Does the idea of humanlike machines or machinelike humans freak you out? Maybe, but if we want to stay relevant in the face of the coming robot revolution, Elon Musk says we'll have to become more cyborg-like. Though he stopped short of warning humankind that "resistance is futile," Musk mentioned that we will have to merge with machines somehow. "Over time I think we will probably see a closer merger of biological intelligence and digital intelligence," Musk told an audience at the World Government Summit in Dubai, where he was launching Tesla in the United Arab Emirates, CNBC reports (warning: link contains auto play video). "It's mostly about the bandwidth, the speed of the connection between your brain and the digital version of yourself, particularly output," he added, explaining that he means computers can communicate "a trillion bits per second", while we lumps of meat can only go at about 10 bits per second by typing.

Google announced today it has acquired machine learning startup Moodstocks in an effort to bolster its work around smartphone image and item recognition. Terms of the deal were not disclosed. See how the cloud is disrupting traditional operating models for IT departments and entire organizations. Moodstocks began developing image recognition technology in 2012 and more recently shifted into object recognition technology. The Paris-based startup said on its website that its "dream has been to give eyes to machines by turning cameras into smart sensors able to make sense of their surroundings."

After a soft start to 2016, the Nasdaq Composite rallied strongly from mid-February through the year's end, finishing with a slightly above-average 9.8% gain. However, 2016 was anything but average for two large-cap tech companies whose shares dramatically outperformed the market averages on the year. Moving large-cap stocks like these requires an impressive catalyst. So let's examine what triggered the rallies in NVIDIA and Computer Sciences shares in 2016 and consider how investors should think about their shares in 2017 and beyond. Investors continued to awaken to NVIDIA's enviable long-term growth potential in 2016, continuing the extended rally in its shares.

Ford is investing $1 billion in a secretive artificial intelligence startup headed by former Google and Uber execs to advance its self-driving car efforts. The startup, Argo AI, was founded by Bryan Salesky, the former director of hardware for Google's self-driving-car efforts, and Peter Rander, Uber's engineering lead at its autonomous cars center. Argo AI is based in Pittsburgh, Penn. The $1 billion investment will be spread out over five years as Ford looks to commercialize its self-driving technology by 2021. According to Ford Chief Technical Officer Raj Nair, $1 billion is what it costs to develop advanced autonomous technology, and the investment is consistent with what Ford said its capital allocation in the space would be when it presented information to investors last year.

Sophos has announced a deal to acquire the core technologies of anti-malware protection outfit Invincea for $100m plus up to $20m, dependent on first-year revenues. Invincea makes a line of signature-less endpoint procession technologies that rely on machine learning and behavioural monitoring to block malware. Sophos plans to integrate Invincea's tech into the Sophos Central endpoint product line, before releasing revamped products later his year. The plan parallels the integration of SurfRight's technology into Sophos's product line following a smaller December 2015 acquisition. In the 12 months to 31 March 2016, Invincea recorded billings of $13.4m, revenue of $9.8m and a loss before tax of $11.8m.

Nvidia continued to see demand for its graphics processors in the emerging world of artificial intelligence in its fourth quarter earnings reported Thursday. In its fourth quarter earnings release, the Santa Clara, Calif.-based company reported revenue of $2.17 billion, up 55% year over year, on earnings per share of $1.13, up 117% a year ago. Wall Street analysts estimated $2.11 billion in revenue on EPS of 83 cents. Traditionally, the company's processors have been mostly used to power the latest gaming graphics, but the chips have become popular to run AI software in the data center and autonomous vehicles. A specific branch of AI, called deep learning, is where Nvidia's processors particularly shine.

Nvidia CEO Jen-Hsun Huang introducing the Nvidia Spot, a USD 49.95 microphone and speaker that will let owners use Google Assistant anywhere in a home, at the company's CES 2017 keynote (Photo by Ethan Miller/Getty Images) Nvidia continued to see demand for its graphics processors in the emerging world of artificial intelligence in its fourth quarter earnings reported Thursday. In its fourth quarter earnings release, the Santa Clara, Calif.-based company reported revenue of $2.17 billion, up 55% year over year, on earnings per share of $1.13, up 117% a year ago. Wall Street analysts estimated $2.11 billion in revenue on EPS of 83 cents. Traditionally, the company's processors have been mostly used to power the latest gaming graphics, but the chips have become popular to run AI software in the data center and autonomous vehicles. A specific branch of AI, called deep learning, is where Nvidia's processors particularly shine.

Nvidia posted its fourth quarter results on Thursday, once again surpassing market expectations. However, its outlook for the current quarter is only slightly above market market consensus. Shares fell in after-hours trading. Non-GAAP earnings for the quarter were $1.13, up 117 percent from a year earlier. Revenue came to $2.17 billion, up 55 percent year-over-year.

Law enforcement agencies across the country are adopting body-worn cameras as a means both of increasing their transparency with the public and generating actionable feedback to improve officer performance. Problem is, all these body cams produce terabytes of data daily, far more than many departments can effectively handle. That's why Taser (yes those guys, they make body cameras too) announced on Thursday that it has acquired a pair of companies that specialize in computer- and machine-vision to create the "Axon AI" group. Together, they'll develop a platform that can efficiently parse this flood of data in real time. The Axon AI group will include about 20 programmers and engineers.

Sophos (LSE: SOPH), a global leader in network and endpoint security, today announced it has entered into an agreement to acquire Invincea, a visionary provider of next-generation malware protection. Invincea's endpoint security portfolio is designed to detect and prevent unknown malware and sophisticated attacks via its patented deep learning neural-network algorithms. It has been consistently ranked as among the best performing machine learning, signature-less next-generation endpoint technologies in third-party testing and rated highly both for high detection and low false-positive rates. Headquartered in Fairfax, Va., Invincea was founded by chief executive officer Anup Ghosh to address the rapidly growing zero-day security threat from nation states, cyber criminals and rogue actors. Invincea's flagship product X by Invincea uses deep learning neural networks and behavioral monitoring to detect previously unseen malware and stops attacks before damage occurs.