Artificial Intelligence in Industry with Dan Faggella

This week on AI in Industry, we speak with Equifax's Dr. Rajkumar Bondugula about how the dynamics, composition and requirements of the data science team have evolved over the years. Raj also shares valuable insights on how to build a robust data science and machine learning team, use its collective intelligence to solve problems, and retain the team by engaging them with the right problems they expect to solve.

For more insights from AI executives, visit:

TechEmergence.com

Direct download: AI_in_Industry-Rajkumar_Bondugula-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:43pm PST

This week on AI in Industry, we explore IoT security with Bob Baxley (Chief Engineer at Bastille). This includes information on how different IoT security is compared to infosec, the unique challenges IoT security presents (for detecting and scanning wireless network traffic that runs on various protocols and for classifying types of cyberthreats), what the future of IoT security might look like, and how deep learning and machine learning tools can be used to better classify and detect threats and attacks in the cyberspace.

For more insight on the applications of AI in industry, visit:

TechEmergence.com

Direct download: AI_in_Industry-Bob_Baxley-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:06pm PST

In this episode of AI in Industry, we explore how artificial intelligence can be use to manipulate human behavior - in gaming and in business. We explore how game designers use psychology and machine learning to drive their own desired outcomes, leaving users to "feel" in control.

Dr. Charles Isbell teaches machine learning at Georgia Tech. He explores the manipulative elements of game design, and how some of the same AI approaches are likely being used at tech giants like Amazon and Facebook. In this episode you learn how businesses leverage the "illusion of choice" with subtly influential AI techniques. Charles also helps us understand which businesses will be most able to use AI to guide user behavior in the years ahead.

For more interviews about the applications of AI in industry, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Dr._Charles_Isbell-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:24pm PST

If you combine the hype-factor of both "blockchain" and "artificial intelligence" you often get a supernova of jargon. This week on the AI in Industry podcast, we aim to get beyond the hype to discuss how blockchain might make AI more accessible for small and mid-sized businesses in the years ahead. Dr. Ben Goertzel - CEO of SingularityNET - is our guest this week.

For more expert interviews about the business applications of AI, visit:

TechEmergence.com

Direct download: AI_in_Industry-Ben_Goertzel-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 3:26pm PST

Expert systems and machine learning are two ends of a spectrum working to solve similar problems quite differently. One one hand you have if-then scenarios and a logical approach, and on the other you have vast neural networks and a big data approach. Some companies exist to try and bridge the gap between the if-then rule systems and the massive piles of data. They hope to find a middle ground of sorts, one that mitigates their individual disadvantages. One such company is Montreal’s fuzzy.ai.

In this episode, we interview its founder, Evan Prodromou about the state of the middle ground, so-called hybrid systems. The middle ground is an elusive, still mostly theoretical concept, but businesses can take steps to prepare for when it becomes accessible to them. What exactly would a hybrid system provide to businesses in terms of automation? How accessible are they now, and what can businesses do to best integrate them when they’re ready? Find out in this episode of the podcast.

For more interviews about the business applications of AI, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Evan_Prodromou-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 12:01pm PST

There’s a lot of hype out there about conversational AI. Although according to our guest, we’re nowhere near the day when AI can generate accurate conversations for the average business to integrate into their customer service, chatbots still have practical applications. In this episode, we interview the head of research at Digital Genius, Yoram Bachrach. Yoram succinctly outlines the current applications of chatbots—what they can and can’t do—and details how business can best prepare to automate their customer service.

For more interviews about the applications of AI in industry, visit us online:

www.TechEmergence.com

Direct download: AI_in_Industry-Yoram_Bachrach-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 7:49pm PST

How can machine learning help us advertise through social media? In this episode, Thomas Jelonek, CEO of Envision.ai, talks to us about how in the next five years, machine learning might automate the laborious guess-and-check process of finding visual content with which users can engage. Right now, finding images and videos that will best generate engagement is a task reserved for a human. He or she shifts through images and video clips that may work for an audience based on anecdotal evidence and perception of past post success. Learn how, according to Thomas, machine learning could help you save time and money, generate you a better ROI, and build you a larger list with more accurate targeting on social media.

For more interviews with AI experts, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Thomas_Jelonek-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 12:58am PST

This episode explores the ways in which artificial intelligence has the potential to revolutionize the field of medicine. This week's guest, Dr. Kristóf Zsolt Szalay speaks to this topic, discussing research that hopes to create automated learning networks and algorithms designed to predict the development of human cells in response to drugs. This technological innovation would make it possible for near-instantaneous simulations to be run, allowing optimal combinations and optimal doses of drugs to be pinpointed and distributed to patients.

