From the CNN Magic Wall to Mixed Reality - A Software Pioneer's Take on the Future of Computer Vision and AI Ethics
Guest: Tim Huckaby, AI and Computer Vision Consultant, Founder of Internology
Hosts: Seth Earley, CEO at Earley Information Science
Chris Featherstone, Sr. Director of AI/Data Product/Program Management at Salesforce
Published on: March 1, 2022
In this episode, Seth Earley and Chris Featherstone sit down with Tim Huckaby - software industry veteran, keynote speaker, and computer vision pioneer who built the CNN Magic Wall for presidential election coverage, led custom application development for Fortune 1000 companies through his firm Internology, and has spent a decade at the forefront of augmented reality, mixed reality, and AI ethics. Tim traces his path from writing enterprise software at Microsoft in the 1990s through bold predictions - some famously wrong - to where he believes the convergence of computer vision, spatial anchors, and processing power is taking us next. The conversation covers quantum computing's potential to break all current encryption, why labeled training data remains the most underappreciated bottleneck in computer vision, how spatial anchors on smartphones can bring historical figures back to life in any physical location, and why the ethics debate around AI and facial recognition is ultimately a tension between security and privacy that no one has cleanly resolved.
Key Takeaways:
- Software development complexity has dropped dramatically since the 1990s - the tools, plumbing, and platforms have improved so much that building good software today requires a fraction of the effort it once did, even as the problems being solved have grown exponentially harder.
- Moore's Law, if it continues on its current trajectory through 2025, will produce CPUs that calculate at the speed of the human brain - which does not mean the singularity, but does mean solving genuinely hard problems in AI, medical research, and healthcare becomes tractable.
- Quantum computing's greatest near-term threat is not that it will replace classical computing but that it will crack every current encryption system - blockchain, Bitcoin, corporate security - within just a few years, requiring a complete rethinking of security architecture before that happens.
- Computer vision applications go far beyond facial recognition - object recognition, cellular structure analysis, automated engine diagnostics via HoloLens, and spatial anchor experiences tied to physical locations represent the more compelling and less ethically fraught frontier.
- Labeled training data is the most underappreciated bottleneck in computer vision: recognizing every tree species requires millions of categorized images with bounding boxes, and companies like InnoData exist specifically to solve this synthetic and licensed data creation problem at scale.
- The last mile of cognitive AI for enterprise use cases - augmented reality repair guides, mixed reality training systems - requires the unique internal knowledge, terminology, procedures, and expertise of each organization, not generalized models, making enterprise data readiness the real barrier.
- AI ethics debates, particularly around computer vision and facial recognition, have produced a patchwork of layered regulations - federal, state, and city-level in the US - with San Francisco having banned police use of computer vision entirely, raising the fundamental question of how to balance security against privacy at every level of governance.
Insightful Quotes:
"I just love computer vision - and that's a computer, some form of lens or endpoint device interpreting what it sees. The world of object recognition was so much more enticing to me than facial recognition. Recognizing animals, trees, traffic patterns, cellular structures - this doesn't have to be a 2D world. You go to the atomic level and have computers look at stuff." - Tim Huckaby
"We've got the algorithms, we've got the tech - we're just waiting for the hardware to get its act together, basically. And we have been for 25 years. Software is always waiting for the hardware to get better." - Tim Huckaby
"When you talk about that augmented reality system showing you how to repair an engine - that has to come from the heads of engineers and design drawings and a corporate knowledge base. Organizations that want to use this have to get their data house in order. It's going to be based on the unique knowledge, expertise, terminology, processes, and procedures of the enterprise. That's going to be an internal piece." - Seth Earley
Tune in to hear Tim explain how John King of CNN was the actual product manager driving every feature of the Magic Wall, why a 12-year-old can get the tools to do harmful things with AI for free on the internet, and why he is miserably failing at being semi-retired because there is just too much opportunity to build world-saving technology.
