Sure, I can make the case for how companies like Lockheed and Monsanto will rely on A.I. in the coming years. I already invest in Amazon. I'd want a company AT LEAST AS compelling an investment as Amazon… tough to come across. An analysis of Facebook and Alphabet's Google by research firm Innography shows a surge in AI patent filings that began in 2010. Alphabet currently has more than 3,000 AI patents that are active or pending government approval.

Facebook today named the recipients of 22 servers that Facebook designed specifically for artificial intelligence (A.I.) research. This comes after Facebook's introduction of the giveaway program for academic researchers back in February. University departments in Austria, Belgium, the Czech Republic, France, Germany, Italy, Russia, Switzerland, and the United Kingdom are getting the machines, the designs of which Facebook open-sourced in December. The servers can support as many as eight graphics processing units (GPUs), which are often used to train artificial neural networks (ANNs) with lots of data. After being trained, the ANNs can make inferences on new data.

Tech giant Microsoft has acquired artificial intelligence (AI)-based scheduling service Genee that simplifies the scheduling and rescheduling of large group meetings for companies. Microsoft will integrate the AI technology into Office 365 before shutting down Genee. Co-founders Ben Cheung and Charles Lee, who plan to join Microsoft, started Genee in 2014 to simplify the time-consuming task of scheduling (and rescheduling) meetings. "It is especially useful for large groups and for when you don't have access to someone's calendar," Jha added. Genee uses natural language processing and optimised decision-making algorithms so that interacting with a virtual assistant is just like interacting with a human one.

Facebook's Mark Zuckerberg hopes to show off his Jarvis-like home AI next month Microsoft's new Catapult v2 server design is targeted at AI Facebook's AI plans to analyse your photographs to check your health Mark Zuckerberg is building a futuristic AI assistant for his home, and he'll unveil it in September

A Friday, Aug. 5, 2016 photo shows land in West Jordan, Utah, that may be purchased by FaceBook for a data center. The race between the small town of Los Lunas in New Mexico and the Salt Lake City suburb of West Jordan to entice a new Facebook data center with millions in tax breaks and subsidies is raising questions about public investments in a booming cloud-computing economy that typically brings few local jobs.

For anyone who's heard the "Oompa Loompa" song or Frankenstein pronounced as "Fronkensteen," news of actor Gene Wilder's death on Monday cuts deeply. Wilder died from complications of Alzheimer's disease at age 83, according to his nephew Jordan Walker-Pearlman. Wilder passed away in his hometown of Stamford, Connecticut, late Sunday, reported the Associated Press. He had been diagnosed with non-Hodgkin's lymphoma, a cancer that originates in the lymphatic system, in 1989. Wilder was born Jerome Silberman in Milwaukee and began studying acting at age 12.

Last summer, I was at a conference having lunch with Hal Daume III when we got to talking about how "Bayesian" can be a funny and ambiguous term. It seems like the definition should be straightforward: "following the work of English mathematician Rev. Thomas Bayes," perhaps, or even "uses Bayes' theorem." But many methods bearing the reverend's name or using his theorem aren't even considered "Bayesian" by his most religious followers. Why is it that Bayesian networks, for example, aren't considered… y'know… Bayesian? As I've read more outside the fields of machine learning and natural language processing -- from psychometrics and environmental biology to hackers who dabble in data science -- I've noticed three distinct uses of the term "Bayesian."

For the casual internet user, a quick Google search is often all it takes to find plenty of information on any particular topic. But for specialized financial research, analysts often find themselves laboriously searching proprietary databases, regulatory filings, and paywalled sources that aren't even indexed by the big search engines, says Jack Kokko, the founder and CEO of financial search engine company AlphaSense. That's why he and cofounder and CTO Raj Neervannan created AlphaSense, which applies natural language processing and machine learning techniques to let users find relevant information in financial documents. "It started from my first job out of college as an analyst at Morgan Stanley, where I was, as every analyst, going through these huge piles of paper on my desk and trying to find information very manually--nights and days spent toiling through that information and still fearing that I'm missing a lot," Kokko says. The San Francisco-based company takes in information from thousands of licensed data sources, as well as public web sources like news reports, and automatically processes them to extract meaning on a sentence-by-sentence level.

Consumer adoption of artificial intelligence-powered virtual assistants will increase, but some brands don't see the capabilities fully replacing humans. The number of active users of virtual assistants will grow to 2 billion consumers in 2021, up from 390 million last year, according to new research from Tractica. Global revenue generated by virtual assistants will grow to 16 billion by 2021, up from 2 billion last year. The majority (75%) of revenues will come from the consumer side of the market, according to Tractica. The Asia Pacific region will lead the market in revenue and multiply in value by 10 times to account for more than 5 billion by 2021. "The consumer and enterprise use cases for virtual digital assistants are proliferating rapidly thanks to accelerated innovation and scalability of underlying technologies, such as natural language processing and artificial intelligence," Mark Beccue, principal analyst at Tractica, said in a statement.

New Delhi: While artificial intelligence is making waves globally, Cognitive Business Intelligence (BI) is the next stage of machine learning to design and analyse unstructured data, video, images and human language, say experts. According to them, we are generating data but is this data being analysed to create insights which could help in running businesses more effectively is the real concern for businesses. "This potential can be leveraged using Business Intelligence. Using BI, we can understand what really the data means," said Nikhilesh Tiwari, Co-Founder, Helical Insight, the world's first open source Business Intelligence (BI) framework. At the moment, less than 0.5 per cent of all data is ever analysed and used globally.