Artificial Intelligence in Industry with Dan Faggella

This week we speak with CEO and Founder of Nexar Inc., Eran Shir, whose company has created a dashboard app that allows drivers to mount a smartphone, which then collects visual information and other data, such as speed from your accelerometer, in order to help detect and prevent accidents. The app also serves as a way to reconstruct what happens in a collision - a unique solution in a big and untapped market. In this episode, Shir gives his vision of a world where the roads are filled with cyborgs, rather than autonomous robots, i.e. people augmented with new sensory information that trigger notifications, warnings or prompts for safer driving behavior, amongst a network of cloud-connected cars.  He also touches on what the transition might look like in response to the question - when will autonomous cars be mainstream?

Direct download: TEP-Eran_Shir-Mixdown.mp3
Category:Robotics -- posted at: 5:00pm PDT

In this episode, we speak with Senior Editor for the Economist in digital and data products and Co-author of "Big Data: A Revolution that Will Transform How We Work, Live and Think", Kenneth Cukier, who speaks on the technologies that underlie big data and make it what it is today. Cukier addresses common misconceptions about machine learning and dives into how companies can catch up with this technology by thinking through, assessing ROI, and making sense of the dynamics of big data. Listen for Cukier's apt analogy in comparing machine learning technology to the dynamics of computing from decades ago.

Direct download: TEP-Kenn_Cukier-Mixdown.mp3
Category:Big Data -- posted at: 5:00pm PDT

What are executives missing the boat on and what do they need to think about when it comes to AI and ML? This week, we speak with John Straw, who has had a number of businesses in the UK and US, currently a senior advisor to McKinsey & Co., and who works with a lot of executive teams in terms of finding new applications for AI and finding ROI for those technologies in industry. We speak this week about how executives can get up to speed, what degree of knowledge and in what way they should learn it so they can find opportunities in their own companies. Straw also touches on what he sees as the biggest areas of oversight, in terms of preventing companies from finding those applications that can keep them up to speed with competitors and the big technology players.

Direct download: TEP-John_Straw-Mixdown.mp3
Category:machine learning -- posted at: 5:41pm PDT

In many ways, AI and finance are made for each other. Machine learning and other techniques make it easier to identify patterns that might otherwise not be detected by the human eye, and finance is quantitative to begin with so that it’s hard not to find traction. Financial firms have also invested heavily in AI in the past, and more are starting to tap into the financial applications of machine learning (ML) and deep learning. This week, we’re joined by CEO and Co-founder of Kavout Alex Lu, whose company offers AI trading applications for enterprises and individuals. Lu speaks today about the kinds of patterns that traders now have access to in finance, and he gives examples of ways Kavout and other institutions are using artificial intelligence in stock trading to build better and more personalized products and services.

 

Direct download: TEP-Alex_Lu-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:30pm PDT

Market research and trends is important when discussing AI and business, but it's also worthwhile to contemplate the ethical and social implications further down the line. How will countries deal with potential unemployment problems? How might countries collaborate to hedge against the risks that AI poses to the future of work and other economic facets? A relatively small group is helping people do just that i.e. getting organizations and countries to think through how they could hedge against the grander risks inherent in a world powered by AI.

In this episode, we speak with Jerome Glenn, head of the Millennium Project, an initiative that focuses on research implementing the organizational means, operational priorities, and financing structures necessary to achieve the Millennium Development Goals or (MDGs). Glenn talks about how he gets principalities of the world to bring their big industrial players and the public to talk through possible scenarios that are 30, 40, even 50 years in the future, and about ways we might potentially hedge against risks and make the most of the upsides of AI in a global economy.

Direct download: TEP-Jerome_Glenn-Mixdown_1.mp3
Category:Artificial Intelligence -- posted at: 12:09pm PDT

A medium-size business with a $20m marketing budget can run into issues when aiming to track an attribute, what marketing dollars brought in customers, etc. But when you're managing $90B for customers all over the world and working in every conceivable channel, things get all the more complicated. Josh Sutton, global head of Data and AI at Publicis.Sapient, speaks in this episode about the future of advertising attribution with machine learning. Specifically, Sutton discusses how his team of publicists is working on managing, tracking, and determining cohorts and attribution across more channels and numerous clients, and touches on ways that the company is applying ML to make sense of marketing data and spend marketing dollars more effectively.

Direct download: TEP-Josh_Sutton-Mixdown.mp3
Category:machine learning -- posted at: 6:12pm PDT

I remember reading an article in Scientific American years ago about a poster of a person looking in the direction people sitting in a school dining room, and that this poster would make people sitting in the dining room less likely to litter. This seems like an absurd example of holding people accountable for their actions, but as it turns out, there are a lot more serious consequences to ensuring behavior change through observation, and one area where this matters is medicine.

Today, there’s a major issue with people who don't adhere to their medical regimens, only to relapse or experience more serious symptoms later on. This week's guest, Cory Kidd, CEO of Catalia Health and known for his work at MIT on human-robotic interaction, is working to help solve this problem by developing a robot that adds some of that physical presence and accountability. This is likely one of many novel medical AI applications that we're likely to see roll out in healthcare over the next decade.

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

Today's episode is about continual learning, a focus of Cogitai, a company dedicated to building AI's that interact and learn from the real world. Cogitai's Cofound and CEO Mark Ring talks about the differences between supervised and reinforcement, and how Cogitai intends to take reinforcement learning in the direction of continual learning. Ring also touches on where he sees an opportunity for applying continual learning in domains like vehicles, consumer apps, etc., and improving abstract levels of understanding by machines.

 

Direct download: TEP-_Mark_Ring-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 8:59pm PDT

There’s not that many serial tech entrepreneurs in the legal space, but Gary Sangha is one of them. Sangha is CEO and founder of Lit IQ, which is applying machine learning and computational linguistics to legal documents to help lawyers avoid making drafting mistakes. In this episode, Sangha talks about where this type of software is most useful and legitimate, what the legal landscape in relationship to machine learning may look like in the next few years, and how this technology may apply across industries.

