WEBVTT 00:00:00.000 --> 00:00:03.580 Imagine someone offers you this piece of land, 00:00:03.980 --> 00:00:06.480 right? Quiet Valley. And then just before you 00:00:06.480 --> 00:00:09.140 decide, they reveal the blueprints for this huge 00:00:09.140 --> 00:00:10.779 city they're going to build there. That's Palo. 00:00:10.970 --> 00:00:12.970 Well, that's sort of where we are with a new 00:00:12.970 --> 00:00:15.949 AI technology today poised to unlock, they say, 00:00:16.250 --> 00:00:19.010 a four hundred billion dollar opportunity. Welcome 00:00:19.010 --> 00:00:20.769 back to Deep Dive. This is where we try to unpack 00:00:20.769 --> 00:00:23.510 these big complex ideas for you. And today we 00:00:23.510 --> 00:00:26.410 are diving deep into Google's Notebook LM, specifically 00:00:26.410 --> 00:00:29.969 its video generation feature. It's powerful, 00:00:30.030 --> 00:00:32.789 but actually remarkably simple to use. Exactly. 00:00:32.829 --> 00:00:35.250 We're going to look at what makes this tool genuinely 00:00:35.250 --> 00:00:37.630 different from other AI, how these new video 00:00:37.630 --> 00:00:40.509 capabilities actually function and maybe most 00:00:40.509 --> 00:00:43.609 importantly for you, five really concrete step 00:00:43.609 --> 00:00:45.729 -by -step ways you could start generating income 00:00:45.729 --> 00:00:48.770 with it, like right now. It's about moving from 00:00:48.770 --> 00:00:51.689 just watching this stuff happen to actually being 00:00:51.689 --> 00:00:55.640 part of it, to, you know, earning. OK, so let's 00:00:55.640 --> 00:00:58.259 just set the stage here a bit. We're really in 00:00:58.259 --> 00:01:00.679 the early, early days of a massive technological 00:01:00.679 --> 00:01:02.619 shift. Think back to the internet or smartphones. 00:01:03.119 --> 00:01:05.180 This feels like it's on that scale. Experts are 00:01:05.180 --> 00:01:08.480 projecting this huge $400 billion opportunity 00:01:08.480 --> 00:01:11.120 in applied AI services. And this tool we're discussing, 00:01:11.560 --> 00:01:13.680 Notebook LM, it seems to be right at the heart 00:01:13.680 --> 00:01:15.700 of that potential. Exactly. It really does feel 00:01:15.700 --> 00:01:18.280 that way. But before we jump into the money side, 00:01:18.280 --> 00:01:20.019 we really need to get a handle on what Notebook 00:01:20.019 --> 00:01:22.280 LM actually is. Because it's not just another 00:01:22.280 --> 00:01:25.219 chatbot like ChatGPT or Jim. and understanding 00:01:25.219 --> 00:01:27.180 that difference is absolutely key to seeing its 00:01:27.180 --> 00:01:30.140 real value. Right. Most of us have probably played 00:01:30.140 --> 00:01:32.780 around with those large language models, LLMs. 00:01:33.000 --> 00:01:35.000 They're trained on just this enormous amount 00:01:35.000 --> 00:01:38.040 of data from the public internet, which makes 00:01:38.040 --> 00:01:40.680 them incredibly knowledgeable about, well, almost 00:01:40.680 --> 00:01:43.939 anything. But that huge data set also leads to 00:01:43.939 --> 00:01:47.079 a pretty critical flaw, hallucination. Yeah, 00:01:47.159 --> 00:01:49.620 hallucination. That's the AI term for when it 00:01:49.620 --> 00:01:52.730 just... make stuff up. It sounds confident and 00:01:52.730 --> 00:01:54.849 sounds plausible, but the information is actually 00:01:54.849 --> 00:01:57.269 wrong. Invented details. And that's a massive 00:01:57.269 --> 00:01:59.950 problem if you need reliable information for, 00:01:59.950 --> 00:02:02.450 say, professional work. Oh, absolutely. You can't 00:02:02.450 --> 00:02:04.829 