We can describe a chatbot as a computer program that conducts a conversation in natural language via auditory or textual methods, understands the intent of the user, and sends a response based on the business rules and data of the organization. Another way to describe chatbot programming is the concept of "micro-engagement," or technology designed to communicate with customers and prospects at various intervals and via multiple channels in order to drive business interactions. Whatever the digital classification, it's important for boards of directors and C-level executives within the insurance industry to understand that chatbots are an increasingly effective way to improve business processes -- but are not a panacea. Roughly 65% of customer interaction can now be automated, and in order to maximize their effectiveness, chatbots must be wed to a comprehensive communications process that also includes humans (who can step in at the appropriate time). Being able to extract information from an insurance claim is a fairly complex task that demands a human component.
COMPUTER BRAINS are tiny rectangles, becoming tinier with each new generation. Or so it used to be. These days Andrew Feldman, the boss of Cerebras, a startup, pulls a block of Plexiglas out of his backpack. Baked into it is a microprocessor the size of letter paper. "It's the world's biggest," he says proudly, rattling off its technical specs: 400,000 cores (sub-brains), 18 gigabytes of memory and 1.2trn transistors.
Tesla showed the computer at the Hot Chips conference. Designing your own chips is hard. But Tesla, one of the most aggressive developers of autonomous vehicle technology, thinks it's worth it. The company shared details Tuesday about how it fine-tuned the design of its AI chips so two of them are smart enough to power its cars' upcoming "full self-driving" abilities. Tesla Chief Executive Elon Musk and his colleagues revealed the company's third-generation computing hardware in April.
Why Partnership Strategy, not Technology, drives Digital Transformation? Known from the 17th century (Blaise Pascal invoked it in his famous wager, which is contained in his Pensées, published in 1670), the idea of expected value is that, when faced with a number of actions, each of which could give rise to more than one possible outcome with different probabilities, the rational procedure is to identify all possible outcomes, determine their values (positive or negative) and the probabilities that will result from each course of action, and multiply the two to give an "expected value", or the average expectation for an outcome; the action to be chosen should be the one that gives rise to the highest total expected value. Decision theory (or the theory of choice) is closely related to the field of game theory and is an interdisciplinary topic, studied by economists, statisticians, psychologists, biologists, political and other social scientists, philosophers, and computer scientists. The need for decision under uncertainty has never been stronger. Although the digital realm is evolving fast, the partnership strategical choice remains a human prerogative and a key driver of the digital ecosystem evolution.
Jan Buytaert is chief information officer at GO!, the public body for state schools in the Flanders region of Belgium. His role is to initiate new IT projects and prove their value to the business, with the hope that business decision makers and policymakers give them the green light. The projects can have huge implications for education in Belgium, as the region has around 750 schools and institutions, and 210,000 students. "There wasn't always a lot of digital innovation so I had to work hard trying to convince management and policymakers that we should invest in tech and digital education, and change the way of teaching and learning," Buytaert tells NS Tech. In 2016, Buytaert and his team analysed the way teaching was carried out in several schools, working alongside teachers, students and principals.
Advances in technology can allow you to order food by voice or unlock your phone with your face, but those new capabilities could take a toll on the environment. Enhanced tech capabilities are being developed through the use of artificial-intelligence approaches like neural networks, which detect patterns in speech and images by training programs across countless data points. That process constantly crunches reams of information on power-hungry servers in data centers that use a substantial amount of energy to power, cool and monitor the servers. The result: Training a neural network can emit 17 times more carbon dioxide than an average American does in a year, and five times the lifetime emissions of an average car. Those are the findings of a recent paper by researchers at the University of Massachusetts, Amherst, which highlighted the substantial power generated by AI technologies.
August 23, 2019: SATS, a Singapore-based ground handler and Singaporean research platform TUMCREATE will be working together to explore commercialisation opportunities for their artificial intelligence (AI) powered robotic air cargo system, SPEEDCARGO. SPEEDCARGO is a system comprised of three of the companies' products – CARGO EYE, CARGO MIND, and CARGO ARM. CARGO EYE produces a digital fingerprint for incoming cargo by dimensioning accepted cargo in real-time using a 3D camera system. The companies are currently working to enhance CARGO MIND and CARGO ARM, which work to optimise cargo palletisation through intelligent unit load device (ULD) planning and automatic ULD packing, respectively, with the aim of commercialising each product in phases. The timeline for the completed project has not been released, but the integrated SPEEDCARGO system will run on an AI-powered operating system enabling them to connect data for end-to-end optimisation of cargo operations.
The UK government has developed a voracious appetite for artificial intelligence (AI), based on a promise of its apparently transformative power across myriad industries. From prime minister Boris Johnson's pledge to fund a £250m AI lab for the NHS, to the Department for Education's recently launched'AI horizon scanning group', AI is being lauded as a panacea to some of the most pressing issues society faces. Education is just one of the sectors that is meeting AI with open arms. As Matthew Jones at Perlego argued for this title, the opportunities being presented for AI to close educational accessibility gaps is exciting. In fact, educators, policymakers and investors are all being bombarded with messages related to AI's seemingly endless benefits in the classroom.