Contact Tim:
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Podcast Transcript: App Dev, AI, Computer Vision, and Ethics - A Software Pioneer's Journey from Microsoft to the Magic Wall and Beyond
Transcript introduction
This transcript captures a conversation between Seth Earley, Chris Featherstone, and Tim Huckaby covering Tim's journey from writing enterprise software at Microsoft in the 1990s through building the CNN Magic Wall, founding custom app development firm Internology, pioneering computer vision and augmented reality applications, and landing on AI ethics - particularly the unresolved tension between security and privacy that facial recognition and computer vision technology has surfaced in jurisdictions from San Francisco to Washington DC.
Transcript
Seth Earley: Welcome to today's podcast. I'm Seth Earley. And before we get started, I want to give a shout out to our sponsors: Simpler Media, Marketing AI Institute, and Earley Information Science. Our guest today is an industry luminary focused on AI, computer vision, machine learning, augmented reality, mixed reality, and emerging user experiences. His list of accomplishments and awards is very long - we would need the whole hour just to list them. He's been around for a long time, has done some amazing work, is sought after as a highly rated speaker, is an author, and has thousands of publications and publishing credits to his name. We are really lucky to have him today. Please welcome Tim Huckaby.
Chris Featherstone: And I'm Chris Featherstone.
Tim Huckaby: Wow - luminary. I wouldn't think that comfortable with it. So yeah, it's awfully nice of you. To sum that up, it just means I've been around a long time and I have gray hair.
Seth Earley: As Woody Allen says, 90% of life is showing up. You've been showing up in a lot of good places in life. And Chris, you've known Tim for a long time. Tell us how you met.
Chris Featherstone: Yeah, before he was luminous. I've known Tim for probably 20-something years now. It's been a long time. He and I met - I was at Microsoft. He was one of our key partners and we just did some fun, fun work together and laughed a lot, played volleyball because we're both down in Southern California. And then over the years it's been fun because we've been able to work different deals, our families know each other, so we hang out. It's been really, really fun.
Plus, to see from the outside what he's been able to do with a lot of companies - one of the things that I think has separated Tim from the industry at large is his ability to help facilitate showing the actual capabilities of core technology, whether it's super brand new and bleeding edge or even contemporary. He actually helps people understand it from a business value perspective, but more importantly, gets people super excited to use it, shows them how to use it. Even the organizations that create the technology - Tim shows them actually how to use it in the market. And I think that's one of the things I have always loved about Tim: his ability to help technologies that come out, separate them from the noise, and say: okay, you created this really unbelievable technology - now let me show you the real value of it.
Seth Earley: I want to make a comment there because so much of the time organizations do not know what they have and it is about separating the noise internally as well. So you worked in the 90s at Microsoft. Tell us about what you were surfacing at that time.
Tim Huckaby: That's a great segue. It's funny because I have this 25-year speaking career in front of audiences - I mostly do keynotes these days. But I kind of walked bass-ackwards into it. I was working within the Windows NT Server Group on a not-so-famous, not-so-good server product that lived within NT Option Pack - Microsoft's internet server, IIS 4, and I worked on the site server part, the e-commerce part of it.
Anyways, the story is: after we shipped the product, Microsoft had this huge conference called TechEd, and the product team - the powers that be said "all right, we need these speakers to do these presentations" - and all my bosses and all my bosses' bosses were like: screw this, I'm not doing that, I'm not standing in front of an audience. No way. So they said: let's make Huckaby do it. Because I seemed to be the only one out of 2,500 people on that team who liked to smile and laugh and could entertain. So without any experience, I stood in front of 2,500 people and I guess I just nailed it. I found out later I had the highest rated session in the entire conference. And that agitated the famous speakers because no one had ever heard about this 25-year-old kid from San Diego.
Seth Earley: Are there any archive videos of that?
Chris Featherstone: That was when we had Nokia phones with monochrome screens.
Tim Huckaby: At Microsoft, that is honestly where I learned how enterprise software was built. The install team for that particular product was about 700 people. The install was so complex. And back then, testing across 36 languages was a nightmare - we did not have automated testing tools, so a lot of it was manual. If you have ever done international language software, you know the German is what you test because all the words in German are a mile long. You click Start and then a German word and it bleeds over the control and you're like - what do we do now?