Direct download: TEP-Gary_Sangha-Mixdown.mp3
Category:natural language processing -- posted at: 5:00pm PDT

OpenAI's Ilya Sutskever on Preparing for the Future of Intelligence

Some organizations are leveraging artificial intelligence (AI) to help the world with research, some to help companies with marketing, and some are intent on ensuring that the future of AI doesn’t result in the end of humanity. Theres’a good likelihood that if you're reading this interview, that you're already familiar with OpenAI, an organization with the sole purpose of ensuring that the future of man and machines is a friendly one, and that the concentration of power and intelligence isn’t centralized in a way that would make AI a dangerous tool. In this episode, we speak with Ilya Sutskever, research director for Open AI. This was a fun but frustrating interview; Sutskever held his cards close to his chest, but we gain some perspective on what he considers to be areas of importance regarding the future of AI and considerations for safely furthering advances in the field.

Direct download: TEP-Ilya_Sutskever-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:23pm PDT

Future Applications of Machine Vision - an Interview with Cortica's CEO

Right now, you can take a picture of a flower in your garden and post it on social media to see if anyone knows its proper name. Wouldn’t it be nice, though, if a machine could identify the correct name and species in the picture you just took? Solving this problem in applications of machine vision is something that CEO Igal Raichelgauz and his team are working on at Cortica, a machine learning company that is not focused on deep learning, but is instead taking a more "shallow" approach. In this episode, Raichelgauz articulates Cortica's approach, which is based on neurology and goes against some of the current approaches in getting machines to learn. We discuss some of these primary differences and dive into Cortica's goals for applying machine vision in consumer products.

Direct download: TEP-Igal_Raichelgauz-Mixdown.mp3
Category:computer vision -- posted at: 5:00pm PDT

What is a GPU, and How Are Companies Using Them Now?

This week’s guest is Kimberly Powell, senior director of business development at NVIDIA. In an interview conducted at the 2016 AI Summit in San Francisco, Powell spoke with TechEmergence about GPUs and the factors that are making them easier to use, how Nvidia and others are working to make this technology more accessible to small businesses and startups, and about some of Nvidia’s and other similar players' innovations in the deep learning field.

Direct download: TEP-Kimberly_Powell-Mixdown.mp3
Category:Deep learning -- posted at: 7:51pm PDT

Accenture's CTO on: The Economic Impact of Artificial Intelligence

Accenture is a pretty large company in the tech space, providing services to many of the Fortune 500 and global equivalents. They recently conducted a study of their own, combined with expertise from economists and AI researchers, about the longer-term economic impact of artificial intelligence on economies around the world. In this episode, I speak with Chief Technology Officer Paul Daughtery, who has been with Accenture since 1986, who was joined by Global Technology R&D Lead Marc Carrel-Billiard. We met up at a coffee shop after an AI Summit in San Francisco, and I asked Paul and Marc about what they had learned from this newly-published study and what they consider to be the significant impacts of AI and automation on the future job market.

Direct download: TEP-Paul_Daughtery-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 9:29pm PDT

Crowdsourcing a Machine Learning Hedge Fund

Crowdsourcing is a relatively common term in technical vernacular today. Even if you're not a self-identified "techie", you may very may well have leveraged crowdsourcing in journalism, the sciences, public policy, or elsewhere. One area in which this concept hasn’t really taken off  is in finance and hedge funds. In this episode, we speak with Richard Craib, founder of Numerai, about the company's model for pooling data science talent, using "anonymous" models to train financial data, and competing against one another, in which winners are rewarded in bitcoin to exchange through virtual markets. Craib speaks about his overarching vision for the company, and also delves into the past, present, and future of AI applications in finance.

Direct download: TEP-Richard_Craig-Mixdown.mp3
Category:fintech -- posted at: 5:00pm PDT

When Will Chatbots Reach Human Level Sophistication?

What does the world look like when we can replicate human expertise in an assistant? Are we close to developing human-level chatbots that we can ask about law or medical conditions? We dive into this topic with Founder and CEO of exClone Dr. Riza Berkan, whose personal assistant and chat-bot company is leveraging day-to-day human conversational templates in machine learning technology in order to better approach the tough task of replicating human expertise through a machine. Berkan talks about the edge layer of his company's “secret sauce”, and touches on the future applications of what might manifest in this field in 5 to 10 years in medical and other consumer applications.

Direct download: TEP-Riza_Berkan-Mixdown.mp3
Category:natural language processing -- posted at: 5:00pm PDT

Deep Learning Applications for Enterprise with Skymind’s Chris Nicholson

In one of our most recent consensus, we took a close look at future trends in artificial intelligence consumer applications, but it's also interesting to see what’s happening now in businesses. Chris Nicholson is the CEO of Skymind.io, which offers deep learning applications that integrate with Hadoop and Spark. In this episode, Nicholson sheds light on current trends that he sees across industries and best practices for implementing AI solutions to gain consistent return on investment.

Direct download: TEP-Chris_Nicholson-Mixdown.mp3
Category:Deep learning -- posted at: 12:18pm PDT

Shopify's Kit - The AI Personal Marketing Assistant

We've interviewed a number of guests on TechEmergence, but very few who have had a serious part of their career in selling automobiles. But Michael Perry did just that for 5 years before founding Kit, his third startup - an AI application that works in marketing for small businesses and was acquired by Shopify in April 2016. In this episode, Perry speaks about how Kit and Shopify leverage AI on a daily basis, and how a “non-tech” person with no formal background in AI or data science can build a team  for an AI project. 

Direct download: TEP-Michael_Perry-Mixdown.mp3
Category:general -- posted at: 5:00pm PDT

Martin Ford on the Rise of Workforce Automation

Martin Ford started off as a software entrepreneur in Silicon Valley, but became better known for his speaking and writing on robotics' and automation's influence on the job market after writing his best-selling book, Rise of the Robots: Technology and the Threat of a Jobless Future. In this episode, Martin talks about why he believes 'white collar' jobs (as opposed to blue) are at a higher risk for automation, and gives his predictions on how automation and robotics will impact the job market over the next 5 to 10 years.

Direct download: Martin_Ford.mp3
Category:Automation -- posted at: 5:00pm PDT

Scaling Virtual Assistant Services for Enterprise

As Senior Director and World Wide Head of the Cognitive Innovation Group at Nuance Communications, Mark Hanson works on bringing Nuance lab innovations to business applications, with the guiding goals of  improving customer experience and business efficiency. In this episode, Hanson speaks about natural language processing (NLP), where he believes this technology is headed in the future and where it's driving value now, and how companies are applying NLP in Silicon Valley and elsewhere.

