Artificial Intelligence in Industry with Daniel Faggella

This week, we spoke with David Carmona, the GM of Artificial Intelligence at Microsoft, about his approach to AI ROI with the enterprise clients of Microsoft. The biggest takeaway from this episode comes right at the beginning. David talks about how to think about artificial intelligence ROI in the long-term and the near-term.

That is to say, how are we going to see a relatively near-term return with AI that might be able to improve our condition while keeping in mind the longer-term disruption in our industry?

Direct download: AI_in_Industry-David_Carmona_ROI-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 2:42pm PDT

It's clear that there's a revolution in how artificial intelligence is done with neural networks as opposed to the old school systems of the '80s and the '90s. It's clear that hardware is beginning to evolve, and it's also quite clear that the way that we power these hardware systems is going to have to change.

GPUs and AI hardware are tremendously power-intensive, and this week we speak with Robert Gendron of Vicor Corporation, a company focused on powering AI systems. Vicor is in partnership with Kisaco Research, which is putting on the 2019 AI Hardware Summit September 17 and 18 in Mountain View, California.

Robert speaks about why the way that they are powered needs to be different than traditional manufacturing equipment. He also discusses how the powering of these systems need to work if businesses want to reduce energy costs and be as efficient as they can when it comes to AI.

Direct download: AI_in_Industry-_Robert_Gendron_-_Vicor_-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 9:32am PDT

This week, we have a bonus episode. 

We spoke with Jonathan Ross, CEO and founder of Groq, an AI hardware company, about software defined compute. Groq is in partnership with the AI Hardware Summit happening n Mountain View, California on September 17 and 18. 

Software defined compute is a way of thinking about how compute can be optimized for machine learning functions. Ross talks about some of the pros and cons of GPUs and where software defined computer might make its way into future machine learning applications.

Direct download: AI_in_Industry-Jonathan_Ross-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 1:37pm PDT

This week, we speak with Dr. Charles Martin of Calculation Consulting. He's a bit of a mentor of mine when it comes to AI knowledge. Charles speaks to us about the pitfalls in getting to ROI, particularly the cultural elements within enterprises that make it so hard to get a return from AI projects.

Charles and I tend to go off in a variety of directions when we talk—he's an animated guy—so be prepared for that. But I think this is an awfully fun episode of the podcast.

For more on the fundamentals of getting started with AI in business, learn more about our newest report: Getting Started with AI: Proven Best Practices of Adoption.

Direct download: AI_in_Industry-Charles_Martin_ROI-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 1:37pm PDT

We have a bonus episode this week. We spoke to Moe Tanabian, General Manager of Intelligent Devices at Microsoft, who is speaking at the AI Hardware Summit in Mountain View, California on September 17 and 18.

Tanabian discusses how to think about and reframe business problems to make them more accessible for AI, as well as AI at the edge, which involves doing AI processing on individual devices rather than in the cloud.

The edge could open up new potential for business problems to be solved with AI. Tanabian also provides representative use cases of intelligent devices.

Direct download: AI_in_Industry-Moe_Tanabian-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 3:20pm PDT

This month, we focus on the ROI of AI, and our guest this week is Sankar Narayanan, Chief Practice Officer at Fractal Analytics, a global AI & analytics firm headquartered in New York City.

In this episode, Narayanan discusses how to measure the ROI of AI in ways that aren't just financial return. In addition, he provides examples from his hands-on experience implementing AI to provide business leaders with ways of thinking about success when it comes to AI projects.

For more on measuring the ROI of AI, learn about our newest report Getting Started With AI: Proven Best Practices of AI Adoption.

Direct download: AI_in_Industry-Sankar_Naranyan-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 7:13am PDT

This is the final episode in the month-long series on getting started with AI. In this episode, Emerj CEO Daniel Faggella breaks down the key insights from all four of this month's interviews, distilling them into core best-practices for getting started with artificial intelligence in business. In addition, Daniel discusses insights from our newest report:

Getting Started with AI: Proven Best-Practices for AI Adoption

Direct download: AI_in_Industry-Analyst-Getting-Started-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:20pm PDT

This week we interview Jan Kautz, Vice President of Learning and Perception Research at NVIDIA. Kautz talks about what people underestimate when they start an AI initiative. In addition, he emphasizes the critical value of data storage.

Kautz dives into the importance of getting started with an AI project when you already have a barometer of success. Essentially, he talks about why it's important to select a first AI project in an area where you already have a way of measuring success.

