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LearningTranscript
00:00Imagine just a single picture of a cat eating a bowl of Japanese ramen.
00:05Right, just a quirky digital file.
00:07Yeah, exactly.
00:08No physical inventory, no warehouse, definitely no four-year graphic design degree,
00:14just a digital file that generated, I mean, nearly $100,000 in exactly 30 days.
00:20It is honestly hard to wrap your head around at first.
00:23It really is.
00:23And today, we are looking at the actual mechanics behind this.
00:26The modern economy's most highly leveraged business models.
00:30So, welcome to the Deep Dive Learner.
00:33We are incredibly glad you're here with us.
00:34Absolutely.
00:35Today, our core mission is dissecting the surprisingly accessible and, frankly, mind-blowing ways
00:41that everyday people are currently generating serious revenue using AI, like right now.
00:46And to unpack this, we're looking at two distinct roadmaps provided by our sources.
00:50On one side, we have this BDC-SO business-to-consumer creative product factory.
00:55We're specifically looking at how creators are leveraging Google's nano-banana AI,
00:59which is based on a really comprehensive breakdown by Wholesale Ted.
01:03Okay, and the other side?
01:04On the other side of the spectrum, we have high-value B2B or business-to-business service
01:09strategies, and these are mapped out by entrepreneur Dan Martel.
01:13Right.
01:13And we should probably establish right away that the sources we are looking at today,
01:18they are not peddling some theoretical, you know, get-rich-quick fantasy.
01:23Yep, not at all.
01:23The strategies outlined are about, quote-unquote, lazy money.
01:27And in this context, lazy simply means highly leveraged and heavily automated.
01:32We are looking at very real business models where the friction of production has been
01:37almost entirely eliminated.
01:38Yeah, the overarching theme across all of this source material is that AI simply provides
01:43the raw horsepower.
01:45It's like, it's the engine block.
01:46The engine block, I like that.
01:48Right.
01:48The actual revenue doesn't come from knowing some secret string of prompt text.
01:52It comes entirely from the application.
01:53Yeah.
01:54It's about how you package that AI output to solve a specific market demand.
01:58So let's start with the absolute lowest barrier to entry.
02:01If you, the learner, are sitting there listening to this and you don't have an established client
02:06roster or a massive B2B network, you need a starting point.
02:10You need something accessible.
02:11Exactly.
02:11And the most immediate avenue staring us in the face is print-on-demand, or POD, and self-publishing.
02:18The tool currently driving a massive wave of this is Nano Banana AI, which, by the way,
02:23is actually available for free right now if you are using the pro version of Google Gemini.
02:27And our sources highlight a really specific sub-genre on Amazon's Kindle direct publishing
02:33platform, Dead KDP, to illustrate just how frictionless this whole thing has become.
02:38What kind of books?
02:39Learn to draw books for children.
02:41Ah, okay.
02:42The mechanics of how this works are what really caught my attention in the wholesale data.
02:46So a creator wanted to make a book showing kids how to draw a smiling goldfish.
02:51Classic kids' book stuff.
02:52Right.
02:53But they didn't hire an illustrator.
02:55They simply asked Nano Banana to generate a reference image of a goldfish, and then they
03:00prompted the AI to break that specific image down into a six-step progressive drawing sequence.
03:06So it basically reverse-engineers the drawing.
03:08Exactly.
03:09The AI outputted the steps in seconds.
03:11And what's crucial here is how forgiving the software is.
03:15Like, if the AI messes up the geometry, say, it puts a close circle where a tail fin should
03:20go, you don't manually redraw it.
03:23You just prompt it again.
03:24Yeah, you just give it a text amount of, like, open that circle on the right side, and it
03:28alters the vector instantly.
03:30That's wild.
03:30And the economics of that specific workflow are just striking.
03:34That single goldfish book, published just two months prior to the source video's release,
03:39was estimated to be selling 23 to 29 copies every single day.
03:43Wow.
03:44Wait, every day?
03:45Every single day.
03:46That translates to roughly $250 to $300 a day in sales.
03:50And get this, the creator actually launched three similar books on the exact same day.
03:56Okay, so what's the math on that?
03:57It brought their total estimated daily sales to between $700 and $800.
04:01For goldfish drawings.
04:03Essentially, yes.
04:04I mean, that strategy scales perfectly into other formats, too, like scavenger hunt books.
