Episode Transcript
[00:00:00] Speaker A: Welcome to Infinite Future. I'm Todd Thomas. And today we're exploring the innovations shaping tomorrow's world. You're watching Now Media tv.
[00:00:11] Speaker B: Welcome to Infinite Future. I'm Todd Thomas. Today, I want to begin with a simple but powerful question. What if some of the biggest breakthroughs of the future are not about inventing something new, but seeing value in what we already throw away?
We're entering an era where artificial intelligence is moving out of the lab and into the physical world.
It's beginning to shape how we manage materials, energy, infrastructure, logistics, and sustainability.
And one of the clearest examples of that shift is what happens when waste becomes data and data becomes a new source of value.
My guest today is Dre Nichenlsson, co founder of Woodchuck AI Woodchuck is working at the intersection of artificial intelligence, construction waste, biomass, renewable energy, and the circular infrastructure.
This is going to be a conversation about using AI not just to optimize information, but to transform physical systems, turning wood waste into usable resources and helping build a cleaner, smarter, more abundant future. Dre, welcome to Infinite Future.
[00:01:24] Speaker C: Hi, Todd. Thanks for having me.
[00:01:27] Speaker B: As we begin, I want everybody watching to think about materials we pass by every day.
Construction debris, discarded wood waste, streams, byproducts and overlooked resources.
What if the future is not only about creating more, but about recognizing what still has value?
Dre, when you look at construction wood waste, what do you see that most people miss?
[00:01:53] Speaker C: Yeah, very good question, Todd. I see unrecognized energy and material supply, right? And most people actually see a disposal cost, if you like, or a mess or a lot of work in front of them.
At Woodshark, we see recoverable value, unused biomass, and I see measurable data.
[00:02:21] Speaker B: Right.
[00:02:22] Speaker C: That's a great opportunity, actually.
[00:02:27] Speaker B: How does artificial intelligence change the way we identify, sort, and redirect these materials that would normally be treated as waste?
[00:02:38] Speaker C: You know, AI gives us the ability to recognize material and scale, right? It's all about reduction of contamination, improving sorting of materials and the accuracy of sorting, and create a trackerable recovery stream, really a workflow in real time.
So that creates a consistency human really alone couldn't do.
[00:03:13] Speaker B: Can you elaborate that a little more? How does AI do that?
[00:03:17] Speaker C: So in our world at Woodshark, we use cameras and image recognition to understand materials in the first place. On job sites, we're looking into dumpsters or piles of material.
The AI is able to understand and confirm that kind of material we're actually gathering or sorting on job sites.
If a human eye would do it. You have to be there 24 hours.
A camera can just stream and can do the job for you. And it doesn't really matter if it is one pile or one dumpster, hundreds or thousands of dumpsters anywhere in the United States. So the same AI would run through it, which is very hard to scale if you would have that done by humans.
[00:04:08] Speaker B: So why is wood waste such an important entry point when we're thinking about waste streams and renewable energy?
[00:04:17] Speaker C: Yeah, you mentioned that in the beginning.
Wood waste is really an intersection of construction, carbon, biomass energy, and landfill reduction.
In the United States alone, we have 51 million tons of wood waste going into landfill from construction alone.
That's an enormous amount of potential biomass we can recover.
That's a really beautiful opportunity to create a recovery cycle, so to speak.
[00:04:50] Speaker B: So what's happening with that material today? If woodchuck is not on job site, what's happening with all that material?
[00:04:59] Speaker C: Well, generally speaking, all of that wood waste material would be unsorted, would be mingled in with other materials, and would be considered as waste hauling, and would go into landfills, where it's a hard opportunity or no opportunity really, to recover any of the CO2 in these landfills.
At the same time, you need to think about how and what kind of material we can actually create, meaning products, out of this potential wood waste.
So it goes in landfill, unfortunately.
[00:05:41] Speaker B: So from a technology standpoint, what technology had to become possible for the Woodchuck AI platform to exist and to function in today's world?
[00:05:51] Speaker C: Yeah, luckily we live in today's world. Right. We have now computer vision, Very, very capable computer vision and AI algorithm. We have a scalable cloud infrastructure. We do have computing which is able to process all of that. And on top of that, we're creating AI models really to understand the physical environment.