Seth Earley: That is so interesting.
Tim Huckaby: You would not believe how difficult it was to build software back then. And I know it bothers the brilliant engineers I get to work with - but I am just telling you, it is just not that hard to build good software anymore because the tools and the plumbing and the platforms are so good compared to 20 years ago.
Chris Featherstone: The fun part too was - and this is illustrative of what Tim is all about - if I wanted to, as a senior technologist or architect at Microsoft, prove that a technology would work, I would find the money and go engage Tim and his resources to actually show it and get it done. It made no sense to go back to the product group and say "can we build something like this?" - because they did not know. So putting it into Tim's hands and saying "let's create something that has nearly never been done before" - he would take it, run with it, and bring something back that was 10 times better than I ever imagined.
Tim, I don't know if you remember, but the original Microsoft Surface was that game table thing. My thought was - I was doing federal healthcare stuff at the time - let's do a 3D heart and just show the power of what you could do. I basically just said: here's the idea Tim, what do you want to do with it?
Tim Huckaby: The NDA doesn't matter 20 years later. We built a 3D rendering of the heart so they could annotate heart surgery. God, we were so before our time. An engineer named Kevin Kennedy was the brilliant mind behind that. And we repurposed that heart numerous ways, shapes, and forms. I know it saved lives.
It was super cool on the Surface table because the Surface table is a touch table - you could spin it, render it, look at all sides, annotate the heart surgery, see the effects. But it also made it to the TV show Grey's Anatomy. And you know how in television - we've built a lot of stuff for Hollywood, but it's all smoke and mirrors. These actors spew out medical mumbo jumbo, they don't know what they're saying. But they used the Surface table in a couple of episodes of Grey's Anatomy, and we built them a wall version of it. And by the way - the answer is yes - Sandra Oh, the actress, is like the nicest person in the world.
Seth Earley: Wonderful to hear. A lot of times you have these images of folks and you think they seem so nice and then they're completely not nice.
Tim Huckaby: In Hollywood, nine out of ten are not the type of person you'd hope they are.
Chris Featherstone: It is amazing to me how many people utilized the things that you guys built as their stepping stone to other lofty heights.
Tim Huckaby: If there is a question in here about what is your proudest accomplishment in your career - it is without a doubt all the careers that my company launched. These brilliant engineers just flourished in Internology, and I am more proud of that than anything. A lot of our alumni went to Microsoft, Facebook, Amazon, whatever.
Seth Earley: They come back when Microsoft buys their venture.
Tim Huckaby: They come back and say: honestly, the happiest parts of my career were at Internology. It launched my career. And I am really proud of that.
Seth Earley: You built an app dev company. Tell us about when you left Microsoft and give us a chronology.
Tim Huckaby: I'll try to make it quick. I worked on that product team and I commuted from San Diego to Redmond, Washington. It was brutal - I was home for 32 hours a week for almost two years, flying in on Sunday night and home Friday night. It was a different Microsoft back then. You worked 18-hour days and had all three meals in Building 25.
But I love people, and I met so many amazing people. Scott Guthrie - the number two person at Microsoft, who owns everything up at Microsoft now and is being groomed to be the next CEO - he started about two months after me. We went to the same meetings. He's now a friend of mine. We were so young back then.
Anyway, the queen - as I affectionately call her, my lovely bride of almost 32 years - said: there is no way in hell we are moving to Redmond, Washington. We're spoiled Southern Californians. My career would have taken a much different path if I had stayed at Microsoft. But the kids were getting big enough that I was missing stuff. So I came home and started the next chapter.
I walked bass-ackwards into an angel investment from a college buddy of mine who said: Tim, you want to start your own company? Here's a bunch of money. And sometimes in life you regret what you asked for. My partner at the time, Dave Lynn from Microsoft, said: well, we've got to do this now. So we started this custom app dev company because we didn't know better. We were all technical people - there was no business in the firm back then. We survived those tough economic times on sheer grit and engineering talent. It's a services company. We built products for other companies - Fortune 1000, totally NDA-type stuff, including bits for Microsoft's own products.
