The AI in Business Podcast

At Facebook headquarters, I learned there are 1 billion active users every month. In a more recent interview at eBay headquarters in San Jose, l learned that the well-known digital store has over 1 billion products for sale. eBay is, without a doubt, the world's largest marketplace, and there's enough incoming data to keep a large team of data scientists busy for years. I speak with Zoher Karu, eB...

In this week's episode, I speak with Igor Baikalov, Chief Scientist at cybersecurity company Securonix, about the trends in data security and where security itself has had to take a step up in the last five years. Igor touches on major meta-trends that have forced data security to advance, as well as what has made AI and machine learning a 'requirement' of modern data security strategy, something...

In this week's episode, we feature an in-person interview from Facebook's headquarters with Hussein Mehanna, director of engineering of the Core Machine Learning group. Mehanna and I talk in-depth about the topic of personalization, touching on the pros and cons, how it works at Facebook, and how his team is working to overcome technological barriers to implement personalization in a way that impr...

When one thinks through important industry apps of AI, law or legal apps are not usually the first to jump to mind, but there's certainly a need. Richard Downe, Ph. D. is Vice President of Data Science at Casetext, a startup working on improving search and natural language processing and democratizing legal information. In this episode, he speaks about the current bottlenecks for people trying to...

Learning about the research behind machine learning is always fun, but so is learning about the real-world applications. In today's episode, we're joined by the CEO and founder of Wrike, Andrew Filev. Filev speak about where Wrike is currently applying machine learning and AI in their fast-growing, data-driven company. He shares his insights as to why he thinks marketing might be the most ripe for...

Today we have a guest who has interviewed more futurists than anyone else I know. While at TechEmergence a lot of our interviews focus on executives in AI, Nikola Danaylov has had the pleasure of interviewing some of the finest futurists and forward-thinking minds in the world, including Ray Kurzweil, Verner Vinge, Marvin Minsky, and many others. We speak today about the trends he's seen aggregate...

A lot of companies in the San Francisco Bay make the claim that they can do something great with data; many fewer are at a degree of scale to make this vision possible. Today we speak with Nicholas Clark, CEO of DoubleDutch, a company now powering thousands of events nationally and implementing machine learning into their operations, including predicting business results from actual attendees. Dou...

Natural language processing (NLP) sounds cool in theory. We're familiar with Siri and Echo of course, but where does it play a role in other companies? In today's episode, we speak with Samiur Rahman from Mattermark, whose entire business model is predicated on organizing and making findable information about companies, and generating a platform to search by unique criterion. Doing so involves som...

We've spoken in the past about computer vision on the TechEmergence show, but we haven't covered much about it in industry apps. Few businesses have better mastered this technology in the form of an app better than Shutterstock. In today's episode, we speak with Nathan Hurst, currently a distinguished engineer with Shutterstock and previously with Google, Amazon, and Adobe. Nathan delves into the...

In addition to focusing on industry applications of artificial intelligence and emerging technology, we also focus on ethical and societal impacts of emerging technology. In this episode, we get back to ethics with Wendell Wallach, a scholar at Yale's Interdisciplinary Center for Bioethics and author of "A Dangerous Master", which addresses tech governance and other emerging technology issues. In...

The artificial intelligence field is normally seen as burgeoning and new, populated with lots of small, scrappy companies aiming to become the next de-facto solution, with maybe one exception - "Big Blue". IBM has been involved since the 'beginning' and is perhaps best known for Watson, which has from Jeopardy to a range of applications in small and big businesses, as well as the public sector. Sw...

"Artificial intelligence (AI) can be seen as a progression in our scalability of labor." This quote comes from this week's guest, Naveen Rao, who received his PhD in Neuroscience from Brown before becoming CEO at Nervanasys, which works on full stack solutions to help companies solve machine learning (ML) problems at scale. In this week's episode, Rao speaks about certain domains in industry where...

