Artificial Lawyer spent 12 happy hours at the Legal Geek Conference on Brick Lane in East London yesterday and can confirm to those who might be wondering, that yes, this was the best legal tech event of the year. The success of the event was very much driven by an entrepreneur himself, Jimmy Vestbirk, who created Legal Geek and set the tone from the get-go, with a great Truman Brewery space for the event and mandatory high fives to the attendees sitting on either side. There was also a no ties policy and that deserves a special commendation. What set this event apart from others was that the speakers were the real thing. They were the founders and/or senior staff members of the legal AI companies everyone else is talking about.

We are on the cusp of an exciting -- and unchartered -- new era in technology, where decisions and problem-solving will be aided by smart machines that will sense, learn, infer and even think on behalf of humans. Although not yet mainstream, smart machines are increasingly making appearances in the form of autonomous cars, robots and other cognitive computing systems that are able to solve problems and make decisions without human intervention. Conversational user interfaces are also on the rise, relying on smart technologies and machine learning to facilitate dialogue between people and bots. The proliferation of data and intelligent platforms has become increasingly prevalent and is beginning to shape the way businesses must transform their own organizations to become more agile and adaptive in how they go to market and engage with their customers. Smart machines can help marketers filter out mountains of noise to pinpoint that single piece of insight needed to make a more informed decision.

Microsoft on Tuesday said that its researchers have "made a major breakthrough in speech recognition." In a paper [PDF] published a day earlier, Microsoft machine learning researchers describe how they developed an automated system that can recognize recorded speech as well as a professional transcriptionist. Using the NIST 2000 dataset of recorded calls, Microsoft's software performed slightly (0.4 per cent) better than the error rate the company attributes to professional transcriptionists (5.9 per cent) for the Switchboard portion of the data, in which strangers discuss a specified topic. It saw a similarly narrow margin of success with the CallHome portion of the data – in which family members converse without guidelines – where the human transcription error rate was 11.3 per cent. A month ago, Microsoft's researchers reported that their software had achieved a 6.3 per cent word error rate.

The major-party presidential candidates, Hillary Clinton and Donald Trump, have spent decades in the public eye as key figures of American culture. Their portraits have covered magazines, newspapers and websites for decades. The major-party presidential candidates, Hillary Clinton and Donald Trump, have spent decades in the public eye as key figures of American culture. Their portraits have covered magazines, newspapers and websites. Photos: A visual history of virtual reality headsets (it ain't always pretty) p In these heady days of tech innovation it's easy to lose track of what's … A centuries-old Yemeni city stands alongside the gleaming towers of Hong Kong as one of the world's most beautiful architectural views, writes Jonathan Glancey.

With more selection available to online shoppers than ever before, finding items that are perfect for you and your budget can be time consuming. At eBay, our focus is to help shoppers find their version of perfect and simplify the shopping experience. In addition to major enhancements we've been making to our core platform, we've also been hard at work on a new commerce experience powered by artificial intelligence (AI), cloud computing, and human judgment. We're starting to bring this experience to life with eBay ShopBot, which debuts today in beta on Facebook Messenger. Our vision is to make shopping with eBay as easy as talking to a friend, whether you are looking for something specific or just browsing for inspiration.

The Royal Navy is planning to step up its use of AI to improve maritime defence, beginning with STARTLE, which is AI software that can can spot potential threats. At a briefing titled "Artificial Intelligence in Royal Navy Warships" hosted by non-profit TechUK, Blighty's navy announced it was keen to explore the potential of using machine-learning to improve operational capability in its fighting units under Project NELSON. Developed by Roke Manor Research, the company claims it is the first supplier to integrate AI software into a Defence Science and Technology Laboratory-sponsored maritime combat system demonstrator. Mike Hook, lead software architect on STARTLE at Roke, told The Register: "It's hard to implement new technology in warships because it has so much proprietary software. But integrating STARTLE will give it new data to do trials with."

If you like this project, please give me a star. This is my multi-month study plan for going from mobile developer (self-taught, no CS degree) to machine learning engineer. My main goal was to find an approach to studying Machine Learning that is mainly hands-on and abstracts most of the math for the beginner. This approach is unconventional because it's the top-down and results-first approach designed for software engineers. Please, feel free to make any contributions you feel will make it better.

Advanced machine learning, artificial intelligence and data science will be among the top new technologies shaping business trends through 2017 and beyond, according to analyst firm Gartner Inc. The research firm presented its Top Ten Strategic Technology Trends for 2017 at the Gartner Symposium/Itxpo in Orlando, Fl., this week. It said it expects to see "intelligence everywhere" permeate through the enterprise IT landscape in the next three to five years, in the shape of new software-based systems that are programmed to learn and adapt. David Cearley, Gartner vice president and fellow, said these intelligent trends will intertwine to create a "digital mesh" that blurs the boundary between digital and physical workspaces. Gartner predicts AI will become "the next battleground through 2020", and we've already seen the battle lines being drawn with companies like Google, Microsoft and IBM all advancing their own machine learning algorithms via the open-source community, while Salesforce.com Inc. recently introduced its own Einstein platform to underpin its services.

Today, a digital stethoscope has the ability to record and store heartbeat and respiratory sounds. Tomorrow, the stethoscope could function as an "intelligent thing" by collecting a massive amount of such data, relating the data to diagnostic and treatment information, and building an artificial intelligence (AI)-powered doctor assistance app to provide the physician with diagnostic support in real-time. AI and machine learning increasingly will be embedded into everyday things such as appliances, speakers and hospital equipment. This phenomenon is closely aligned with the emergence of conversational systems, the expansion of the IoT into a digital mesh and the trend toward digital twins.

In my first blogpost, I introduced the basic concept of machine learning and how it contributes to the world of IT security. Now I want to dig deeper and showcase those machine learning algorithms used by Blindspotter, BalaBit's user behavior analytics tool. Blindspotter does not rely on a single "silver bullet of algorithms", but combines eight algorithms to achieve better predictive performance. A well-disguised and well-prepared insider or external attacker may deceive one, two or in rare cases even three algorithms, but it is more than improbable that he or she would able to deceive all of them. Let's see an example, in which Mallory, the malicious senior sysadmin tries to steal valuable intellectual property of her employer and sell it to a competitor. Blindspotter's main concept is the prioritization of security incidents and events.