I left Internology just a few months ago, by the way - other people run it now, I sold my interest. My joke about Internology always was: awesome company to work at, great high-profile projects like the CNN Magic Wall - just a really tough company to own, because you're always on the elephant hunt. You're always looking for the next big project. You get to eat what you kill, and you have to kill the big thing.
Chris Featherstone: Hold on just a second, Seth. He brought up the CNN Magic Wall. That was the key tool they used for the presidential race - the projection tool everybody in the world has seen where the news anchors go through: well, look at this - if this county goes here and this one gets this many votes. They built that entire thing.
Tim Huckaby: And that has a great story behind it. The first version we built was in WPF - Windows Presentation Foundation. Because of the SLA on that application, which is essentially 100% - you cannot crash software when you are live with 250 million people worldwide watching. We were actually exposing bugs in the XAML stack of WPF and Microsoft was fixing them hot because the application was so high-profile. Just imagine that world.
They are still using it. You still see it on almost every version of CNN election coverage. It was a DirectX-based application.
Seth Earley: When you did something like that, how many people, how long were those projects?
Tim Huckaby: That was a big one - abnormally large because of the 100% SLA, because of WPF, and because of data integration. It also had a producer console - because John King or Wolf Blitzer or Anderson Cooper, whoever is on air, has an earphone in and the producer is talking to them constantly while they're talking. So we had a separate application where you could introduce content into the Magic Wall depending on what was going on live. It was an elaborate application. That one took about six months, probably a team of four to six brilliant people.
And I will say this: John King of CNN really gets all the credit for the design and functionality. That was his brainchild. He was literally our product manager driving features. By the way, he is a totally nice guy. Realize this - John King is like any other talent from CAA. He makes a ton of money, negotiated by his agent. He could move to Fox in a heartbeat if they doubled his salary. He is just good. He could survive on any network.
Chris Featherstone: I would love to get your take on where you went from building all that cool stuff to now - what this looks like for augmented reality and the metaverse type world, and how those visual elements are now preceding these new visual elements and the interactivity of them.
Tim Huckaby: You know, I'm infamous for some bold predictions. One of my really wrong predictions was the death of the internet - when I was young, coming up from a Win32 background at Microsoft.
Seth Earley: Why was it going to die? What was the context?
Tim Huckaby: I vividly remember Bill Gates writing that famous email - "we're late to the internet, we've got to switch on everything." Part of my team's job was that first internet server, IIS 4. And I looked at this HTML thing and went: God, this is not programming, this is stupid, this form submit is a joke. And I looked into TCP/IP and I'm like - this is going to die because of the way it routed traffic with all the router hops, it was so inefficient. If you hit timhuckaby.com, that is like 35 router hops.
What I did not anticipate was that Cisco would create that first router and overcome the hop problem through routing efficiency. So that leads into Feather's question. We are building Win32 apps in WPF and this incredible surge of the internet happens. And I probably said: they can never do the CNN Magic Wall in a web app. Well, guess what? We had to rebuild the whole thing in web. And it was actually a pleasure with some JavaScript 3D libraries.
One of the famous predictions I made was that once the smartphone arrived, we'd start building compiled apps again - basically Win32s. I was spot on with that one. But cut to today, we're building most of our mobile apps through web technology because it has gotten so good. And at the same time, Moore's Law has continued on its path and our processors can overcome the performance overhead of high-level platforms and programming languages.
The other problem, of course, was battery tech. Feather, you were around when we were testing on the Compact iPad. We were running Windows on the Compact iPad and the current battery tech gave us 90 seconds at full charge. At full charge. This was 20 years ago.
Chris Featherstone: Oh yeah, I was there.
Tim Huckaby: Battery tech has kept pace since then. And whoever invents the battery wins - those companies doing high-tech batteries are doing really well.