For more interviews on the applications and implications of AI in business, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Kristof_Zsolt_Szalay-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 6:17pm PST

In this episode, discover how chatbots and conversational agents can provide you an advantage in the realms of customer support, product, support, lead engagement, and more, and learn the theory behind creating useful chatbots you can use in your own business. Right now, if we intend to find a piece of information or purchase something on the Internet, we might use a search engine that provides us with a list of sites we can browse in order to find ourselves a resolution for that intent. This week’s guest, Chief Scientist at Conversica, Dr. Sid J Reddy, talks about how AI and ML can usher in the next a new era of search software, one that will bring you a faster, more accurate resolution to your intent.

Most importantly, Dr. Reddy discusses how chatbot technology can be integrated into areas such as customer service, product support, and lead engagement. By the end of the episode, listeners will have a better idea of the importance of collecting data and how they can use that data to  to build chatbot templates they can use in multiple domains and applications.

For more interviews on the business applications of AI, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Sid_J_Reddy-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:13pm PST

This week on AI in Industry, we speak to Paul Barba (Chief Scientist at Lexalytics) about what how companies are using natural language processing, and what it takes (in terms of expertise, time, and training) to get these systems working. From sentiment analysis to categorization, Paul walks us through interesting and fruitful use-cases and sheds light on the back-end "tweaking" required to keep NLP productive in a changing business environment.

For more interviews on the applications of AI in business, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Paul_Barba-Mixdown.mp3
Category:general -- posted at: 3:19pm PST

In this episode, we speak with Alan O'Herlihy, Founder and CEO of Ireland-based Everseen. Alan speaks to us about how machine vision systems can be used to detect theft or mistakes at a checkout counter (including forgetting to scan items, customers intentionally hiding items, and more). Alan not only explains where these technologies are in use today, but he also breaks down some of his own predictions about what these computer vision systems might make possible in the workplace of tomorrow.

For more interviews and use-cases of AI in industry, visit:

TechEmergence.com

Direct download: AI_in_Industry-Alan_OHerlihy-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 10:00pm PST

In this episode, we talk to Murali Aravamudan, Founder and CEO of AI-driven drug discovery startup Qrativ, a joint venture by the Mayo Clinic and biotech/data science firm nference. Murali and I discuss the surge of medical information and data in the medical industry, the role of artificial intelligence in developing drugs for treatments to various diseases, and the future of AI in drug discovery.

For more in-depth interviews on the business applications of artificial intelligence, find us online at:

www.TechEmergence.com

Direct download: AI_in_Industry-Murali_Aravamudan-Mixdown.mp3
Category:general -- posted at: 6:44pm PST

In this episode, we talk to Daniel Nigrin, MD, Senior Vice President and CIO at Boston Children’s Hospital. Daniel and I discuss why hackers have come to prey on the healthcare industry, how these hackers benefit from their illicit activities, and what healthcare IT security precautions can be taken to prevent such attacks.

For more interviews on AI applications in business, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Daniel_Nigrin-Mixdown.mp3
Category:Cyber Security -- posted at: 5:00pm PST

Natural language processing has gained more and more attention with the raise of (or rather, the "fad" of) chatbots. Despite the flurry of press releases from companies about their conversational agents (only a few of which seem to be delivering real business value), few business leaders understand the value of NLP for customer service, sales enablement, or eCommerce.

In this week's episode of AI in Industry we interview Narjes Boufaden, computational linguistics PhD and CEO of Keatext, an NLP company based in Montreal. Narjes explores the possible business applications of NLP - specifically for customer service and customer experience - and she also explains (in layman's terms) how NLP systems are trained and integrated into businesses today.

The ROI on this episode (in my opinion), is a firm understanding of what NLP can and cannot do, and what business applications it can realistically solve today. I was fortunate to meet Narjes in person during my Montreal trip, and I'm glad we were able to bring her on the program shortly thereafter.

For more expert interviews on the business applications of AI, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Narjes_Boufaden-Mixdown.mp3
Category:general -- posted at: 2:42pm PST

As a human, we can often understand the mood, intention, and future action of another person just by looking at them. We see their posture, their facial expression, where their eyes are focused, and we can get a decent understanding of what they might do next. The problem of computer vision for body language is a much harder problem to solve, but we are indeed making progress.

Our guest this week is Paul Kruszewski, an computer science PhD who's spent nearly the last 20 years focused on 3D modeling and artificial intelligence. Today, he's CEO of Wrnch, a Montreal-based AI company focused on reading and understanding human body language.

Paul explains how advances in 3D modeling and computer vision have allowed researchers to get machines to "understand" the posture, movements, and intentions of human being - and he also helps explore the future applications that this technology might have in security, retail, sports, and more.

