For those of us that follow artificial intelligence (AI), we are often bombarded with negative messages about the role of AI. Generally, these messages are either based on a false understanding of AI, thinking that it is some sort of replacement for knowledge workers instead of a tool, or the negativity that comes from Hollywood films. However, once in a while a non-biased academic source publishes research on the role of AI and the future of work. Early this month, Stanford University released an artificial intelligence impact study as part of its One Hundred Year study of Artificial Intelligence. "Contrary to the more fantastic predictions for AI in the popular press, the Study Panel found no cause for concern that AI is an imminent threat to humankind… Instead, increasingly useful applications of AI, with potentially profound positive impacts on our society and economy are likely to emerge between now and 2030, the period this report considers."

The sale of artificial intelligence-based platforms to business started off as a multi-million dollar pitch targeted toward the CEO, according to Nova Spivack, the founder and CEO of Bottlenose. The Los Angeles-based startup is looking to automate the application of AI to business intelligence, as well as much of the work of data scientists, currently in scarce supply. That should lower the price, a lot. In recent years, AI-driven applications have been targeted toward the CIO. In the future, Mr. Spivack says, they well may be sold directly to business leaders, and the price will drop to thousands or even hundreds of dollars per user, he told CIO Journal.

"Inbenta was founded in 2005 with a vision of leveraging artificial intelligence in an entirely new manner to transform how companies and customers interact," said Jordi Torras, founder and CEO, Inbenta. "That vision has been realized, and now Inbenta is in a period of dramatic and profitable growth including global expansion into 23 countries and support for over 20 languages. This Series B financing will help bring our technology to a much larger group of demanding customers who need enterprise-grade solutions, and to further drive the innovation that underpins our technology." The funding will be used to expand sales and marketing, and to further drive product development for Inbenta's industry-leading natural language processing (NLP) technology that powers search, chatbots, and self-service solutions for customer support and e-commerce. Inbenta's products are now used by over 200 customers around the world, including Ticketmaster, B&H, CA Technologies and 8x8 to enhance customer engagement, increase retention, and drive sales.

As cars become more computerized, they're also facing a greater risk of being hacked. That's why Volkswagen is founding a new cyber security company devoted to protecting next-generation vehicles. On Wednesday, the automaker said it would partner with a former Israeli intelligence agency director to jointly establish a new company, called Cymotive Technologies. It's unclear how much Volkswagen is investing in the new firm, but security experts have been warning that internet-connected cars and self-driving vehicles could one day be a major target for hackers. Even older cars from Volkswagen are vulnerable.

Tech investor Marc Andreessen took the stage Tuesday at TechCrunch Disrupt in San Francisco. SAN FRANCISCO – For tech entrepreneurs, these are both the best of times and the gnarliest of times. But only standout ideas with either unique intellectual property or quantifiable traction are likely to benefit in the form of investments or acquisitions from this buoyant climate. "Only strong companies are getting acquired," Greylock Ventures' Josh Elman told attendees at TechCrunch Disrupt Tuesday, citing the 1 billion price tags paid for self-driving car startup Cruise Automation (General Motors) and Dollar Shave Club (Unilever). Elman might have added another recent purchase to the list, Microsoft's 26 billion spend for professional networking site LinkedIn, founded by Elman's fellow Greylock colleague and panelist, Reid Hoffman.

The White House is lifting economic sanctions and restoring trade benefits to former pariah state Myanmar, officials said Wednesday, as Aung San Suu Kyi, a former political prisoner and now the nation's de facto leader, met with President Obama. Suu Kyi's party swept historic elections last November, and the visit by the 71-year-old Nobel peace laureate, deeply respected in Washington, is a crowning occasion in the Obama administration's support for Myanmar's shift to democracy, which the administration views as a major foreign policy achievement. The U.S. has eased broad economic sanctions since political reforms began five years ago but has retained more targeted restrictions on military-owned companies and dozens of officials and associates of the former ruling junta in Myanmar, also known as Burma. U.S. companies and banks have remained leery of involvement in one of Asia's last untapped markets. Human rights groups, however, say there are powerful reasons for retaining sanctions.

The stated purpose of the research was to warn privacy and security enthusiasts of the threat from machine learning and AI to be used as a tool for identification and data collection. However, the threat may not be as bad as they claim. Machine learning cannot reverse the pixelation and recreate images, so anyone worried about blurred pictures of them can rest vaguely easy, at least for now. It can't actually recreate the pictures. It is also only successful when identifying things it's been specifically trained to look for.

Consider your repetitive daily tasks. Do you, or your employees, follow a process to perform these? If so, then this job, or at least the repetitive part of it, will almost definitely be replaced by a robotic usurper. No industry will be unchanged from the "robot revolution". Disruption is already occurring in many of the commoditised functions of accounting and legal advice, for example.

Recurrent neural networks are one of the staples of deep learning, allowing neural networks to work with sequences of data like text, audio and video. They can be used to boil a sequence down into a high-level understanding, to annotate sequences, and even to generate new sequences from scratch! The basic RNN design struggles with longer sequences, but a special variant – "long short-term memory" networks – can even work with these. Such models have been found to be very powerful, achieving remarkable results in many tasks including translation, voice recognition, and image captioning. As a result, recurrent neural networks have become very widespread in the last few years. As this has happened, we've seen a growing number of attempts to augment RNNs with new properties. Individually, these techniques are all potent extensions of RNNs, but the really striking thing is that they can be combined together, and seem to just be points in a broader space.

Diane Greene, executive vice president of Google Cloud Enterprise, appeared on stage at TechCrunch Disrupt San Francisco with TechCrunch editor Matt Burns today, and talked about her role running Google's massive cloud business. She came on board last year when Google bought her startup, bebop Technologies for 348 million, and she immediately brought with her enterprise credibility. Her resume includes helping start VMware before selling the company to EMC for 635 million, then helping bring it public under the EMC federation in 2007. At VMware, she worked on the virtual machine technology that would become the basic building blocks for cloud infrastructure services. Today, with that depth of experience, she is trying to help Google catch market leaders Amazon Web Services and Microsoft Azure.