Doom and gloom scenarios for massive unemployment usually put the blame square on emerging cognitive technologies, including Robotics Process Automation (RPA), artificial intelligence and machine learning. This disruptive digital destiny is predicted by some to affect two-thirds of the knowledge worker marketplace and eliminate millions of jobs from the economy. However, automation can also create new jobs and enhance human skills and expertise. Certainly, as businesses and governments seek to streamline processes and reduce costs, many jobs will likely be reconfigured and redesigned, especially middle-income routine work. But that doesn't mean humans are going anywhere: Ultimately, cognitive technologies can transform the enterprise into a powerful innovation engine.

At its Cloud Next conference in San Francisco, Google today announced the launch of a new machine learning API for automatically recognizing objects in videos and making them searchable. The new Video Intelligence API will allow developers to build applications that can automatically extract entities from a video. Until now, most similar image recognition APIs available in the cloud only focused on doing this for still images, but with the help of this new API, developers will be able to build applications that let users search and discover information in videos. That means you can search for "dog" or "flower," for example. Besides extracting metadata, the API allows you to tag scene changes in a video.

Artificial intelligence (AI) is not just transforming ecommerce. Ecommerce came about because the internet made it easy to find what you were looking for. The digital age made the physical world appear closer, so you could buy things from distant countries. Early adopters assumed ecommerce would be fueled by economics of scale and lower costs, but those weren't the main drivers: It was convenience. Websites made information freely available.

Deep learning, a form of artificial intelligence (AI) where computers are taught to recognize patterns in huge datasets, can now be useful in identifying breast cancer. Google reported March 3, Friday, that it has achieved groundbreaking results in using AI to analyze thousands of cancer cell slides from a Dutch university and diagnose the common form of cancer. A pathologist's report is usually the gold standard in diagnosing many diseases, including breast cancer. But even with extensive training and experience, there can be variations in diagnoses by different pathologists. "[A]greement in diagnosis for some forms of breast cancer can be as low as 48 [percent], and similarly low for prostate cancer," Google wrote in a blog post.

Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer. Artificial intelligence (AI) is no longer science fiction. And like any game-changing technology, AI is not exactly what we expected – at least not yet.

Fei-Fei Li, chief scientist of artificial intelligence and machine learning at Google Cloud, came on stage at Google's Next Cloud conference today to talk about the current and next-generation applications of AI that Google's working on. These technologies will make a difference in self-driving cars and healthcare, sure, but also Snapchat's filters and Google Photos' search capabilities. But the big highlight came when she announced a new way to allow software to parse video. This new "Video Intelligence API" was demoed onstage, and it offered the kind of "whoa" moment you expect from a Google keynote. By playing a short commercial, the API was able to identify the dachshund in the video, when it appeared in the video, and then understand that the whole thing was a commercial.

Imagine that, in 20 or 30 years, a company creates the first artificially intelligent humanoid robot. She looks like a person, talks like a person, interacts like a person. If you were to meet Ava, you could relate to her even though you know she's a robot. Ava is a fully conscious, fully self-aware being: She communicates; she wants things; she improves herself. She is also, importantly, far more intelligent than her human creators.

There is no such thing as AI. And in the true human sense there never will be. Skynet will not take over the world. But yes, Skynet will be used by humans to try and take over the world. Both technologies are perfect for Big Brother.

Machine learning is complex, but nonetheless has pushed its way to professional and maker communities alike. Nvidia has lead much of this with their TK1 and TX1 modules; now, with the new release of the Jetson TX2, the AI capabilities we have access to have just doubled. The new hardware, announced last night at a press event in San Francisco, retains the same form factor as the TX1 -- roughly the size of a credit card, it's meant as a drop-in replacement. It replaces the TX1's Mawell GPU with a Pascal unit, doubles the TX1's storage and memory, and increases its video encoding and decoding specs. With it, the company states that it can get either twice the performance of the TX1 (handling object detection and tracking from two 4K cameras simultaneously), or get double the efficiency running the same configuration as a TX1.

"Let us consider an augmented architect at work. He sits at a working station that has a visual display screen some three feet on a side, this is his working surface, controlled by a computer with which he can communicate by means of small keyboards and various other devices." This vision of the future architect was imagined by engineer and inventor Douglas Engelbart during his research into emerging computer systems at Stanford in 1962. At the dawn of personal computing he imagined the creative mind overlapping symbiotically with the intelligent machine to co-create designs. This dual mode of production, he envisaged, would hold the potential to generate new realities which could not be realized by either entity operating alone.