For more interviews on the applications of AI in business, visit:

TechEmergence.com

Direct download: AI_in_Industry-Paul_Kruszewski-Mixdown.mp3
Category:general -- posted at: 2:37pm PST

In the future, the vast majority of photos and videos recorded won't be seen and used by humans - they'll be seen and used by machines. This week we interview Allan Benchetrit, CEO at Algolux - a Montreal-based AI company focusing on computational imaging.

If you take an image for a human being in a consumer application (maybe an iPhone app or a recreational DSLR camera), you probably want it to be visually appealing and clear to the human eye.

As it turns out, machines don't need pretty images, they need to do their jobs. If a computer vision system needs to detect road signs, or suspicious people in an airport, or the presence of weeds in a cornfield - it may create images that are ugly to the human eye, but perfectly calibrated for being interpreted by machines for their jobs. As it turns out, this is a complicated AI-related problem itself, and Allan walks us through it.

If your business uses cameras heavily - or may do so in the future - this interview will provide an around-the-corner look at what it takes to create effective computer vision applications.

For more expert interviews about the business applications of artificial intelligence, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Allan_Benchetrit-Mixdown.mp3
Category:general -- posted at: 7:55pm PST

Procurement isn't usually seen as a "sexy" aspect of a business's operations. Procurement personnel are responsible for sourcing suppliers or vendors, determining criterion of success, negotiating deal terms, and tracking results and deliverables - all of which could be considered "under appreciated" work. This week, Tamr's Eliot Knudsen walks us through the ways that AI is making it's way into the procurement process, and what it means for the future of this job function.

For more executive interviews about the applications and implications of AI, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Eliot_Knudsen-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 4:23pm PST

This week we speak with Bastiaan Janmaat (CEO and co-Founder of DataFox) about the current and future applications of artificial intelligence in the CRM.

No matter what business you're in, there's a high likelihood that managing relationships with customers, wholesalers, suppliers, or affiliates is important to your daily operations. Artificial intelligence is currently being employed to help with automating data entry, automating email and phone reminders, and even prompting salespeople with the right phone scripts in real time.

In addition to covering "what's being done now" - spend the end of the interview asking Bastiaan about his predictions of the most likely AI-for-CRM capabilities that will become commonplace in the next 5 years.

For more AI executive interviews, and insights into current and future AI trends that are shaking up industries, visit:

www.TechEmergence.com

 

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

Artificial intelligence is coming - should be worried about our jobs? Well, it depends. Our guest Dr. Kevin LaGrandeur spent the last two years researching the impacts of automation and artificial intelligence on society and the job market. In this interview on AI in Industry, we explore the near future of AI's impact on the world of work, and I ask Kevin some important questions, including:

  • What skills are least "automate-able" in the next decade?
  • What middle class professions have the greatest risk of automation, and what should those professionals be doing now to hedge against job loss?
  • What should business leaders be doing now to prepare for "phasing out" work while still taking care of their employees?

For more interviews with AI executives and researchers (and more insight on applying AI in your organization) - visit us online at:

www.TechEmergence.com

Direct download: AI_in_Industry-Kevin_Lagrandeur-Mixdown.mp3
Category:general -- posted at: 1:15am PST

Though we don't think about it on a daily basis - the technologies around us often "work" because of an underlying standard that they depend on. These technologies include: Wifi, ethernet, fax, and much of the internet itself. Do certain AI applications need their own set of standards in order to scale?

Imagine if you needed a new type of cable or input every time you wanted to jack your computer into the wall? Imagine if you needed different hardware to pick up wifi in every location you moved around to? Imagine if all websites had totally different protocols for how they were loaded or served to your computer? If this were the case, it would be extremely challenging for a robust "ecosystem" of internet companies and technologies to emerge, because the technology wouldn't scale or work well at all.

This week we interview Konstantinos Karachalios,‎ Managing Director of the Standards Association at the Institute of Electrical and Electronics Engineers (IEEE). Konstantinos holds a PhD in Physical and previously worked for 25 years at the European Patent Office. He speaks with us this week about the kinds of AI standards that may need to arise in order for AI to be safe and trusted enough to support a business ecosystem.

Konstantinos also speaks to us about some of the current AI standards that IEEE is working on developing currently, and the implications they might have businesses everywhere.

Direct download: AI_in_Industry-Konstantinos_Karachalios-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:19pm PST

It would be great if instead of having our car break down - could have them fixed as soon as the underlying problem began. It would be great if instead of having to diagnose a malfunctioning piece of mechanical equipment - would could have the right "fix" presented to us immediately. As it turns out, artificial intelligence may be working its way to accomplish both of those goals in the not-so-distance future.

This week we interview Tilak Katsuri, CEO of Predii, a predictive maintenance AI company based on Palo Alto. Predii focuses on helping service people by using AI and sensor data to prescribe proper repairs. In this episode, Tilak speaks with us about what's currently possible within the world of "predictive maintenance," as well as the possible ramifications of industrial IoT and AI in the next 5 years.