build a business strategy or write an accurate 00:02:04.829 --> 00:02:07.890 report based on fabricated facts. The trust just 00:02:07.890 --> 00:02:10.650 isn't there. So Notebook LM approaches this completely 00:02:10.650 --> 00:02:13.110 differently. It uses what's called a restricted 00:02:13.110 --> 00:02:15.530 knowledge base. Sometimes people call it grounded 00:02:15.530 --> 00:02:17.550 AI. And this is where it gets really interesting 00:02:17.550 --> 00:02:21.189 because you become the source of truth. How does 00:02:21.189 --> 00:02:23.069 that work exactly? Well, instead of relying on 00:02:23.069 --> 00:02:25.650 the whole internet, you feed it specific trusted 00:02:25.650 --> 00:02:28.909 documents. Think PDFs, Google Docs, notes you've 00:02:28.909 --> 00:02:31.069 taken, even transcripts from videos or meetings. 00:02:31.789 --> 00:02:34.409 The AI then operates only within those sources 00:02:34.409 --> 00:02:37.189 you provided. Ah, okay. So it doesn't pull in 00:02:37.189 --> 00:02:39.550 random stuff from outside. Nope. It's like you've 00:02:39.550 --> 00:02:42.550 given it its own private curated library and 00:02:42.550 --> 00:02:44.729 locked the door to everything else. And the really 00:02:44.729 --> 00:02:47.490 big deal here, the game changer, is that every 00:02:47.490 --> 00:02:50.750 single piece of information it generates, it's 00:02:50.750 --> 00:02:54.250 directly tied back to a specific passage in your 00:02:54.250 --> 00:02:56.990 documents. It actually provides citations right 00:02:56.990 --> 00:03:00.139 there in the output. Exactly. built -in citations. 00:03:00.419 --> 00:03:02.819 So you never have to guess if the AI just invented 00:03:02.819 --> 00:03:05.319 something. You know it's 100 % faithful to the 00:03:05.319 --> 00:03:07.479 material you gave it. Which is a huge leap in 00:03:07.479 --> 00:03:09.780 terms of reliability and accountability. Makes 00:03:09.780 --> 00:03:12.400 it incredibly valuable for anyone needing precision. 00:03:13.000 --> 00:03:15.460 Researchers, legal teams, students, and as we're 00:03:15.460 --> 00:03:17.860 about to dig into, content creators like you. 00:03:18.379 --> 00:03:21.159 So the core difference is that total reliance 00:03:21.159 --> 00:03:23.400 on user -provided information, right? That's 00:03:23.400 --> 00:03:26.490 its superpower. Yes, absolutely. It ensures accuracy 00:03:26.490 --> 00:03:29.490 by sticking strictly to only your specific sources. 00:03:30.169 --> 00:03:32.169 And Notebook LM had already got some attention 00:03:32.169 --> 00:03:34.530 for doing something pretty neat before this video 00:03:34.530 --> 00:03:37.289 update. It could generate these podcast -style 00:03:37.289 --> 00:03:39.250 audio conversations directly from documents. 00:03:39.569 --> 00:03:41.629 Oh, yeah, I remember that. You could feed it 00:03:41.629 --> 00:03:44.210 a dense research paper. Right. And it would spit 00:03:44.210 --> 00:03:46.930 out a two -person discussion, breaking down the 00:03:46.930 --> 00:03:50.689 key concepts. made complex text way more accessible. 