SYS-CON Events announced today that OpsGenie will exhibit at SYS-CON's 20th International Cloud Expo, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Founded in 2012, OpsGenie is an alerting and on-call management solution for dev and ops teams. OpsGenie provides the tools needed to design actionable alerts, manage on-call schedules and escalations, and ensure that the right people are notified at the right time, using multiple notification methods. All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades.

Roughly 600,000 people in China die from lung cancer every year. Already the leading cause of death in the pollution-choked and chain-smoking-prone nation, the incidence of lung cancer among China's citizens is actually going to increase to 800,000 cases per year by 2020. The situation has gotten bad enough that China's state media has not only been forced to report on the spread of cancer in the country, but also lay the blame squarely at the feet of the nation's runaway pollution problem. The issue is compounded by a lack of quality healthcare in much of the country, which means that cancers often go undetected until it's too late. For Chen Kuan, the chief executive and founder of Infervision, a Beijing-based company using machine learning and computer vision to help diagnose cancers, the problem isn't just academic.

Historically, most of the data businesses have analyzed for decision-making has been of the structured variety--easily entered, stored, and queried. In the digital age, that universe of potentially valuable data keeps expanding exponentially. Most of it is unstructured data, coming from a wide variety of sources, from websites to wearable devices. As a recent McKinsey Global Institute report noted: "Much of this newly available data is in the form of clicks, images, text, or signals of various sorts, which is very different than the structured data that can be cleanly placed in rows and columns." At the same time, we have entered an era when machine learning can theoretically find patterns in vast amounts of data to enable enterprises to uncover insights that may not have been visible before.

As large tech companies gear up to make a stronger push into machine learning and artificial intelligence, Apple has acquired a company to fill out its own capabilities in the area. Specifically, Apple has picked up Lattice Data, a company that applies an AI enabled inference engine to take unstructured, "dark" data and turn it into structured (and more usable) information. We've heard from a single source that Apple has paid a price of around $200 million. The deal was closed a couple of weeks ago, the source said, and about 20 engineers have joined the larger company. A source first alerted us to this, and we've received the standard Apple confirmation.

Malware has proven increasingly difficult to detect via signature or heuristic-based methods, which means most Antivirus (AV) programs are woefully ineffective against mutating malware, and especially ineffective against APT attacks (Advanced Persistent Threats). Typical malware consists of about 10,000 lines of code. Five to six years ago marked the beginning of the use of machine learning to solve non-linear problems such as facial recognition or understanding malware, and what features one needs to extract to uniquely identify such programs. Other techniques, such as sandboxing and machine-based techniques, are not as fast nor as accurate as Deep Learning. Deep Instinct, founded by Guy Caspi and Eli David, Israeli Defense Force Cybersecurity veterans, applies artificial intelligence Deep Learning algorithms to detect structures and program functions that are indicative of malware.

Sometime in the coming decades, an external system that collects and analyzes endless streams of biometric data will probably be able to understand what's going on in my body and in my brain much better than me. Such a system will transform politics and economics by allowing governments and corporations to predict and manipulate human desires. What will it do to art? Will art remain humanity's last line of defense against the rise of the all-knowing algorithms? In the modern world, art is usually associated with human emotions.

We've talked before about the prospects of artificial intelligence (AI) and how it will likely disrupt things like we've never seen before with some estimates predicting that up to 80% of all service jobs will be impacted. Healthcare is one area where AI is receiving a good chunk of funding. We looked before at one example of an artificial intelligence company called Enlitic that uses machine learning technology to read X-rays better than a human radiologist who makes $286,000 a year on average. There are actually quite a few artificial intelligence companies in healthcare and CB Insights recently identified 65 of them at various stages of funding. Founded just last year, Chinese company iCarbonX has taken in nearly $200 million in funding from investors that include the $200 billion Chinese internet giant Tencent.

Chatbots have a long and venerable history dating back to the 1960s and the famous Eliza bot that fooled some people into thinking they were chatting with a real human. Since then, computer programs capable of conducting conversations have become progressively more advanced with greater ability to understand content and respond appropriately. And yet the ability to reproduce human speech convincingly still eludes chatbots. Talk to one for any length of time and it soon becomes clear that it is a machine. One reason is that computers are unable to gauge the emotional content of conversations and empathize accordingly.

Innovation continues to be a strategic priority in the banking industry, with new business models emerging including partnerships with fintech startups. As competition expands and consumer expectations for enhanced digital banking services increases, new business models in banking are emerging and being deployed in real applications. Investment in innovation and in technologies like artificial intelligence are transforming the way rich data is analyzed and applied, creating the potential for real-time contextual banking engagement. The innovation agenda has become intertwined with the digitalization agenda, with both requiring changes in culture and back office operating systems. Investment in delivery channel innovation continues to be the most important focus for the banking industry, responding to expectations set by other industries.

They speak with Roman Luchin, CEO of CyberTech Labs., about a robotics development platform called Trik. Trik is intended to be an intermediate step when learning about robotics between Lego Mindstorms and programming on an embedded platform. Trik allows users to program with a graphical interface by ordering blocks. These blocks contain code in several common programming languages (python, F#, Pascal, etc.) and the code can be modified directly. This is the second of three interviews from the conference.