For more interviews about the real-world applications of artificial intelligence in business, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Tilak_Kasturi-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 7:13pm PST

A huge percentage of digital advertising dollars today go to Google and Facebook, who dominate that sector - and are inevitably central for the future of programmatic advertising. There’s a lot of evidence to suggest that the growth in digital advertising in the last two to three years has gone almost entirely into their coffers. At least for the foreseeable future, Facebook and Google will retain the ability to dominate that space.

The ability to be able to bid for the attention of particular target audiences, whether they’re searching for a specific term, live in a specific place or they like a specific sports team, is something that doesn’t seem to be going away, and seems to be rather efficient, thanks in the large part to Artificial Intelligence.

In this episode we talk to Lior Tasman who is the CEO of PredictiveBid, an Israeli-based predictive advertising optimization start-up. The team focuses on applying AI to some of the bigger issues in programmatic advertising to help draw out more ROI from ads. We discuss some of the challenges of programmatic advertising and what the future of programmatic advertising may look like from an advertiser’s perspective.

For more executive interviews on the applications of AI in Industry, visit:

TechEmergence.com

Direct download: AI_in_Industry-Lior_Tasman-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 10:33pm PST

The big tech giants, such as Amazon, Google and Netflix, tend to set the stage in a lot of different domains and set public expectations to raise the aggregate tide of consumer experience. Our online experience is somewhat different each time we use these and other sites. This is because many of these tech giants alter their experience user per user in a real time iterative fashion in order to create sticky experiences and to beat their competitors.

In this episode we talk to Adam Spector, the Co-Founder & Chief Business Officer at LiftIgniter, a company which provide a service which modulates website experience per users, for an array of different businesses. Adam and I discuss what the tech giants are doing to customize their business experiences, what data they’re using to continually alter user experience and what industries and sectors might be impacted by this aggregate trend as it moves forward.

See more interviews with AI industry innovators at:

www.TechEmergence.com

Direct download: AI_in_Industry-Adam_Spector-Mixdown.mp3
Category:general -- posted at: 12:13pm PST

Imagine you work in a large organization with tens of thousands of employees across multiple countries, a business that’s been around for over a hundred years, and all of a sudden you have people in one department who are interested in applying chatbots, colleagues in another department who wish to implement sentiment analysis and still another department that wants to begin using AI for fraud and risk analysis. How do you manage to put all these pieces together?

That is exactly the situation that Muriel Serrurier Schepper found herself in.  Muriel is the Business Consultant Advanced Data Analytics & Artificial Intelligence at Rabobank Digital Bank in Naarden, Netherlands. In this episode, Muriel and I discuss the Artificial Intelligence Center of Excellence at Rabobank, where she manages projects and has connected ad virtual and physical team across the company which is comprised of over 60,000 employees spread across the world.

For more interviews on the applications of AI in industry, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Muriel_Serrurier_Schepper-Mixdown_v2_1.mp3
Category:general -- posted at: 2:20pm PST

If you work in healthcare, or in an established business that is looking to implement AI for the first time - then this won't be an interview you'll want to miss.

AYASDI is one of those rare AI startups that has raised over $100MM since it's inception in 2008. This week on the "AI in Industry" podcast, Sangeeta Chakraborty of AYASDI breaks down some of AI's important recent applications in the healthcare field. She also explores how hospitals are "modernizing" their processes and systems to include data science and AI applications - and we pick apart those "modernizing" strategies in a way that makes them applicable to nearly any "stodgy" business or industry that is just beginning to implement AI.

For more interviews, research, and case studies on AI in industry, visit:

www.TechEmergence.com

 

Direct download: AI_in_Industry-Sangeeta_Chakraborty-Mixdown.mp3
Category:general -- posted at: 11:12am PST

Marshall Brain discusses how wetware (the human brain) is increasingly becoming a part of a bigger system which may in itself be managed by software systems. The roles and relationships of humans and machines are rapidly changing. With the increasing advances in technology, there are fewer and fewer skills or activities that an enterprise needs from human beings, and they only need those until they can be replaced by software or hardware.

For example, computer vision systems are often still not as effective as the human eye, so we still need human vision systems to recognize text or to recognize object placement, and take action accordingly (in a store, warehouse, or other setting). A human can fill that role as a piece of wetware until the software or the hardware catches up. How will man and machine collaborate in the future? We explore these dynamics in depth in this week's interview.