And it's finally mature enough to deploy on such a complex physical environment as a job site. So 10 years ago, you would have a very hard time to do that.
[00:06:25] Speaker B: So the image recognition that you are using, that you've built into the Woodchuck platform, is that new technology.
[00:06:35] Speaker C: So image recognition as such, image processing is not necessarily new. The way how we actually train our algorithm is new. The approach is very new.
First of all, we use data which actually does exist only on job sites. That really tailors our algorithm.
What that means at the end of the day is that we only need to understand the material we actually want to gather. We don't have to understand the entire world.
Think of it this way, positive and negative sorting.
You want to have red tomatoes on the left and everything Else on the right. What you do is you train your algorithm to understand what red tomatoes look like. You don't need to understand how an apple look like or anything else.
So that keeps it super performative and low energy range when we run our algorithms. So that's a new approach really.
[00:07:41] Speaker B: So how did you start training your algorithm?
[00:07:46] Speaker C: Very good question.
We actually started in the early process by generating imagery through AI. So we used AI to train our algorithms.
That was obviously just a bridge technology, a very agile way to get started. To prove our concept in the first place, that wasn't really operational.
The moment we had our own processing facilities. The first thing we did is deploying real cameras on a controlled environment. Controlled means we did have a fence around, which is important.
We did have somewhat control of light conditioning and obviously the material we want to test and recognize and train.
So with that running almost a year, if not even a little bit longer than a year, we gathered so much data that our algorithm now is stable and mature enough to be able to be deployed on job sites.
[00:08:52] Speaker B: Now, the Woodchuck platform, you made the choice to build this from scratch. You didn't buy building blocks or other people's base code. You built this from scratch, both the platform and the image capture system that you use, is that correct?
[00:09:08] Speaker C: That's right, yes. We wanted to start really from scratch.
We wanted to use a approach like, as I mentioned, really tailored to the specifics of our industry and really building a platform which has the user in mind in the first place. We have seen many systems out there. Some of them are really great, others fail because they don't really solve a real problem, or they're very abstract in the way, how they're actually being deployed and being used and have nothing really much to do with the operation.
At Woodshark, we have the benefit that we combine the operation of waste management on job site on one hand and building the technology to support and optimize the operation at the same time. So these things are actually falling together. And that means for us, a great opportunity to build a platform which at the end of the day really solves the problem on job sites for our people or the industry as such.
[00:10:12] Speaker B: That's. That's fantastic.
So now when waste becomes measurable and usable, how does that change the economics around sustainability?
[00:10:25] Speaker C: So the moment waste becomes measurable, becomes reportable, optimizable and also moneterable. Right. Sustainability shifts now from a cost center into a true infrastructure opportunity.
So data creates accountability and accountability creates value.
[00:10:50] Speaker B: Thank you very much. DRE CO FOUNDER of Woodchuck.
What stands out here is that the future may not only be built from new materials and new machines or new platforms. It may also be built from better intelligence applied to the materials already moving through our world.
When AI helps us see waste differently, we begin to see the possibilities of a cleaner system.
One where resources are not simply discarded, but redirected with purpose. We'll take a short break. When we come back, we'll look at how artificial intelligence moves from digital theory into physical infrastructure.
[00:11:27] Speaker A: We'll be right back with more conversations at the edge of technology and transformation. Stay tuned.
Every week on Infinite Future, we explore breakthrough innovation across every major frontier. We talk to AI architects, biotech pioneers, space entrepreneurs, clean energy disruptors, and the thinkers redesigning global systems. We don't just talk trends. We examine scalability, ethics, economic impact and real world implementation.
If you're building, investing in or leading the future, join me on Infinite Future only on NOW Media tv. Because the future isn't predicted, it's engineered.
And we're back. I'm Todd Thomas and this is Infinite Future on NOW Media tv. Let's look ahead.
[00:12:20] Speaker B: Welcome back to Infinite Future. Stay connected to this show and every Now Media TV favorite live or on demand anytime you like at Now Media TV. Or you can download the Now Media TV app. Or you can watch your favorite shows on YouTube, Spotify or iHeartRadio.