00:03:50.870 --> 00:03:52.949 That was already pretty powerful. It really was. 00:03:53.449 --> 00:03:55.789 But this latest update, the video generation, 00:03:55.949 --> 00:03:59.169 takes it quite a bit further. Now, we should 00:03:59.169 --> 00:04:02.469 be clear. This isn't about creating, you know, 00:04:02.849 --> 00:04:05.710 Hollywood -level movies with AI actors and complex 00:04:05.710 --> 00:04:09.050 scenes. No, no. Its beauty is really in its elegant 00:04:09.050 --> 00:04:11.969 simplicity and how efficient it is. So what does 00:04:11.969 --> 00:04:14.729 it actually create? It makes these clean, professional 00:04:14.729 --> 00:04:18.290 -looking slide -style visuals. And crucially, 00:04:18.410 --> 00:04:21.050 they're perfectly synchronized with the AI -generated 00:04:21.050 --> 00:04:23.310 audio narration, which is also based on your 00:04:23.310 --> 00:04:25.529 document. Think of it like a really dynamic, 00:04:25.870 --> 00:04:27.689 intelligent presentation. OK, so like lecture 00:04:27.689 --> 00:04:31.370 slides almost. Kinda, yeah. But smarter. As the 00:04:31.370 --> 00:04:33.790 AI audio discusses a concept from your text, 00:04:34.290 --> 00:04:36.629 a slide pops up with relevant text, maybe some 00:04:36.629 --> 00:04:39.069 bullet points or a key quote, all pulled directly 00:04:39.069 --> 00:04:40.889 again from your source material. So it's like 00:04:40.889 --> 00:04:42.990 a podcast, but it comes with perfectly timed 00:04:42.990 --> 00:04:45.649 visual A's that reinforce the points. Exactly. 00:04:45.829 --> 00:04:47.730 And these aren't just generic templates either. 00:04:47.810 --> 00:04:50.569 That's the cool part. Every slide, every bullet 00:04:50.569 --> 00:04:53.529 point is dynamically generated based on the specific 00:04:53.529 --> 00:04:56.389 content you fed it. So every video is unique 00:04:56.389 --> 00:05:00.089 and perfectly tailored to your information. It 00:05:00.089 --> 00:05:02.569 sounds like the absolute fastest way to turn 00:05:02.569 --> 00:05:05.350 a block of text into a professional, shareable 00:05:05.350 --> 00:05:08.550 video. It really is. Takes minutes. Whoa. Just 00:05:08.550 --> 00:05:10.569 thinking about the scale of that. Imagine you 00:05:10.569 --> 00:05:13.110 have recordings from an entire conference, all 00:05:13.110 --> 00:05:15.689 the talks, the panels. You could turn that mountain 00:05:15.689 --> 00:05:18.329 of content into hundreds of these short, engaging 00:05:18.329 --> 00:05:21.230 videos, dynamically generated, all perfectly 00:05:21.230 --> 00:05:23.490 aligned with what was actually said. The potential 00:05:23.490 --> 00:05:26.670 for sharing knowledge there is immense. So it's 00:05:26.670 --> 00:05:29.250 really about turning text into these engaging, 00:05:29.550 --> 00:05:32.230 visually supported learning experiences faster. 00:05:32.509 --> 00:05:34.689 Exactly. It makes complex information much easier 00:05:34.689 --> 00:05:36.730 to understand and share visually and at serious 00:05:36.730 --> 00:05:39.269 speed. Yeah. Okay, so now let's connect this 00:05:39.269 --> 00:05:42.230 cool tech to actual practical income streams, 00:05:42.269 --> 00:05:44.370 because these methods we're going to talk about, 00:05:44.389 --> 00:05:46.050 they solve real problems that businesses are 00:05:46.050 --> 00:05:48.709 already paying to fix. Right, moving from the 00:05:48.709 --> 00:05:51.350 what's to the how you can use it. Let's dive 00:05:51.350 --> 00:05:54.870 into method one, daily research automation. This 00:05:54.870 --> 00:05:57.149 sounds like becoming sort of an indispensable 00:05:57.149 --> 00:06:00.430 automated intelligence source for a specific 00:06:00.430 --> 00:06:03.009 industry. Precisely. Think about we're all grounding 00:06:03.009 --> 00:06:05.639 in information. Business leaders, investors, 00:06:06.079 --> 00:06:09.100 policymakers. They spend hours every single day 00:06:09.100 --> 00:06:12.100 just sifting through news, reports, articles. 00:06:12.339 --> 00:06:14.339 Trying to find the signal and the noise. Exactly. 