Learn more about AI adoption in our full report, Getting Started With AI: Proven Best Practices for AI Adoption.

Direct download: AI_in_Industry-Jan_Kautz-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 9:56am PDT

This week, we speak with Jan Neumann, Senior Director of Applied AI Research at Comcast. Comcast is an enormous company; it has lots of data, lots of application areas for AI, and a lot of opportunity for confusion about AI. As such, Neumann speaks with us about scaling AI expertise in the enterprise.

Neumann talks about a very strong distinction between software and AI and how to think through problems to determine whether or not it's a software problem or an AI problem.

He also talks about scaling the problem-solving abilities of business experts in the organization. Lastly, Neumann talks about his ideas for how to determine a first AI initiative.

Direct download: AI_in_Industry-Jan_Neumann-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 1:00pm PDT

This week we speak with David Carmona, General Manager of AI at Microsoft. Carmona discusses how redefining a business process is a very different kind of AI adoption project than working on something that is horizontal.

He discusses how to attack both of these scenarios, which to handle first, and why. 

In addition, Carmona talks about proprietary data and things that are close to your own IP. How do you take advantage of the real strategic data value within your own organization? How should you be thinking about that differently? Carmona poses three different questions to determine where those valuable opportunities are for you.

Direct download: AI_in_Industry-David_Carmona_Adoption-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 7:00am PDT

It's the first episode of the new style of AI in Industry, in which we spend a month at a time on a specific theme. This month is AI adoption.

This week we speak with Vlad Sejnoha at Glasswing Ventures, an AI-focused VC firm. Sejnoha spent many years as the CTO at Nuance Communications. He talks to us about the table stakes AI insights the C-suite have to know and the dangers of relying entirely on consulting firms and vendor companies for these insights.

In addition, Sejnoha discusses the need for a "BS-o-meter" for when someone is making a claim about AI to determine if it's real or hype.

Lastly, Sejnoha discusses how he would go about choosing a first AI project.

Direct download: Vlad_Sejnoha-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 11:33am PDT

This episode of the AI in industry podcast is all about where the rubber meets the road for AI in Insurance. We interview Jerry Overton, Head of AI and a Fellow at DXC Technology. He speaks to us about his experience implementing AI in insurance, about where there's real traction with AI in insurance, and where there's only hype. In particular, Overton discusses how anomaly detection technology is a natural fit for AI in the insurance sector.

This is the last episode of its kind on AI in Industry. Starting next Tuesday, we'll be kicking off a new format for the show. Each month, we'll focus on a specific theme, and in August, we're focusing on AI adoption in the enterprise. We hope you'll join us.

 

Direct download: AI_in_Industry-Jerry_Overton-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 7:59am PDT

When we polled our audience about what they were interested in, the most selected response was "business intelligence." As a follow-up, we asked them what business intelligence meant to them, and their responses boiled down to anything about understanding the data businesses are already collecting.

That kind of broad definition gets to the heart of the confusion surrounding the differences between business intelligence and artificial intelligence. The line is starting to get blurry. 

Our guest this week is Elif Tutuk, Senior Director at Qlik. Tutuk talks about how business intelligence is evolving and how we might define it now that a lot of BI is becoming AI. Tutuk discusses where AI is making its way into business intelligence and what that might enable for businesses.

Read our comprehensive definition of machine learning for business leaders here: https://bit.ly/2Ya2NxK

Direct download: AI_in_Industry-Elif_Tutuk-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 12:45pm PDT

This week, we interview Jay Budzik, CTO at ZestFinance, about where AI applies to the world of auto-lending. We speak with Budzik about how underwriting and credit scoring is evolving as a result of advances in machine learning.

In addition, we talk about how companies might solve the "black box" of machine learning in finance, particularly how ZestFinance is focusing on transparent models. The financial sector has to contend with complex regulations that prevent certain information from being leveraged in credit models. It can be near impossible to determine how machine learning comes to the conclusions it does, but ZestFinance claims their software in part solves this problem.

Direct download: AI_in_Industry-Jay_Budzik-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 11:10am PDT

Some say that the competitive dynamics between the US and China in terms of AI are overblown, but there's a lot of truth to them. The US has access to more of the base research, but China can orchestrate various organizations (corporations, government bodies) and secure government funding.