From business and news to lifestyle, culture and beyond, Now Media TV is streaming around the clock. Ready whenever you are.
I'm continuing my conversation with Dre Nietzsche Nelson, co founder of Woodchuck.
Now I want to talk about one of the most important shifts happening in innovation. AI is entering the physical world.
For many people, artificial intelligence still feels like something that lives inside their search engines and chatbots.
But the next major wave is physical. AI will increasingly help us classify materials, guide industrial processes, improve energy supply chains, reduce waste and make infrastructure more intelligent.
In this segment we want to explore the operational side of AI. How is practical intelligence applied to messy material real world environments?
So Dre, what changes when AI is no longer just analyzing digital information, but helping make decisions about physical materials in the real world?
[00:13:46] Speaker C: Yeah, it is a shift where AI is just informational and now becomes really operational. For us at Woodshark, it begins to influence logistics, recovery, quality of the material we're gathering on job sites. It does affect the infrastructure efficiency till even energy systems. When you think about what we actually providing at the end of the day. So we're transforming waste into product. So it is wood waste on job sites and it becomes biomass, which then transforms into energy systems or green energy.
So all of that is actually affected by AI injected in our operation.
So it really starts to have an impact on the real ecosystem.
[00:14:42] Speaker B: That's really interesting. Can you walk us through that process? So you're on a job site and you've got a pile of wood waste. How is that transformed into energy? Can you walk us through that process?
[00:14:54] Speaker C: Absolutely.
So imagine a job site is usually very messy, there's a lot of stuff going on and job sites are very little or enormous.
[00:15:04] Speaker B: Right.
[00:15:04] Speaker C: Depending on the project as such. So we're working for huge production, excuse me, construction efforts at the moment. And you think of materials that are already clean and sorted. It's not the reality. They're mingled in with plastic, they're mingled in with metal and so forth. All of that requires people on location. I will not be able to help with that. That there is a lot of operational effort needed.
So the moment we decouple materials from each other and put it in piles or put it in dumpsters, we still have no really a good understanding of what material quality we are talking about.
Think about wood waste in a variety of different qualities and it can be painted, it can be treated, it can be just being clean wood if you like, or what we call green wood.
AI and camera and image recognition will help us to pre sort that kind of material.
So this is really where the magic happened. On location we have ability to sort materials depending on what the biomass quality is going to be, or the quality of the biomass should be depending on what it is going to become. Either green energy or does it go back and remanufacturing.
So there are certain materials we cannot get into this supply chain and AI can help us and it can scale rapidly, it can be deployed on multiple locations and multiple dumpsters.
And it can help us to ensure that the income waste material quality achieves the level. We want to really ensure that the biomass quality at the end of a day is what we want.
[00:17:08] Speaker B: What is the hardest part of applying AI to something as variable and as imperfect as construction? Wood waste?
[00:17:19] Speaker A: Yeah.
[00:17:19] Speaker C: You have a uncontrolled physical environment. You have situations are influenced by light conditions, by weather.
Many other things are influencing this entire process, like contamination.
So you want to create a reliable biomass quality at the end.
So you need to deploy the AI in a way that it can help you to overcome these challenges. That means training data is the key. The more training data you have and all variances of either material, you want to gather light conditions and so Forth will help you to achieve that goal. It's a very interesting challenge to create, to deploy that kind of technology in something which is a construction site.
[00:18:12] Speaker B: So how does this image recognition really help to improve the quality and the usefulness of the of the biomass feedstock?
[00:18:21] Speaker C: So we're using it in a variety of different ways. First of all, we use it as what we call a chain of custody. Right.
Why is that important?
We have end clients, endpoints if you like, or offtakes like a power plant, which really needs to understand from where the material came from to be compliant and to ensure that the quality of the biomass they're actually transforming into green energy was indeed wood waste and not a forestry or something.
We use image recognition at the starting point. We collecting or rescuing that wood waste from the job site.
So there are cameras and mobile application being used. And our AI gives us confirmation that this material we're gathering is indeed the material we have promised together.
We also use geodata and we know where and what time it was gathered. So that's the starting point of our chain of custody. And we have the ability to deploy cameras on job sites to help us to optimize the chain of events. So what does that mean? That is not to confuse with AI agents. It's just simply helping us to optimize certain process which needs to take place. I give an example. A dumpster is usually picked up on schedule every so often, every day, once a week, whatever the schedule is. But that's set in stone.