00:06:14.720 --> 00:06:17.459 You can solve that pain point. Deliver concise, 00:06:17.540 --> 00:06:19.740 maybe five -minute video briefing each day that 00:06:19.740 --> 00:06:21.500 cuts right through it. You're not just selling 00:06:21.500 --> 00:06:24.540 news, you're selling curated intelligence. You're 00:06:24.540 --> 00:06:26.800 selling back their time. Okay, so how would you 00:06:26.800 --> 00:06:29.779 actually do that? First, you pick a high -value 00:06:29.779 --> 00:06:32.300 niche, something where timely information is 00:06:32.300 --> 00:06:35.560 critical, maybe AI regulation updates or specific 00:06:35.560 --> 00:06:38.060 crypto market movements or breakthroughs in biotech. 00:06:38.160 --> 00:06:40.000 Something specific where people pay for insights. 00:06:40.379 --> 00:06:42.040 Right. Then you automate the info gathering. 00:06:42.240 --> 00:06:44.879 You could use tools like Manus AI to scrape specific 00:06:44.879 --> 00:06:47.920 websites or set up really targeted Google Alerts. 00:06:48.100 --> 00:06:50.540 That curated daily report becomes your source 00:06:50.540 --> 00:06:52.899 document for Notebook LM. Got it. So you feed 00:06:52.899 --> 00:06:56.600 that report in. Yep. with a prompt like, uh, 00:06:56.740 --> 00:06:58.620 generate a four -minute video script summarizing 00:06:58.620 --> 00:07:01.839 today's AI regulation news. Create visuals for 00:07:01.839 --> 00:07:04.160 the key updates using two, three essential bullet 00:07:04.160 --> 00:07:06.240 points per slide. And then you deliver that video 00:07:06.240 --> 00:07:09.240 how? Through a paid newsletter, maybe, or a private 00:07:09.240 --> 00:07:11.980 online community. Look at successful models like 00:07:11.980 --> 00:07:14.860 morning brew or stratetry. They charge recurring 00:07:14.860 --> 00:07:18.079 fees for valuable, concise intelligence. So you 00:07:18.079 --> 00:07:21.199 could potentially charge, what, $29, maybe $99 00:07:21.199 --> 00:07:24.259 a month for a daily video brief like this? Easily, 00:07:24.420 --> 00:07:26.139 yeah, depending on the niche and how much value 00:07:26.139 --> 00:07:28.500 you're providing. OK, interesting. What's next? 00:07:28.759 --> 00:07:31.620 Method two, ghost thought leadership. This is 00:07:31.620 --> 00:07:33.860 a really good one for busy executives, experts, 00:07:34.180 --> 00:07:36.120 consultants, people with tons of knowledge and 00:07:36.120 --> 00:07:38.720 unique insights, but absolutely zero time for 00:07:38.720 --> 00:07:41.959 personal branding stuff on LinkedIn or X. Yeah, 00:07:42.379 --> 00:07:44.100 you see those profiles that are just kind of. 00:07:44.189 --> 00:07:46.750 dormant. Right. So this service basically mines 00:07:46.750 --> 00:07:48.610 their intellectual property. You take their past 00:07:48.610 --> 00:07:50.750 podcast interviews, maybe transcripts of talks 00:07:50.750 --> 00:07:53.649 they gave, articles they wrote, even internal 00:07:53.649 --> 00:07:56.110 meeting recordings if they have them. You upload 00:07:56.110 --> 00:07:59.730 all that into Notebook LM. So Notebook LM becomes 00:07:59.730 --> 00:08:02.730 like their personal knowledge base, their second 00:08:02.730 --> 00:08:05.709 brain. Exactly. Filled with their ideas, their 00:08:05.709 --> 00:08:08.730 unique perspectives, all organized and searchable. 