That said, very few people talk about K-12 education and what countries are doing to prepare their future workforce for AI. David Touretzky talks to us about just that. He is a research professor in the Computer Science Department and the Center for the Neural Basis of Cognition at Carnegie Mellon University. He's heading up an initiative for K-12 education, and he discusses what countries should be doing to secure their positions and technological leadership in the 21st century.

Direct download: AI_in_Industry-Dave_Touretzky-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 7:00am PDT

While AI is certainly finding its footing in finance, we still find most of our subscribers are in a phase where they're trying to catch up in terms of data and data infrastructure and figure out where there's real traction with AI in finance: in banking, investing, or insurance.

In this episode, we explore AI use-cases in a number of these areas of the financial industry. We interview Carlos Pazos and Anwar Ghauche at Spark Cognition about how to maximize a smaller data science team at a financial institution, how AI and alternative data is being used for quantamental investing, and how AI is automating some financing and underwriting processes.

Direct download: AI_in_Industry-Spark_Congition-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 4:19pm PDT

Building an AI strategy - there's hardly anything more vague and open-ended than that. Business leaders have probably gotten the idea that they should develop one, but where should they start? That's what we talk about this week with Charles Martin, PhD.

Martin talks about how to go about starting an AI strategy, what to avoid, and the challenges and struggles of applying AI at existing businesses. Also, Martin discusses what business leaders should ignore and what business leaders should tune into and prioritize for an effective AI strategy that will propel them toward success in the coming years.

Direct download: AI_in_Industry-Charles_Martin-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 12:27pm PDT

One of the best conversations I ever had on the topic of AI business strategy on the podcast was with the guest I've brought back this week: Madhu Shekar, Head of Digital Innovation for Amazon Internet Services in Bangalore.

I wanted to do a deeper session with Madhu, who has seen a lot of companies go from no AI to beginning with AI, about where to start with AI adoption. How do companies build the expertise and experience with AI that lets them scale it to their organization? He also talks about how to prepare realistically for AI, including data requirements, integration times, and more. 

Direct download: AI_in_Industry-Madhu_Shekar-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 12:10pm PDT

As it turns out, often times terms like predictive analytics and data science are used incorrectly. By the end of this podcast, you'll have greater clarity on five potentially vague AI and data science terms that are sometimes overused in conversations about AI in the enterprise. This week, I introduce you to German Sanches, who focused his PhD on NLP and has done a lot of AI work in business. He also helps us with our research projects. This episode is all about addressing use-cases in reference to five terms that a lot of folks get wrong.

Direct download: AI_in_Industry-German_Sanchis-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 1:53pm PDT

This week, we interview Arnab Kumar, Founding Manager, Frontier Technologies for the NITI Aayog, the wing of the Indian government focused on rolling out AI into areas like healthcare and agriculture.

In this episode, we talk about critical factors for applying AI at the national level, such as where to begin applying AI and what the low-hanging fruit is for gaining traction, leverage, and data assets that are going to transfer elsewhere.

We also talk about how governments, much like enterprises, need a future vision for critical capabilities they're going to enable with AI.

Finally, Kumar discusses what he thinks are the most transferable lessons for the enterprise from his experience building out a national AI strategy.

Direct download: AI_in_Industry-Arnab_Kumar-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 3:47pm PDT

Erin Knealy is the portfolio manager of the cybersecurity division of the Us Department of Homeland Security. She is the interface between the US government and the startup and tech ecosystems. We speak with her about transferable lessons from the AI use-cases in the public sector into the private sector. How does an existing organization pick the right first AI project? How should look through a lens of opportunity when it comes to AI? In this episode, we discuss how these lessons learned in the public sector can apply to the private sector.

Direct download: AI_in_Industry-Erin_Keneally-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 9:05am PDT

It's curious to see how much more there is of sensor tech and internet of things than there was 18 months ago. This week, we speak with Cormac Driver, PhD and Head of Product Engineering at Temboo, an IoT vendor.

We talk about how to spot AI and IoT opportunity where sensors and equipment in the physical world can actually deliver ROI and drive value for an enterprise. In addition, Cormac discusses how to get the most out of an IoT project and what's involved in terms of data and infrastructure. Finally, I ask Cormac in what sector IoT will become ubiquitous first.

Direct download: AI_in_Industry-Cormac_Driver-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:47pm PDT

There's an entire artificial intelligence ecosystem for enterprise search. Most of this is in a purely digital world. Most vendors help with a layer of AI-enabled search that understands terms or phrases and is able to return the results or answers to questions that someone types in. But the problem is compounded when it comes to searching the physical world.

