Facebook has acquired a facial image analysis firm FacioMetrics as it tries to give users new features to add special effects to photos and videos. The technology developed by the startup also includes capabilities for face tracking and recognizing emotions, which could potentially open up other applications for Facebook. The financial terms of the acquisition of FacioMetrics, a startup that was spun off from Carnegie Mellon University, were not disclosed. Facebook will discontinue the products, which are no longer available on app stores.The FacioMetrics website now only has a message about the acquisition. "How people share and communicate is changing and things like masks and other effects allow people to express themselves in fun and creative ways," a Facebook spokesman wrote in an email Wednesday.
Machine learning and the artificial intelligence that it promises to deliver are clearly here to stay. The only remaining question is what will these technologies conquer next? The algorithms and techniques that have been exciting researchers and practitioners over the last few years are being dramatically improved, tuned for perfection, and in some cases completely replaced by a new generation of increasingly powerful algorithms. The investments in areas such as deep learning and the promise of building multi-layer perceptron (or artificial neurons) to solve a host of challenging problems has started to move out of dusty offices and laboratories toward the center of our economy in areas such as healthcare, marketing, communications, finance, energy, education, and even public safety. The number of useful applications is growing rapidly and the benefits of early investments by technology giants and influential research institutions are paying off nicely.
At Facebook's recent annual developer conference, Marc Zuckerberg outlined the social network's artificial intelligence (AI) plans to "build systems that are better than people in perception." He then demonstrated an impressive image recognition technology for the blind that can "see" what's going on in a picture and explain it out loud. From programs that help the visually impaired and safety features in cars that detect large animals to auto-organizing untagged photo collections and extracting business insights from socially shared pictures, the benefits of image recognition, or computer vision, are only just beginning to make their way into the world -- but they're doing so with increasing frequency and depth. It's busy enough that the upcoming LDV Vision Summit, an annual conference dedicated to all things visual tech, from VR and cameras to medical imaging and content analysis, is already in its third year. "The advancements in computer vision these days are creating tremendous new opportunities in analyzing images that are exponentially impacting every business vertical, from automotive to advertising to augmented reality," says Evan Nisselson of LDV Capital, which organizes the summit.
In 2025, in accordance with Moore's Law, we'll see an acceleration in the rate of change as we move closer to a world of true abundance. Here are eight areas where we'll see extraordinary transformation in the next decade: In 2025, 1,000 should buy you a computer able to calculate at 10 16 cycles per second (10,000 trillion cycles per second), the equivalent processing speed of the human brain. The Internet of Everything describes the networked connections between devices, people, processes and data. By 2025, the IoE will exceed 100 billion connected devices, each with a dozen or more sensors collecting data. This will lead to a trillion-sensor economy driving a data revolution beyond our imagination. Cisco's recent report estimates the IoE will generate 19 trillion of newly created value. With a trillion sensors gathering data everywhere (autonomous cars, satellite systems, drones, wearables, cameras), you'll be able to know anything you want, anytime, anywhere, and query that data for answers and insights. SpaceX, Google (Project Loon), Qualcomm and Virgin (OneWeb) are planning to provide global connectivity to every human on Earth at speeds exceeding one megabit per second. We will grow from three to eight billion connected humans, adding five billion new consumers into the global economy. They represent tens of trillions of new dollars flowing into the global economy. And they are not coming online like we did 20 years ago with a 9600 modem on AOL. Existing healthcare institutions will be crushed as new business models with better and more efficient care emerge. Thousands of startups, as well as today's data giants (Google, Apple, Microsoft, SAP, IBM, etc.) will all enter this lucrative 3.8 trillion healthcare industry with new business models that dematerialize, demonetize and democratize today's bureaucratic and inefficient system. Biometric sensing (wearables) and AI will make each of us the CEOs of our own health. Large-scale genomic sequencing and machine learning will allow us to understand the root cause of cancer, heart disease and neurodegenerative disease and what to do about it. Robotic surgeons can carry out an autonomous surgical procedure perfectly (every time) for pennies on the dollar. Each of us will be able to regrow a heart, liver, lung or kidney when we need it, instead of waiting for the donor to die. Billions of dollars invested by Facebook (Oculus), Google (Magic Leap), Microsoft (Hololens), Sony, Qualcomm, HTC and others will lead to a new generation of displays and user interfaces.
CEVA, Inc. (NASDAQ: CEVA), the leading licensor of signal processing IP for smarter, connected devices, today announced that Novatek Microelectronics, Taiwan's 2nd largest fabless IC design house, has licensed and deployed the CEVA-XM4 intelligent vision DSP for its next-generation vision-enabled System-on-Chips (SoCs) targeting a range of end markets requiring advanced visual intelligence capabilities. Novatek's current camera SoC lineup for car DVR and surveillance systems integrates the 3rd generation CEVA-MM3101 imaging & vision DSP and is shipping in volume. By integrating CEVA-XM4 as a dedicated vision processor in their next-generation SoC designs, Novatek and its customers can rapidly deploy highly-sophisticated vision algorithms to enable advanced applications such as surveillance systems with face detection and authentication, drone anti-collision systems and advanced driver assistance systems (ADAS). These types of applications are built utilizing CEVA's Deep Neural Network (CDNN2), a proprietary software framework that enables deep learning tasks to run on the CEVA-XM4 and outperform any GPU or CPU-based system in terms of speed, power consumption and memory bandwidth requirements. "The CEVA-XM4 is an exceptional processor for imaging and computer vision, offering outstanding performance, flexibility and power efficiency for applications requiring visual intelligence capabilities," said Allen Lu, Assistant Vice President of iVoT SBU, Novatek.