Seth Earley: It is so astounding to think about. I am holding my iPhone in my hand right now, and that was a physical impossibility 20 years ago. When you think about all the problems that had to be solved in most experts' minds - it is problem after problem after problem at so many different levels. No one could really imagine 20 years ago that we would have this kind of power and capability. No one knew that they needed all of their music available all the time, that they'd be connected all the time.
Now we're at this really critical inflection point in human history where so many things are coming together. When you start looking at the work you've done with visual and video and all the things that came before - now you're really looking at how computer vision, facial recognition, AI, and all these elements around meshing the physical with the digital are coming together. What are we on the cusp of? And the metaverse world - I know there's this question about quantum computing that seems to have so many issues to overcome.
Tim Huckaby: You're spot on. Let me start with just a few years ago when we had this wave of machine learning - maybe four, five years ago. I had the pleasure of meeting with some really sharp scientists trying to solve some really hard problems, whether genetic or even physics at an atomic level. At the time, this machine learning craze hit a big dead end because we did not have enough processing power. And I could not get my arms around that, because we had the cloud and we had more processing power in the two major cloud players than I could ever dream of needing. I'm like - what do you mean you don't have enough processing power? And they said: I would need Azure and AWS combined, and I would need to replicate them by a hundred thousand times, to have the processing power I need to track photons and electrons to truly battle some type of cancer.
It is hard to get your head around needing that much power. And then we're back to Moore's Law - still continuing on its path of doubling the amount of transistors on a circuit board every two years. If Moore's Law continues through 2025 - which is just three years from now - our CPUs will calculate at the speed of the human brain.
Seth Earley: Just wrap your arms around that.
Tim Huckaby: That does not mean the machines are taking over, or the singularity. But it does mean we solve some really interesting problems in artificial intelligence and medical research and healthcare.
Seth Earley: Before we go on, just want to take a moment and remind our listeners that we are talking to AI and machine learning expert Tim Huckaby, and I want to thank our sponsors: Marketing AI Institute, Simpler Media, CMSWire, and of course Earley Information Science.
Now Tim, I want to make a comment about biological processes in the human brain. When people start talking about equating computing technology and computing power to the human brain - there are 100 different neurotransmitters in the brain, all of them analog, working at varying levels of concentration and along gradients. A single neuron can be connected to 10,000 other neurons and you have 3 billion of them. The scale of combinatorial mathematics and combinatorial physics involved is just beyond what we can conceptualize.
But then you add in quantum computing - which is still beyond my grasp. Positrons traveling backward in time, being annihilated before they're created - I have a hard time with that. And quantum computers will allegedly be able to break any encryption. Where does that leave us? Can you talk about those themes?
Tim Huckaby: Fair enough. Just understand - like you, Seth, I fully admit I have zero expertise in quantum computing. I'm just trying to get my arms around it at a high level. Because like artificial intelligence, it has this potential to end the world and at the same time to make the world so much better.
It's like the metaphor with nuclear technology. With nuclear technology, we have the worst bombs in the world that can literally exterminate the planet. But at the same time, we got the microwave oven, which is pretty darn cool.
Seth Earley: Nuclear magnetic resonance spectroscopy.
Tim Huckaby: All this greatness came out of nuclear technology. Quantum computing does have - in fact, the experts are predicting the end of security as we know it within just a few years. Because a quantum computer can crack anything we have right now - which means the whole Bitcoin thing, the whole blockchain thing, every corporation - it all gets exposed to bad actors.
At the same time, if you were able to build the algorithms... the problem with quantum computing is inputs and outputs. It does not really have traditional inputs or outputs. What it has is this incredible analytical engine in between. Remember when computers required you to flip switches to get them to run anything? That is the analogy for inputs. The problem with quantum computing is there is a ton of really high-end, hard work just to get an input into the thing so it can analyze it.
