary Update," scheduled for release Aug. 2, will let users activate Cortana with a spoken command ("Hey Cortana") even while their screen has gone into sleep mode. Cortana will be able to recall more types of information, such as frequent flier numbers or parking locations. Users can also ask Cortana to remember specific photos, such as a wine bottle to buy again later.

Professor Soibelman and his research group at the Sonny Astani Department of Civil and Environmental Engineering will have access to Crunchflow's large metadata database that has anonymous performance information from thousands of projects and employees allocated in professional service organizations. The researchers' mission is to find in this data preliminary patterns and results that help to understand how companies can boost efficiency levels. They also want to demonstrate the potential for extracting knowledge from such a database. Crunchflow's CEO Daniel Knijnik believes that the collaboration will place the company in the forefront of a technology that has the potential to revolutionize how artificial intelligence is applied to business. "We will have top researchers entirely dedicated to innovation, using the latest and most modern technology", he said.

Two stories this past week caught my eye. The first is Nvidia's revelation of the new, AI-focused Tesla P100 computer chip. Introduced at April's annual GPU Technology Conference, the P100 is the largest computer chip in history in terms of the number of transistors, "the product of around 2.5 billion worth of research and development at the hands of thousands of computer engineers." Nvidia CEO Jen-Hsun Huang said that the chip was designed and dedicated "to accelerating AI; dedicated to accelerating deep learning." But the revolutionary potential of the P100 is dependent on AI engineers coming up with new algorithms that can leverage the full range chip's capabilities.

During the recent Consumer Goods Forum global summit here in Cape Town, I had the opportunity to briefly chat with Vivienne about some of the issues confronting the digital disruption of this industry sector. [The original transcript has been edited for clarity and space.] Named one of 10 Women to Watch in Tech in 2013 by Inc. Magazine, Vivienne Ming is a theoretical neuroscientist, technologist and entrepreneur. She co-founded Socos, where machine learning and cognitive neuroscience combine to maximize students' life outcomes. Vivienne is a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience, where she pursues her research in neuroprosthetics. In her free time, Vivienne has developed a predictive model of diabetes to better manage the glucose levels of her diabetic son and systems to predict manic episodes in bipolar suffers. She sits on the boards of StartOut, The Palm Center, Emozia, and the Bay Area Rainbow Daycamp, and is an advisor to Credit Suisse, Cornerstone Capital, and BayesImpact. Dr. Ming also speaks frequently on issues of LGBT inclusion and gender in technology. Every once in a while I have the opportunity to discuss wide-ranging topics with an intellect that stimulates, is passionate and really cares about the bigger picture. Those opportunities are more rare than one would think. Although set in a somewhat unexpected venue (the elite innards of consumer capitalism) her observations on the inescapable disruption that the new wave of modern technologies are prescient and thoughtful. Ed: In a continent where there is a large focus on putting people to work, how do you see the challenges and disruptions resulting from AI, robotics, IoT, VR and other technologies playing out? These technologies, as did other disruptive technologies before them, tend to replace human workers with machine processes. Vivienne: There is almost no domain in which artificial intelligence (AI), machine learning and automation will not have a profound and positive impact. Medicine, farming, transportation, etc. will all benefit. There will be a huge impact on human potential, and human work will change. I think this is inevitable, that we are well on the way to this AI-enabled future.

Last month Salesforce released details on some recent acquisitions in machine learning, reporting spending of almost 33 million on the AI startup MetaMind, and an additional 41.6 million for two other companies, including the intelligence systems startup PredictionIO. This all furthers the Salesforce commitment to bolster their AI capabilities. Current predictions suggest that the global AI market in general will grow to over 5 billion by 2020, driven in part by the rising adoption of predictive marketing intelligence and natural language processing technologies across all business sectors. SugarCRM recently announced that they are developing a new intelligence service with a Siri-like agent called Candace. According to their literature, Candace will be able to listen in on business meetings and use natural language processing to analyze the conversations.