04:08You know, the ones, massive, highly detailed pages where a child has to find hidden objects.
04:12Oh, yeah, I used to love those.
04:14Right.
04:14So you prompt Nana Banana to generate a massive, busy picture spread across two pages, like
04:20a crazy zoo scene.
04:21Then you take that image into a free design platform like Canva, drop a blank white rectangle
04:26in the corner, and feed that file back into the AI.
04:29Okay, and what does the AI do with the rectangle?
04:31You instruct it to turn the blank rectangle into a can-you-spot-this panel featuring specific
04:37animals from the main scene.
04:38Our sources found one creator utilizing this exact method, whose book is selling an estimated
04:445,000 to 9,000 copies every single month.
04:47The underlying mechanism here, Kindle Direct Publishing combined with AI, is what makes
04:52this so viable for a single operator.
04:54When a customer clicks buy on that scavenger hunt book, Amazon's facilities print that single
04:59copy on demand.
05:00Just one copy at a time.
05:02Exactly.
05:02They box it, ship it out, take their cut for the logistics, and drop the net profit into
05:07the creator's account.
05:08The person who designed the book literally never touches physical paper.
05:11It's basically like owning a global printing press, but without having to pay for the warehouse
05:16space.
05:16You are essentially just minting digital assets and letting Amazon or apparel companies like
05:22Printify or Printful handle the physical reality of the product.
05:26Right.
05:27And we see this exact same set-and-forget architecture in the apparel space.
05:31Going back to that t-shirt design you mentioned in the intro, the picture of a cat eating a bowl
05:36of Japanese ramen.
05:37Such a weird, specific thing.
05:39It is.
05:40It wasn't high art at all.
05:41It was just a quirky, highly specific trend on Etsy and Amazon.
05:45Yet that single digital file resulted in over 4,000 sales in one month.
05:49The math on that comes out to roughly $79,000 to $99,000 in gross sales in a 30-day
05:54window.
05:55Which just goes to show AI effectively removes the technical skill barrier of graphic design
05:59entirely.
06:00Because you no longer need to spend years mastering Adobe Illustrator to draw a ramen-eating cat,
06:05the value in the market shifts completely.
06:07It moves away from the execution of the art.
06:09Exactly.
06:10And it lands squarely on market research and trend spotting.
06:14The winner is the person who can find the hungry crowd and feed them exactly what they
06:18want instantly.
06:20That volume play is fascinating.
06:22You are essentially throwing a massive net to catch thousands of buyers interested in
06:27a broad trend.
06:29But there is a totally different approach outlined in our sources where you trade that massive
06:34volume for a much higher margin.
06:36By personalizing the output.
06:38Exactly.
06:38Yeah.
06:38You're looking at the premium market there.
06:40Personalization is historically the single highest valued trait by consumers.
06:44But, you know, it was always bottlenecked by human labor.
06:48Because it takes time to make something custom.
06:50The prime example the sources give is custom pet portraits.
06:54Let's trace the workflow on this because it's brilliant.
06:56You, the customer, take a photo of your dog on your phone and upload it to a specific Etsy
07:01store.
07:02Okay.
07:02Pretty standard so far.
07:03Right.
07:04The store owner has a library of pre-generated AI templates like a 19th century king, a medieval
07:10knight, an astronaut, whatever.
07:12They feed your dog's photo and the template into Nano Banana.
07:15And in under a minute, the AI seamlessly maps the dog's head onto the template.
07:21Under a minute?
07:21That's the crazy part.
07:22Yeah.
07:22And the store isn't even printing physical products in some cases.
07:25They're just selling the digital download for people who want custom portraits in, say,
07:31a cute chibi anime style or a Pixar 3D style, which the customer then just prints at home.
07:36And the output is incredibly convincing because the AI understands ambient lighting, texture,
07:41and pixel blending.
07:42Doing that manually would take a human Photoshop expert hours of masking and color grading to
07:48get right.
07:48Hours versus 60 seconds.
07:50Exactly.
07:50The financial upside of removing that bottleneck is massive.
07:54One Etsy store executed these custom shirts, was doing around 259 sales in a single 24-hour
07:59period.
07:59Oh my God.
08:00Yeah.
08:01It's $26 a shirt.
08:02That's roughly $6,700 a day in revenue.
08:04Okay.
