Artificial Intelligence in the context of Alternative Asset management will manifest itself across a number of dimensions; the need to understand the vast quantities of data being generated by economic activity moving online, the ubiquity of networks for conducting these online transactions, and the emergence of algorithms for seeking investment opportunities and making investment decisions. There has already been a rise in the number of Quantitative Funds – such as Aidyia- relying on machine intelligence, neural networks and the ability to mine Big Data to compete alongside the likes of Renaissance Technologies, DE Shaw, Two Sigma and a host of other brand name funds such as Bridgewater Associates and Point72 Asset Management that investigating the scope for AI to generate Alpha. The rise of this machine intelligence can be broken down into two categories: "Active" AI uses technology to seek out opportunities for hedge fund alpha by analyzing data in unconventional ways, uncovering hidden correlations in market data or interpreting "signals" in the marketplace which then generate trading ideas. "Passive" AI takes place in the post-trade arena, opening up time-series of data, connecting flows between markets, counter parties and assets to support Portfolio Managers and Traders in their decision making. By using AI to open up post trade data more aggressively, funds could find their optimal financing mix or most credit-worthy counter parties by searching the market for news that may impact their credit rating or actively size/shape trading portfolio positions in real-time.

We've all experienced grabbing drinks with friends and getting stuck talking to someone where the conversation seems to go on too long. That same dynamic plays out in voice skills, and it's really important to measure, test, and refine your overall session length. You don't want your voice skill to be the bore of the party. The best way to measure when your app gets boring is to use a tool like VoiceLabs.co to track when the majority of your users start to drop off your user flow. For every voice skill, you'll hit a point where you've asked users too many questions and they drop off.

Google's self-driving cars have graduated from the company's "moonshot division", X labs, to become a full-blown subsidiary of umbrella group Alphabet, called Waymo. The new company, headed by X alumni John Krafcik, is charged with turning the self-driving car technology that Google has been developing behind closed doors into a viable business for the future. How that will actually happen, though, Waymo has apparently not yet decided. Mooted revenue streams include Uber-style driverless ride sharing, disrupting the trucking and logistics sector, fitting self-driving technology into public transit vehicles, improving the "last mile" of postal delivery or even simply licensing the software to car manufacturers who will sell cars to end users. "Self-driving technology is awesome in all these categories," said Krafcik at an event to announce the launch of Waymo.

Snapchat has finally launched group conversations, letting the app take on competitors like WhatsApp. The company will finally let people talk to a group of friends – up to 16 of them – rather than starting individual conversations with a range of different people. The move is perhaps one of its biggest launches in recent years. The company has been gradually looking to become more of a centre for people to have conversations, something that was severely limited by its inability to have group conversations like competitors including WhatsApp and Facebook Messenger. In its facilities, JAXA develop satellites and analyse their observation data, train astronauts for utilization in the Japanese Experiment Module'Kibo' of the International Space Station (ISS) and develop launch vehicles 32/39 The robot developed by Seed Solutions sings and dances to the music during the Japan Robot Week 2016 at Tokyo Big Sight.

The Universal Store team in WDG is developing some of Microsoft's largest scale and business critical cloud services. These services have a huge global footprint of over 240 markets and process millions of transactions daily, with loads growing linearly as Microsoft moves to a "cloud first", "mobile first" strategy. The platform powers all of Microsoft's key services Windows App Store, Windows Phone, XBOX, Bing Ads, Office 365, Azure to name just a few. Whether renting a movie or buying a game on Xbox LIVE, purchasing an app on a Windows or Windows Phone device, signing up for an Office 365 subscription or paying for Azure services, you are using the Universal Store platform. We are the Developer Engagement & Monetization team in Bangalore with in the Universal Store organization in OSG responsible for providing the high yield monetization, data platform, developer knowledge graph, data/ML models, insights, intelligence, engagement & Monetization.

Some videos are available only by enrolling in a Coursera or EdX class. It is free to do so, but sometimes the classes are no longer in session so you have to wait a couple of months, so you have no access. I'm going to be adding more videos from public sources and replacing the online course videos over time. I like using university lectures.

Is artificial intelligence and conversational computing the next great frontier in IT? Microsoft believes so; the company is bullish on AI and is doubling down on opportunities it sees for the technology. "Our goal here is democratizing AI so that we make AI available for everyone," including developers, consumers, and businesses, said Harry Shum, executive vice president in Microsoft's AI and Research Group. The company officially introduced its Zo chatbot, an AI-driven, English-speaking conversation partner that is a follow-up to Tay, which had been contorted into misuse and abuse. More than 115,000 people have already been using Zo, according to Microsoft. With bots, developers can build applications offering interactive services and human-to-computer conversations.

Within the silos of incumbent financial services, so-called fintech companies are good at picking off one thing only and doing it well. This approach is also taken within data science, where a lot of the properly intelligent work is about understanding the domain (problem) and how best to use the information/data for the problem you have. In doing so, a fintech approach – collaboration, open-sourcing code – is helping to gradually change the culture of finance, even in some hitherto heavily guarded domains. Dr Tristan Fletcher, research director, Thought Machine, said: "Without this specialisation and domain knowledge, it's very hard to rise above the noise. However, the algorithms themselves are often applicable in many areas or problems, and we are probably seeing decreasing specialisation here. "Fintech lends itself particularly to specialisation because there are many well-packaged problems that need to be solved and can be clearly delineated – KYC, AML, credit checking etc.

Uber's self-driving cars are making the move to San Francisco, in a new expansion of its pilot project with autonomous vehicles that will see Volvo SUVs outfitted with sensors and supercomputers begin picking up passengers in the city. The autonomous cars won't operate completely driverless, for the time being – as in Pittsburgh, where Uber launched self-driving Ford Focus vehicles this fall, each SUV will have a safety driver and Uber test engineer onboard to handle manual driving when needed and monitor progress with the tests. But the cars will still be picking up ordinary passengers – any customers who request uberX using the standard consumer-facing mobile app are eligible for a ride in one of the new XC90s operated by Uber's Advanced Technologies Group (ATG). There's a difference here beyond the geography; this is the third generation of Uber's autonomous vehicle, which is distinct from the second-generation Fords that were used in the Pittsburgh pilot. Uber has a more direct relationship with Volvo in turning its new XC90s into cars with autonomous capabilities; the Fords were essentially purchased stock off the line, while Uber's partnership with Volvo means it can do more in terms of integrating its own sensor array into the ones available on board the vehicle already.

In addition, we've made advances in machine learning applied to time-series data, a type of data prevalent in the energy industry." To learn more about WattzOn's QEV Utility Data platform, contact Jon Enberg, VP of Business Development, jon.enberg(at)wattzon.com Partners across the U.S. use WattzOn's software platform to rapidly acquire customer utility data, analyze the data for actionable insights and engage consumers to increase solar adoption and deliver verified energy savings. To learn more about WattzOn's QEV Utility Data platform, contact Jon Enberg, VP of Business Development, jon.enberg(at)wattzon.com Partners across the U.S. use WattzOn's software platform to rapidly acquire customer utility data, analyze the data for actionable insights and engage consumers to increase solar adoption and deliver verified energy savings.