00:08:08.889 --> 00:08:12.670 Then, you use prompts to pull out sharp, insightful 00:08:12.670 --> 00:08:15.170 video clips from that material. Give me an example 00:08:15.170 --> 00:08:18.529 prompt. OK, maybe something like, analyze the 00:08:18.529 --> 00:08:21.589 client's last three podcast transcripts. Identify 00:08:21.589 --> 00:08:24.050 three non -obvious insights about managing remote 00:08:24.050 --> 00:08:27.509 teams. Create a 90 -second video script for each 00:08:27.509 --> 00:08:30.069 insight using simple slides that highlight the 00:08:30.069 --> 00:08:32.350 key phrases. And these are short, shareable videos 00:08:32.350 --> 00:08:34.879 for social media. Perfect for it. And here's 00:08:34.879 --> 00:08:37.139 the kicker for really personalizing it. You can 00:08:37.139 --> 00:08:39.620 use voice cloning services. Eleven Labs is a 00:08:39.620 --> 00:08:42.419 popular one. Whoa, voice cloning. How does that 00:08:42.419 --> 00:08:44.539 work? You just need a short audio sample of the 00:08:44.539 --> 00:08:46.820 executive's voice. The AI learns their voice 00:08:46.820 --> 00:08:49.460 profile, and then it can generate the audio for 00:08:49.460 --> 00:08:51.879 the video script in their exact voice. So it 00:08:51.879 --> 00:08:53.440 sounds like they actually recorded it themselves. 00:08:53.539 --> 00:08:56.500 It's uncanny, as this incredible layer of authenticity. 00:08:56.879 --> 00:08:58.559 And the executive didn't have to spend any time 00:08:58.559 --> 00:09:00.960 recording. That sounds like a seriously premium 00:09:00.960 --> 00:09:04.220 service. It is. Standard executive ghost writing, 00:09:04.399 --> 00:09:07.399 just for text posts, can easily command retainers 00:09:07.399 --> 00:09:10.539 of $2 ,000 to $6 ,000 a month, sometimes more. 00:09:11.179 --> 00:09:13.659 Your video offering is arguably more valuable 00:09:13.659 --> 00:09:17.570 because video is so engaging. Wow. Okay, so these 00:09:17.570 --> 00:09:20.190 first two methods, they're really about leveraging 00:09:20.190 --> 00:09:23.669 time -saving and deep personalization for potentially 00:09:23.669 --> 00:09:25.950 high -value clients. Yeah. Yes, exactly. They 00:09:25.950 --> 00:09:28.610 save clients huge amounts of time and create 00:09:28.610 --> 00:09:31.730 highly personalized professional content with 00:09:31.730 --> 00:09:34.549 minimal client effort. Sponsor. All right, let's 00:09:34.549 --> 00:09:36.289 get these methods coming. What's number three? 00:09:36.590 --> 00:09:38.929 Method three, evergreen brand education. This 00:09:38.929 --> 00:09:41.169 sounds like tackling repetition within companies. 00:09:41.289 --> 00:09:43.309 That's exactly it. It's about transforming a 00:09:43.309 --> 00:09:46.210 company's repetitive internal and external explanations 00:09:46.210 --> 00:09:49.169 into a permanent library of on -demand videos. 00:09:49.370 --> 00:09:51.649 The broken record content, you mean? Yeah. Every 00:09:51.649 --> 00:09:54.110 growing business has it. Sales teams explaining 00:09:54.110 --> 00:09:56.669 the same product features over and over. HR managers 00:09:56.669 --> 00:09:59.009 going through the company values with every single 00:09:59.009 --> 00:10:01.259 new hire. Customer support answering the same 00:10:01.259 --> 00:10:03.320 frequently asked questions day in day out. That 00:10:03.320 --> 00:10:06.059 sounds like a huge, often invisible drain on 00:10:06.059 --> 00:10:08.440 productivity. And consistency, too, probably. 00:10:08.820 --> 00:10:11.759 Totally. So your service identifies these frequently 00:10:11.759 --> 00:10:15.039 repeated explanations. Think sales pitch components, 00:10:15.360 --> 00:10:18.220 employee onboarding modules, common FAQs, product 00:10:18.220 --> 00:10:20.620 how -to guides. You gather the source material 00:10:20.620 --> 00:10:23.740 for those maybe handbooks, internal wikis, call 00:10:23.740 --> 00:10:25.700 scripts. And you build a knowledge base for the 00:10:25.700 --> 00:10:27.960 company in Notebook LM using that stuff. Right. 