08:05I have to push back a little on the lazy aspect of this specific model, though.
08:08If you are processing 259 bespoke orders, managing the uploads, and running the prompts
08:14for every individual customer, isn't that just a new type of manual labor?
08:19That's a fair point.
08:20I mean, doesn't doing custom one-off portraits defeat the purpose of the highly automated
08:25printing press analogy we just discussed?
08:27Well, it does require more active management than the set and forget book, sure.
08:31But you have to view it through the lens of leverage.
08:34People will pay a massive premium to see their own pet in a piece of art.
08:38True.
08:38People love their pets.
08:39Right.
08:40What the AI is doing is collapsing the production time required to capture that premium.
08:45Historically, a bespoke portrait of a pet took days of painting or digital rendering.
08:51Now, mapping ahead takes 60 seconds.
08:53You are processing orders, yes.
08:54But the AI allows a single operator to scale a highly personalized bespoke product line in
09:00a way that was literally impossible just five years ago.
09:03So, the premium totally justifies the 60 seconds of manual processing per order.
09:09And, you know, if we are talking about high perceived value and collapsing production time,
09:14we have to look at the breakdown of AI time-lapse video generation.
09:18Oh, this one is fascinating.
09:19The sources detail a workflow for creating those incredibly satisfying viral videos where an
09:25empty room magically transforms into a luxury space.
09:28You know, the ones on Instagram.
09:29I get lost in those all the time.
09:31This specific process utilizes NanoBanana to generate the static assets, and then it combines
09:38them with an AI video animator called Clink.
09:41The daisy-chaining process here is brilliant.
09:43First, you ask NanoBanana for a high-resolution picture of an empty concrete room.
09:48You save that file.
09:49Then, you prompt the AI to edit that exact image by adding black decorative stones to the
09:54floor.
09:54You save that second file.
09:55Okay, so you have a before and an after.
09:57Right.
09:58You take those two static images to Clink, setting the empty room as the start frame and
10:03the stone floor as the end frame.
10:05You type a prompt-like time-lapse of workers adding stones.
10:09Clink doesn't just transition the images.
10:12It literally hallucinates the video frames in between, generating little digital workers
10:17physically laying the stones down.
10:19And then you just repeat that process sequentially.
10:21Exactly.
10:22You take the image of the stone floor back to NanoBanana, ask it to add an epoxy layer, and run
10:28those
10:28two through Clink.
10:29Then you add luxury furniture and run it through Clink again.
10:33So you're building a whole narrative.
10:34Yeah, you stitch those generated mini-clips together in a basic video editor, speed the
10:39whole thing up, and you have a viral home renovation time-lapse.
10:42But here is the kicker.
10:44The server cost for doing this completely blew my mind.
10:47What did it come out to?
10:48Using Clink's basic plan, that entire video sequence costs about 54 cents in server credits.
10:5454 cents.
10:55When you compare that to the traditional alternative, the disruption is just obvious.
10:59I mean, hiring a human 3D animator to build the wireframes, texture the models, and render
11:04that sequence would cost anywhere from $200 to $500.
11:08Not to mention days of rendering time.
11:10Exactly.
11:11The cost of production has collapsed to literal pennies.
11:14And creators are monetizing these time-lapses by posting them as Instagram reels.
11:19One account analyzed in the sources had 4.8 million views on a renovation video.
11:24Wow.
11:24Yeah, and their profile linked directly to a phone number.
11:27They're basically capturing the attention of people mesmerized by luxury home improvements,
11:32and selling those captured phone numbers as high-quality leads to local contractors.
11:36That is so smart.
11:38Others are operating on a smaller scale, too, using the same animation tools to create looping
11:42visual canvas covers for musicians on Spotify.
11:45They sell the service on freelance marketplaces like Fiverr for around $60 a gig.
11:49But there is a ceiling to consumer markets based purely on discretionary income, right?
11:56Dan Martell's data suggests that if you want to make the jump from a $50-a-day side hustle
12:00to generating $500 to $1,000 a day, you have to stop selling to individual people.
12:06And start selling to businesses.
12:07Exactly.
12:08You have to start solving critical bottlenecks for businesses.
12:10Right, because businesses operate with dedicated budgets designed to solve painful problems.
12:15And in the modern digital landscape, one of the most painful problems for any brand
12:20operating on YouTube is getting viewers to actually click on their videos.