That is the topic of this week's episode of AI in Industry. Our guest is Anke Conzelmann, Director of Product Management at Iron Mountain. Iron Mountain is a four-billion-dollar physical and digital storage company based in the Boston area. They handle the records of some of the largest financial, health care, and retail brands around the world. IConzelmann speaks with us about the future potential of artificial intelligence for search within an enterprise, not just of digital files, but across formats.

Direct download: AI_in_Industry-Anke_Conzelmann-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 3:09pm PDT

The AI in Industry podcast is all about transferrable lessons. Today we speak with Andrew Byrnes, an investment director at Comet Labs in San Francisco about the competitive edge with AI. What does it look like when companies adopt AI in a way that gives them a competitive advantage? Byrnes breaks down the idea into two categories: automation and augmentation.

Direct download: AI_in_Industry-Andrew_Byrnes-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:15pm PDT

We did a lot of focus on healthcare for the World Bank, and we presented a lot of that research in South Africa. When I was there, I interviewed DataProft cofounder Frans Cronje about the intersection of AI and manufacturing.

We talk about what's possible with AI in manufacturing today and just how instrumented and challenging it is to add a layer of AI insight into a manufacturing environment. This is much harder than a lot of other domains where data is maybe more accessible, and in some cases it's also higher risk.

Direct download: AI_in_Industry-Frans_Cronje-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 11:23am PDT

This week we speak with founder and CEO of Aidoc, Elad Walach, about the challenges of adopting AI to become part of a workflow in healthcare. We speak to him about what it is that makes it so challenging to get these tools to become part of the process of treating patients.

Direct download: AI_in_Industry-Elad_Walach-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 12:08pm PDT

This week, we speak with arguably one of the best-known folks in the domain of neural networks: Jurgen Schmidhuber. He's working on a lot of different applications now in heavy industry, self-driving cars, and other spaces.

We talk to him about the future of manufacturing and more broadly, how machines and robots learn. Schmidhuber uses the analogy of a baby learning about the world around it. He has a lot of interesting perspectives on how the general progression of making machines more intelligent will affect other industries outside of where AI is arguably best known today: consumer tech and advertising.

If you're in the manufacturing space, this will be an interesting interview to tune into. If you're just interested in what the next phase in AI might be like, I think Schmidhuber actually frames it pretty succinctly.

Direct download: AI_in_Industry-Jurgen_Schmidhuber-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 11:12am PDT

The AI In Industry podcast is often conducted over Skype, and this week's guest happens to be one of its early developers. Jaan Tallinn is recognized as sort of one of the technical leads behind Skype as a platform. I met Jaan while we were both doing round table sessions at the World Government Summit, and in this episode, I talk to Tallinn about a topic that we often don't get to cover on the podcast: the consequences of artificial general intelligence. Where's this going to take humanity in the next hundred years?

Direct download: AI_in_Industry-Jaan_Tallinn-Mixdown_1_1.mp3
Category:Artificial Intelligence -- posted at: 3:22pm PDT

In this episode of the AI in Industry podcast, we speak with Marshall Choy, VP of Product at SambaNova, an AI hardware firm based in the Bay Area. SambaNova was founded by a number of Oracle and Sun Micro Systems alumni. We speak with Choy on two fundamental questions:

  • How will business models fundamentally change with respect to new AI hardware capabilities?
  • How can business leaders think about their AI hardware needs?

SambaNova is one of many firms that's going to be advertising at the Kisaco Research AI Hardware Summit in Beijing June 4th and 5th.

Direct download: AI_in_Industry-Marshall_Choy-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 8:50am PDT

Danny Lange heads up the AI efforts at Unity, one of the better-known firms in terms of simulations and computer graphics. They work in several different industries, but this week we speak mostly about automotive.

This is a man that has been in the AI game since before it was cool, and now he is working on some cutting-edge projects with Unity. In this interview, we speak with Danny about where simulated environments are becoming valuable.

We hear about simulations mostly in the context of video games, and of course, Unity does apply their technology in that domain, but what about a space like automotive, where navigating within an environment is important?

Certainly we need to have physical cars on the road to drink in data from physical roads and physical environments, but is it possible to splinter some digital cars into digital environments that model the physics, that model the roads, that model the same number of pedestrian risks, and see how well they succeed in all these different environments with no real physical risk of damaging an actual vehicle or an actual person on the road?

