Researchers in the Robot Learning Lab at Cornell University developed a robot that can prepare a cup of latte without ever having seen the machine before – the robot does this by visually observing the machine and by reading online instruction manuals, similar to how humans learn. The team used CUDA and TITAN X GPUs to train their deep learning models and then also uses the GPU during testing where the robot is trying to infer which human manipulation motion is best suited for the object it has never seen before. "We use a deep learning neural network that can tell the robot which action in a database is the closest to the one it has to perform," said researcher Jaeyong Sung. The researchers turned to the Amazon Mechanical Turk crowdsourcing service to collect a large library of actions -- they invited hundreds of visitors to guide a robot through the motions to perform various tasks described in a set of printed instructions. To make crowdsourcing possible, the researchers created a web interface that lets the user guide an imaginary robot arm, almost like playing a video game.

At the annual Gartner Symposium/ITxpo in Orlando, Florida this week, over 8000 technology leaders gathered to get analyst predictions on where we are heading. Artificial intelligence, machine learning, and smart things were key analytics themes for a savvy digital future. The overall top three themes this year were intelligent, digital, and mesh. For a fantastic free overview, check out the following openly published article, "Gartner's Top 10 Strategic Technology Trends for 2017" and linked resources. Last week I shared an article and webinar regarding the Fourth Industrial Revolution aka Digital Transformation.

In May, Google research scientist Douglas Eck left his Silicon Valley office to spend a few days at Moogfest, a gathering for music, art, and technology enthusiasts deep in North Carolina's Smoky Mountains. Eck told the festival's music-savvy attendees about his team's new ideas about how to teach computers to help musicians write music--generate harmonies, create transitions in a song, and elaborate on a recurring theme. Someday, the machine could learn to write a song all on its own. Eck hadn't come to the festival--which was inspired by the legendary creator of the Moog synthesizer and peopled with musicians and electronic music nerds--simply to introduce his team's challenging project. To "learn" how to create art and music, he and his colleagues need users to feed the machines tons of data, using MIDI, a format more often associated with dinky video game sounds than with complex machine learning.

"It's the straw that stirs the drink," says Roger Barnette, president at IgnitionOne. "We started as a search company, so it seems natural to morph into more of a data business when you think about how the data impacts search." As Google and Bing build out their services, IgnitionOne will continue to focus on that data that supports ad-copy creation and ad targeting. It's also about modifiers based on a transaction and how search on a mobile phone in a specific geolocation supports clients like Bridgestone, Fiat, General Motors, LaQuinta, and Land Rover, which are listed as clients on the company's Web site. Perhaps the reason for the realignment shows up in the quarterly digital marketing report IgnitionOne publishes each quarter.

Once customers choose a product or service, the continuing success of their relationship with that company depends on customer support. Get it right and win loyal customers for life. Miss the mark and you lose customers, who may then broadcast their dissatisfaction and do more damage to your brand. Customers are using multiple channels to give feedback. They may air concerns via surveys, online chats, calls to a support center, or in person.

The idea of artificial intelligence (AI) has dominated scientific and popular culture for decades. Most fictional works that explore the idea of AI focus on its dangers to humanity, with the premise often involving robots or super-advanced computer interfaces that have developed their own freewill and turned against humanity (a la HAL 9000 from Space Odyssey). But despite fearmongering around AI, scientists have been developing software and tech to make machines smarter than ever. We have already seen AI programs beat humans at complex games, computers that can reproduce classical works of art and robots that can play football (albeit not convincingly). One area where AI brings a lot of opportunity is the marketing industry.

The Jetsons lasted on TV for just three seasons, but its impact was far greater. According to Smithsonian Magazine, "The Jetsons stands as the single most important piece of 20th century futurism." As we stand on the cusp of a revolution in AI and robotics, it's amazing how much the show informed the way "Americans think and talk about the future." In the coming decades, we will see a world where every person has a team of robots working for them, all powered by AI and Deep Learning. These robots will take care of tasks like cleaning our homes, driving our cars, and acting as our personal assistants.

NVIDIA's (NVDA) quarterly revenues have been surging at double-digit rates in the last three quarters and, looking at the guidance for the next quarter, it's clear that the company is expecting the growth rate to continue unabated in the near future. One of the key factors that has added fuel to their engines is NVIDIA's new growth drivers: the data center segment and auto segment. In the most recent quarter, NVIDIA's data center unit reported 151 million in sales, a growth of 109.72% The growth in data center revenues is much higher than other segments, and there are several reasons why this growth can, in fact, continue its breakneck pace for several more quarters. NVIDIA's expertise in the GPU segment has given it a range of must-have products for hyperscale data centers.

If talking to Siri, Cortana and Alexa aren't cutting it for you, know that researchers are looking for a way to spice things up with characters from popular TV shows. A team of researchers at the University of Leeds--James Charles, Derek Magee and David Hogg--have turned to algorithms and machine learning tools for digitizing avatars of well known characters. The algorithms will have the ability to identify specific characters and catch individual facial expressions, speech patterns, body language and voice. Then, a machine learning tool will analyze scripts to learn how the character pieces words together. The final result will be a "virtually immortalized" version of the character that can create new sentences in the style and appearance of the character.

How do you explain machine learning to a child? Answer by Daniel Tunkelang, data scientist, search/discovery expert, led teams at LinkedIn and Google, on Quora. I'd pick a universally accessible binary classification problem: learning which foods are yummy and which are yucky. We want to teach a computer to recognize which foods are yummy and which foods are yucky. But the computer doesn't have a mouth or any way of tasting the food.