12:24It's all about the click.
12:25It is.
12:26This is the foundation of high-ticket AI thumbnail design.
12:29To a casual viewer, a thumbnail seems pretty trivial.
12:33But to a YouTube creator running a business, the click-through rate dictated by that thumbnail
12:37is literally the difference between a video losing money or generating massive ad revenue.
12:43So the stakes are high.
12:44Martell's sources emphasize that you aren't just typing a vague prompt into MidJourney
12:49and hoping for a pretty picture.
12:50It is a highly analytical process.
12:53You're using data.
12:54Heavily, you use dedicated data platforms like 1 of 10 or ViewStats to relentlessly study
13:00the viral geometry, color theory, and text placement of successful videos within a very
13:05specific niche.
13:06You identify the visual patterns that drive clicks, and then you use AI tools to execute
13:11those patterns flawlessly for your clients.
13:13And creators are happily paying $50 to $400 a day for this.
13:17Martell mentions observing a dedicated thumbnail designer sitting in a room with two monitors
13:22just iterating high-converting designs for five different YouTube channels simultaneously.
13:27That's incredible leverage.
13:28And the B2B applications expand significantly when you look at web infrastructure, too.
13:33There are roughly 22 million small businesses in North America, many with severely outdated web
13:38presences.
13:39Oh, absolutely.
13:39The local plumber with a website from 2004.
13:41Exactly.
13:42Historically, building a robust custom website cost a business $5,000, $10,000, sometimes $25,000
13:48and took months.
13:49Now, the workflow utilizes no-code AI builders like Framer AI, Bolt, or Reloom.
13:55The mechanics of Reloom are particularly interesting here.
13:58Instead of writing CSS code, you simply describe the site architecture to the AI.
14:05The AI generates the structural wireframe.
14:07Just from a description.
14:09Yep.
14:09Then, you use ChatGPT to analyze the target audience and write highly targeted sales copy
14:15while utilizing mid-journey to generate bespoke brand imagery.
14:19The no-code AI stitches it all together into functional code.
14:23So, you can literally build a highly optimized, beautiful site in a single afternoon and charge
14:28top dollar because the business is paying for the final result, not the hours it took
14:32you to assemble it.
14:34Exactly.
14:34Which brings us to the million-dollar question for you, the learner, listening to this.
14:38How do you actually convince these businesses to hand you their money when you don't have
14:41a massive portfolio or insider connections?
14:43Right.
14:44The hardest part is getting the client.
14:46This is where Martell's audit-to-deal framework comes into play.
14:49It is arguably the single most valuable behavioral strategy discussed in the B2B sources.
14:54So, let's break it down.
14:55The process starts with picking a highly specific niche.
14:58Think local dentists, specialized auto shops, or maybe fitness influencers.
15:04Next, you scrape the leads, building a comprehensive database from LinkedIn or Google.
15:10A process Martell calls mapping the universe.
15:13Okay.
15:14So, you have your targets.
15:15Then what?
15:16The third step is where the leverage really kicks in.
15:18You run an audit, you go to a prospect's YouTube channel or their outdated website, and you record
15:24a free 60-second Loom video capturing your screen.
15:28So, you're talking directly to them.
15:30Right.
15:30You say something like, hey, I was looking at your site, and I noticed your landing page
15:33structure is causing you to lose conversions.
15:36Here are three specific things I would change right now.
15:38And by the way, I actually used AI to build a custom mock-up of what your new site could
15:43look like.
15:44And you just give that away.
15:45You send that video directly to the decision maker, leading to step four, which is the low-risk
15:49offer.
15:49I love that.
15:50The psychology of the audit-to-deal process is basically, it's like a mechanic noticing
15:54your car has a flat tire while you're in a grocery store parking lot.
15:58Oh, that's a great analogy.
15:59They walk up with a jack, change the tire perfectly in 60 seconds flat, and then they
16:03hand you their business card.
16:05You aren't pitching a theoretical service.
16:07You are proving undeniable, hyper-specific competence up front.
16:12And the reason this strategy is viable today, and wasn't 10 years ago, comes down to the
16:16zero marginal cost of labor.
16:18AI allows you to do bespoke, speculative work like the mock-up thumbnail or the draft website
16:24wireframe at zero cost to yourself.
16:27Right.
