Artificial Intelligence in Industry with Dan Faggella (general)

This week’s episode of the AI in Industry podcast focuses on two main questions. First, how should business leaders determine the most fruitful, potential applications of AI in their business? Second, how do they choose the right one into which to invest resources?

This week, we interview someone who has spoken with a number of CTOs and CIOs about early adoption strategies for machine learning for customer service, marketing, manufacturing and other applications. He is Madhusudan Shekar, Principal Evangelist at Amazon Internet Services.

See the full interview article here: www.techemergence.com/how-to-determine-the-best-artificial-intelligence-application-areas-in-your-business

Direct download: AI_in_Industry-Madhusudan_Shekar_-Mixdown.mp3
Category:general -- posted at: 12:40pm PDT

At TechEmergence, we often talk about the software capabilities of AI and the tangible return on investment (ROI) of recommendation engines, fraud detection, and different kinds of AI applications. We rarely talk about the hardware side of the equation, and that will be our focus today. For hardware companies like Nvidia, stock prices have soared thanks to the popularity of new kinds of AI hardware being needed not only in academia but also among the technology giants. Increasingly, AI hardware is about more than just graphics processing units (GPUs).

Today we interview Mike Henry, CEO of Mythic AI. Mike speaks about the different kinds of AI-specific hardware, where they are used, and how they differ depending on their function. More specifically, Mike talks about the business value of AI hardware. Can specific hardware save money on energy, time, and resources? Where can it drive value? Where is AI hardware necessary to open new capabilities for AI systems that may not have been possible with older hardware? What is the right business approach to AI hardware?

This interview was brought to us by Kisaco Research, which partnered with TechEmergence to help promote their AI hardware summit on September 18 and 19 at the Computer History Museum in Mountain View California.

See the full interview article here:

www.techemergence.com/financial-roi-ai-hardware-top-line-bottom-line-impact

Direct download: AI_in_Industry-Mike_Henry-Mixdown.mp3
Category:general -- posted at: 1:24pm PDT

Episode Summary: Facebook and Google’s advertising complex is founded on machine learning, allowing people to self-serve their data needs across a broad audience. India-based InMobi is a company in the advertising technology space that delivers 10 billion ad requests daily.

Today, we speak with Avi Patchava, Vice-President of Data Sciences and Machine Learning at InMobi, which operates in China, Europe, India, and the US. Patchava explains how machine learning plays a role in appropriately matching advertising requests to the right audience at scale,  whether on mobile, desktop or different devices and media. Patchava paints a robust picture of what this technology will look like moving forward and how it will change the game for marketers and advertisers, especially with the emphasis on data and machine learning.

See the full interview article here:

www.techemergence.com/future-advertising-machine-learning-audience-targeting-reach

Direct download: AI_in_Industry-Avi_Patchava-Mixdown.mp3
Category:general -- posted at: 4:22pm PDT

This week, AI in Industry features Jeremy Barnes, Chief Architect at Element AI. Jeremy talks about the common mistakes some businesses might make while adopting AI to solve broad business problems. He also sheds light on the problem areas that could raise the market value of businesses through AI adoption, hiring the right talent with the right combination of subject matter expertise and business experience, and the business and technical aspects executives should consider before contemplating the adoption of AI.

For more insights on the B2B applications of AI, go to techemergence.com

Direct download: AI_in_Industry-Jeremy_Barnes-Mixdown.mp3
Category:general -- posted at: 12:00am PDT

This week, AI in Industry features Dr. David Franke, Chief Scientist at Vast. David talks about how AI can work with scarce transaction data to derive meaningful analytics for big purchases, such as cars and houses. He elaborates on how the AI can glean information from user interaction and marketplace data to provide customers with the relevant product fit, deals and recommendations on big purchases. He also discusses the future trends and business benefits for early adopters of AI for purchase recommendations of high-cost items. 

For more insights on this topic, go to www.techemergence.com

 

Direct download: AI_in_Industry-David_Franke-Mixdown.mp3
Category:general -- posted at: 11:30pm PDT

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 PDT

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 PDT

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 PDT

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 PDT

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 PDT