For more interviews and insights from leading thinkers in AI and automation, visit:

www.TechEmergence.com

Direct download: AI_in_Industry-Marshall_Brain-Mixdown.mp3
Category:Automation -- posted at: 7:31pm PST

Machine learning currently faces a number of obstacles which prevent it from advancing as quickly as it might. How might these obstacles be overcome and what impact would this have on the machine learning across different industries in the coming decade? In this episode we talk to Dr. Hanie Sedghi, Research Scientist at the Allen Institute for Artificial Intelligence, about the developments in core machine learning technology that need to be made, and that researchers and scientists are working, on to further the application of machine learning in autonomous vehicles. We also touch on some of the impact that might be made if machine learning is able to overcome its own boundaries in terms of computational research, in terms of certain algorithms, and what kind of impact that might have in the arena of autonomous driving and in the realm of natural language processing (NLP).

See more episodes online at:

www.TechEmergence.com

Direct download: AI_in_Industry-Hanie-Sedghi-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 8:59pm PST

Fraud attacks have become much more sophisticated. Account takeovers are happening more often. Many security attacks involve multiple methods and unexpected attacks can devastate businesses in just a few days, as we saw with Neiman Marcus and Target. False promotion and abuse is seen not only on social media sites but is also targeted at business. To combat these risks, fraud solutions need to be smarter to keep pace with fraudsters to prevent attacks and react quickly when they do happen. This requires a fast-learning solution with the ability to continually evolve. In this episode we talk to Kevin Lee from Sift Science and examine the shifts in the info security landscape over the past ten or fifteen year. Lee also highlights what new kinds of fraud are now possible and what machine learning solutions are available.

See more episodes at:

www.TechEmergence.com

 

Direct download: AI_in_Industry-Kevin_Lee-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 9:23pm PST

Unlike the field of self-driving cars, the fields of construction, mining, agriculture, and other classes of “heavy industry” involve a huge variety of equipment and use-cases that go beyond traveling from A to B. The heavy industry leaders of today are no farther behind automakers in their understanding that AI and automation will be essential for the future of their companies. In this episode, guest Dr. Sam Kherat discusses the areas in heavy industry where AI is currently playing a role in heavy industry, what type of capabilities and functions are automatable, and at what level. He also shines a light on how AI might affect the future of the industry within the next 2-3 years, and in what ways we can expect large equipment to become more autonomous.

Direct download: AI_in_Industry-Sam_Khera-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:24am PST

Although machine learning in finance is far from new, it is merely at the cusp of a much wider set of applications (in all segments of finance, from insurance to bookkeeping and beyond). Already machine learning has overhauled so many aspects of the financial landscape, from accounting to trading, and it is destined to have more and more impact as it develops further. Guest Alexander Fleiss and his team at Rebellion Research are developing and using AI which uses quantitative analysis to pick investments. Fleiss discusses the current status of machine learning in the world of finance as well as lesser-known niche applications that don’t make headlines - but do make a big impact on how businesses are run. He then goes on to explore the effects of future innovative applications of AI in the financial domain.

Direct download: AI_in_Industry-Alexander-Fleiss-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:34pm PST

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.

Direct download: AI_in_Industry-Will_Jack__Nikhil_Buduma-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 6:46pm PST

If there's any industry ripe for disruption by AI and ML applications, it's healthcare. This week, we speak with ElevenTwo Capital's Founder and Managing Partner Shelley Zhuang, whose investment focus (among other spaces) is on innovative healthcare services. In addition to discussion how AI is helping propel genomics, diagnostics, therapeutic treatment, and other innovations, 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 companies that have been successful in smart preparation 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.

 

Direct download: AI_in_Industry-Shelley_Zhuang-Mixdown.mp3
Category:Emerging Technology -- posted at: 5:03pm PST

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.

Direct download: AI_in_Industry-Ann_Miura-Ko-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 7:20pm PST

Getting an investor's perspective in AI is always a good idea for companies looking to raise money, in terms of understanding of excites VC's, but 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, including the commonalities that matter for any company, in any industry, leveraging these tools that are increasingly embedded with AI. In this episode we interview Polaris Partners' Gary Swart, who speaks about elements of companies that are laying the right foundations for using AI optimally and making a more defensible, durable company in an increasingly competitive landscape.

Direct download: AI_in_Industry-Gary_Sart-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 9:26pm PST

The upsurge of malware and sophisticated attacks continue to keep cybersecurity in the spotlight, but new developments in AI and deep learning offer more advanced solutions to combat security threats. This week, we catch up with Eli David, CTO of Deep Instinct—a company founded in Israel with US headquarters in San Francisco—that applies deep learning to information security. David spoke with us about why and how the deep-learning approach to AI is relevant to the future of cybersecurity.

Companies that are actively building their own security infrastructure, or are in growth mode and know they will eventually need to, should find this interview particularly relevant. David shares his perspective on how and where potential cyberthreats focus their attacks and the resulting ramifications for industries as they look for best ways to respond and prevent attacks.