00:10:28.250 --> 00:10:31.009 Then you generate a library of short professional 00:10:31.009 --> 00:10:34.070 videos, each tackling one specific topic. So 00:10:34.070 --> 00:10:36.330 imagine, from the employee handbook, you create 00:10:36.330 --> 00:10:39.149 a crisp five -minute video explaining the company's 00:10:39.149 --> 00:10:42.549 code of conduct. Clear slides for each main policy 00:10:42.549 --> 00:10:45.330 point narrated clearly. Or a quick video demo 00:10:45.330 --> 00:10:47.710 of a complex software feature that usually takes 00:10:47.710 --> 00:10:50.309 a support agent an hour to explain on a call. 00:10:50.590 --> 00:10:53.509 Exactly. Now think about the cost savings. Traditional 00:10:53.509 --> 00:10:55.830 corporate training videos can cost thousands, 00:10:55.950 --> 00:10:58.399 like $2 ,000 to $5 ,000, sometimes more. for 00:10:58.399 --> 00:11:01.360 a single video. Wow. And studies show that automating 00:11:01.360 --> 00:11:04.120 even just one hour of typical employee onboarding 00:11:04.120 --> 00:11:06.840 can save a company over $1 ,300 per employee 00:11:06.840 --> 00:11:09.059 in lost productivity time. So you could package 00:11:09.059 --> 00:11:11.700 these, like the new higher onboarding video package, 00:11:11.940 --> 00:11:16.139 five key videos for, say, $3 ,000. Absolutely. 00:11:16.340 --> 00:11:19.639 You're offering a clear ROI based on time saved 00:11:19.639 --> 00:11:22.179 and improved consistency. It's a strong value 00:11:22.179 --> 00:11:24.580 proposition. OK, makes sense. Method number four. 00:11:24.840 --> 00:11:28.019 Method four, nonprofit story mining. This one's 00:11:28.019 --> 00:11:30.799 about helping nonprofits unlock the power hidden 00:11:30.799 --> 00:11:33.820 in their own archives, transforming dense reports 00:11:33.820 --> 00:11:36.500 and old documents into powerful, emotionally 00:11:36.500 --> 00:11:38.879 resonant stories. Because donors connect with 00:11:38.879 --> 00:11:41.899 stories, not just statistics. Precisely. Nonprofits 00:11:41.899 --> 00:11:44.980 often have a goldmine of incredible human stories 00:11:44.980 --> 00:11:48.059 buried in old annual reports, maybe board meeting 00:11:48.059 --> 00:11:51.299 minutes, grant applications, beneficiary testimonials. 00:11:51.820 --> 00:11:54.370 But... They rarely have the time or, frankly, 00:11:54.529 --> 00:11:56.970 the tools to dig them out and package them effectively. 00:11:57.190 --> 00:11:59.610 So you become their sort of digital archivist. 00:11:59.909 --> 00:12:02.389 Kind of, yeah. You feed all that historical material, 00:12:02.629 --> 00:12:04.409 reports, testimonials, old press clippings into 00:12:04.409 --> 00:12:07.330 Notebook LM. You essentially create an AI historian 00:12:07.330 --> 00:12:09.549 for them, a searchable, intelligent database 00:12:09.549 --> 00:12:11.570 of their impact. And then you use it to find 00:12:11.570 --> 00:12:14.740 the stories. Right. You prompt Notebook LM, maybe 00:12:14.740 --> 00:12:17.580 something like, scan all uploaded documents for 00:12:17.580 --> 00:12:19.799 personal anecdotes related to our youth mentorship 00:12:19.799 --> 00:12:22.440 program. Structure a two -minute video script 00:12:22.440 --> 00:12:25.279 focusing on a story of transformation using powerful 00:12:25.279 --> 00:12:28.019 quotes from beneficiaries or staff. Create simple 00:12:28.019 --> 00:12:30.879 slides for the key quotes. And these short, focused 00:12:30.879 --> 00:12:33.259 videos would be perfect for... Fundraising emails, 00:12:33.799 --> 00:12:37.059 social media campaigns, grant applications, website 00:12:37.059 --> 00:12:39.580 impact sections, anywhere they need to connect 00:12:39.580 --> 00:12:41.759 emotionally. What's the value comparison there? 