But stepping back from it, I realized that Siri was everywhere in the roughly two-hour and fifteen-minute presentation. What we saw on Monday was next-level Siri. The software started as a pretty simple voice assistant, then graduated to digital assistant. It is now nothing less than an artificial intelligence -- one that can rain AI fairy dust on any number of services and third-party apps. Hello, SiriKit As predicted, Siri finally has an SDK -- sort of.

Artificial intelligence and robotics are leading a transformation in Silicon Valley. Artificial intelligence (AI) and robotics are leading a transformation in Silicon Valley, which is expected to be as significant as the personal computing industry and commercial Internet eras were. "Whenever there is a new idea, the valley swarms it," says Nvidia CEO Jen-Hsun Huang. "But you have to wait for a good idea, and good ideas don't happen every day." Some technologists see innovations such as deep learning establishing a platform for machines with human-level intelligence, and although past efforts in the field have come up short, many investors are confident the renewed interest in AI will bear fruit.

Sure, Facebook has "M", Google has "Google Now", and Siri's voice isn't always that of a woman. But it does feel worth noting that (typically male-dominated) engineering groups routinely give women's names to the things you issue commands to. Is artificial intelligence work about Adams making Eves? The response to this critique is usually about the voices people trust and find easy to understand. Adrienne LaFrance over at The Atlantic does a good job discussing those points, so go read her article.

John Melas-Kyriazi is a senior associate at Spark Capital interested in the AI and machine learning space. When I woke up this morning, I asked my assistant a simple question: "Siri, is it going to rain today?" Siri understood my intent, pulled the local weather data via an API and answered me in less than two seconds: "There's no rain in the forecast for today." In the not-too-distant past, this kind of human-computer interaction would have blown away technologists and delighted consumers -- but in 2016, it's nothing special. Conversations with Siri are commonplace, just like they are with Microsoft's Cortana and Amazon's Alexa.

Artificial intelligence won't be able to control all aspects of operating a motor vehicle for quite some time, said technology trend spotter Scott Kupor. "It's going to be a long time ... before we get to fully autonomous vehicles," the managing partner of venture capital powerhouse Andreessen Horowitz told CNBC's "Squawk Box" on Wednesday. "We're not going to go from where we are today to fully autonomous vehicles tomorrow. There are different stages of autonomous vehicles," he said, such as human-assisted autonomous driving. In the race to build self-driving cars, Silicon Valley heavyweights, including the Google unit of Alphabet and Tesla Motors -- and traditional automakers, such as Toyota and General Motors, are vying to own the road.

Machines may not be known for their EQ (emotional quotient), but a new collaboration between Cogito Corp. and the U.S. Military Academy is on track to change our perceptions. The art of negotiation, which may have once been a distinctly human skill set, is being enhanced by Cogito, a company that specializes in real-time emotional intelligence solutions. Cadets at West Point will use this technology to improve their own tactics when it comes to striking a bargain and gaining crucial information. "We believe that the ability to effectively negotiate is a critical skill that will serve military personnel well in numerous situations over the course of their careers," said Col. James Ness, Ph.D. Director: Engineering Psychology Program, West Point. "Cogito's behavioral analytics technology will systematically analyze communication patterns within negotiating sessions and provide insight into the cadet's psychological state. This technology will provide an unbiased assessment of how each cadet is being perceived by the other party. It will deliver insights into how they can modify their behavior to improve negotiation outcomes."

Machine learning technology is poised to move from niche data analytics applications to mainstream enterprise big data campaigns over the next two years, a recent vendor survey suggests. SoftServe, a software and application development specialist based in Austin, Texas, reports that 62 percent of the medium and large organizations it polled in April said they expect to roll out machine learning tools for business analytics by 2018. That majority said real-time data analysis was the most promising big data opportunity. The survey authors argue that artificial intelligence-based technologies like machine learning are moving beyond the "hype cycle" as enterprise look to automate analytics capabilities ranging from business intelligence to security. The goal is to demonstrate that that cyber defenses can be automated as more infrastructure is networked via an Internet of Things.)

Extracting value from a universe of data, analysing sentiment around company names (equities) or about anything else (macro), is a complex journey and we are only about 5% down that road. The parameters are evolving by which an ever-expanding data set, including the likes of Twitter, pictures, text, video is processed; relying on experts versus the wisdom of the crowd; sentiment derived from a "bag of words", as opposed to structured linguistic analysis. Last week's Unicom conference, AI, Machine Learning and Sentiment Analysis Applied to Finance (July 14) brought together a group of experts in this area. Professor Gautum Mitra, OptiRisk Systems introduced Elijah DePalma and James Cantarella, Thomson Reuters; Pierce Crosby, StockTwits; Anders Bally, Sentifi; Peter Hafez, RavenPack; Stephen Morse, Twitter. DePalma differed somewhat from the others because the Thomson Reuters sentiment engine uses only accredited Reuters news data, rather than raw social media chatter.

Companies large and small are embracing machine learning in a bid to make better use of their data. Last week, eBay Inc. led the charge by acquiring SalesPredict Ltd., an Israeli startup that uses the technology help marketers gain a better understanding of their customers. Its cloud service can analyze a company's sales records to identify the most valuable type of leads and then single out the accounts that match the description in its CRM system. Moreover, SalesPredict says that the data produced by its technology also makes it easier to identify new high-value prospects and optimize advertising campaigns. No terms were disclosed for the acquisition, but eBay did divulge that the startup's team will join its Israeli engineering team to help with product development efforts.

The Rio Olympics 2016 is something everyone is looking forward to. But the Olympics have been a frontier for individuals flexing their physical muscles and achieving greatness. Well, it's time for it to move over to the Cyber Grand Challenge (CGC) is here. Individuals wanting to showcase their brain muscles in a competition could change how we defend against cyber attacks. The challenge organized by the Defense Advanced Research Projects Agency (DARPA) of the United States where the seven finalists will battle it out with the Artificial Intelligence system to detect flaws and scan networks for exploits.