We have been hearing predictions for decades of a takeover of the world by artificial intelligence. In 1957, Herbert A. Simon predicted that within 10 years a digital computer would be the world's chess champion. That didn't happen until 1996. And despite Marvin Minsky's 1970 prediction that "in from three to eight years we will have a machine with the general intelligence of an average human being," we still consider that a feat of science fiction. The pioneers of artificial intelligence were surely off on the timing, but they weren't wrong; AI is coming.

New Delhi: With its new research lab,based outside United States (US), Google is all set to focus on machine learning as a part of its artificial intelligence. Machine learning is a type of artificial intelligence that provides computer with the ability to learn without being explicitly programmed. Based in Zurich, Switzerland, the new unit called Google Research, Europe is one of largest Google's engineering office outside US. It will be a part of the wider Google Research operation, which includes thousands of people worldwide. The search engine giant made this announcement in its official blogpost where it mentioned that the new group, led by Emmanuel Mogenet will mainly focus on three areas- machine intelligence, natural language processing (NPL) and machine perception.

Since the end of Google IO 2016, a new narrative has been looming around the messaging industry: "AI is the new black". Although the hype has been growing earlier for Privacy-by-Default, Google said: "No, we're choosing AI-by-default". AI, according to Google, will revolutionize how you perceive messaging. For that, Google's new app, Allo, will be listening to all your conversations, thus analyzing your photos and text messages. The goal is to provide you with smart replies and to suggest services that you might need without leaving the app.

The new machine-learning research center will focus on turning Google's ambitions in this space to reality, the company says.

'Til your good is better and your better is best." H2O now has random hyperparameter search with time- and metric-based early stopping. Bergstra and Bengio[1] write on p. 281: Compared with neural networks configured by a pure grid search, we find that random search over the same domain is able to find models that are as good or better within a small fraction of the computation time. Even smarter means of searching the hyperparameter space are in the pipeline, but for most use cases random search does as well. Nearly all model algorithms used in machine learning have a set of tuning "knobs" which affect how the learning algorithm fits the model to the data.

Intelligent, often autonomous, systems are making headway in the datacenter as developers seek to offload manual processes and move beyond traditional approaches like prescriptive IT automation as they struggle to keep up. That's the conclusion of a vendor-backed survey of IT executives about the adoption of intelligent machines and systems based on new AI approaches and other expert systems. Still, the survey sponsored by IT management software specialist Ipswitch notes that early adopters of automated systems are struggling to gauge security and access risks associated with handing the keys to bots and other electronic assistants. "IT decision makers recognize that, while a force for good, these technologies also expose the enterprise to new internal and external risk vectors," Tony Lock, an analyst with survey author Freeform Dynamics, noted in a statement. "As the pace of adoption increases, there will be no escaping the impact of intelligent systems on the enterprise, regardless of whether or not organizations directly invest in such technologies."

Honda Motor Co. will open a new artificial intelligence (AI) research center in Tokyo to commercialize self-driving cars in the future. Honda R&D Co., Honda's research and development subsidiary, announced on June 2 that it will establish Honda R&D Innovation Lab Tokyo by around September in Tokyo's Akasaka district. The move came as Japanese auto companies are desperately seeking personnel who specialize in the cutting-edge area. AI is viewed as the core technology to develop futuristic driverless vehicles. Honda already has a research center in the northern Kanto region, but it will set up a new facility in the capital to hire more skilled information technology engineers.

Artificial intelligence is a common topic explored within the science-fiction genre. Sunspring, a new sci-fi short, instead of using the theme of artificial intelligence in its narrative, used AI to actually produce the narrative in the first place. The film, which had its online debut on Ars, had its screenplay written by an AI which goes by the name of'Benjamin'. The film was submitted as part of the 48-Hour Film Challenge at the Sci-Fi London film festival by Oscar Sharp, a BAFTA-nominated filmmaker and Ross Goodwin, a creative technologist and former Obama administration ghostwriter. Sunspring comes to life through the acting and production. The screenplay is sufficiently vague and nonsensical to leave a lot of room for interpretation.

SugarCRM held its annual user conference, SugarCon, earlier this week in San Francisco. Over 1,200 people were on hand to see what direction the company was taking its platform in. And while many of its competitors are expanding their offerings to include ecommerce, configure-price-quoting (CPQ), marketing automation and other related areas, SugarCRM CEO Larry Augustin emphatically stated that Sugar is staying true to its CRM roots and explore the many ways CRM can be even more important to business success in the near future. I had a chance to speak with Augustin and hear how the company is looking to bring the latest and greatest technology developments to the platform to make CRM a system more relevant, and attractive, for sales professionals to turn to in order to build successful relationships with modern consumers. Below is an edited transcript of that conversation, as well as the video of our full conversation.

At lunch last week, I learned that a couple colleagues were engaged in a little duel--trying to out-walk each other, as tracked by their new Fitbits. Self-improvement was definitely the goal, but seeing peer performance and benchmarks provided the required motivation to achieve that goal. If you're a data science or analytics leader, your job is to manage analysts who produce insights. So, if you want to drive your business through these insights, you have two options. You can either hire more analysts or you can increase the productivity of your existing analysts.