Many employers (and employees) are familiar with the 'painful' learning curves of using multiple software products or platforms at once, but these may not be gripes you want to share with Amotz Maimon. This week, we feature an interview recorded at Yahoo headquarters with its Chief Architect, Amotz Maimon. He speaks about technology governance and how companies small and large can make faster and...

If you're in the San Francisco Bay area, it's not all that novel to be trained in or working on some form of AI; however, to be doing so in the 1980s and 1990s was a more rare occurrence. Dr. Lorien Pratt has been working with neural nets and AI applications for many decades, and she does lots of consulting work in implementing these technologies with companies in the Bay area. In this episode, Lo...

When we think about applying AI and data science to different areas of business, we often think about those domains that offer a wide swath of quantitative metrics that we can feed a machine, like marketing or finance. Human resources (HR) normally doesn't fit the bill. How we hired someone, how we felt about them when we hired them, how they perform qualitatively, these are things that are often...

There are hedge funds and financial institutions that already use real-time data and sentiment analysis from social media, articles and videos in real-time to potentially make better trading decisions - but what does it mean when those same companies can use real-time satellite information to detect company activities and make trades based on that data? In this episode, Research Director of Capita...

Ten years ago, it would have been difficult to talk into your phone and have anything meaningful happen. AI and natural language processing (NLP) have made large leaps in the last decade, and in this episode Dr. Catherine Havasi articulates why and how. Havasi talks about how NLP used to work, and how a focus on deep learning has helped transform the prevalence and capabilities of NLP in the indus...

When it comes to data science and machine learning, what are the related skills that are getting people jobs and what are the industries that are supplying those in-demand jobs? These are two important questions that we discuss in this week's episode with CrowdFlower's CEO Lukas Biewald, whose company is providing a pragmatic perspective of the industry by focusing on assessing job listings and re...

When you go to Harvard Business School and then to McKinsey company to work in private equity, there's really only one thing left to do - go to Silicon Valley and start an AI startup. At least, this is exactly what CEO Praful Krishna did when he moved to San Francisco to start Coseer, an AI company focused on understanding natural language and unstructured data. In this week's episode, we speak ab...

While we've featured quite a few companies that use and implement AI systems, we've more rarely gone behind the scenes with companies or consultants providing AI-related services to companies. In this week's episode, we talk with Machine Learning Consultant Charles Martin, a data scientist and machine learning expert who has done freelance consulting on machine learning systems at companies includ...

Tad Slaff is the founder of Inovance, the creator of TRAIDE - a strategy creation platform that use machine learning algorithms to help traders uncover patterns in assets and indicators and build more reliable trading strategies. In this episode, Tad speaks about the state of machine learning in finance today, and touches on how future applications of machine learning and trends may alter what giv...

It's more common to ask what AI can to do to win at games, but it's less common to ask what games can do to help develop AI. This is a particularly fitting topic after Google's DeepMind's defeat of Go, and in this episode we talk with New York University's Julian Togelius about his research in how games can help us develop AI. We discuss how simple AI has been used in more common video games; the...

What is intelligence? For some researchers, it may be quite possible to create an intelligent machine 'in a box', something without physical embodiment but with a powerful mind. Others believe general intelligence requires interaction with the outside world, inferring information from gestures and other features of functioning in an environment. Dr. Vincent Müller is of the belief that intelligenc...

You're a business, and you've collected data - now how do you now make sense of it? Bring in a technology called 'sentiment analysis', a form of machine learning that determines whether text is positive or negative. Slater Victoroff's company Indico provides a sentiment analysis API product that specializes in this task. In this episode, we talk about about the common misconceptions that businesse...

How does automation influence society today? This is an open-ended question with likely endless answers that can be observed in many different areas of society. As a Writer, Speaker, and Professor in Media Theory and Economics, Douglas Rushkoff has made it his livelihood to examine the impacts of automation in our evolving digital society. In this episode, we speak about his 'disappointment' in ho...