I'm reviewing a different type of Chart today since while reviewing Google's Demo Account while working on some new learning materials for our members I noticed the intriguing new Conversion Probability feature Beta. Here's what it shows for the one hundred thousand odd sessions in the Demo account: You can see that it breaks down these sessions into likelihood to convert, so if we can learn more about what turns the high-converting visitors onto our products, we have more chance of finding and converting more visits in future. As we explain in our AI and machine learning guide, for us, the most exciting marketing application of artificial intelligence is using machine learning to learn from historic interactions with our audiences see what influences their propensity to convert. Using this insight we can tailor our communications to be more relevant. Here, Google analyses historic visits of sites which have at least 1,000 e-commerce transactions to see which of all the variables available in analytics like visitor source, content consumed and path determine propensity to purchase.
AI start-ups Crossbar, Gyrfalcon Technology, Neural Networks Corporation and Robosensing are getting together to deliver an AI platform and standard for edge computing, gateways, cloud and data centers. The group, called SCAiLE (SCalable AI for Learning at the Edge), is already working with Japanese authorities to review opportunities for the 2020 Olympics, including video-based event detection and response capability. The organization will combine advanced acceleration hardware, resistive memory (ReRAM), optimized neural networks to create ready-made, power-efficient solutions with unsupervised learning and event recognition capability. The consortium addresses the restrictions of traditional AI methodologies that depend on classification of data. The huge growth of IoT systems including thousands of remote edge devices such as sensor-equipped cameras creates a torrent of unstructured information in multiple forms that pours into cloud-located servers and that cannot be handled effectively by classification alone.
The HPE SGI 8600 platform will be the core component of the Jean Zay Aiu supercomputer in France. In this podcast, the Radio Free HPC team asks whether a supercomputer can or cannot be a "AI Supercomputer." The question came up after HPE announced a new AI system called Jean Zay that will double the capacity of French supercomputing. So what are the differences between a traditional super and a AI super? According to Dan, it mostly comes down to how many GPUs the system is configured with, while Shahin and Henry think it has something to do with the datasets.
Venture capital (VC) investment in the UK's growing artificial intelligence (AI) sector leapt almost six-fold from 2014 to 2018, with funding comprising almost as much as the rest of Europe combined. According to research prepared for Tech Nation and the Digital Economy Council by Dealroom, investment in UK AI startups reached US$ 1.3 billion in 2018. Notable deals in 2018 included Bristol-based Graphcore which raised US$200m. Throughout 2018, Dealroom recorded 82 venture capital fundraisings across UK companies, compared to 70 in the previous year-- that's a continuation of a trend that's seen investment in AI companies grow sharply over the last five years. "These statistics are further confirmation that the UK is Europe's undisputed number one tech hub," said the UK digital secretary, Jeremy Wright.
If you've been following the work of Boston Dynamics (currently owned by Softbank) you've probably seen some of their four legged and wheeled robots which are able to navigate all sorts of obstacles and remain standing after being kicked, shoved, and pushed. While some of these robots, such as their BigDog, WildCat, and Spot appear to have an amazing ability to mimic an animal's gait. However, last year they introduced a two-legged anthropomorphic robot called Atlas, which was based on a more primitive biped called Petman. When I first saw Atlas I was impressed by its (his?) ability to perform some basic human-like tasks, such as picking up objects and resisting a human's attempts to knock it over. Still, it most often looked as though it would have a tough time passing a field sobriety test when it attempted to traverse even moderately rough terrain.
You very well know that Artificial intelligence has already made its impact on many industries. Has Artificial Intelligence also made an impact in a similar area? This new technology has made many changes in the testing area of software. So, today, Applications act with many via the application protocol interface. The complex situations get solved with ease via the AI algorithms.
Research groups at KAIST, the University of Cambridge, Japan's National Institute for Information and Communications Technology, and Google DeepMind argue that our understanding of how humans make intelligent decisions has now reached a critical point in which robot intelligence can be significantly enhanced by mimicking strategies that the human brain uses when we make decisions in our everyday lives. In our rapidly changing world, both humans and autonomous robots constantly need to learn and adapt to new environments. But the difference is that humans are capable of making decisions according to the unique situations, whereas robots still rely on predetermined data to make decisions. Despite the rapid progress being made in strengthening the physical capability of robots, their central control systems, which govern how robots decide what to do at any one time, are still inferior to those of humans. In particular, they often rely on pre-programmed instructions to direct their behavior, and lack the hallmark of human behavior, that is, the flexibility and capacity to quickly learn and adapt.
Last October, Google Developers brought their Machine Learning Bootcamp to Jakarta, Indonesia! ML Bootcamp is a one-stop solution to learn about Google's latest machine learning offerings from both Googlers and other industry experts. The 4-day intensive bootcamp consists of instructor-led trainings, hands-on codelabs, and saw 35 companies, as well as 12 startups represented from across Indonesia. If you're an aspiring ML developer, be sure to check out the following online courses: ML crash course with TensorFlow APIs http://bit.ly/2MLUDkU
In the Digital Age, we often contemplate which professions today won't exist five or 10 years from now. But, fortunately, innovation is creating new ones to replace them, with many of these positions commanding salaries well into six-figure territory. Even better, a great deal of jobs in emerging tech qualify as "very cool"; they're all about pursuing intriguing discoveries while using the latest versions of IT tools. To find out which seven stand out as the very best, consider this list of the "Hottest Emerging Tech Jobs in 2019" from FitSmallBusiness.com. They include R&D test engineers for self-driving cars, machine learning experts and blockchain developers.