Direct download: TEP-Mark_Hanson-Mixdown.mp3
Category:natural language processing -- posted at: 1:33pm PDT

Human Resource Management Meets Predictive Analytics

How do you know if you’ve made the right decision for a hire? Often, employers go off gut instinct and make a decision retrospectively, but it turns out AI might be able to help out in human resource management through shedding light on best hiring decisions. In this episode, Pasha Roberts, chief scientist at Talent Analytics, tells us about how his company is working on helping companies make better decisions before they hire by applying machine learning and artificial intelligence to various data points on a given applicant, including information from aptitude tests that may help predict not only performance but retention.

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

Zillow: Data-Driven Real Estate Appraisals at Your Fingertips

Big data is often a buzz word, but if you're trying to quantify data around homes in the U.S. and pair that with hard to quantify information  - like images - you're likely running into the frontiers of machine learning technology. This is something Zillow deals with daily. In this episode, Stan Humphries, chief analytics officer and economist for Zillow, speaks about where they're leveraging machine learning and artificial intelligence (hint: almost everywhere), and what he believes are the keys for deriving real ROI opportunities using this technology. Humphries also offers insights for how other companies can model the successful decision-making processes and implementation strategies used by Zillow.

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

Network Intrusion Detection Using Machine Learning

When Google’s DeepMind won against one of the best modern Go champions, is used multiple AI approaches and exposed gaps in some individual strategies. This even has shed more light on AI, but also on the utility in combining approaches to AI for individual problems. Data security is one of these problem areas where multiple AI approaches is being used to make our information safer. Dr. Sal Stolfo has been a professor at Columbia in Computer Science since 1972 and is now also the CEO of Allure Security, with a focus on engineering network intrusion detection solutions using AI applications. In this episode, Stolfo talks about the various styles of AI and statical methods that have been and are being used to detect malicious activity, as well as how he believes the future of security is going to have to adapt as increasing amounts of data become available.

Direct download: Sal_Stolfo_New.mp3
Category:Cyber Security -- posted at: 5:00pm PDT

MuleSoft's CTO Envisions Connected Machine Learning Network

This episode's guest is Uri Sarid, CTO at Mulesoft. Sarid speaks about where he believes the future of machine learning (ML) applications in industry might go - he thinks applications might stay small and niche-based, and will develop based on how well they each serve their individual purposes. He also speaks on his belief that companies will get used to dealing with disparate ML technologies and that finding ways to connect these technologies will be an important path for future trends in technology development.

Direct download: Uri_Sarid.rtf
Category:machine learning -- posted at: 5:00pm PDT

Could Swarm Intelligence Be Used to Teach AI?

It isn’t by chance that birds fly in flocks and fish swim in schools -  they’re actually smarter when they act in a group. Could it be possible to extend that collective intelligence to human beings, and even AI? Louis Rosenberg is a PhD from Stanford, previously founder of Immersion and who now runs Unanimous AI, a company focusing on harnessing swarm intelligence with human beings. In this episode, Rosenberg speaks about how this collective-intelligence approach has been applied to human beings in terms of garnering improvements in a range of predictions, and he also touches on what this type of swarm intelligence might mean when we talk about multiple AI’s in the future.

Direct download: Louis_Rosenberg.mp3
Category:Artificial Intelligence -- posted at: 5:00pm PDT

How Companies Can Get Started Using Machine Learning for Business

Predictive analytics and machine learning are all the rage in Silicon Valley, but how do companies actually derive value by leveraging these technologies? We asked this question to Dr. Ronen Meiri, CTO and Founder of DMWay, a predictive analytics and machine learning platform company based in Israel. In this episode, Ronen speaks about what his company does and how smart executives are starting to make decisions how to choose and decide on the a smart, user-friendly platform that fits their business' needs.

Direct download: TEP-Ronen-Meiri-Mixdown_1.mp3
Category:machine learning -- posted at: 7:27pm PDT

The Business Value of Unstructured Data - with LoopAI Chief Scientist Patrick Ehlen

Our guest in this episode has spent a large part of his life on figuring out how to make machines more intelligent. LoopAI Chief Scientist Patrick Ehlen has worked on a number of important projects, from DARPA projects to big-company AI solutions at places like AT&T. LoopAI works on getting AI to make sense and meaning of unstructured text, and Ehlen talks about the potential business applications for this technology and where it's making way its way into industry. Ehlen also touches on the implications for developers in the nascent AI field - like LoopAI - that are vying to implement its technology as an industry standard, and how such organizations will have to market themselves and deliver services to develop a thriving AI ecosystem.

Direct download: Patrick_Ehlen_Finished.mp3
Category:Artificial Intelligence -- posted at: 4:00pm PDT

This week's guest is Senior Vice President of SPARK, an economic development organization dedicated to getting startups and other early-stage companies off the ground in Ann Arbor. Skip Simms speaks on how to convey complex technologies to investors who don’t necessarily have your technical expertise, and still close the deal and get the investment. Simms talks about companies he’s seen do this well (and not so well), and how aspiring companies can do a better job of convincing investors to get in on new or unfamiliar technologies, something many AI company founders will have to deal with in some shape or form in launching a new entity.

 

Direct download: Skip_Simms_Mixed.mp3
Category:Angel Investment -- posted at: 5:00pm PDT

Why Big Data in Business Still Needs Human Intuition

For some companies, big data remains an abstraction; for others, it's an integral part of the lifeblood of a business. Mat Harris is vice president at Sojern, a travel marketing platform that has leveraged big data to grow $3 billion in bookings and 1/3 of a billion traveler profiles across its platform. In this episode, Harris speaks about how Sojern and other businesses are using a combination of their data and other sources of data (what he calls third and "second" data sources) in order to make informed marketing decisions and better market their services to buyers. Harris sheds light on the direct ROI for big data in different businesses, and it's an interesting episode from the perspective of an executive who is using big data to make decisions on business directions.