00:12:41.850 --> 00:12:44.549 Well, a dedicated nonprofit storytelling agency 00:12:44.549 --> 00:12:47.470 might charge upwards of $11 ,000 a year just 00:12:47.470 --> 00:12:49.870 to produce maybe four polished stories. With 00:12:49.870 --> 00:12:51.629 this AI -driven approach, you could potentially 00:12:51.629 --> 00:12:55.029 deliver a library of, say, five to seven compelling 00:12:55.029 --> 00:12:58.610 video stories for maybe $3 ,000 to $5 ,000. And 00:12:58.610 --> 00:13:00.950 good storytelling can directly boost donor conversion 00:13:00.950 --> 00:13:04.009 rates, sometimes by as much as 300%. Okay, so 00:13:04.009 --> 00:13:05.789 these two methods, three and four, are really 00:13:05.789 --> 00:13:08.230 about creating scalable, consistent communication 00:13:08.230 --> 00:13:10.909 assets for organizations, businesses, and causes. 00:13:11.149 --> 00:13:13.909 Yes, spot on. They turn time -consuming, repetitive 00:13:13.909 --> 00:13:17.450 tasks into valuable, consistent, and easily scalable 00:13:17.450 --> 00:13:20.070 video content. Alright, one more method to cover. 00:13:20.429 --> 00:13:23.970 Method five. Event knowledge mining. This sounds 00:13:23.970 --> 00:13:27.009 like making conference content live longer. Exactly. 00:13:27.389 --> 00:13:29.649 Companies spend huge amounts of money on conferences, 00:13:30.029 --> 00:13:32.590 summits, big corporate events. They bring in 00:13:32.590 --> 00:13:35.490 amazing speakers, share cutting -edge insights. 00:13:35.590 --> 00:13:37.429 And then a few weeks later, most of it's forgotten. 00:13:37.549 --> 00:13:40.149 Pretty much. It's a huge pain point for event 00:13:40.149 --> 00:13:43.009 organizers. How do you extend the value, the 00:13:43.009 --> 00:13:45.909 ROI, beyond the few days of the event itself? 00:13:46.210 --> 00:13:48.769 You solve that by turning all that valuable event 00:13:48.769 --> 00:13:51.129 content into an on -demand knowledge library. 00:13:51.330 --> 00:13:53.389 So how do you get the content? You'd gather the 00:13:53.389 --> 00:13:55.990 transcripts, keynotes, panel discussions, breakout 00:13:55.990 --> 00:13:58.289 sessions. Often the event organizers have these 00:13:58.289 --> 00:14:01.190 from the AV recordings. You feed those potentially 00:14:01.190 --> 00:14:04.250 hundreds of pages into Notebook LM. And let it 00:14:04.250 --> 00:14:06.850 process all that information. Right. Then you 00:14:06.850 --> 00:14:09.289 prompt it to extract the key insights and themes. 00:14:09.529 --> 00:14:13.009 For example, analyze all 15 speaker transcripts 00:14:13.009 --> 00:14:15.750 from the Future of Finance conference. Identify 00:14:15.750 --> 00:14:18.330 the top 10 recurring themes and actionable insights 00:14:18.330 --> 00:14:21.269 discussed. Create a three -minute summary video 00:14:21.269 --> 00:14:24.110 for each theme. Start each video with the most 00:14:24.110 --> 00:14:26.710 relevant speaker's name and a key quote, then 00:14:26.710 --> 00:14:29.210 elaborate with supporting points from the transcripts. 00:14:30.139 --> 00:14:33.080 create a whole menu of video assets from the 00:14:33.080 --> 00:14:36.419 event content. Exactly. Individual session summaries, 00:14:36.720 --> 00:14:38.820 videos focused on specific recurring themes, 00:14:39.259 --> 00:14:41.419 maybe even a greatest hits compilation video. 