Our AI is able to recognize the fill level of materials in a dumpster and can kick in a chain of event to call a pickup earlier or later to optimize the transportation cost, but also the CO2 efficiency for transporting material from A to B. So that's enormous if you think of a scale and not one dumpster, but hundreds if not thousands over a certain time.
[00:20:31] Speaker B: So where do human judgment and machine intelligence need to work together in this kind of system?
[00:20:39] Speaker C: Yeah, also very interesting. And I think that's important to me to get across. I think Woodshark AI is not a threat to jobs. It's the opposite. We have this hybrid approach, right? We do have obviously the operation on location, where people with expertise and experience help us to run the operation.
So it is important to get the context from these humans and the operational understanding. AI cannot really do that. AI handles the scale, the pattern, the recognition, the consistency and the speed of all of that. So the best of both systems are actually really coming together. That's what I call a Hybrid approach.
[00:21:28] Speaker B: So what does this teach us about the future of AI beyond software? What does it teach us about AI and energy, construction and infrastructure?
[00:21:38] Speaker C: Well, to me, I think the next wave of AI is the physical infrastructure, construction, logistics, energy, manufacturing and resource management. I think that's something we underestimate. Resource management is becoming a huge topic in the future, particularly with all of the construction we have ahead of us.
So we are moving really from a digital intelligence into an industrial intelligence, is what I would say.
[00:22:07] Speaker B: So, as the designer, the architect of this platform, how are you bridging this digital and physical gap?
[00:22:18] Speaker C: That's something I am very passionate about and have done for many decades. Willy. I think that design taught me that technology only matters if it really, truly solves the problem and if technology is adaptable to what operations and the physical environment actually provides us. So it's an important aspect that innovation really needs to improve to be adopted by the end user. So good systems reduce friction and do not add complexity. I think that's the secret of human centered design and product development.
[00:23:06] Speaker B: Do you have a particular example of your own work that you can give us on, say, a success story of where that really worked?
[00:23:15] Speaker C: First of all, it works at Woodshark. We are super excited about that.
The combination of physical and digital is a challenge in the, for instance, automotive industry.
I have been working in the automotive industry for many years.
Every time when we have a challenge to digitalize a physical space, that is the beauty of the work, Willie of digitalizing the that that can be an exhibit in the Peterson Car Museum, which I have been working on, which was phenomenal and fun and beautiful to see how children now engaging with your technology and understand context and learn by playing around with your solution as an exhibit in a museum or highly complex systems in a vehicle. When you think of autonomous driving vehicles or transition concepts between manually driving and semi autonomous driving.
So I think that's a muzzle I can bring in and bring in here at Woodchuck, digitalizing something very messy and complex like a construction site.
[00:24:41] Speaker B: Thank you so much, Dre.
What becomes clear is that the future of AI is not only digital. It's physical, it's operational.
It's deeply connected to the systems that power daily life.
The breakthroughs that matter most may not always look like science fiction. Sometimes they look like better sorting, cleaner materials, smarter infrastructure.
Finally, we're beginning to understand that.
We'll take a short break. When we return, we'll talk about design thinking and why the future needs innovators who can connect technology behavior, business and Sustainability.
[00:25:18] Speaker A: We'll be right back with more conversations at the edge of technology and transformation.
[00:25:23] Speaker B: Stay tuned.
[00:25:25] Speaker A: Every week on Infinite Future, we explore breakthrough innovation across every major frontier. We talk to AI architects, architects, biotech pioneers, space entrepreneurs, clean energy disruptors, and the thinkers redesigning global systems. We don't just talk trends. We examine scalability, ethics, economic impact and real world implementation.
If you're building, investing in or leading the future, join me on Infinite Future only on NOW Media tv.
Because the future isn't predicted, it's engineered.
And we're back. I'm Todd Thomas and this is Infinite Future on NOW Media tv. Let's look ahead.
[00:26:11] Speaker B: If you are an entrepreneur, a builder, designer or a technologist, this is the part of the conversation to lean into.
