John Chambers, founder and chief executive officer of JC2 Ventures LLC, stands for a photograph... [ ] following a Bloomberg Technology Television interview in San Francisco, California, U.S. John Chambers, who just turned 70, prefers to take any stage at a run. In his tech trendy uniform--blue blazer, designer jeans, checked shirt, and blue boat shoes--he still exudes the physical energy of his successful tenure as CEO at Cisco Systems, which he grew from an annual revenue of $2.2 billion in 1995 to $49 billion in 2015 when he stepped down. Today Chambers runs his own boutique investment firm, JC2 Partners, in Palo Alto, California. He prefers to call himself a mentor to startup CEOs rather than a venture capitalist. When he's not in Silicon Valley he can often be found in India, where he advises Prime Minister Narendra Modi's government on digital transformation and the economy.

Europe has a growing and thriving Artificial Intelligence industry where most of the AI companies are in the data analytics market. The United Kingdom takes the lead as the strongest AI ecosystem in Europe. Germany with Berlin comes in second place as the main AI hub supporting 30 AI companies. Data Analytics companies make up the bulk of AI firms in Europe also hosts a lot of data exhibitions, fests, and conferences. Some of them are DataFest held in March each year which showcases Scotland's leading role in data science and artificial intelligence on the international stage while offering an unparalleled networking platform to interact with local and international talent, industry, academia and data enthusiasts.

Click on one of the buttons below to see the agenda of the day. If only Hollywood... (demystifying AI) It is good to invest in AI and even better to understand the uses of AI Stefano Quintarelli, Serial entrepreneur and member of the High-Level Expert Group on Artificial Intelligence of the European Commission

The recent AI revolution was based on a few important pillars: abundance of data, lower costs in storing it, faster computing speed and distributed computing. To date, however, there still are some critical steps that are missing to achieve true continuous intelligence. Continuous intelligence refers to a design in which real-time analytics is seamlessly integrated within a business operation to support decision automation. Data processing can therefore be used to respond real-time to events. In order to achieve true continuous intelligence we are still missing a couple of key elements, in particular explainable AI and better graph analytics. Deep Learning uses multi-layers neural nets that have been extremely popular in recent years, in particular for computer vision.

IBM Corp. today updated its Watson AI tools to help customers eliminate some of the data complexities that prevent them from implementing artificial intelligence-based technologies. The updates are all part of IBM's so-called "Watson Anywhere" initiative that involves scaling AI across any kind of cloud computing platform. Watson Anywhere's main aim is to make data accessible to AI no matter where it's stored. It's built on top of the open source Kubernetes project and enables customers to connect data regardless of where it resides. Watson Anywhere also provides access to a suite of microservices including Watson Openscale and Watson Assistant. Openscale is an open AI platform that helps customers to detect issues such as AI model bias and understand how AI comes to its decisions, while Assistant helps companies to build conversational interfaces like virtual customer assistants.

AI can be harnessed in a wide range of economic sectors and situations to contribute to managing environmental impacts and climate change.Some examples of application include: AI-infused clean distributed energy grids, precision agriculture, sustainable supply chains, environmental monitoring and enforcement, and enhanced weather and disaster prediction and response. Research by PwC UK, commissioned by Microsoft, models the economic impact of AI's application to manage the environment, across four sectors – agriculture, water, energy and transport. It estimates that using AI for environmental applications could contribute up to $5.2 trillion USD to the global economy in 2030, a 4.4% increase relative to business as usual. In parallel the application of AI levers could reduce worldwide greenhouse gas (GHG) emissions by 4% in 2030, an amount equivalent to 2.4 Gt CO2e – equivalent to the 2030 annual emissions of Australia, Canada and Japan combined. At the same time as productivity improvements, AI could create 38.2 million net new jobs across the global economy offering more skilled occupations as part of this transition.

Artificial Intelligence (AI) has been the subject of books and movies alike. It's been a growing concern for its ability to be used in political censorship and to create deep fake news, to be misused in the hands of authoritarian governments to track and control citizens, to create a huge potential loss in jobs over time, ushering in Biblical end time prophecies, and the possibility of a Terminator or Matrix type scenario. There's also been concern over probable long-term agendas concerning the technology. However, that doesn't mean we have to throw AI out the window (and with the looks of things, it seems like that would be very hard to do in the future). Artificial Intelligence can have many benefits, especially in the field of digital marketing, which we'll be talking about in this article.

IT firm Hexagon to introduce the nuts and bolts of Artificial Intelligence (AI) to school students from Class 8. The AI Community Centre, which will offer free courses, to come up in Hyderabad early next year. Stockholm (Sweden)-based Hexagon, a sensor, software and autonomous solutions, has tied up the National Association of Software and Services Companies (Nasscom) to establish the AI Community Centre. "The school is open to all. It will run introductory courses in AI for students from Class 8 to senior level, which include engineering students," Navaneet Mishra, vice-president and Country Manager of Hexagon Capability Center India (HCCI), said.

Using a fluorescent probe that lights up when brain cells are electrically active, MIT and Boston University researchers have shown that they can image the activity of many neurons at once, in the brains of mice. This technique, which can be performed using a simple light microscope, could allow neuroscientists to visualize the activity of circuits within the brain and link them to specific behaviors, says Edward Boyden, the Y. Eva Tan Professor in Neurotechnology and a professor of biological engineering and of brain and cognitive sciences at MIT. "If you want to study a behavior, or a disease, you need to image the activity of populations of neurons because they work together in a network," says Boyden, who is also a member of MIT's McGovern Institute for Brain Research, Media Lab, and Koch Institute for Integrative Cancer Research. Using this voltage-sensing molecule, the researchers showed that they could record electrical activity from many more neurons than has been possible with any existing, fully genetically encoded, fluorescent voltage probe. In the top row, neurons are labeled with a fluorescent probe that reveals electrical activity. In the bottom row, neurons are labeled with a variant of the probe that accumulates specifically in the neuron cell bodies, preventing interference from axons of neighboring neurons.

An algorithm developed by scientists at UC San Francisco and UC Berkeley did better than two out of four expert radiologists at finding tiny brain hemorrhages in head scans--an advance that one day may help doctors treat patients with traumatic brain injuries (TBI), strokes and aneurysms. The continued increase in diagnostic imaging studies, including 3D imaging studies such as computed tomography (CT), means that radiologists are looking at thousands of images each day, searching for tiny abnormalities that can signal life-threatening emergencies. The number of images from each brain scan can be so large that on a busy day, radiologists may opt to scroll through some large 3D stacks of images using mice with frictionless wheels, almost like viewing a movie. But it could be much more efficient--and potentially more accurate--if AI technology could pick out the images with significant abnormalities, so radiologists could examine them more closely. "We wanted something that was practical, and for this technology to be useful clinically, the accuracy level needs to be close to perfect," said Esther Yuh, MD, PhD, associate professor of radiology at UCSF and co-corresponding author of the study, published the week of Monday, Oct. 21, 2019, in Proceedings of the National Academy of Sciences (PNAS).