Originally posted on The Horizons Tracker. I recently took the'Learning How To Learn' course from the University of California, San Diego on Coursera, and they highlight the crucial role analogies play in the way humans learn. It's something that researchers from Northwestern University are trying to rectify. They have developed a model1, called the structure-mapping engine (SME), that allows machines to reason in a way that's reminiscent of how humans do. The model uses analogical problem solving in the same way that we use analogies to solve the various moral dilemmas we may face in our daily lives. "In terms of thinking like humans, analogies are where it's at," the authors say.

Alphabet Inc's Google has launched a spinoff of its Android operating system for home appliances and other machines, following mixed results with Android offshoots for cars, smartwatches and televisions. 'Android Things', which arrives as Google opens its annual conference for developers, could bring its Google Assistant virtual helper to refrigerators and robots and familiar designs to cash registers and vending machines. 'The goal is to enable them to be built faster, cheaper and more secure,' said Venkat Rapaka, a product management director at Google. Google has struggled to extend Android's dominance into other areas over the last four years, technology and financial analysts said

Regardless of where you stand on the matter of Data Science sexiness, it's simply impossible to ignore the continuing importance of data, and our ability to analyze, organize, and contextualize it. Drawing on their vast stores of employment data and employee feedback, Glassdoor ranked Data Scientist #1 in their 25 Best Jobs in America list. So the role is here to stay, but unquestionably, the specifics of what a Data Scientist does will evolve. With technologies like Machine Learning becoming ever-more common place, and emerging fields like Deep Learning gaining significant traction amongst researchers and engineers -- and the companies that hire them -- Data Scientists continue to ride the crest of an incredible wave of innovation and technological progress. While having a strong coding ability is important, data science isn't all about software engineering (in fact, have a good familiarity with Python and you're good to go).

The online games were easy–until I got to challenge number six. I was applying for a job at Unilever, the consumer-goods behemoth behind Axe Body Spray and Hellmann's Real Mayonnaise. I was halfway through a series of puzzles designed to test 90 cognitive and emotional traits, everything from my memory and planning speed to my focus and appetite for risk. A machine had already scrutinized my application to determine whether I was fit to reach even this test-taking stage. Now, as I sat at my laptop, scratching my head over a probability game that involved wagering varying amounts of virtual money on whether I could hit my space bar five times within three seconds or 60 times within 12 seconds, an algorithm custom-built for Unilever analyzed my every click. I furiously stabbed at my keyboard, my chances of joining one of the world's largest employers literally at my fingertips.

Finally, a comprehensive hands-on machine learning course with specific focus on classification based models for the investment community and passionate investors. In the past few years, there has been a massive adoption and growth in the use of data science, artificial intelligence and machine learning to find alpha. However, information on and application of machine learning to investment are scarce. This course has been designed to address that. It is meant to spark your creative juices and get you started in this space.

Bangassou, Central African Republic - As an IT specialist, Djamaladine Mahamat Salet is used to providing solutions to complex problems. When he discovered there were no high-school classes for the displaced children in his community, he decided to start teaching them basic computer skills. The big challenge was that he would have to do so without electricity, an internet connection, and no laptops. "These children are stuck here due to this conflict," said 38-year-old Salet. "I am trying to prepare these students so that when they can finally go on to university, they will thrive."

Today, chatbots used in e-learning are completely changing the workplace, with an aim to increase business productivity, employee efficiency and morale. Bots are communication interfaces that provide ample applications through spacing effect, virtual assistance, new hire onboarding process, learning scoring and more. Anubha Goel is a Senior Executive in the Marketing team at G-Cube Solutions. Her passion is to write innovative content that caters the customized learning needs of diverse audiences from different industry domains.

Google and its partners have slowly but surely trying to revitalize Android-based smartwatches, and it looks like they may use fitness as the way to reel you in. Android Police (which has a history of accurate leaks) claims to have word of Google Coach, a Wear OS-oriented assistant that would use AI to improve your health and fitness. Rather than just track your activities and popping up an endless stream of reminders, it would "proactively" recommend changes to your activity and provide prompts that are genuinely useful. The coaching tool would look at your exercise and suggest new routines, or even provide alternatives if you couldn't make it to the gym on time. And while nutrition tracking by itself isn't new, Google Coach could suggest healthy meals on nights out, generate meal plans (possibly using your calendar) and create shopping lists.

Check out the "Deep Learning models" sessions at the Artificial Intelligence Conference in San Francisco, September 4-7, 2018. One of the key findings of a survey we released earlier this year (How Companies are Putting AI to Work through Deep Learning) was that the leading reason holding companies back from incorporating deep learning was their lack of access to skilled people. One-fifth of respondents pointed to a skills gap as one of the reasons they haven't integrated deep learning, and at the time of the survey, 75% of respondents indicated their company had some combination of internal and external training programs to address this issue. We've continued to monitor interest in topics relevant to building AI products and systems, specifically areas that also warrant investment in skills development. In this post, I'll share results of related studies we've conducted.

Disruption is inevitable, but also deeply feared. We've seen this with every significant technological leap -- from the printing press to automobiles to computers. But, as we enter the next iteration of technology with AI, we know it will have a profound, transformative effect on global business and society. However, we must reflect on how we want this transformation to occur. Early adoption has already begun: AI is transforming everyday activities and processes such as virtual assistants, fraud detection and driverless cars. Various forms of AI solutions are already in the market, including automation, speech recognition, machine learning, decision-making and natural language processing.