In our latest episode of the In Context Podcast, we're joined by Eric Colson, the Chief Algorithms Officer for Stitch Fix, an online subcription personal shopping service whose tech blog, Multithreaded, may have the coolest algorithms tour on the internet. In a fascinating discussion, he and Kathryn Hume analyze how Stitch Fix's engineering culture works, including what they value, what they look for in new hires, and how they’ve architected their platform to enable astounding success. You'll also hear about the critical role that autonomy plays in how Eric organizes his data science teams.

In this episode, you'll learn about:

- The importance of autonomy in the workplace
- How autonomy should look at both the department and individual levels
- The role of autonomy as a driver of job satisfaction and business outcomes
- Best practices for building autonomous data science teams

Find out more by checking out the show notes: https://bit.ly/2uKEMMP

Episode 9: Hiring for Autonomy in Data Science Teams with Eric Colson

In this continuation of their earlier conversation (see Episode 79), Jon Prial and Alistair Croll, the Founder and Content Chair of Fwd50, discuss GDPR, the critical role of trust and how computing will evolve in the months and years ahead.

You’ll Hear About:

- Personal data and trust
- The economic interests of smart agents

Learn more by checking out the show notes: https://bit.ly/2NFD8Db

Episode 80: Trust and the Future of Computing with Alistair Croll

Differential privacy is a technology that's quickly moving from academia into business. And it’s not just the big companies that are using it. With the intersection of trust and AI a hot topic right now, differential privacy is well on its way to becoming an integral part of the conversation. In this episode, Jon Prial welcomes Chang Liu to the show. Chang is an Applied Research Scientist at Georgian Partners and an expert on differential privacy. In the episode, they talk about what differential privacy is, why it’s important, and why every company needs to think about having it as part of its product and technical strategy.

You'll hear about:

- The limits of data anonymization
- What differential privacy is and why it's so important
- Ways to protect your data and be differentially private
- What epsilon is and what its role is
- Differential privacy's potential to solve the cold-start problem
- Implications for trust

To learn more about this episode, check out the show notes: http://bit.ly/2MTjjLR

Understanding Differential Privacy

Episode 83: Understanding Differential Privacy with Chang Liu

On October 17th the Scale Tech Conference (www.scaletechconf.com) is happening in Toronto. Georgian Partners is co-hosting the event as part of our annual portfolio conference and Jon Prial, host of the Georgian Impact Podcast, sat down to chat with some of the speakers to hear a little more about them and what they’ll be talking about at the event.

In this episode we meet Susan Etlinger, an Industry Analyst at Altimeter Group. She is a globally recognized expert in digital strategy and has authored a series of reports and frameworks on topics including artificial intelligence, big data, analytics and digital ethics.

Susan was named one of the “Must Know” Top Writers in Technology by LinkedIn in 2016. Her TED talk, “What Do We Do With All This Big Data?" has been translated into 25 languages and has been viewed more than 1 million times. Susan’s research is used in university curricula around the world. She is a frequent keynote speaker, and has been quoted in numerous media outlets including The Wall Street Journal, Fast Company, The New York Times and the BBC.

Susan works with global clients to evaluate emerging technologies and incorporate them into organizational culture and practice. She also works with technology vendors to refine product roadmaps and strategies based on her independent research.

Susan is a published translator and holds a Bachelor of Arts in Rhetoric from the University of California at Berkeley. Find her on Twitter at @setlinger.

Scale Tech Conference Preview: Susan Etlinger

Everything is going digital. Why should restaurants be an exception? In this episode, Jon Prial talks with Ray Reddy, the Co-founder and CEO of Ritual, a company that has built a fascinating consumer-facing social app that allows people to order food for pickup. And while that may seem simple enough, there’s much more to the story. In their conversation, Jon and Ray talk about rise of the digital restaurant and how technologies like artificial intelligence are changing the way that we purchase food.

You’ll hear about:

- How Ritual uses AI to assist users with their interactions
- The social retail space
- Designing a platform people will want to use every day
- Approaches for bringing data together
- How Ritual has approached scaling
- How restaurants will evolve over the next few years

For more information, check out the show notes: http://bit.ly/2Q7QZEd

Episode 84: The Rise of the Digital Restaurant with Ray Reddy

On October 17th the Scale Tech Conference (www.scaletechconf.com) is happening in Toronto. Georgian Partners is co-hosting the event as part of our annual portfolio conference and Jon Prial, host of the Georgian Impact Podcast, sat down to chat with some of the speakers to hear a little more about them and what they’ll be talking about at the event.

