Ron Bodkin talks with Lisa Martin at Big Data SV 2018 at the Forager Eatery in San Jose, CA. #BigDataSV #theCUBE https://siliconangle.com/2018/03/19/fail-fast-trip-ai-true-north-says-googler-bigdatasv-guestoftheweek/ Fail fast on the trip to AI true north, says Googler Businesses are aiming to digitally transform themselves in hopes of staying abreast of disruptive competition; the bullseye is applied artificial intelligence across a range of business processes. The tyranny of choice visited on them by vendors selling products for AI’s purpose leaves many unsure about what direction to take. Google became the richest company on earth largely due to its machine learning and AI prowess; could it be the true north to others? “We’ve got this massive capability that we’ve built for our own products that we’re now making available for customers,” said Ron Bodkin (pictured), technical director of applied artificial intelligence at Google. This explains the rising wave of interest in the Google Cloud Platform. Google has spent major time and effort on open-source, deep learning frameworks like its own TensorFlow, specialized hardware and scalable infrastructure for machine learning. That is how it sailed to the head of the class in areas like big data analytics and AI, according to Bodkin. “All those types of advances mean that all kinds of business processes can be reconceived of and dramatically improved with automation taking a lot of human drudgery out,” he said. “So customers are like, ‘That’s really exciting, and at Google, you’re doing that. How do we get that?'” Google is answering with a variety of products and a guiding light in the form of its Applied AI team. Bodkin spoke with Dave Vellante (@dvellante) and Lisa Martin (@LuccaZara), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at the BigData SV event in San Jose, California. They discussed fumbles and field goals in big data and where to begin with digital transformation and AI. This week, theCUBE spotlights Ron Bodkin in our Guest of the Week feature. Big data’s quantum leap Bodkin got an early jump on big data in 2007 as the vice president of engineering at a startup called Quantcast Corp. The company began using the open-source, Apache Hadoop big data framework to crunch petabytes of data and perfect data science models. The potential for such technology to rock enterprise business models was palpable to Bodkin. The problem was that the available tools were not sophisticated enough to produce stellar results for most users. “A lot of people thought that big data would be magic, that you could just dump a bunch of raw data without any effort and out would come all the answers,” Bodkin said. “That was never a realistic hope. … You have to at least have some level of structure in the data. You have to put some effort in curating the data so you have valid results.” Big data analytics technology has mutated in the past decade; cloud elasticity and and scalability have allowed data to break out of silos — a key to meaningful analysis, Bodkin exlained. “The conversation’s changed so much, we almost forget how much things have evolved,” he stated. Google has put a stake in the ground and committed itself to being an “AI-first” company. A little over five years ago, it conceived the 10x team — the engine driving the company’s ripsaw innovation. The team sparked a major movement toward deep learning within the company. In addition to developing deep learning algorithms, the team invested heavily in graphics processing units, massive-scale tensor processing unit and other specialized hardware. The deadly combo resulted in a machine-learning machete that slashed through long-standing problems, Bodkin pointed out. It is now central to a wide range of Google products, from search and advertising to keyword-based photo search. The 10x philosophy sets the bar right up in the stratosphere at 10 times improvement over the competition, according to Bodkin. When they set out on a project, they embrace a bit of recklessness in service of that goal. This doesn’t always result in gold-embossed sure things. Less-than-practical moonshots like Google Glass come to mind. But those fallen arrows are a fair price to pay for eventual kills like Gmail, which came from a hare-brained project, according to Bodkin. ... Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the BigData SV event.