Hilary Mason is the Founder of Fast Forward Labs. She has been involved in the data science space for over a decade. She is a real thought leader in the data space. This keynote was delivered at ODSC East 2020.

Last Tuesday, I had the privilege of leading an insightful conversation at the Gartner IT Symposium with a badass panel of AI technologists – Hillery Hunter, Hilary Mason and Margaret Dawson – about the obstacles that organizations need to overcome if they are to successfully implement AI. The foundation of our panel discussion was based on a study that we recently commissioned to understand how enterprise executives are approaching AI. I will share more of the research in coming weeks, but one big takeaway is that companies that see results from AI are keeping AI capabilities at the core of the business. While most organizations are still experimental, we are seeing a strong correlation between organizations with highly dedicated on-premise AI capabilities to high performance, measurable ROI and less failure. Net-net, on-prem AI capabilities and solutions are fulfilling the AI hype.

Today's leading minds talk AI with host Byron Reese Listen to this episode or read the full transcript at www.VoicesinAI.com Byron Reese: This is Voices in AI, brought to you by Gigaom and I am Byron Reese. Today, our guest is Hilary Mason. She is the GM of Machine Learning at Cloudera, and the founder and CEO of Fast Forward Labs, and the Data Scientist in residence at Accel Partners, and a member of the Board of Directors at the Anita Borg Institute for Women in Technology, and the co-founder of hackNY.org. That's as far down as it would let me read in her LinkedIn profile, but I've a feeling if I'd clicked that'More' button, there would be a lot more.

Today's leading minds talk AI with host Byron Reese Listen to this episode or read the full transcript at www.VoicesinAI.com Byron Reese: This is Voices in AI, brought to you by Gigaom and I am Byron Reese. Today, our guest is Hilary Mason. She is the GM of Machine Learning at Cloudera, and the founder and CEO of Fast Forward Labs, and the Data Scientist in residence at Accel Partners, and a member of the Board of Directors at the Anita Borg Institute for Women in Technology, and the co-founder of hackNY.org. That's as far down as it would let me read in her LinkedIn profile, but I've a feeling if I'd clicked that'More' button, there would be a lot more.

Artificial intelligence is cast all at once as the technology that will save the world and end it. To cut through the noise and hype, VentureBeat spoke with luminaries whose views on the right way to do AI have been informed by years of working with some of the biggest tech and industry companies on the planet. Below find insights from Google Brain cofounder Andrew Ng, Cloudera general manager of ML and Fast Forward Labs founder Hilary Mason, Facebook AI Research founder Yann LeCun, and Accenture's responsible AI global lead Dr. Rumman Chowdhury. We wanted to get a sense of what they saw as the key milestones of 2018 and hear what they think is in store for 2019. Amid a recap of the year and predictions for the future, some said they were encouraged to be hearing fewer Terminator AI apocalypse scenarios, as more people understand what AI can and cannot do.

Modern data science emerged in tech, from optimizing Google search rankings and LinkedIn recommendations to influencing the headlines Buzzfeed editors run. But it's poised to transform all sectors, from retail, telecommunications, and agriculture to health, trucking, and the penal system. Yet the terms "data science" and "data scientist" aren't always easily understood, and are used to describe a wide range of data-related work. What, exactly, is it that data scientists do? As the host of the DataCamp podcast DataFramed, I have had the pleasure of speaking with over 30 data scientists across a wide array of industries and academic disciplines.

We created a list of artificial intelligence and machine learning experts from different companies, startups, and universities -- and scanned their Twitter profiles for book recommendations. Did you discover new books to read? Hold down the below so other people will read it too.

Today's topic is machine learning and I'm talking to one of the brightest minds in the field, Hilary Mason. She also advises startups through Accel, a prominent venture capital firm.

But how do you separate hype from reality? How can your company apply AI to solve real business problems in 2017? In September 2016, Luminary Labs convened 30 executives in healthcare, machine learning, and analytics for a grounded discussion on these questions with machine learning expert Hilary Mason, founder and CEO of Fast Forward Labs, and Sandy Allerheiligen, VP of data science and predictive and economic modeling at Merck. Here's a synopsis of what we discussed, and what AI learnings your business should keep in mind for 2017. AI and the Near Term 3 We've all seen the sensational headlines: The robots are coming, and they'll take our jobs! AI can do your job faster and more accurately than you can!

The internet strongly agrees there's an artificial intelligence (AI) revolution going on, and it's come to pharma marketing. IBM Watson, the AI brain being infused all over healthcare, will form the backend of an interactive display ad for GSK Consumer Healthcare's Theraflu. The cold-and-flu product was one of seven brands, across four beta partners, to sign on with Watson Ads, an initiative announced this past summer by the Weather Co. -- an IBM property -- aiming to develop a new wave of ads that people will be able to communicate with. According to the firm, it marks the first consumer use of IBM's cognitive technology for advertising. "This is a whole new foray into marketing," says D. J. Reali, SVP, national ad sales for the Weather Co.