Direct download: Mat_Harris_Mixed.mp3
Category:Big Data -- posted at: 11:50am PDT

Investing in Artificial Intelligence - With Motus Ventures' Robert Seidl

Companies looking to raise money are often asking what investors think of their company, their industry, and how they're making investment decisions in related companies. In this episode, I ask these questions of Robert Seidel, who is managing partner of Motus Ventures, an investment firm focusing on autonomous Vehicles and the IoT. Seidl talks about various data sources and the people and networks from which investors draw information when they don’t have what they need on-hand and need to make important investment decisions. He also shares his perspective on the high-energy and competitive investment world of AI, including his thoughts on the most exciting (and confusing) areas in the industry.

Direct download: Robert_Seidl_Mixed.mp3
Category:Artificial Intelligence -- posted at: 4:23pm PDT

The Future of Chatbots and Personal Assistants at Nuance's AI Lab

This week's interview was recorded live at Nuance's Silicon Valley office with guest Charlie Ortiz, director of the AI and Natural Language (NL) Processing Lab for Nuance Communications in Silicon Valley. In this episode, Ortiz speaks about what he sees as the most important developments in natural language processing (NLP) over the last few years, what advancements brought us to where we are today, and where progress might take NLP in the coming years ahead (both at Nuance and beyond).

Direct download: Charlie_Ortiz_Mixed.mp3
Category:natural language processing -- posted at: 5:00pm PDT

Comet Labs' Saman Farid - An Investor's Take on the AI Landscape

Fifteen years ago, investing in AI may have seemed a bit far-fetched, but today it's not at all a rare occurrence; however, it's more rare to find entire firms dedicated to investing entirely in AI. In today's episode, we're joined by Saman Farid, co-founder of Comet Labs, an investment firm focused on investment in AI companies across industries. He speaks about his investment hypothesis in the future of AI, why he’s decided to hone his funds in this domain, and the different domains where he believes AI is ripe to disrupt on a global level in the coming few years.

Direct download: Saman_Farid_Mixed.mp3
Category:general -- posted at: 5:00pm PDT

DeepMind's Nando de Freitas - Why Deep Learning is Like Building with Legos

One of the most memorable moments from this interview is when our guest mentioned that Larry Page hired him to solve intelligence; very few people can say this, and this says something about today’s guest, Dr. Nando de Freitas - a senior researcher at Google and professor at Oxford - as well as the gravity of his present work. Today, I speak with Nando about a topic well known through his research at Google, deep learning. de Freitas gives his perspective on the basics of deep learning, the applications in conversational interfaces and recognizing images and videos, and what the future of this technology might look like in the nearer future.

Direct download: Nando_De_Freitas_Mixed.mp3
Category:Deep learning -- posted at: 5:00pm PDT

Your.MD's CEO on the Future of AI in Medicine

In this episode, we speak with Dr. Matteo Berlucchi, the founder of Your.MD, which uses artificial intelligence to create one of the first personal health assistant platforms in 70+ countries. Berlucchi talks about the challenges in making an AI do what you want, specifically helping people self diagnose and seek proper treatment. He discusses the multiple approaches to AI that are blended together in order to yield optimal results, and touches on the sometimes stark differences between what AI can do in the lab versus the functional application for tens of thousands of people. If you're interested in the diverse applications of AI and the challenges in running a startup, Dr. Berlucci's makes for an interesting episode.

Direct download: Matteo_B.mp3
Category:Artificial Intelligence -- posted at: 5:29pm PDT

Sumo Logic CTO - How Machine Learning Shines Light on Business Blind Spots

CTO and Co-founder of Sumo Logic Christian Beedgen gives his take on how to glean return on investment from applying machine learning to companies. There are o easy answers, but Beedgen boils down simple concepts for thinking about humans thinking through causation, machines working out correlations, and how the combination of the two can glean us better ideas and get to answers faster than humans could do alone.

Direct download: Christian_Beedgen_Mixed_1.mp3
Category:machine learning -- posted at: 5:00pm PDT

Lucid VR’s CTO Talks Machine Learning for Virtual Reality

Artificial intelligence (AI) and virtual reality (VR) are often seen as different trends, but there is a lot of overlap in these areas, where you might not expect. Lucid VR's CTO Adam Rowell speaks today about how AI plays a role in making VR work, augmenting the accuracy of images and making a more immersive and convincing experience for users. Rowell also touches on non-gaming VR apps that he and his company are excited about launching in the future.

Direct download: Adam_Rowell_Mixed.mp3
Category:Virtual Reality -- posted at: 5:00pm PDT

How Machine Learning Shapes Your eBay Experience

At Facebook headquarters, I learned there are 1 billion active users every month. In a more recent interview at eBay headquarters in San Jose, l learned that the well-known digital store has over 1 billion products for sale. eBay is, without a doubt, the world’s largest marketplace, and there’s enough incoming data to keep a large team of data scientists busy for years. I speak with Zoher Karu, eBay’s chief data officer, about how eBay leverages data and machine learning to create a better experience for its customers and also their sellers, shedding light on important lessons for anyone looking to sell a product online.

Direct download: Zoher_Karu_Mixed.mp3
Category:machine learning -- posted at: 5:00pm PDT

Machine Learning Cyber Security May Help Speed Response to Hack Attacks

In this week’s episode, I speak with Igor Baikalov, chief scientist at cybersecurity company Securonix, about the trends in data security and where security itself has had to take a step up in the last five years. Igor touches on major meta-trends that have forced data security to advance, as well as what has made AI and machine learning a ‘requirement’ of modern data security strategy, something that has changed significantly in the last decade. Igor sheds light on these issues and likely future trends in cybersecurity over the next five to 10 years.

Direct download: Igor_Baikalov_Mixed.mp3
Category:machine learning -- posted at: 5:08pm PDT

Facebook Artificial Intelligence and the Challenge of Personalization

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

Direct download: Hussein_Mehanna.mp3
Category:machine learning -- posted at: 9:08pm PDT

What Can Machines Do That Lawyers Can't? A.I. Applications for Law

When one thinks through important industry apps of AI, law or legal apps are not usually the first to jump to mind, but there’s certainly a need. Richard Downe PhD is vice president of Data Science at Casetext, a startup working on improving search and natural language processing and democratizing legal information. In this episode, he speaks about the current bottlenecks for people trying to get more out of of legal case documents, as well as some of the apps on which the Casetext team is working, to make these processes easier and to gain strategic advantage in this industry.