As it turns out, there's value there.

Direct download: AI_in_Industry-Danny_Lange-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 9:01am PDT

Have you ever been frustrated with how Alexa or Siri don't always understand your verbal requests? If so, then you already understand the problem that our guest this struggles with. He's Tom Livine, co-founder and CEO of Verbit.ai.

Verbit is a company that focuses on AI for transcription. They use a combination of machine learning and human experts to transcribe audio in different accents, in different noise environments, with different diction, to give people more accurate results and hopefully help the process scale.

In this episode, Levine explains five different factors that go into getting transcription right and getting AI to be able to aid in the process. In addition, Tom talks about some of the critical factors for where transcription will come into play in terms of bringing value into business.

Direct download: AI_in_Industry-Tom_Livne-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 11:13am PDT

Have you ever been frustrated with how Alexa or Siri don't always understand your verbal requests? If so, then you already understand the problem that our guest this struggles with. He's Tom Livine, co-founder and CEO of Verbit.ai.

Verbit is a company that focuses on AI for transcription. They use a combination of machine learning and human experts to transcribe audio in different accents, in different noise environments, with different diction, to give people more accurate results and hopefully help the process scale.

In this episode, Levine explains five different factors that go into getting transcription right and getting AI to be able to aid in the process. In addition, Tom talks about some of the critical factors for where transcription will come into play in terms of bringing value into business.

Direct download: AI_in_Industry-Tom_Livne-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 11:13am PDT

I hope that by the end of this episode of the AI in Industry podcast, you'll not only be able to hire better data scientists who will be a fit for your business problems and build better data science teams, but also pick the AI applications and use cases that you should bring into your business versus those that you shouldn't.

This episode, we interview Brooke Wenig, the machine learning practice lead at Databricks. Databricks was founded by the folks who created Apache Spark. Those of you who are technically savvy with AI will be familiar with Apache Spark as an open source language for artificial intelligence and distributed computing.

Wenig works with a lot of companies with Databricks. Databricks is now close to 700 folks and helps implement AI applications into, oftentimes, large enterprise environments. Wenig speaks with us this week about what to look for in an actual data scientist and how to find data science folks with the right skills to be able to communicate to business people, not just to work with models. What should people be capable of; how should they be capable of thinking? Hopefully, some of you will have better interview questions by the end of this podcast.

In addition, we ask Brooke about what the value of covering the cutting edge applications of AI is, looking at what's working in industry. How does that help us in our own business make better decisions?

Read the full article on Emerj.com

Direct download: AI_in_Industry-Brooke_Wenig-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 2:02pm PDT

If you want to understand the international competitive dynamics of artificial intelligence, particularly the US and China, starting with the United Nations is probably not a bad move. This week, I spoke with Irakli Beridze, the head of the Center for Artificial Intelligence and Robotics at the UN, particularly under the wing called UNICRI, the organization's crime and justice division.

Irakli was kind enough to invite me to speak at a recent event in Shanghai held by the UN and by the Shanghai Institutes for International Studies on national security, and when we were there, we talked a good deal about China's unique AI-related strengths.

I spoke with Irakli about the strengths of the ecosystem in China for artificial intelligence and how that stacks up against the US.

In addition, I asked Irakli about what it's going to look like to encourage more and more multilateral action. In other words, how do we get countries to be on the same page so AI doesn't become an arms race?

Direct download: AI_in_Industry-Irakli_Beridze-Mixdown_2.mp3
Category:Artificial Intelligence -- posted at: 11:02am PDT

Discover how so-called autoML, or automated machine learning, could bring AI to more businesses by allowing users to build AI models faster and cheaper.

Read the full article, where we go into further detail, at Emerj.com. Search for "AutoML and How AI Could Become More Accessible to Businesses"

Direct download: AI_in_Industry-Yiwen_Huang-Mixdown_1.mp3
Category:general -- posted at: 9:12am PDT

AI has numerous use cases in legal, from document search to compliance and contract abstraction. This week, we speak with Lars Mahler, Chief Science Officer for LegalSifter, about what's possible with AI for legal departments today and how AI applications for legal teams, such as natural language processing-based contract analysis, work. In addition, Mahler discusses how lawyers at companies and data scientists work together to train machine learning algorithms.

He provides some insight into how a company has to make its way into the legal space and the challenges of training an NLP system and collecting data for it.