 

Direct download: TEP-Eli_David-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:00pm PST

One of the most clear insights from our recent consensus in marketing and advertising was that companies who have more digital touch points along the path to conversion—and more conversion in general—have an advantage when applying AI and ML technologies. In this week's episode, Scopely Co-Founder Ankur Bulsara shines a light on this dynamic and describes how gaming companies are taking advantage of digital trails and applying machine learning technologies. We don't cover much gaming on the TechEmergence podcast, so this interview is a bit off the beaten path. Bulsara speaks about how dialed-in and instrumented the mobile gaming environment is and how data is used to leverage higher conversions over time, as well as how Scopely's systems are set in place to ensure success of their business model. We think his insights on how gaming companies leverage higher conversions with (and without) machine learning can serve as an analogy for companies in other industries that are considering how to set in place similar, optimal digital processes over time.

Direct download: TEP-Ankur_Bulsara-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 10:10pm PST

In this episode, we speak with Co-founder and CEO Alex Holub of  Vidora, about how AI can be put to work to improve marketing results. Holub touches on the resources needed—time, money, in-house or outside expertise, calibration, and data— in order to leverage AI in a realistic way. It's safe to say that today, some businesses are not yet set up to be leveraging AI, while others should be seriously considering taking the leap to using machine learning. Holub draws some firm lines as to what kinds of businesses are primed to take advantage of AI, and what it takes to flip the switch and make AI a useful and inspired revenue driver in the marketing domain.

Direct download: AI_in_Industry-Alex_Holub-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 4:35pm PST

I'm always a little shocked when I see how much venture investing goes into the healthcare space, which brings me to the subject of this week's episode: just how the healthcare industry is (and isn't) being impacted by innovations in AI technology. Guest Steve Gullans of Boston-Based Excel Venture Management talks about some of the various healthcare-related ML and AI applications that he sees being brought to light, and touches on which innovations have a better chance of getting blocked and redirected by parties of interest and those that have more promise in being accepted and rolled out sooner. By the end of this episode, listeners will have a more clear picture of practical considerations in healthcare technology adoption, reasons that are often less about quality or potential of the technology and more about clarity on ROI for investors.

Direct download: TEP-Steve_Gullans-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:00pm PST

At TechEmergence, we like to look around the corner at where AI is impacting industries and how people can make better business decisions based on that information. AI and software is an emerging topic of interest to many companies, and in this episode we get a venture capitalist's perspective on where AI will play a vital and necessary role with real results in software and industry.

Jake Flomenberg, a partner with venture capital firm Accel in Palo Alto, shared his insights on how software can integrate AI in intuitive and valuable ways for users. He cites some of the companies that Accel has invested in to illustrate some of the potential software features that may be introduced to the enterprise in the next five years or so. Flomenberg's insights may be useful for anyone building a business or planning to buy a product or service from a software vendor in the near future. If you're interested in getting other founders' perspectives on the feedback and interest shown by investors in their startups, our AI startup consensus on investor sentiment is a good place to start.

Direct download: TEP-Jake_Flomenberg-Mixdown.mp3
Category:Emerging Technology -- posted at: 4:57pm PST

In some ways, investors in AI have to do a lot of what we do at TechEmergence, which is sort through marketing fluff and determine what's actually working and what's more of a pipe dream, as well as what's coming up in the next five years that seems inevitable and what's more likely to flop. In this episode we're joined by Li Jiang, a venture capitalist with GSV Capital whom I was connected with through Bootstrap Labs as a pre-event interview — we'll both be at Bootstrap Labs' Applied AI event in San Francisco on May 11. This week, Jiang speaks about the current areas of AI applications that he sees driving value in business, as well as what technologies he believes will make a long-term impact in terms of automation. His insights on where AI automations are generating cost savings and increased efficiency, as well as what roles might be completely replaced or significantly augmented by AI, are useful nuggets for companies who are thinking through some of their own business processes and are eager to identify low-hanging fruit.

Direct download: AI_in_Industry-Li_Jiang-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 10:43pm PST

As it turns out, survival of the fittest applies as much to algorithms as it does to amoebas, at least when we're talking about genetic algorithms. We recently interviewed Dr. Jay Perrret, CTO of Aria Networks, a company that uses genetic algorithm-based technology for solving some of industry's toughest problems, from optimization of business networks to pinpointing genetic patterns correlated with specific diseases. Dr. Perrett has been working for years in this domain, testing algorithms that use variations of parameters in order to gradually arrive at a best result, when there's no simple way to program a solution. In this episode, Dr. Perrett discusses how genetic algorithms (GA) work and ways that they can be tested and applied in a business context. He provides two very useful case studies, including a recent example with Facebook that involved planning out an optimal (and massive) data network.

