If you ask 100 people for the definition of "artificial intelligence," you'll get at least 100 answers, if not more. At AWS, we define it as a service or system which can perform tasks that usually require human-level intelligence such as visual perception, speech recognition, decision making, or translation. On this new AWS blog, we'll be covering these areas and more, with in-depth technical content, customer stories, and new feature announcements. The challenges related to building sophisticated AI systems center mostly around scale: the datasets are large, training is computationally hungry, and inferring predictions can be challenging to do at scale or on lower-power and mobile devices. Customers have been using AWS to solve these general problems for years, and the ability to be able to access storage, GPUs, CPUs, and IoT services on demand has emerged as a perfect fit for intelligent systems in production.

Ford is investing $1bn (£801m) over the next five years in tech startup Argo AI to help the Detroit company achieve its goal to deliver a fully autonomous vehicle by 2021, the companies announced on Friday. Pittsburgh-based Argo AI was founded last year by Bryan Salesky and Peter Rander who previously worked at Google and Uber respectively on the companies' self-driving vehicle initiatives. "We've made significant progress and are on track to achieve our goal," Ford president and CEO Mark Fields wrote in a Medium post. "At the same time, we know rapidly evolving technologies and fierce competition require us to remain flexible and open to new ways of strengthening our team." In August last year, Ford announced plans to sell fully autonomous self-driving cars, without steering wheels, for urban ride-sharing fleets by 2021.

As of last month, Google, Facebook, Amazon, IBM and Microsoft are all joining forces to create a new AI partnership called the Partnership on Artificial Intelligence to Benefit People and Society. The collaboration, aside from having a lengthy name, will advance public understanding of AI, and agree on a list of standards for future development. Although there's currently a clear domestic trend, AI has uses that stretch beyond analysing the traffic. A number of companies involved with AI research are looking well beyond family applications. Right now, though, the immediate aim seems to be to get consumers to adopt AI as part of their everyday lives.

Interesting write-up by Jennifer L. Schenker published end of January on Techonomy. "We should not let Silicon Valley be the mission control for humanity," argues futurist Gerd Leonhard, author of a new book called Tech versus Humanity: The coming clash between man and machine. If autonomous AI software, crunching data far more rapidly than humans, can help eradicate disease and poverty and introduce societal improvements and efficiencies, then we must embrace it, Leonhard says. But "at the same time we have to have governance. And right now there is no such thing."

Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving". As machines become increasingly capable, mental facilities once thought to require intelligence are removed from the definition. For example, optical character recognition is no longer perceived as an exemplar of "artificial intelligence", having become a routine technology.

UMass today rolled out its new GPU cluster – Gypsum – aimed at deep learning. Like many institutions, UMass is seeking to attract Ph.D. students drawn to deep learning and artificial intelligence. At 400 GPUs, Gypsum is on the large side for academic GPU clusters according the university. The new systems will be housed at the Massachusetts Green High Performance Computing Center in Holyoke, Mass., and is the result of a five-year, $5 million grant to the campus from the Massachusetts Technology Collaborative made last year. It represents a one-third match to a $15 million gift supporting data science and cybersecurity research from the MassMutual Foundation of Springfield.

In this article, I cover the 12 types of AI problems i.e. I address the question: in which scenarios should you use Artificial Intelligence (AI)? Recently, I conducted a strategy workshop for a group of senior executives running a large multi national. In the workshop, one person asked the question: How many cats does it need to identify a Cat? This question is in reference to Andrew Ng's famous paper on Deep Learning where he was correctly able to identify images of Cats from YouTube videos.

Stanford: With the rise of user-web interaction and networking, as well as technological advances in processing power and storage capability, the demand for effective and sophisticated knowledge discovery techniques has grown exponentially. Businesses need to transform large quantities of information into intelligence that can be used to make smart business decisions. With the Mining Massive Data Sets graduate certificate, you will master efficient, powerful techniques and algorithms for extracting information from large datasets such as the web, social-network graphs, and large document repositories. Take your career to the next level with skills that will give your company the power to gain a competitive advantage. The Data Mining and Applications graduate certificate introduces many of the important new ideas in data mining and machine learning, explains them in a statistical framework, and describes some of their applications to business, science, and technology.

Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development. The emergence of joint attention (JA), the coordinated orienting of 2 people toward an object or event, occurs during the first 2 years of life, arguably the most dynamic and important period of early child development (Scaife and Bruner 1975). It is theorized that engaging in JA lays the foundation for prosocial cooperative behavior, from basic social-communicative functioning and language development (Premack 2004) to sophisticated forms of empathy (Mundy and Jarrold 2010) and theory of mind (Adolphs 2003). In fact, early exhibition of joint attention is strongly associated with later language ability (Morales et al. 2000; Mundy et al. 2007), and atypical development of the initiation of joint attention (IJA) is strongly indicative of autism spectrum disorder (ASD) (Bruinsma et al. 2004). The neural substrates underlying IJA in early childhood are poorly understood (Barak and Feng 2016), due in part to significant methodological challenges in imaging localized brain function that supports social behaviors in children during the first 2 years of life.

The platform is providing a holistic online solution for teachers, students, and parents. Over two decades ago, Educomp set out to change the entire education system in the country. Since then, it claims to have empowered over 30 million learners and educators across over 65,000 schools. While Educomp was continuing to overhaul the education ecosystem through its smart class programmes, the top leadership in the company realised that they needed to take education beyond the conventional classrooms. Now, instead of taking students to classrooms, they had to flip the normal course and take classrooms to students, beyond boundaries.