And its potential is great. They're talking about commodity quantum computers. But getting your arms around how it works is really tough. We came from ones and zeros and it's easy to conceptualize binary. But in quantum computing, as I'm told, a one can turn into a zero, or it could be half of a one, or it could morph back to one and a half. That is the basic concept of quantum - that is both its bold potential and why it is so difficult to comprehend.
Chris Featherstone: Let's get your take on augmented reality. I know the key thing about all the quantum discussion is that nefarious people will prove it out before business figures out how to use it - that's usually how it goes. But I love the fact that people are trying to get ahead and figure out what it looks like for augmented reality. I'd love your take on what you've been doing there.
Tim Huckaby: I have this 10-year love affair with computer vision. There's a lot of stuff in AI, but I just love computer vision - and that's a computer, some form of lens or endpoint device interpreting what it sees. That was the genesis of the augmented and mixed reality work.
Granted, some of the projects we did were a little bit creepy - looking at the human face to get an emotional profile, a demographic profile, age, race, gender. That's facial recognition. But the world of object recognition was so much more enticing to me. Identifying animals, trees, traffic patterns, cellular structures - this does not have to be a 2D world. You go to the atomic level and have computers look at stuff. And that led into augmented reality and then mixed reality.
If you're not familiar with these terms - virtual reality is what you see in the TV commercials, you put on a pair of lenses and you don't see anything else in the real world. Augmented reality is where you're looking at the physical world but these virtual things appear in it. So picture me gazing across the street and looking at a tree, but seeing a bunch of animals in the tree in a virtual way. Mixed reality - and I think Microsoft made up that term - is the HoloLens scenario where you're basically wearing glasses and interacting. The best HoloLens use cases are where you're learning about some type of procedure: you're looking at a broken automobile engine and it's identified what's wrong and showing you how to fix it in an augmented way.
Well, it's the same problem - processing power and battery. No one wants to wear a HoloLens. My wife would not let me wear a HoloLens in a public place like an airport. Nobody used to see people in Google Glass walk around.
Chris Featherstone: The best were the parodies of people walking around in those glasses running into stuff.
Tim Huckaby: So right. So augmented reality went to the smartphone because the smartphone started to get real CPUs. You could do some really interesting stuff by pointing your phone at something. What really got me was this concept of spatial anchors - you pin something virtual to a very specific physical place in the world, to about a two-inch resolution. I stick a spatial anchor next to that tree across the street. Now anytime someone comes by with their smartphone and runs an application, they point it at that tree and they get an augmented reality experience.
The experience might be: you point at the tree and Euell Gibbons - the famous naturalist - appears on your phone and starts talking about the tree and the animals there. You ask him questions: hey, Euell, are there any mammals that hang around this tree? Does it produce fruit? And virtual Euell, who has been gone for 50 years, is interacting with you back and forth.
If you're a sports person like I am - and Feather is - maybe you point at Petco Park down here in San Diego and Tony Gwynn appears - who is no longer with us, died of cancer. And you start talking with Tony Gwynn. Hey Tony, what was your favorite year? And Tony replies: well, most people would think it was the year we went to the World Series in 1997 against the Yankees. But really it was when I was at San Diego State...
We are all back to processing power and battery. We have got the algorithms, we have got the tech - we are just waiting for the hardware to get its act together, basically. And we have been for 25 years. Software is always waiting for the hardware to get better.
Seth Earley: And the whole learning thing hits a real obstacle because of data. In computer vision, imagine training something to recognize trees. Imagine the amount of data you need to recognize every tree species in the universe - literally millions of images, and they need to be categorized. You draw a bounding box around them and say: this is a pine tree. Then another: this is a cottonwood. Millions, if not tens of millions, of images. Data is a huge, huge problem in this world.
There is a company - InnoData - that is literally the only player in the space that I know of. It's a publicly traded company and that is all they do. They create labeled data synthetically, get it naturally, and license it. If you want to recognize trees, you go to InnoData and say: how much is it going to cost to get the training data for tree recognition? Great business to be in.
Tim Huckaby: Great business to be in.