Read more about AI in legal at Emerj.com

Direct download: AI_in_Industry-Lars_Mahler-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 2:33pm PDT

There's a lot of venture money pouring into artificial intelligence in healthcare. From pharma to hospitals and beyond, the potential applications in healthcare are promising. 

Late last year, we spoke for The World Bank about our proprietary AI in healthcare research, and speaking with governments, it's clear that there are hurdles that healthcare companies have to overcome to access data for training AI systems. 

Broadly, most of the folks that we speak with who are innovating in AI and healthcare are frustrated with how hard it is to streamline the data to make use of it for applications such as diagnosing illnesses.

But why is that? That's a question that we asked our guest this week.

Our guest this week is Zhigang Chen, and he speaks about why this problem exists and how it can be overcome. In addition, Chen talks about the AI ecosystem in China and how it differs from Silicon Valley.

Direct download: AI_in_Industry-Zhigang_Chen-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 11:53am PDT

Saying that your company does artificial intelligence might still have a slightly cool ring to it if you're talking to one of your peers at a conference, but it doesn't mean very much to venture capitalists today, who've been battered with machine learning and artificial intelligence in every pitch deck they've seen for the last three or four years.

I wondered, from a venture capitalist perspective, what makes an AI company's value proposition actually strong? What is it that makes an AI startup actually seem like a company that maybe could use AI to really win in the market? Not just to be another company that says they're going to do it or says they are doing it, but where can it actually provide enough of that competitive edge to make a VC want to pull the trigger?

Getting a grasp of the answer to that question seems pretty critical.

This week, we speak with Tim Chang, partner at Mayfield Fund in Menlo Park, California. Chang and I both spoke at the Trans Tech Conference, held every year in Silicon Valley, focused on wellness and health-related technologies.

Chang talks about what it is about an AI company's pitch, product, and market that actually makes AI an enhancement to the business in a way that's compelling to someone who wants to invest potentially millions and millions of dollars.

Direct download: AI_in_Industry-Tim_Chang_-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 1:33pm PDT

If one wants to start a general search engine, they're going to have to compete with Google. If one wants to start a general eCommerce platform, they'll have to compete with Amazon. But the same dynamics play out on a smaller scale. There are going to be some established players, some big tech giant, be it IBM or someone else, who already has a product.

When it comes to getting a new AI product out to market, how does one compete with the big guys?

This week's guest is Mike Edelhart, who runs Social Starts and Joyance Partners, seed stage investment firms out in the Bay Area. Edelhart has invested in a number of companies, and in this episode, we get his perspective on not only the patterns among successful AI startups and where AI plays a role in their competitive strategy, but what a "land and expand" strategy looks like for a new product that already has larger and more established competitors.

Direct download: AI_in_Industry-Mike_Edelhart-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 8:41am PDT

A lot of AI in the press is CMOs or marketing people talking about what a company can do in a way that really is aspirational. They're speaking about what they can do, but in reality, the things that they're talking about, the capabilities won't be unlocked for maybe a year or more. These are just things on the technology road map, but people speak about them like they exist now.

This week, we speak with Abinash Tripathy, founder and Chief Strategy Officer at Help Shift. They've raised upwards of $40,000,000 in the last six years to apply artificial intelligence to the future of customer service, and we speak about the hard challenges of chatbots and conversational interfaces, as well as how long it's going to be until those are actually robust. This in opposition to how people at large companies might put out a press release touting their own chatbots that simply aren't capable of doing what they say they can to any meaningful degree.

We also talk about where AI can augment and make a difference in existing customer service workflows.  Even if we can't have all-capable chatbots to handle banking or insurance or eCommerce questions from people, where can AI easily slide it's way in and actually make a difference today? In this episode, we draw a firm line on where the technology currently stands.

Overall, though, this episode is about the challenges of actually innovating in AI. We talk about why it really is the big companies that do a lot of the actual cutting edge breakthroughs of AI and why others are going to have to license those their technologies from large firms like Google and Amazon.

We also discuss why companies maybe need to have a realistic expectation about where they can apply AI, as well as why actually innovating and coming up with new AI capabilities on their own might just be wholly unreasonable given their data, their company culture, and their density of AI talent.

Read the full interview article on emerj.com

Direct download: AI_in_Industry-Abinash_Tripathy_-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 11:07am PDT

This week we interview a leader at Facebook. Jason Sundram is the lead of World.ai at Facebook, which is one of their efforts to work with public data around roads and population and other projects of that kind. But Sundram is also highly involved in the Boston office here, where Facebook will soon have around 650 employees. Many of them focus on data science and artificial intelligence.

