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Episode summary: Guests Will Jack and Nikhil Buduma co-founders of Remedy Health Inc discuss the challenges involved in collecting, setting up and structuring data in order to implement AI in healthcare. By the end of this episode, listeners will have gained insight into the challenges of healthcare data systems, and the potential solutions to cleaning and organizing this data for healthcare AI applications.

Burger flipping is often used as derogatory shorthand for low-skilled, low-tech work, but fast food companies have been making major investments in automation, apps, analytics, artificial intelligence, and robotics. We set out to ask the questions that business leaders would need to know:

There’s a lot of buzz about artificial intelligence shaking up enterprise procurement over the next five years. Procurement leaders wonder what elements of their jobs will be augmented - or even fully automated - by the intelligent systems. Which roles are secure from full automation, and how will more “automate-able” jobs have to adapt in the years ahead?

A company by company examination of the top car makers public investment and statements by their top executives makes it clear that most car companies are betting that artificial intelligence utilized in self-driving will be inevitable, and they're all jumping in with investment and initiatives.

Episode Summary: If there's any industry ripe for disruption by AI and ML applications, it's healthcare. This week, we speak with Eleven Two Capital's Founder and Managing Partner Shelley Zhuang, whose investment focus (among other spaces) is on innovative healthcare services and applications. In addition to discussing how AI and ML is helping propel genomics, diagnostics, therapeutic treatment, and other innovations into a new paradigm, she touches on what the healthcare space might look like in the next 10 years. For healthcare startups looking to break into the healthcare market, Zhuang doesn't pretend to have simple answers; however, she identifies commonalities among smart companies that have prepared early for meeting regulatory and other industry considerations. This interview was recorded live in San Francisco at Re-Work's Machine Intelligence in Autonomous Vehicles Summit in March 2017.

This article was originally written in 2017 by Lauren D'Ambra, former editor at Emerj.com.

Women in artificial intelligence (AI) and machine learning (ML), or the lack thereof, is not a new topic in media, just as gender equity and disparity in the workplace is not a new subject of research for academics and think tanks. But discussing these issues openly is no less important. While we address the potential reasons and implications of these issues toward the end of this article, our initial interest in this subject came from our desire to know the following:

Episode Summary: In the last few months, we've had a string of fantastic interviews with investors and have gained a cross-industry picture of what's important for start-ups and emerging trends in the AI and ML space. This week's interview is no exception. Ann Miura-Ko, co-founder and partner at Floodgate, starts with an explanation of the "self-driving enterprise" concept, her functioning idea about AI investing and the future of software in general. Her high-level insights embody an interesting emphasis on the dynamic of human-machine interactions and relationships cross industries, including the constant workflows and interactions of people using software and bolstering the predictive and prescriptive analytics capabilities of that software. While forward-thinking, Miura-Ko also paints a picture of how these synergistic relationships between humans and machines are happening with companies today.

The last few years have yielded a tremendous amount of attention at the intersection of AI and healthcare, from DeepMind's partnership with the UK's National Health Service to IBM's continued pushes into areas of genomics and drug discovery. From the perspective of healthcare executives, however, many important questions are left unanswered and rarely addressed in detail:
What difference are healthcare's machine learning innovations likely to make in the lives of patients?
What disruptions should healthcare executives prepare themselves for now?
How will the healthcare industry operate differently in 5 or 10 years into the future?
We surveyed over 50 executives of healthcare companies leveraging AI. We aimed to do the hard work of separating the companies actually applying AI from those who use it as a buzzword (over 15 of our initial survey responses were turned down due to lack of evidence of real AI in use), presenting important predictions and industry insights in clear and interactive charts and graphs.
The following research article is broken down into five sections:

Episode Summary: This week we interview Polaris Partners' Gary Swart, who gives his perspective on companies that are doing "AI right" i.e. laying strong foundations for using AI applications optimally. Swart provides valuable examples of how he's seen companies use AI as a tool to build more defensible and durable business models in an increasingly competitive landscape. Getting an investor's perspective in AI is always a good idea for companies looking to raise money, particularly when it comes to understanding the types of AI trends that excite VC's. Even more broadly, an investor's perspective can point to emerging factors in how AI is going to impact a particular industry, shining a light on industry developments and commonalities that matter for companies across industries who are leveraging an increasing number of AI tools and applications.

Enterprise seems to be entering a new era ruled by data. What was once the realm of science fiction, AI in business intelligence is evolving into everyday business as we know it. Companies can now use machines algorithms to identify trends and insights in vast reams of data and make faster decisions that potentially position them to be competitive in real-time.