The future will not belong only to people who invent advanced technology.
It will belong to people who make that technology useful, trusted and scalable. I'm here today with Dre Nietzsche Nelson, co founder of Woodchuck. And now I want to shift from AI itself to the way design systems around it.
Dre brings a background connected to design leadership, digital product experience, user interfaces, user experience and innovation.
That matters because technology does not create impact simply because it exists. It has to fit into the real world. It has to work for contractors, operators, energy producers, manufacturers, investors, communities and the people who actually touch the system every day.
Climate tech solutions in particular often sound promising, but they only scale when they are operationally clear and easy enough for real people and businesses to use consistently.
So, Dre, how does design thinking translate and improve sustainability execution?
[00:27:23] Speaker C: So I think it is very important to always start with a problem you actually want to solve and not just bringing in technology for the stake of technology is now there. So you see many platforms out there which are developed in a good manner that I think like, okay, we want to solve a problem, but that's not enough. It is not related to a real existing operational process.
Sometimes these platforms are too abstract and not translating into the real operation on a daily basis.
But people who using those platforms are actually coming from that operational process and now wonder what to do with any of these very complex systems.
All of that to say you always have to have not only the problem you want to solve in mind, but also the user or your audience you are designing for. I think that's a very important aspect and I think the main success really for very good digital products out there.
[00:28:45] Speaker B: So Dre, how does your design background shape the way you think about building a company like Woodchuck?
[00:28:53] Speaker C: Yeah, it has multiple aspects. Again, it is the User centric design approach.
For whom are we designing for? What is the problem you want to solve?
And every time I would deploy something and develop something, we have obviously on one hand our vision in mind, but we're iterating on a daily or weekly time window on optimizing any features or solutions we're bringing in. It's a step by step incremental improvement with real users using your software and your solution on a daily basis.
At the same time, staying honest on your brand and product promise with a North Star vision ahead of you.
Very important. Otherwise you get lost in the sauce is what I would call it.
[00:29:48] Speaker B: So when you're designing for contractors for a construction site or for energy partners, what do you have to understand about their real world behaviors?
[00:29:59] Speaker C: Man, that's pretty clear. They want to move fast.
It has to be simple and it has to be applicable in their daily operation. It cannot add another friction. It cannot be another loop they have to go through to solve something they actually need to solve.
It's all about speed, ease of use, intuitiveness, and solving a true problem.
[00:30:28] Speaker B: So Dre, why do some sustainability technologies fail?
And how are you going to guarantee that Woodchuck does not follow that same pattern? How will Woodchuck succeed where other sustainable technologies have failed?
[00:30:44] Speaker C: I mean, luckily I would start here by myself.
I went through a variety of different projects or similar projects in terms of technology, but different industries where I learned a lot, I learned my lesson and all of that knowledge. And this experience comes here now and unfolds A B and you're looking at this from a distance, you can see that these systems have failed because either the workflows are way too complex or complicated and they're disconnected from the real operational behavior.
Right.
So what we do at Woodshark is we have the benefit of a very close relationship to not only the operation as we do the operation we operating the construction sites, we also have that great relationship to our construction companies.
So they give us immediate feedback. We have questionnaires we're sending out. We gain knowledge every day, working with them in a collaborative fashion. We understand the problems even better every day.
So you know, it is not enough to just have a great idea. You have to have the user and usability in mind. If you ignore that, your product will fail.
[00:32:09] Speaker B: So how do you balance vision with practicality when you were building something meant to change an existing waste stream or energy workflow?
[00:32:18] Speaker C: I'm a big fan of rapid prototyping and failing fast for many people. It sounds strange when you say fail fast.
Fail fast means just simply I learn much quicker.
And if I fail fast, I can adapt, I can adjust, and I can reinvent or even reconsider my current approach before I throw a lot of effort and money towards something which is not being proven right.
So to start with that, we need to have that long term vision and we solving these immediate operational problem on a daily basis with real adoption. And that happened incrementally over sprints like two weeks iterating, deploying something new, optimizing operation, getting the feedback from the operation team back and inject that in our digital platform.
So in order to earn that future, you have to go that step by step process and it requires a little patience, but it's significantly faster than just coming out of the box and saying, here it is, here's my solution. And you failed and burned a lot of money.
