A big shakeup happening in the world of deep learning, as Salesforce announced that it has acquired startup darling MetaMind. As part of the acquisition, MetaMind will shut down on May 4 for unpaid users and June 4 for paid users. Don't miss our biggest TNW Conference yet! With MetaMind and Salesforce coming together, we'll be able to offer customers real AI solutions with breakthrough capabilities that further automate and personalize customer support, marketing automation, and many other business processes. We'll extend Salesforce's data science capabilities by embedding deep learning within the Salesforce platform.

MetaMind, a Palo Alto-based AI startup founded in July 2014, is being acquired by Salesforce. According to a new post published at the company's website by CEO Richard Socher -- a Stanford PhD who studied machine learning, deep learning, natural language processing and computer vision -- Salesforce plans to use its technology to "further automate and personalize customer support, marketing automation, and many other business processes. Salesforce confirmed the deal but isn't disclosing financial details of the transaction or commenting on whether MetaMind's entire team will join its ranks. As a standalone company, MetaMind's general-purpose platform was designed to predict outcomes for language, vision and database tasks. As of the middle of last year, its technology could reportedly answer everything from specific queries about snippets of text to the sentiment of that text.

Dave Perkon is technical editor for Control Design. He has engineered and managed automation projects for Fortune 500 companies in the medical, automotive, semiconductor, defense and solar industries. Put simply, the IoT provides the connection, the cloud provides online storage and convenient applications, and big data provides analysis, management and maintenance of information, which, when combined, can overwhelm the data users and decision makers. Fortunately computers and specifically machine-learning applications, although in their early stages, can help. From the industry or manufacturing side of business, machine learning can be applied to just about any control system that is smart enough to actually alter how it controls a machine in response to changing conditions, but there is much more to it than that.

Silicon Valley was taken aback when Bloomberg profiled a 26-year-old named George Hotz in December who said he had single-handedly built a self-driving car in his garage. It was true that Hotz was an accomplished hacker, being the first person to jailbreak an iPhone. But could a solo effort comprised of 13 cameras really produce results to rival the work of giants like Google, Ford, and General Motors, not to mention well-funded upstarts like Tesla? The skepticism has turned to validation, as Hotz--who made a name for himself by hacking the first iPhone and later, the Playstation 3--has received 3.1 million in funding, led by one of the Valley's most prestigious firms, Andreesen Horowitz. A partner at the firm, Chris Dixon, wrote on Medium that he had tested Hotz's car, brought AI experts to inspect it, and generally "dug deep" into the system.

George Hotz is the founder of Comma.ai, an autonomous driving startup that's roughly six months old. On Monday, top VC firm Andreessen Horowitz announced a 3.1 million investment in the company. Comma.ai is working on a kit that will make it possible to turn regular vehicles into semi-autonomous ones. In October, Hotz purchased a 2016 Acura ILX, cameras and GoPro mounts and started developing the technology out of his San Francisco garage. The goal is to bring the kit -- both computer vision software and the cameras -- to market for less than 1,000 a pop before the end of 2016.

Salesforce.com Inc. is acquiring MetaMind, an artificial-intelligence startup that specializes in deep-learning services, boosting its capabilities for the new technology. The Palo Alto, California-based company helps business users employ deep learning technology, which trains networks of computers to mimic the human brain's ability to recognize and analyze pictures or text without explicit instructions. The acquisition will help Salesforce offer AI capabilities to automate and personalize customer support, marketing and many other business processes, MetaMind said on its website. "We thought about how to maximize our impact with deep learning and we feel like Salesforce is the best place to do that," Richard Socher, MetaMind's chief executive officer, said in an interview. Salesforce is boosting its focus on machine learning and automation as it looks for new ways to bolster its approach to helping customers tackle sales with their own clients.

Toyota (TM - Get Report) announced Monday a collaboration with Microsoft (MSFT - Get Report) in which the automaker would use Microsoft's Azure cloud-based technology to initiate a "data science hub" for Toyota's global operations in Plano, Texas. Toyota said the business unit, called Toyota Connected and headed by Zack Hicks, the Japanese automaker's chief information officer for North America, "will support a broad range of consumer-, business- and government- facing initiatives." Toyota Connected also will coordinate with the automaker's 1 billion artificial intelligence initiative, announced in early November and headed by Gil Pratt, to work on driverless car and related technologies. In the past year, Toyota's American depositary receipts have fallen about 28% compared to a Dow Jones Industrial Average that's about flat. The latest move in digital technology by a global auto giant is another attempt to adapt rapidly to a shifting strategic landscape and a potential upset of the industry's business model.

Here are the basics of what the Panama Papers leak is all about. Photo shows the building where the office of Panamanian law firm Mossack Fonseca is located in Panama City, Panama, April 03, 2016. SAN FRANCISCO -- The 11.5 million leaked documents from the Panamanian law firm Mossack Fonseca are providing a treasure trove of data on a hidden world of offshore accounts and murky dealings. "It's becoming much easier than it used to be to store and move very large amounts of data. I would expect this to continue," said John King, a professor of information at the University of Michigan in Ann Arbor, Mich.

For many people in Zambia with health queries, sending a text message is the best way to get it answered. U-report, a free SMS-based service set up by UNICEF and run by volunteers, receives many thousands of questions a month, many specifically about HIV and AIDS. Also popular in Uganda, U-report has seen usage triple in the last three years, and about a thousand new users register every day. The volume of messages is growing so fast that the volunteers can't keep up, so UNICEF is testing software that reads and responds to many of the messages automatically. In Zambia, there are roughly 27,000 new HIV infections a year, according to UNICEF, and 40 per cent of these are in those aged 15 to 24.

Whether we realize it or not, machine learning is already a part of our everyday lives. Think about a simple Google search, a quick query to Apple's Siri, an afternoon visit to Facebook, or, of course, a great product recommendation on Amazon. As the prevalence of high-performance computing continues to grow, the thought of computers doing things we could only dream of is exhilarating and, for many, almost magical. This is especially true when it comes to marketing. Yet, as we apply machine learning to marketing and unique business goals, oftentimes all of that mystery and intrigue turn to disillusion and struggle with the practical applications.