Direct download: Richard_Downe_Mixed.mp3
Category:machine learning -- posted at: 6:40pm PDT

Start with a Problem: How Fast-Growing Startups Can Leverage Machine Learning

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

Direct download: Andrew_Filev_Mixed.mp3
Category:machine learning -- posted at: 12:00pm PDT

Technology Meta-trends and a Bird's Eye View of the Singularity

Today we have a guest who has interviewed more futurists than anyone else I know. While at TechEmergence a lot of our interviews focus on executives in AI, Nikola Danaylov has had the pleasure of interviewing some of the finest futurists and forward-thinking minds in the world, including Ray Kurzweil, Verner Vinge, Marvin Minsky, and many others. We speak today about the trends he’s seen aggregated (if any) amongst futurists, and about how technology may be dragging us farther into a transhuman future, whether that be closer to a utopia or a dystopia.

Direct download: Nikola_Dana_Mixed.mp3
Category:Artificial Intelligence -- posted at: 7:58pm PDT

How Business Event Data and Predictive Analytics Help Deliver Better ROI

A lot of companies in the San Francisco Bay make the claim that they can do something great with data; many fewer are at a degree of scale to make this vision possible. Today we speak with Nicholas Clark, CEO of DoubleDutch, a company now powering thousands of events nationally and implementing machine learning into their operations, including predicting business results from actual attendees. DoubleDutch is at the beginning of its journey with predictive analytics, having to make hard choices around what sort of information and thought processes they need in order to use machine learning and remain profitable. Nicholas gives his perspective on these decisions, as well as how he thinks DoubleDutch’s efforts will impact the conference/event industry at scale.

Direct download: Nicholas_Clark.mp3
Category:Big Data -- posted at: 6:30pm PDT

How Natural Language Processing Helps Mattermark Find Business Opps

Natural language processing (NLP) sounds cool in theory. We’re familiar with Siri and Echo of course, but where does it play a role in other companies? In today’s episode, we speak with Samiur Rahman from Mattermark, whose entire business model is predicated on organizing and making findable information about companies, and generating a platform to search by unique criterion. Doing so involves some conceptual work with NLP to make things findable. Samiur talks about what Mattermark is doing with this technology now and where he thinks the future may take the field, and interesting topic for investors and founders alike.

Direct download: Samuir_Rahman.mp3
Category:natural language processing -- posted at: 9:39pm PDT

A Close Up of Computer Vision with Shutterstock

We’ve spoken in the past about computer vision on the TechEmergence show, but we haven’t covered much about it in industry apps. Few businesses have better mastered this technology in the form of an app better than Shutterstock. In today’s episode, we speak with Nathan Hurst, currently a distinguished engineer with Shutterstock and previously with Google, Amazon, and Adobe. Nathan delves into the topic of business apps that can “see”, and touches on what that means for the industry, some of the exciting developments that he’s seen over last the 10 years, and what he sees coming up in the next few years.

Direct download: Nathan_Hurst.mp3
Category:computer vision -- posted at: 7:00pm PDT

Searching for Higher Ground in Rough Seas of Emerging Tech Governance

In addition to focusing on industry applications of artificial intelligence and emerging technology, we also focus on ethical and societal impacts of emerging technology. In this episode, we get back to ethics with Wendell Wallach, a scholar at Yale’s Interdisciplinary Center for Bioethics and author of “A Dangerous Master”, which addresses tech governance and other emerging technology issues. In this week’s episode, Wendell talks about the problems of governing technologies that are developing faster than we can possibly assess all the risks, a topic that Wendell has thought about in-depth through both his extensive consulting, speaking and writing.

Direct download: Wendell_Wallach.mp3
Category:Ethics -- posted at: 6:00pm PDT

Predictive Analytics Offers Customized Solutions to Complex Problems

The artificial intelligence field is normally seen as burgeoning and new, populated with lots of small, scrappy companies aiming to become the next de-facto solution, with maybe one exception - “Big Blue”. IBM has been involved since the ‘beginning’ and is perhaps best known for Watson, which has from Jeopardy to a range of applications in small and big businesses, as well as the public sector. Swami Chandrasekaran is chief technologist of industry apps and solutions for IBM, and he speaks in this episode about what he sees as some of the low-hanging fruit for applying predictive models to business data. Swami has seen this technology applied in a variety of contexts, from automotive and shipping to telcos and more, providing an informed perspective for industry executives, data scientists, and anyone else interested in the intersection of predictive analytics and business.

Direct download: Swami_Chandrasekaran.mp3
Category:Big Data -- posted at: 8:09pm PDT

Follow the Data: Deep Learning Leads the Transformation of Enterprise

“Artificial intelligence (AI) can be seen as a progression in our scalability of labor.” This quote comes from this week’s guest, Naveen Rao, who received his PhD in Neuroscience from Brown before becoming CEO at Nervanasys, which works on full stack solutions to help companies solve machine learning (ML) problems at scale. In this week’s episode, Rao speaks about certain domains in industry where he feels optimistic about machine learning (ML) making a difference in the next five to 10 years, providing interesting perspectives that include advances in the areas of agriculture and oil & gas.

Direct download: Naveen_Rao.mp3
Category:Deep learning -- posted at: 7:00pm PDT

Building to Scale: How Yahoo! Turns Machine Learning into Company-Wide Systems

Many employers (and employees) are familiar with the ‘painful’ learning curves of using multiple software products or platforms at once, but these may not be gripes you want to share with Amotz Maimon. This week, we feature an interview recorded at Yahoo headquarters with its Chief Architect, Amotz Maimon. He speaks about technology governance and how companies small and large can make faster and better decisions around what technologies to use, how to integrate and streamline the processes, and how to integrate machine learning into the mix (which Yahoo has been using for the past decade). This episode provides important insights for those looking to scale such technologies within their own businesses.

Direct download: Amotz_Maimon.mp3
Category:machine learning -- posted at: 5:01am PDT

Pulling Back the Curtain on Machine Learning Apps in Business

If you’re in the San Francisco Bay area, it’s not all that novel to be trained in or working on some form of AI; however, to be doing so in the 1980s and 1990s was a more rare occurrence. Dr. Lorien Pratt has been working with neural nets and AI applications for many decades, and she does lots of consulting work in implementing these technologies with companies in the Bay area. In this episode, Lorien provides her unique perspective on decades of development and adoption in AI as we ask, where is the traction today in places where it wasn’t 5 or 10 years ago? We also discuss where Lorien thinks machine learning applications in business and government seem to be headed in the near term.