[00:33:30] Speaker B: So what role does story play?
Pardon me? What role does storytelling play in. In helping people understand that waste can become a resource. How does it play into helping people understand this platform and this process?
[00:33:46] Speaker C: Yeah, I love this question and I appreciate that actually, because storytelling doesn't really sound like a design method, but it is. It's actually a core of design methods and what it actually does, it helps people to emotionally understand the value of what you're trying to do before the economics really come up to scale and prove it right. So storytelling is a way to engage with people to help them to imagine what it actually looks like you do.
So it changes the perspective from, in our case, from waste to resource in a very simple way. Just tell the story.
People adopt ideas much faster if they're able to imagine the impact you're creating.
Storytelling is fundamental and I think a beautiful way to design a product.
[00:34:47] Speaker B: Thanks so much, Dre. What I hear in this part of the conversation is that innovation does not scale through technology alone. It scales through design, trust, usability, and storytelling.
The future needs systems that are not only intelligent, but adoptable. Because if people cannot understand it, use it, or see the value in it, even the best breakthrough remains stuck in as an idea. We'll take a short break. When we come back, we'll bring this all together. AI, energy, entrepreneurship, and the circular infrastructure needed for an abundant future.
[00:35:24] Speaker A: We'll be right back with more conversations at the edge of technology and transformation.
[00:35:29] Speaker B: Stay tuned.
[00:35:30] Speaker A: Every week on Infinite Future, we explore breakthrough innovation across every major frontier. We talk to AI architects, biotech pioneers, space entrepreneurs, clean energy disruptors, and the thinkers redesigning global systems. We don't do just talk trends. We examine scalability ethics, economic impact and real world implementation.
If you're building, investing in or leading the future, join me on Infinite Future only on NOW Media tv. Because the future isn't predicted, it's engineered.
And we're back. I'm Todd Thomas and this is Infinite Future on NOW Media tv. Let's look ahead.
[00:36:17] Speaker B: Welcome back to Infinite Future.
Stay connected to this show and every Now Media TV favorite live or on demand anytime you like at NowMedia TV. Or you can download the Now Media TV app and watch your favorite shows on YouTube, Spotify or iHeartRadio. From business and news to lifestyle, culture and beyond, Now Media TV is streaming around the clock. Ready whenever you are.
I'm closing out today's conversation with Dre, co founder of Woodchuck. And now I want to look at the bigger future this work points toward. If we can use AI to identify waste, redirect materials and give companies a transparent digital record of material flows, then we are not just improving one process, we're building the foundations for a transparent circular infrastructure systems where waste streams become supply chains and supply chains become part of the energy future.
Dre, when you think about the infinite future, how big could the opportunity become if we start start treating waste as intelligent supply chains and capturing and certifying auditable data throughout the chain of custody?
[00:37:33] Speaker C: Todd, there are many things to say, really. I think one thing to start with is looking at the limited resources we are going to face in the future.
With that said, I think this potential here is enormous because waste streams now could evolve to an intelligent supply chain to power energy reporting material recovery and a circular infrastructure. If you think of recycling and remanufacturing and so forth.
But the interesting thing is we're just tipping in there. This is just the beginning of this shift.
So I think we have a very, very interesting future here in front of us.
[00:38:24] Speaker B: What role can biomass play in a broader energy future that also includes solar, wind, battery storage, AI infrastructure and the next generation of grid demands?
[00:38:37] Speaker C: I see it as biomass and this is proven obviously already as a complementary layer alongside all of these other energy sources like solar, wind and so forth, as we just mentioned, and the demand for growing AI driven energy demand, it's even more important to stabilize that biomass supply chain and Woodchuck actually can do that.
[00:39:11] Speaker B: So the interesting thing to me, when I think about biomass and I think about Woodchuck's role, Woodchuck is really tapping into a net new biomass source.
When I think people think about biomass, they think about forestry residuals or paper and pulp residuals or agricultural residuals. But construction wood waste or manufacturing wood waste, that's really a net new source of biomass feedstock. How does that play into our energy future?