16:27It takes you two minutes of generating prompts instead of five hours of manual coding.
16:31Exactly.
16:31And the business owner doesn't care that an AI assisted you.
16:34They care that you proactively identify their specific bottleneck and handed them the solution
16:40before they ever opened their wallet.
16:42It creates this almost irresistible sense of reciprocity.
16:45It's so powerful.
16:47But, you know, everything we've explored so far, whether it's selling custom shirts or pitching
16:51a website audit, still involves actively selling a product or a service.
16:55Right.
16:55You're still doing a transaction.
16:57But the sources push the boundary even further.
16:59We need to examine what happens when you use these AI tools to build completely autonomous
17:04digital machines.
17:05Ah, okay.
17:07This is the realm of true systems automation and faceless media empires.
17:12We are moving from single transactions to building recurring revenue engines.
17:16Let's look at faceless YouTube channels as an example.
17:19The sources detail channels operating in high CPM niches, meaning the topics command premium
17:25rates from advertisers, like personal finance or software tutorials.
17:29So the ads pay out a lot.
17:30Right.
17:31These channels are generating $50,000 to $70,000 a month in ad revenue.
17:35And you never see a human face on screen.
17:37The workflow is entirely orchestrated by AI.
17:40How does the workflow actually look for the operator, though?
17:43The human operator acts essentially as a conductor.
17:46You utilize ChatGPT to analyze successful videos and structure the narrative arc of the script
17:51to maximize viewer retention.
17:52Then you feed that script into tools like Synthesia or 11 Labs.
17:57Oh, I've heard of 11 Labs.
17:59The voice cloning.
17:59Yes.
18:00These platforms generate incredibly realistic virtual avatars and clone human voices with
18:05natural cadence, you know, adding breath sounds and pauses to read the script perfectly.
18:09The creator is just orchestrating the assembly of digital parts.
18:12The same structural approach is being applied to text, too, with AI blog generation for SEO.
18:18The sources emphasize a massive shift in how we find information.
18:22The quote they use is, search is the new chat prompt.
18:25Search is the new chat prompt.
18:27That's a big shift.
18:27It's huge.
18:28Because consumers are asking questions directly to large language models instead of traditional
18:33search engines, companies are desperate to ensure their data ranks inside the AI's training
18:39ecosystem.
18:39So they need a ton of content.
18:41Exactly.
18:42This is resulting in mass generation workflows.
18:45Operators are using AI to pump out highly structured specific blogs at $10 a piece for massive SEO farms.
18:52On the more bespoke end of things, Martell highlights a client who generates over $100,000 a month doing nothing
18:59but adapting long-form podcast audio into high-ranking SEO blogs for corporate clients.
19:04Which is brilliant because the mechanism there relies on the fact that large language models heavily favor structured, comprehensive text.
19:11The AI takes an unstructured rambling audio transcript, extracts the core arguments, and formats it with the precise semantic HTML
19:18headers and bullet points that search crawlers prioritize.
19:21It organizes the chaos, which naturally leads to the ultimate high-ticket B2B service discussed, the AI automation agency.
19:30Yes.
19:30This involves going into a business and building internal bots to automate their back-end workflows.
19:36We're talking things like managing cold email outreach campaigns or parsing messy spreadsheets to automate their bookkeeping.
19:43But this is where I actually found myself questioning the longevity of the model a bit.
19:46Oh, really? Why?
19:47Well, Dan Martell mentions in his breakdown that he actually taught this AI automation process to his 12-year-old
19:53son.
19:54Right.
19:54So if a 12-year-old can sit down and learn how to automate a company's back-end workflows using
19:59these tools, won't the market be completely flooded with competitors by next week?
20:04Like, where is the protective moat for this business?
20:06It is a valid concern.
20:07It really is.
20:08But it fundamentally misinterprets how corporate value is actually generated.
20:12Martell introduces this concept of 10,000 iterations versus 10,000 repetitions.
20:18The protective moat is not access to the AI tool itself.
20:21I mean, everyone has an internet connection.
20:23Everyone has access to ChatGPT.
20:25Right.
20:25The tools are democratized.
20:26Exactly.
20:27The actual moat is the continuous 1% improvement in applying that tool to a highly complex, specific business problem.
20:35You give an example of that.
20:37Sure.
20:37Take bookkeeping automation.
20:39Historically, a hard-coded bot would completely break if a spreadsheet had a typo.