Direct download: Lorien_Pratt.mp3
Category:machine learning -- posted at: 10:40pm PDT

Machine Learning Opening New Doors in Human Resource Industry

When we think about applying AI and data science to different areas of business, we often think about those domains that offer a wide swath of quantitative metrics that we can feed a machine, like marketing or finance. Human resources (HR) normally doesn’t fit the bill. How we hired someone, how we felt about them when we hired them, how they perform qualitatively, these are things that are often difficult to discern in team dynamics. That being said, big teams like Google are applying machine learning (ML) to some of their HR choices, and our guest today believes more companies will be doing the same in future. CEO of Humanyze Ben Waber applies ML  to HR decision-making, helping people get better employees and better performance by measuring and improving using data science in new ways.

Direct download: Ben_Waber.mp3
Category:Emerging Technology -- posted at: 6:00pm PDT

There are hedge funds and financial institutions that already use real-time data and sentiment analysis from social media, articles and videos in real-time to potentially make better trading decisions - but what does it mean when those same companies can use real-time satellite information to detect company activities and make trades based on that data? In this episode, Research Director of Capital Markets at Celent Securities discusses the focus on emerging technologies in trading and finance. He talks about the way that analytics and machine learning have affected the ways banks operate, the kinds of data that hedge funds and individual investors now have at their fingertips, and what that means for the future implications of AI-related technology in the finance world.

Direct download: Brad_Bailey.mp3
Category:Emerging Technology -- posted at: 6:00pm PDT

NLP Systems Have a Lot to Learn from Humans

Ten years ago, it would have been difficult to talk into your phone and have anything meaningful happen. AI and natural language processing (NLP) have made large leaps in the last decade, and in this episode Dr. Catherine Havasi articulates why and how. Havasi talks about how NLP used to work, and how a focus on deep learning has helped transform the prevalence and capabilities of NLP in the industry. For the last 17 years, Havasi has been working on a project through the MIT Media Lab called ConceptNet, a common sense lexicon for machines. She is also Founder of Luminoso, which helps businesses make sense of text data and improve their business processes.

Direct download: Catherine_Havasi.mp3
Category:natural language processing -- posted at: 9:21pm PDT

Insights on the Symbiotic Relationship Between Data Science and Industry

When it comes to data science and machine learning, what are the related skills that are getting people jobs and what are the industries that are supplying those in-demand jobs? These are two important questions that we discuss in this week’s episode with CrowdFlower’s CEO Lukas Biewald, whose company is providing a pragmatic perspective of the industry by focusing on assessing job listings and related information in the field of data science. If you’re a company that is interested in finding someone with in-demand data science and related skills, or if you’re in the market to find a position in this field, this episode will likely be very useful!

Direct download: Lukas_Biewald.mp3
Category:general -- posted at: 9:31pm PDT

How Cognitive Computing Can Change the Nature of Business Operations

When you go to Harvard Business School and then to McKinsey company to work in private equity, there’s really only one thing left to do - go to Silicon Valley and start an AI startup. At least, this is exactly what CEO Praful Krishna did when he moved to San Francisco to start Coseer, an AI company focused on understanding natural language and unstructured data. In this week’s episode, we speak about where unstructured data lives in a business, and how a business can be changed if the right data is unlocked. Krishna also discusses his experience in how executives are making decisions around how or how not to leverage AI in their companies.

Direct download: Praful_Krishna.mp3
Category:machine learning -- posted at: 6:25pm PDT

Machine Learning Still Getting Sea Legs in the World of Midsize Business

While we’ve featured quite a few companies that use and implement AI systems, we’ve more rarely gone behind the scenes with companies or consultants providing AI-related services to companies. In this week’s episode, we talk with Machine Learning Consultant Charles Martin, a data scientist and machine learning expert who has done freelance consulting on machine learning systems at companies including eBay, GoDaddy, and Aardvark. In this interview, Charles talks about the areas in AI that he believes are ripe for implementation in a business context, and where he sees businesses getting AI ‘wrong’ before getting to the hard work of implementing systems that work for them.

Direct download: Charles_Martin_.mp3
Category:machine learning -- posted at: 7:17pm PDT

Machine Learning Not a Crystal Ball, But It Brings Clarity to Investment Decisions

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

Direct download: Tad_Slaff.mp3
Category:Artificial Intelligence -- posted at: 12:00am PDT

How Gaming Could Win Us More Adaptable Artificial Intelligence

It’s more common to ask what AI can to do to win at games, but it’s less common to ask what games can do to help develop AI. This is a particularly fitting topic after Google’s DeepMind’s defeat of Go, and in this episode we talk with New York University’s Julian Togelius about his research in how games can help us develop AI. We discuss how simple AI has been used in more common video games; the ‘smoke and mirrors’ effect that is more often used to mimic AI; and the more innovative ways that AI are being used in gaming at present, setting precedents for the future role of AI in gaming.

Direct download: Julian_Togelius_new.mp3
Category:Artificial Intelligence -- posted at: 4:03pm PDT

Is Embodied Intelligence a Necessity for Flexible, Adaptive Thinking?

What is intelligence? For some researchers, it may be quite possible to create an intelligent machine ‘in a box’, something without physical embodiment but with a powerful mind. Others believe general intelligence requires interaction with the outside world, inferring information from gestures and other features of functioning in an environment. Dr. Vincent Müller is of the belief that intelligence may involve more than just mental algorithms and may need to include the capacity to sense rather than just run a program. Vincent focuses on cognitive systems as an approach to AI, and in this episode he talks about what this means and implies, how this approach is different from classical AI, and what this might permit in the future if the field is developed.

Direct download: Vincent_Mueller.mp3
Category:Artificial Intelligence -- posted at: 11:42am PDT

Why Big Data is Not Necessarily the Best Data for Business

You’re a business, and you’ve collected data - now how do you now make sense of it? Bring in a technology called ‘sentiment analysis’, a form of machine learning that determines whether text is positive or negative. Slater Victoroff’s company Indico provides a sentiment analysis API product that specializes in this task. In this episode, we talk about about the common misconceptions that businesses have about where ‘big data’ may be applicable, and the lessons he’s learned by gaining more tangible insights from smaller sets of data for companies. He explains why big data is not necessarily better, and discusses the steps that companies should take early on to make sure they’re prepared when it’s time to apply machine learning to their processes.

