Mark Zuckerberg expects artificial intelligence will progress to make computers better than humans at basic sensory perception within the next 10 years, and that Facebook will end up knowing a lot more about you than it does now. The prediction is the latest from a top tech CEO to indicate the fast improvement being made in machine learning systems that just a few years ago would have struggled to recognize a dog from a cat. The Facebook CEO was speaking about core things that humans do, such as seeing, hearing and understanding language and was careful to clarify that computers will still have limited abilities elsewhere. "That doesn't mean that the computers will be thinking or be generally better, but that is useful for a number of things," he told financial analysts on a conference call on Wednesday. In recent months, senior executives at Google have also talked up AI.

Zhang Yaqin, president of Baidu Inc, speaks at the global business forum during Baidu Technology Innovation Conference 2016, on Sept 2. [Photo provided to chinadaily.com.cn] Chinese internet giant Baidu Inc seems to be dazzling the world nonstop. Robin Li, its chairman and chief executive, announced "Baidu Brain" on Thursday, the core of the tech company's plans on artificial intelligence, which consists of three parts - artificial intelligence algorithms, computing power and big data. The next day, at the global business forum also during Baidu Technology Innovation Conference 2016, Baidu's President Zhang Yaqin said the company's revenue coming from its global business has more than quintupled by September from a year earlier. Baidu's globalization, along with "Baidu Brain", is the next big vision for the company, said Zhang.

NVIDIA CEO Jen-Hsun Huang made the announcement today during the Baidu World Conference, noting that the companies will unit to merge their individual technical capabilities to crate a new self-driving car architecture from scratch: "end-to-end, top-to-bottom, from the cloud to the car," as Huang explained. Baidu will use the platform created in tandem with NVIDIA to roll out self-driving taxis in China. Though that's the primary purpose for the partnership, the software's applications are numerous, as both Baidu and NVIDIA are working to make it open for other automotive creators to fit with their own plans for self-driving vehicles. NVIDIA already has its own ideas for autonomous cars, with the Drive PX supercomputer for processing data that's inbound from various sensors, a cloud-based 3D map, and an AI operating system. It's called Drive PX 2, and Volvo is already testing it with a set of self-driving vehicles.

Auto accidents kill more than 33,000 Americans each year, more than homicide or prescription drug overdoses. Companies working on self-driving cars, such as Alphabet and Ford, say their technology can slash that number by removing human liabilities such as texting, drunkenness, and fatigue. But Christopher Hart, chairman of the National Transportation Safety Board, says his agency's experience investigating accidents involving autopilot systems used in trains and planes suggests that humans can't be fully removed from control. He told MIT Technology Review that future autos will be much safer, but that they will still need humans as copilots. What follows is a condensed transcript.

The Chinese Internet giant Baidu Inc. has been making big progress in applying deep learning neural networks to improve image recognition, language translation, search ranking and click prediction in advertising. Now, it's going to give a lot of it away. The company, often called "China's Google," will announce Thursday at the annual Baidu World conference in Beijing that it's offering the artificial intelligence software that its own engineers have been using for years as open source. Available in an early version on GitHub with full availability Sept. 30, it's code-named PaddlePaddle, for PArallel Distributed Deep LEarning. Deep learning is the branch of machine learning that attempts to emulate the way neurons work in the human brain to find patterns in data representing sounds, images, and other data.

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Recently I heard the strains of Bach's Sonata No 3 in G Minor (BWV 1029) Allegro, and as I pondered on the richness, harmony and texture of the sounds. I recalled I had heard this before listening to a live broadcast of the same piece of music on the BBC. It was Alissa Firsova's fantastic arrangement of the final movement of Bach's Viola da Gamba sonata in G minor performed by the Royal Philharmonic Orchestra conducted by Andrew Litton on 14th August 2010 at the Royal Albert Hall. I pulled out my phone and loaded Shazam I wanted to find out who had performed this particular piece. Shazam did its thing and in seconds I had the details of Glenn Gould Remastered Columbia Album, of course it had to be.

In his fifteenth post in the series, Marshall Kirkpatrick focuses on the intersection between artificial intelligence and social media. By way of reminder, Marshall launched a 30 day series that explores the intersection between AI and the various innovation components on my emerging futures visual. As he has in each post, Marshall identifies the key subject matter experts that sit at the intersection of AI and the visual component in question. In the case of social media, the key influencers are: Marshall Kirkpatrick, Tamara McCleary, and Amber Armstrong. Here is the foresight and related future scenarios identified at the intersection of Artificial Intelligence and social media (taken straight from Marshall's post): Much of AI today is focused on recommendations.

AI is also emerging as a force for startups and emerging companies, too, as several entrepreneurial ventures in North Carolina are demonstrating in "fintech." Financial technology, better known as fintech, startups account for 10 percent of the some 90 companies chosen to present at the upcoming Council for Entrepreneurial Development's annual venture conference. A new report cites the plunging costs and advances of artificial intelligence as key drivers. AI's impact alone in one sector of fintech shows its potential. According to Juniper Research, fintech platforms are being used for review and approval/disapproval of unsecured consumer loans at a remarkable rate.

We identified over 90 companies that are applying machine learning algorithms and predictive analytics to reduce drug discovery times, provide virtual assistance to patients, and diagnose ailments by processing medical images, among other things.