Last time we talked about personalization in AI with Hussein Mehanna, who was Director of Engineering at Facebook at the time. This time, we'll talk about two topics that all established sectors need to be focusing on:

  • How does one build ML and data science teams?
  • How does one pick an AI project?

For business leaders who are considering hiring data science talent or thinking about how to start with AI in terms of making a difference in their bottom line, this should be a useful episode.

Direct download: AI_in_Industry-Jason_Sundram-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 9:53am PDT

One of the promises of artificial intelligence is aiding humans in making smarter decisions. Whether it's in pharma, retail, or eCommerce companies, the idea of being able to pool together streams of data and coax out the insights that would help make the best call for the organization to reach its goals is the promise of artificial intelligence. As it turns out that same dynamic is sort of happening in the public sector where AI is now being used to inform policy.

This week we interview Professor Joan Peckham at the University of Rhode Island. Previously, she was Program Director at the National Science Foundation. PhD in computer science and she runs the Data Science Initiatives at URI. The University of Rhode Island is home to DataSpark, an organization that helps policymakers inform the decisions that they're going to make about the economy, the environment, the opioid crisis, a variety of social issues, based on deeper assessments of the data.

The ability to find objective insights might help policymakers make better decisions about where they allocate budget and what decisions are made. Right now, policymakers are beginning to tune into artificial intelligence as a source of informing their decisions. The same dynamic will likely play out in the C-suite, particularly when the data is actually there.

For more on AI in government, visit Emerj.com

Direct download: AI_in_Industry-Joan_Peckham-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:01pm PDT

Sales is a big part of any sort of B2B firm. We speak this week with Micha Breakstone, co-founder of Chorus.ai. He holds a PhD in Cognitive Sciences from the Hebrew University in Jerusalem, and prior to starting his own company, he studied for a few years at MIT and was working on NLP at Intel.

He speaks with us this week about where AI is being applied to sales, answering questions such as:

  • How can managers better train salespeople?
  • How can salespeople better find the patterns that lead to closing a deal?
    • The next appointment?
    • A bigger contract?

This is a nascent domain. There are very few companies are actively leveraging artificial intelligence in their sales process, but in the two years ahead we'll likely see more and more firms who are.

For more information on Ai for sales enablement, go to emerj.com

Direct download: AI_in_Industry-Micha_Breakstone-Mixdown_1.mp3
Category:general -- posted at: 12:16pm PDT

Close to a year ago, we had an interview here on the AI in Industry podcast with Jeremy Barnes of Element AI. We visited their headquarters in Montreal, and we'd interviewed Yoshua Bengio a couple years before that. Jeremy had brought up one point in that interview that I really like and that transfers its way into this conversation, which is that businesses should think not just about being more efficient with artificial intelligence, but places where they can actually make a real difference in the bottom line for the company beyond shaving off some savings.

In this week's episode, we focus on compliance and analyzing contracts. At first, one might think about such an application in terms of cost savings. We speak with Shiv Vaithyanathan, an IBM fellow and Chief Architect of Watson Compare & Comply, about the following:

  • What's possible with AI when it comes to analyzing contracts, and, most importantly
  • Where is the business upside for AI as it relates to contract analysis. How can we analyze contracts not just in a way that saves money, but that allows us to optimize our deals for revenue, for the likelihood that they'll go through?  What's that farther vision?
Direct download: AI_in_Industry-Shivakumar_Vaithyanathan-Mixdown_1.mp3
Category:general -- posted at: 12:27pm PDT

Episode Summary: Recently, we were called upon by the World Bank to do a good deal of research on the potential of applying artificial intelligence to health data in the developing world. Diagnostics was a very big focus of the information that we presented. It appears as though diagnostics is an area of great promise with regards to AI, and that's what we're focusing on in this episode the podcast.

This week, we speak with Yufeng Deng, Chief Scientist of Infervision, a company that focuses on computer vision for medical diagnostics. We speak with Deng about the expanding capability of machine vision, including what kind of data one needs to collect and what is now possible with the technology.

In addition, Deng also speaks about how Infovision found a business problem to solve using AI, and in that he provides transferable lessons to business leaders in a variety of industries.

Direct download: AI_in_Industry-Yufeng_Deng-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 1:54pm PDT

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