 

Direct download: TEP-Jay_Perrett-Mixdown.mp3
Category:general -- posted at: 7:37pm PST

Getting beyond the marketing and jargon on the homepage of AI companies and figuring out what's actually happening, what results are being driven in business, is part of our job at TechEmergence. Shaking those answers out of founders is not always easy, but we didn't have to do much shaking with Yohai Sabag, chief data scientist for Optimove, a marketing AI and automation company in Israel. In this episode, he speaks about what humans are needed for in the optimization process, and what facets can be automated or distributed to a machine. Sabag gives an excellent walk-through of how marketers can use the "human-machine feedback loop" to optimize individual campaigns at scale.

 

Direct download: TEP-Yohai_Sabag-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:00pm PST

You might be aware that some of the articles online about sports or financial performance of companies are article written by machines; this machine learning-based technology is the burgeoning field of natural language generation (NLG), which aims to create written content as humans would—in context— but at greater speed and scale. Yseop is one such enterprise software company, whose product suite turns data into written insight, explanations, and narrative. In this episode we interview Yseop's Vice President Matthieu Rauscher, who talks about the fundamentals of natural language generation in business, and what conditions need to be in place in order to drive key objectives. Rauscher also addresses the difference between discover-oriented machine learning (ML) and production-level ML, and why different industries might be drawn to one over the other.

Direct download: TEP-Matthieu_Rauscher-Mixdown.mp3
Category:machine learning -- posted at: 8:00pm PST

There is in fact a dark side to AI, although we’re certainly not at the point where we need to fear terminators, but it’s certainly been leveraged toward malicious aims in a business context. In data security, tremendous venture dollars are going into preventing fraud and theft, but this same brand of technology is also being use by the “bad guys” to try and steal that information and break into those systems. In this episode, I speak with Justin Fier, director of cyber intelligence at Dark Trace, who speaks about the malicious uses of AI and how companies like Dark Trace have been forced to fight these “AI assailants”.

Direct download: TEP-Justin_Fier-Mixdown.mp3
Category:Cyber Security -- posted at: 5:00pm PST

Most of our recent investor interviews have been Bay area investors, like Accenture and Canvas, and we don't usually get to speak with investors overseas, particularly in Asia. This week, however, we interviewed Tak Lo, a partner with Zeroth.ai, an accelerator program and cohort investing firm based in Hong Kong and focused on startup artificial intelligence (AI) and machine learning (ML) companies. Lo speaks about when he saw AI take off in China and the differences in that rise compared to the U.S. He also gives valuable insight on consumer differences in how the two populations interact with technology, and how these differences in the Asian market drive different business opportunities in China than in the U.S.

Direct download: TEP-Tak_Lo-Mixdown.mp3
Category:Startup Funding -- posted at: 5:51pm PST

If you're going to apply machine learning (ML) in a business context, you need a lot of data, and algorithms across the board perform better with more recent, rich, and relevant data. Today, there are companies whose entire business models are predicated on helping others make sense of and use of this type of information. In this episode, we speak with the CTO and Co-Founder of one such company—Palo Alto-based Cloudera. CTO Amr Awadallah, PhD, speaks with us this week about where he sees "data lakes" (or "data hubs", Cloudera's preferred term) and warehouses play an important role in ML applications in business. Based on his experiences helping a variety of companies in many countries set up data lakes, Amwadallah is able to distill and communicate these uses in three broad categories that apply across industries as companies look to solve tougher problems and ask more complex questions using unstructured data.

Direct download: TEP-Amr_Awadallah-Mixdown.mp3
Category:machine learning -- posted at: 7:55am PST

One facet of business that nearly any industry has in common is the need to stay on top of news in their respective market, including competitor strategies or understanding changes in news related to the field. Media monitoring is a domain that machine learning (ML) is well suited for, with it's ability to coax out headlines, contextual information, and financial data from the seemingly endless stream of social, blog, and other information on the web today. Signal is a company that uses ML specifically for these purposes. In this episode, we speak with Signal Media's Chief Data Scientist and Co-founder Dr. Miguel Martinez, who dives into real business use cases illustrating the use of machine learning for media monitoring across industries.

 

Direct download: TEP-Miguel_Alvarez-Mixdown_v2.mp3
Category:machine learning -- posted at: 6:30pm PST

What does it mean to tune an algorithm, how does it matter in a business context, and what are the approaches being developed today when it comes to tuning algorithms? This week's guest helps us answer these questions and more. CEO and Co-Founder Scott Clark of SigOpt takes time to explain the dynamics of tuning, goes into some of the cutting-edge methods for getting tuning done, and shares advice on how businesses using machine learning algorithms can continue to refine and adjust their parameters in order to glean greater results.