Seth Earley: And then there is the last mile of what I call cognitive AI and the interpretation. When you talk about that augmented reality system showing you how to repair an engine - that has to come from the heads of engineers and design drawings and a corporate knowledge base. For organizations that want to use this, they have to get their data house in order. That is not going to be generalized from a public model or even a large language model. It is going to be based on the unique knowledge, expertise, terminology, processes, procedures, and expertise of the enterprise. So a lot of these things we are going to see are just going to take a lot of work to get those corporate data houses in order - which is different from what InnoData does around large labeled datasets for more public things. The inner workings and the competitive advantage - that is going to be an internal piece.
But before we finish - we only have a couple of minutes left - I do want to get your thoughts on the ethics of AI. When you start looking at all these data issues, whether it's corporate data, public data, personal data, private data, or the algorithms - give us a couple of minutes on your thinking around what is going on in the ethics space around AI.
Tim Huckaby: Yeah, sure. But I just have to comment - we are done? We could talk about this for hours.
Most of the keynotes I do these days have a technical session that augments the keynote and it is about the ethics of AI. It is super interesting for me and the audience. I am a demo type person on stage. I demonstrate some compelling stuff and then I demo some stuff that has been used for bad. And let's face it - a 12-year-old can get the tools for free on the internet to do some really bad things.
A lot of the ethics of AI work centers on computer vision because that is my area. And we have this privacy law issue - it's not just a US thing. This is a worldwide, super interesting debate. It's a balance between security and what one calls privacy.
Privacy law in the United States exists at a federal level. There is also privacy law at a state level that can supersede it. And now we have city-level privacy law that supersedes the state. The leading example is San Francisco - San Francisco has its own privacy law which is more strict than California, which is more strict than the United States federal standard. In San Francisco, you cannot use computer vision. The police have had their tools taken away from them. They cannot use license plate readers, they cannot use the facial recognition systems that identify suspects.
All of that has been taken away in the city of San Francisco because the policymakers - not the people, I would say, but the policymakers - have decided it is an invasion of privacy. So there you get into: do you really want terrorists running freely through San Francisco? What is the balance between privacy and being safe? And at the same time, you have got the ethical issue that the Googles and the Facebooks and the Instagrams of the world have built multi-billion dollar industries on breaking privacy law. They are tracking everything you do. And some of it is super creepy.
Seth Earley: Yep.
Tim Huckaby: So - interesting debate. And that is why I love talking about it.
Seth Earley: All right. Anything else coming up that you want to let people know about? Do you have a keynote coming? A project?
Chris Featherstone: What is next for Tim?
Tim Huckaby: Well, Feather and I - and I think Seth you were in that conversation - I am miserably failing at being semi-retired. There is so much opportunity out there. I am currently doing some consulting projects for the large chip maker I have been working with for the last six or seven years, and some other interesting consulting projects. I am trying to make this the year of fly fishing, but my goodness, there is so much opportunity - from starting another company to joining one of the big companies as a senior executive. There's plenty of funding to start another company, and I would do it in some of the things we've talked about today. At this stage in my career, I'd like to be on a life-saving or world-saving type project as opposed to building software for the company that kills people with its cheeseburgers.
I love software and I love learning and I just cannot imagine stopping. But I am really trying to stave it off for at least two or three months. Plus, I've got so many fly-fishing trips booked this year that there's no way anybody's going to hire me.
Seth Earley: I love it. Well, listen - we've really come to the end of our time today. It has been a tremendous pleasure talking with you today, Tim.
Tim Huckaby: Right back at you guys. Super fun.
Chris Featherstone: Love you, brother. Thanks for doing this. It's fun to hear some of the pioneering stuff that you've done.
Tim Huckaby: It's exciting. They're part of the family, Feather.
Seth Earley: Before we close, I also want to thank our sponsors: Simpler Media, Earley Information Science, and the Marketing AI Institute. And again, thank you all. Thank you, Sharon, for your work behind the scenes producing the episode. Thank you, Chris, and thank you, Tim. Appreciate it.
Tim Huckaby: Thank you, Seth. Super fun.