20:44But large language models understand semantic context.
20:48They don't just read the cell.
20:49They comprehend that an entry for St. Bucks actually means Starbucks.
20:53Ah, I see.
20:54Right.
20:54And they categorize the expense correctly without human intervention.
20:58So a 12-year-old can easily learn the mechanics of the software interface.
21:02But understanding the nuanced logic of a specific company's financial pipeline to build the right contextual automation, that requires deep
21:11business acumen.
21:12So the value isn't knowing which buttons to push.
21:14The value is knowing why the machine needs to be built in the first place and what logic it needs
21:18to follow.
21:19Exactly.
21:20Furthermore, the goal of internal AI automation isn't to fire the workforce.
21:24It is about freeing up human capital.
21:26When you automate the tedious data entry of a company's bookkeeping, you aren't replacing the accountant.
21:32You are freeing that expert up to focus on creative, needle-moving financial strategy instead of manually dragging spreadsheet cells
21:40around.
21:41We are watching a real-time shift in the workforce here.
21:44The most valuable skill is no longer processing information.
21:48Because, let's face it, computers simply process information better now.
21:52The most valuable skill moving forward is orchestrating systems.
21:55You want to be the conductor of the orchestra, not the person trying to play the flute faster than a
22:00machine.
22:00Exactly.
22:01And if you're trying to sell this kind of internal automation to a company, but the audit-to-deal process
22:07feels impossible because you obviously can't see their messy internal spreadsheets from the outside, Martel's advice is simple.
22:13You just do the work for free.
22:15Just give it away.
22:15Yeah.
22:16You reach out, offer to build a specific, tailored automation at zero cost, entirely in exchange for a documented case
22:22study.
22:23Once you do that five or ten times, you possess undeniable proof of your value in the market.
22:29And those same companies will likely just put you on retainer to maintain the systems you just built.
22:33We have covered a massive amount of ground today.
22:36Let's briefly summarize the two distinct blueprints we've explored for generating revenue with AI.
22:40First, we have the B2C Creative Volume and Premium Play.
22:45This involves utilizing tools like Google's Nano Banana to create highly leveraged digital products.
22:51Right.
22:51Your learn-to-draw books, print-on-demand trends, custom pet portraits.
22:56Or capturing those high margins with time-lapse video generation.
22:59It is all about leveraging AI to operate as a one-person digital factory.
23:03And then the second blueprint is the B2B high-value service play.
23:06This requires taking those exact same generation capabilities and applying them to solve expensive bottlenecks for actual businesses.
23:14Like the YouTube thumbnails or the web design.
23:16Exactly.
23:17Building highly optimized YouTube thumbnails, generating no-code website infrastructure, or orchestrating internal AI automations.
23:26And the key to unlocking those corporate budgets is the audit-to-deal framework, leveraging the zero marginal cost of
23:33AI to prove your hyper-specific competence up front before ever asking for a dollar.
23:38It all comes directly back to you, the learner.
23:41Whether you are looking for a highly leveraged side hustle, or you want to entirely streamline the workflows of your
23:47current day job, the technical barrier to entry has officially been demolished.
23:51The tools we dissected today are essentially free, or they cost literal pennies per use.
23:57The only remaining requirement is targeted action.
23:59You just have to pick a specific niche, study the patterns, and start iterating.
24:03The technology itself is no longer the hurdle holding anyone back.
24:06Your willingness to strategically apply it to a market demand is the only variable left.
24:11But as we wrap up this deep dive, I want to leave you with one final lingering thought to ponder.
24:16We talked earlier about how AI has collapsed the cost of production.
24:20If artificial intelligence drops the cost of creating a stunning home renovation time-lapse, a deeply personal custom pet portrait,
24:28or a flawlessly formatted 2,000-word SEO blog post to literal pennies, what happens to the perceived value of
24:36human imperfection?
24:37That's a great question.
24:38Ten years from now, when AI can generate anything instantly and flawlessly, will a product that is stamped 100%
24:44human-made, complete with all its inherent flaws, asymmetrical lines, and inefficiencies, become the ultimate, ultra-expensive luxury status symbol?
24:52It is a fascinating question about the future of how we assign value.
24:55Something for you to chew on.
24:56Until next time, keep learning.
24:58Something for you to chew on.
24:58Something for you to chew on.