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.

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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.

The past decade or so has seen a strong focus on risk and compliance technologies that make use of analytics in financial services. These technologies, which might be called "defense" technologies--in contrast to "offense" technologies that involve marketing and revenue growth--include applications and infrastructure for risk management, fraud prevention, regulatory, and anti-money laundering (AML) compliance. They bring the power of analytical insights--initially used for identifying marketing opportunities in many companies--to risk mitigation in banking. While these distinctions are somewhat blurred by integrating risk-based insights into "offense" activities, they are a useful shorthand. The Great Recession of the late 2000s drove both a greater focus on risk management and substantial new regulation for financial firms.

Ford Motor Co. is investing $1 billion in a months-old startup founded by two pioneers in the nascent autonomous vehicle sector. The Pittsburgh-based artificial intelligence company Argo AI will develop the brains -- specifically, a virtual driver system -- for the fully autonomous vehicles Ford has promised to bring to market in 2021. Founders Bryan Salesky and Peter Rander are former leaders of the self-driving car teams at Uber Technologies Inc. and Alphabet Inc.'s Google. "This is a unique partnership," Mark Fields, Ford's chief executive officer, said in an interview. "A lot of tech companies are looking for customers and a lot of OEMs are looking for technology partners. We are getting expertise, and Argo AI is getting a customer in Ford."