In this episode we meet Chris Amen-Kroeger, the VP of Ads Engineering at Twitter. Over the last several years, Chris has led world class engineering teams that focus on advertiser value by building machine learning driven multiformat (Display, Video, Search) monetization platforms such as Pinterest and Yahoo.

Prior to joining Twitter, Chris served as the Head of Ads Engineering at Pinterest where he focused on building Pinterest's Search, Display and Video advertising products. While at Pinterest, Chris successfully spearheaded an overhaul of the ad platform which enabled a much more personalized and relevant ad experience for Pinners. Before joining Pinterest, Chris led the Display and Video Ads Engineering teams at Yahoo, which build and run the Yahoo DSP (BrightRoll DSP+), Exchange (BRX) and Premium Ads platforms ($1.6B revenue in 2016). In late 2014, Yahoo acquired BrightRoll, the premiere programmatic video platform, for $640M where Chris led the technology teams (Product, Engineering and Operations).

Scale Tech Conference Preview: Chris Amen-Kroeger

In this episode, Jon Prial talks with Jana Eggers, the CEO of Nara Logics, a company with an AI platform that works as a matching engine, helping companies connect their data. They talk about the realities of artificial intelligence, including what it’s actually good for, where to use it, and how to run a successful AI project.

You’ll hear about:

- The work that Nara Logics is doing to aggregate data
- How the company’s synaptic network works
- Whether or not AI is a panacea
- The key components of a successful AI project
- How to think about AI tools and teams

For more information, see the show notes: http://bit.ly/2NPwQED

AI, What is It Good For?

Episode 85: AI, What Is It Good For with Jana Eggers

After spending the past six months traveling across North America and talking to dozens of companies, Jason Brenier, our VP of Strategy, got seem clear insights into the challenges today's businesses face. When it comes to conversational AI, one of the biggest is figuring out how to build the right team to support their business. In this episode, Jon Prial talks with Jason about how to go about building a successful conversational AI team, drawing on insights from a new guide Jason and his team have written that's being published this week.

You'll learn about:

- The latest trends in conversational AI
- How to build a successful conversational AI team
- The importance of having a cross-functional team
- What skillsets are essential for the success of the team

Access the show notes here: http://bit.ly/2xLAnuo

Episode 86: Building Conversational AI Teams with Jason Brenier

Is it unethical if your company doesn’t do it’s due diligence on avoiding bias? In this episode, Jon Prial talks with Kathryn Hume, the Vice President of Product and Strategy at integrate.ai. Kathryn and her team recently published a paper entitled “Responsible AI in Consumer Enterprise” which offers a framework to help organizations operationalize ethics, privacy and security as they apply machine learning and artificial intelligence. Jon and Kathryn discuss the paper and highlight some of its key takeaways for today’s businesses.

You’ll Learn About

- How ethics can make or break a company
- How machine learning systems can negatively impact people
- Using a framework to examine ethical issues as you build ML systems
- Practical advice for being more ethical with AI

Learn more by accessing the show notes: http://bit.ly/2ycJALW

Episode 87: Trust and the Data Scientist's Dilemma

Could something like measurement, which seems boring on the surface, actually be the secret to getting value from machine learning? Measurement isn’t always what you think it is. Great product developers and applied machine learning practitioners are finding creative ways to incorporate it as part of their feedback loops and machine learning products. In this episode, Kathryn Hume talks with Danny Lange, the VP of and Machine Learning at Unity Technologies. In addition to discussing the role of measurement in putting reinforcement learning systems into production, they also dive into why gaming is an excellent simulation ground for the some of the most exciting developments in applied machine learning and reinforcement learning research. 

You’ll learn about:
•	What reinforcement learning is and how it works
•	How to overcome the challenges of getting great labeled data
•	The important role of measurement in reinforcement learning
•	Exploring counterfactuals within the context of reinforcement learning
•	Working on machine learning in the gaming industry

Episode 11: The Reinforcement Learning Game with Danny Lange

Are we currently experiencing a deep transformation in the concept of software unlike anything we’ve seen in the past 30 years? Peter Wang, the Co-Founder and CTO of Anaconda, the world’s most popular Python data science platform, thinks so. In this episode of In Context, he joins Kathryn Hume for a discussion of data-centric computing and how the data and operations that enable software are moving closer together.

You’ll learn about: 

•	How data and operations are moving closer together
•	The implications of this data-centric computing for data scientists and businesses alike

Episode 13: The Transformation of Software with Peter Wang

Episode 12: The Transformation of Software with Peter Wang

A podcast exploring the latest developments in Artificial Intelligence, within the context of the personal biographies, motivations, world views and beliefs of the leading researchers, practitioners, and entrepreneurs in the field.

Episode 9: Hiring for Autonomy in Data Science Teams with Eric Colson

In Context

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