Direct download: TEP-Scott_Clark-Mixdown2.mp3
Category:machine learning -- posted at: 5:00pm PST

In this episode, recorded live at Canvas Ventures in Portola Valley, I speak with Ben Narasin, a partner with Canvas and an avid venture investor in AI and ML companies, some of which we've interviewed (Crowdflower and Mulesoft), along with many others that we haven't (like Siri). Ben doesn't look for AI to invest in; instead, he looks for companies to invest in, a subtle but important difference in a business world increasingly caught up in the explosion of AI and ML technologies.

From investments in Nuance to more recent one such as Houzz, Narasin has solid ideas as to what makes an investment interesting when AI is involved, what might actually add value to a model with AI, and what's wholly irrelevant when it comes to overall business model. Besides making important distinctions on where investments can make a return and how to raise money for your AI startup, this interview is also chock full of great analogies (give me golden dragons all day long—anyone?)

Direct download: TEP-Ben_Narasin-Mixdown.mp3
Category:Startup Funding -- posted at: 5:00pm PST

There’s been lot of hype around AI and ML in business over the past five years. Even among investors exist a lot of misconceptions about using ML in a business context, and how to get up to speed on and grasp and understand leveraging related technologies in industry. Recently, I talked with Benjamin Levy of BootstrapLabs in San Francisco, who I met through an investment banking friend in Boston.

BootstrapLabs invests in Bay area companies, and Levy also travels around the world speaking about investing in AI companies and raising funds for new ventures. In this episode, Levy gives his perspective on what investors and executives get wrong about ML and and AI, and discusses how they can get up to speed on the applications for these technologies and leverage them and related expertise to really make a difference (i.e. increased ROI) in their businesses.

Direct download: TEP-Ben_Levy-Mixdown.mp3
Category:Startup Funding -- posted at: 6:52am PST

Uday Veeramachaneni is taking a new approach to machine learning in infosecurity, AKA infosec. Traditionally, infosec has approached predicting attacks in two ways: through a system of hand-designed rules, and through anomaly detection, a technique that detects statistical outliers in the data. The problem with these approaches, Veermachaneni says, is that the signal-to-noise ratio is too low. In this episode, Veermachaneni discusses how his company, PatternEx, is using machine learning to provide more accurate attack prediction. He also discusses the cooperative role of man and machine in building robust AI applications in data security and walks us through a common security attack scenario.

Direct download: TEP-Uday_Veeram-Mixdown.mp3
Category:machine learning -- posted at: 8:00pm PST

When it comes to finding an expert on interviewing and finding machine learning (ML) talent, Parshu Kulkarni may just be the guy to ask. Not only is Kulkarni one of a small subsegment of the global population with an advanced degree in data science who has also been hired to work in tech companies like eBay, but he's been on the unique side hiring of ML and AI talent. Today, Kulkarni works full-time as Head of Data Science at Hired, Inc., a giant platform for hiring top talent in tech and other areas. In this episode, he provide an interesting distinction between what individuals with experience in data science look for in potential hires versus those who do not have the tech background tend to look for, and also dives into the supply-and-demand landscape for data scientists now and in the future—an interesting interview for anyone looking to hire or be hired in the ML and AI space.

Direct download: TEP-Parshu_Kulkarni-Mixdown.mp3
Category:machine learning -- posted at: 5:00pm PST

In marketing, there are lots of applications in AI and machine learning (ML), from recommendation engines to predictive analytics and beyond. At the company Adgorithms, there are even more ambitious projects underway - like automating the process of marketing altogether by having a machine run and generate ads, or test and spend the marketing budget of a company. Or Shani, CEO of Adgorithms, focuses on the quantitative aspects and optimization of online advertising, using algorithms to improve advertising processes. In this interview, Shani talks about how Adgorithms' smart marketing platform "Albert" meshes with humans’ role in marketing, and also discusses how these roles might change over the next 5 to 10 years as we move towards ever more automated marketing processes.

Direct download: TEP-Or_Shani-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:57pm PST

Not all knowledge work can be crunched by a program, but there are some hard-to-automate business processes that a select few entities are making an attempt to automate now. Boston-based Rage Frameworks, Inc. is one such company, and in this episode we speak with Senior Vice President (SVP) Joy Dasgupta about specific applications of automation technologies applied to white collar environments. Rage Frameworks has developed intelligent machines that have been able to take over process that, prior to the emergence of AI and automation technologies, would have required thousands of people to accomplish. These developments are a microcosm of what is to come, and the process is not without its ethical considerations (as discussed in a previous interview with Yoshua Bengio). But Dasgupta's insights provide a concrete glimpse into how these processes are being automated in the knowledge workplace today and what that might mean or look like decades from now.

Direct download: TEP-Joy_Dasgupta-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 9:54pm PST

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