[00:39:45] Speaker C: Yeah, I think you just said it. It was overseen, overlooked, underestimated, and again, the numbers are impressive. We're talking about 51 million tons of biomass, or actually wood waste ending up in landfills just from construction. These are old numbers. That is all before the huge peak of enormous construction efforts as they happen today with data centers, for instance, hyperscale. And imagine the huge amount of wood waste we recovering and transforming that wood waste into a product and providing communities with green energy, I think is. And as an additional source to all of the others we already mentioned, it's starting to become a very impactful, trustful, stabilized source of supply chain for power plants.
[00:40:54] Speaker B: So, Dre, how should new entrepreneurs think about building companies at the intersection of climate impact, infrastructure and artificial intelligence?
[00:41:09] Speaker C: Yeah, what I would say is the vision alone doesn't really matter. You have to find way to operationalize your vision to start executing it. Only execution will really transform your vision and reality.
So my suggestion is put the feet on the ground and start executing. Learn, fail fast, iterate, deploy, learn and take risks. And everybody with you has to have a certain risk tolerance to do that in that exact way.
[00:41:51] Speaker B: So what has the Woodchuck journey taught you about turning big vision into a real operating company?
[00:42:02] Speaker C: Oh, good question. I think the same what I just proposed as a suggestion to entrepreneurs is applicable here.
When we started with Woodshark, we had that vision and we needed to get to a point to prove that what we have in mind truly works.
You need to have great partners. Without a partner, you will not make that. You have to have an understanding about technology and business and in an ideal scenario, also design to create something which is at the end of the day, a problem solving desirable solution for a market.
You also need to understand the market you are getting into the industry you want to work in.
So become an expert is mission critical.
But having partners with you who can extend on your expertise is the same exact way mission critical.
So that is what we learned at Woodshark.
I think our operational team is impressively strong. They're so fast, they're phenomenal. The work they do on location is breathtaking.
I have never seen such a clean and organized job site than a Woodshock job site. And I'm saying this as a German and I love it. I love when I see it and it is so well organized and that helps us to deploy technology.
It helps us to even improve those very, very strong operations we do and run.
That's my lesson learned.
[00:43:55] Speaker B: Okay, Dre, so looking into the future, what is the next big breakthrough that you believe is closer than most people think?
[00:44:06] Speaker C: I think it's around the corner. We're talking about AI driving resource intelligence, a system that understands the flow of materials in real time and can help us to automate across all industries.
So we are approaching this future where systems become an intelligent network. Really?
[00:44:42] Speaker B: And do you see Woodchuck leading the charge into the waste hauling and material recovery segment?
[00:44:50] Speaker C: We're leading the pack, Todd. We're leading the pack.
Yes, absolutely. We are ahead. We're definitely ahead.
[00:45:01] Speaker B: So, Dre, if the audience would like more information about Woodchuck, where can they find you and connect with you?
[00:45:09] Speaker C: We have a wonderful webpage that's Woodshark AI.
Please join, please visit, Please learn more about us.
If you want to reach out to us, you have all the contact information on that webpage. You can find us on LinkedIn, you can find us on Instagram. We are an open book and we are happy to connect.
[00:45:33] Speaker B: Are there any little surprise nuggets on that website that people should make sure to find?
[00:45:38] Speaker C: We have a beautiful section of videos and other news sections right there. We have a how it works and a little bit behind the scenes.
And we also going to have a new web page pretty soon.
[00:45:56] Speaker B: Any other big surprises or reveals that you can share with us coming up for Woodchuck.
[00:46:02] Speaker C: So we're working on a few technologies right now. I think one of the most exciting things is bringing the AI image recognition in the hand of our operational teams through a very intuitive mobile application.
So that really helps us to scale significantly faster with less investment in hardware to do the exact same job. Even better, we are right away on deploying it, and I'm really excited about that. And we'll hear pretty soon how operation team likes the application.
[00:46:42] Speaker B: Thank you so much, Dre. Thanks for being our guest here today. Really enjoyed the conversation.
Would love to have you back again.
Thanks so much for watching Infinite Future. You can see us at every Friday night, 7 o' clock central, or you can always download the Now Media TV app, or you can catch this show on Spotify, iHeartRadio or anywhere that you like to watch your podcast. Thank you so much.