Direct download: Slater_new.mp3
Category:Big Data -- posted at: 12:00am PDT

Advocating a More Sustainable Business Culture in an Automated World

How does automation influence society today? This is an open-ended question with likely endless answers that can be observed in many different areas of society. As a Writer, Speaker, and Professor in Media Theory and Economics, Douglas Rushkoff has made it his livelihood to examine the impacts of automation in our evolving digital society. In this episode, we speak about his 'disappointment' in how automation has been used by many industries without regard for employees' long-term well being, and how a cultural shift in industry priorities may be what's needed to make automation beneficial for the majority.

Direct download: Doug_Rushkoff.mp3
Category:Automation -- posted at: 6:30am PDT

How Will the World Be Different When Machines Can Finally Listen?

This week's in-person interview is with Dr. Adam Coates, who spent 12 years at Stanford studying artificial intelligence before accepting his current position of Director of Baidu's Silicon-Valley based artificial intelligence lab. We speak about his ideas around consumer artificial intelligence applications and impact and what he's excited about, as well as what he thinks may be more 'hype' than reality. He gives a an idea about applications that Baidu is working, to potentially influence billions of mobile and computer users worldwide. If you're interested in the developments of speech recognition and natural language processing, this is an episode you won't want to miss.

Direct download: Adam_Coates_Finished.mp3
Category:Deep learning -- posted at: 6:00am PDT

Closing Gaps in Natural Language Processing May Help Solve World’s Tough Problems

People often mark progress by what they see, but there’s often much more going on behind the scenes, the up and coming, that marks actual current progress in any particular field. The same can said to be true for natural language processing, and Dr. Dan Roth’s research in this field makes him privy to the advancements that most of us are bound to miss.

In this episode, Dr. Dan Roth explains what the last 10 years of progress in natural language processing (NLP) have brought us, what’s happening with approaches in developing this technology today, and what the next steps might be in a computer capable of real conversational speech and understanding language in context.

Direct download: Dan_Roth.mp3
Category:Deep learning -- posted at: 5:46am PDT

The Rise of Neural Networks and Deep Learning in Our Everyday Lives

How do neural networks affect your life? There’s the one that you walk around with in your head of course, but the one in your pocket is an almost constant presence as well. In this episode, we speak with Dr. Yoshua Bengii about how the neural nets in computer software have become more ubiquitous and powerful, with deep learning algorithms and neural nets permeating research and commercial applications over the past decade. He also discusses likely future opportunities for deep learning in areas like natural language processing and individualized medicine. Bengio was a researcher at Bell Labs with Yann LeCun and Geoffrey Hinton, now at Facebook and Google respectively, and was working on neural nets before they were the "cool" new AI technology that they're seen as today.

Direct download: Yoshua_Bengio.mp3
Category:Artificial Intelligence -- posted at: 3:00am PDT

Fear Not, AI May Be Our New Best Creative Collaborators

Statements about AI and risk, like those given by Elon Musk and Bill Gates, aren’t new, but they still resound with serious potential threats to the entirety of the human race. Some AI researchers have since come forward to challenge the substantive reality of these claims. In this episode, I interview a self-proclaimed “old timer” in the field of AI who tells us we might be too preemptive about our concerns of AI that will threaten our existence; instead, he suggests that our attention might be better  honed in thinking about how humans and AI can work together in the present and near future.

Direct download: Jim_Hendler.mp3
Category:Artificial Intelligence -- posted at: 6:00am PDT

Neural Nets Just One Strand in a Braided Approach to Building Strong AI

TechEmergence has had a number of past guests who have talked about neural networks and machine learning, but Dr. Pieter Mosterman speaks in-depth about the pendulum swing in this approach to AI from the 1960s to today. What we call neural networks as a general approach to developing AI has come in and out of favor two or three times in the last 50+ years. In this episode, Dr. Pieter Mosterman speaks about the shift in this approach and why neural networks have gone in and out of favor, as well as where the pendulum may take us in the not-too-distant future.

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Direct download: PieterMosterman.mp3
Category:Big Data -- posted at: 3:00am PDT

Open-Minded Conversation May Be Our Best Bet for Survival in the 21st Century

Few astrophysicists are as decorated as Martin Rees, Baron Rees of Ludlow, who was a primary contributor to the big-bang theory and named to the honorary position of UK's astronomer royal in 1995. His work has explored the intersections of science and philosophy,  as well as human beings’ contextual place in the universe. In his book "Our Final Century", published in 2003, Rees warned about the dangers of uncontrolled scientific advance, and argued that human beings have a 50 percent chance of surviving past the year 2100 as a direct result. In this episode, I asked him why he considers AI to be among one of the foremost existential risks that society should consider, as well as his thoughts around how we might best regulate AI and other emerging technologies in the nearer term.

Direct download: Martin_Rees.mp3
Category:Artificial Intelligence -- posted at: 9:12pm PDT

Putting the Art in Artificial Intelligence with Creative Computation

When we think about AI, we often think about optimizing some particular task. In most circumstances through computation there is an optimal chess move, or an optimal way to determine pattern in data, or solve a math problem, or route info through servers. Most of us are aware of these uses, but what about creative tasks? Can these also be optimized? If we want to give a computer information and tell it to create powerpoint slides, is there an optimal way to create such slides? Dr. Philippe Pasquier’s computational research is focused on artificial creativity. In this episode, we talk about how to define a very new field, train machines in this area, and also discuss trends and developments that might permit such technology to thrive in the next 10 years.

Direct download: Philippe_Pasquier_1.mp3
Category:Artificial Intelligence -- posted at: 4:00am PDT

How Machine Learning Builds Meaning from Our Chats, Tweets, and Likes

There’s a small lab in Pennsylvania that may know your gender, age, and understands facets about your personality, whether you’re introverted or extroverted, for example…and it's using machine learning to help make conclusions from social media information. For those who are raising an eyebrow, know that they’re not tapping into people’s accounts without permission. The described study is happening at University of Pennsylvania and is led in part by Dr. Lyle Ungar. In this episode, we talk about the focus of his work - on finding patterns between users and their language on social media content, and building an understanding for how this information might help individuals and communities in the future.

Direct download: Lyle-Ungar_1.mp3
Category:machine learning -- posted at: 6:00am PDT

AT&T Predicts Future, Save Service with Machine Learning

We’ve featured a number of artificial intelligence researchers on the show, but today we switch gears and dive into the business side of the industry. In this episode, Dr. Mazin Gilbert (who earned his PhD in Engineering) breaks down AT&T’s efforts to make more intelligent systems large-scale. How do they train their network to route traffic through the right nodes on holidays, when certain areas of traffic are overloaded? How can a system know, based on signals from hardware, which pieces might be going bad and need replacing and send out a message to alert the company? Making a network ‘aware’ is a large challenge, but Mazin gives an insider’s perspective as to how economic and business pressures are driving AT&T to implement machine learning technologies in order to remain profitable.

 

Direct download: Mazin_Gilbert.mp3
Category:Artificial Intelligence -- posted at: 6:00am PDT

Snuggle up with Technology, But Don't Leave Empathy in the Cold

Are we losing something with technology? There are two sides to every argument, including this one. Dr. Sherry Turkle is of the belief that there’s enough mounting scientific evidence that points toward loss of empathy and self knowledge due to increasing interaction with machines. In this episode, we discuss Dr. Turkle’s research and her subtle fears for the future, particularly of those about machines that replicate emotions or conversation but that don’t actually feel anything - is the ability to form real connections between two beings at risk of being lost?

Direct download: Sherry_Turkle.mp3
Category:Artificial Intelligence -- posted at: 6:00am PDT

Putting the Horse Before the Cart May Lead the Way to Artificial General Intelligence

A lot of AI applications are not really “smart”, at least not in the sense of the word as most humans might envision a true artificial intelligence. If you know how Deep Blue beat Gary Kasparov, for example, then you may not believe that Watson is a legitimate thinking machine. Our guest this week, Dr. Pei Wang, is of the belief that building a Artificial “General” Intelligence (AGI), what researchers define as an entity with human-like cognition, is a separate question from figuring out AI applications in the more narrow sense. In this episode, Dr. Wang lays out three differentiating factors that separate AGI from AI in general, and also talks about three varied and active approaches being taken to try and accomplish AGI.

Direct download: PeiWang.mp3
Category:Artificial Intelligence -- posted at: 6:00am PDT

Brain Gains on the Road to Mapping a Personal Connectome

It goes without saying that the brain is difficult to understand, with the billions of neurons, fine individual synapses between each neuron, and the different regions responsible for the innumerable behaviors exhibited by human beings. A new burgeoning and promising intermediary field called Connectomics is making waves in mapping the brain and figuring out how these various connections work together to make us sentient. In this episode with Dr. Olaf Sporns, who is in part credited with coming up with the term Connectomics, we explore the progress that’s been made in this new field in the past decade, and take a tentative but hopeful look ahead at what the next decade might bring as the field progresses into its adolescence.

Direct download: Olaf_Sporns.mp3
Category:Neuroscience -- posted at: 12:00am PDT

Deciphering the Discovery Engines that Decipher Our Digital Wants and Needs

Ever had the perfect book recommended to you by Amazon or gave a pleasantly-surprised thumbs up for a song selected for you by Pandora? Both services are powered by recommendation engines, which are gaining steam int he commercial space. In this episode, we speak with Entrepreneur Raefer Gabriel, who works for Delvv on the commercial applications of recommendation engines. We talk about how this technology works, and how it comes to learn from reviews, ratings, and consumer interactions. Gabriel also gives perspective on how these engines might be enhanced and applied in the future, a good topic for those of you in the startup world.

Direct download: Raefer_Gabriel.mp3
Category:general -- posted at: 3:00am PDT

When Many Intelligent Agents are Better than One

The beauty of a platform like eBay is that you can set a price that you’re willing to spend and let eBay do the bidding long after you’ve left the site. What if, in similar fashion, your washing machine could turn on and serve up clean clothes once it had found the cheapest rate and time of day by autonomously communicating with local electricity providers?

In this episode, we discuss multi-agent intelligent systems with Computer Scientists Dr. Mehdi Dastani, who provides a perspective on how this emerging dynamic technology is changing the landscape of how and how companies and governments operate, allowing for greater systemic change that might not be possible otherwise.

Direct download: Mehdi.mp3
Category:general -- posted at: 6:00am PDT

A Global Call to Ban Autonomous Killer Robots for Good

Over the last decade, many first-world militaries have developed, and in some cases deployed, autonomous “killer”  robots. Some proponents believe that such robots will save human lives, but another side believes that an accidental arms race of this type would yield long-term detriments that outweigh any good. University of Sheffield’s Dr. Noel Sharkey stands by the latter argument.

As Cofounder for the International Committee for Robot Arms Control, he has spent a good part of the last decade trying to create an international ban on such robots. In this episode, he speaks about the developments in the domain of autonomous killer robots, as well as how groups of global leaders might come together to convince nations and other global policy platforms to adhere to such an agreement for the benefit of all humankind.

 

Direct download: NoelSharkey-_11616_2.10_PM.mp3
Category:Robotics -- posted at: 6:00am PDT

Seeing the World through Machine Eyes - with Dr. Irfan Essa

Most of us forget that just about a decade ago, Facebook’s software was incapable of tagging people in a photo, but today can so without difficulty, sometimes without us even knowing. Machine vision has progressed to the point where it’s also common for computers to be able to pick out dogs from cats in images, another task that was not possible 10 years ago.

In this episode, we talk with Dr. Irfan Essa, an expert in Computer Vision at the Georgia Institute of Technology (GA Tech), about progress made in machine vision over the last 10 years, related projects in the works today, and where machine vision may be headed in the next decade.

Direct download: Irfan_Essa.mp3
Category:Artificial Intelligence -- posted at: 6:00am PDT

Have you ever seen a humanoid robot and felt creeped out? In this episode, we talk with Robotics Engineer Derek Scherer about the psychology of the uncanny valley and our relationships with robots. Scherer talks about the factors in robotics that tend to spook people and provoke a feeling of disgust, and how we might be able to move beyond this resistance as they become a more active part of the social fabric of our society.

Direct download: Derek_Scherer.mp3
Category:Robotics -- posted at: 8:00am PDT

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