00:14:41.720 --> 00:14:44.480 This provides massive long -term value for attendees 00:14:44.480 --> 00:14:46.879 who want to revisit the content, for sponsors 00:14:46.879 --> 00:14:48.919 looking to showcase their involvement, and for 00:14:48.919 --> 00:14:51.100 the organizers themselves as marketing material 00:14:51.100 --> 00:14:53.559 for next year's event. And compared to traditional 00:14:53.559 --> 00:14:55.960 event videography. Well, just getting basic highlight 00:14:55.960 --> 00:15:00.539 reels can cost $1 ,500 to $3 ,000. packages capturing 00:15:00.539 --> 00:15:02.679 and editing multiple sessions run into the tens 00:15:02.679 --> 00:15:05.860 of thousands easily. Your AI -driven process 00:15:05.860 --> 00:15:08.279 means you could potentially deliver a comprehensive 00:15:08.279 --> 00:15:10.960 library of these focused summary videos within 00:15:10.960 --> 00:15:13.419 days of the event ending while the buzz is still 00:15:13.419 --> 00:15:16.419 high. That's a huge advantage. OK, five really 00:15:16.419 --> 00:15:19.379 distinct valuable methods there. But how does 00:15:19.379 --> 00:15:21.940 someone listening actually go from hearing these 00:15:21.940 --> 00:15:25.019 ideas to earning income? Is there a practical 00:15:25.019 --> 00:15:27.580 plan? There is. The source lays out a pretty 00:15:27.580 --> 00:15:30.009 clear five -step action plan. Step one, choose 00:15:30.009 --> 00:15:32.809 your niche. And this is critical. Pick just one 00:15:32.809 --> 00:15:34.970 of these five methods to start. Whichever one 00:15:34.970 --> 00:15:37.210 genuinely interests you the most, or maybe aligns 00:15:37.210 --> 00:15:38.610 best with people you already know. Don't try 00:15:38.610 --> 00:15:41.610 to do everything at once. Focus. Focus is key. 00:15:41.769 --> 00:15:45.450 Okay. Step two. Step two, master your toolkit. 00:15:46.169 --> 00:15:49.690 Get hands on. Notebook LM itself is free, so 00:15:49.690 --> 00:15:51.509 sign up and start playing with it immediately. 00:15:51.929 --> 00:15:53.649 Feed it some articles, generate some videos, 00:15:53.710 --> 00:15:55.870 see what kind of prompts work best. If you pick, 00:15:56.049 --> 00:15:58.370 say, the research automation method, Maybe explore 00:15:58.370 --> 00:16:01.409 tools like Manus AI. If you're interested in 00:16:01.409 --> 00:16:03.450 the Go's leadership angle, check out the free 00:16:03.450 --> 00:16:06.269 tier of 11 labs for voice cloning. Just experiment. 00:16:06.529 --> 00:16:08.789 Get comfortable with the tools. You know, I still 00:16:08.789 --> 00:16:11.350 wrestle with Promtript myself sometimes. even 00:16:11.350 --> 00:16:14.190 after doing this for a while. That's when the 00:16:14.190 --> 00:16:16.610 AI's responses kind of subtly veer off track 00:16:16.610 --> 00:16:18.850 if your problems aren't super clear over time. 00:16:19.169 --> 00:16:21.029 So really practicing, seeing the limitations, 00:16:21.289 --> 00:16:23.350 understanding what it does well, that's absolutely 00:16:23.350 --> 00:16:25.309 crucial. Understand the tech deeply helps you 00:16:25.309 --> 00:16:27.409 sell the solution with real confidence. Makes 00:16:27.409 --> 00:16:29.450 sense. That vulnerability helps, knowing even 00:16:29.450 --> 00:16:31.690 experienced folks are still learning. Okay, step 00:16:31.690 --> 00:16:35.049 three. Step three, find your first pilot client. 00:16:35.590 --> 00:16:37.509 Don't wait until you feel like a total expert 00:16:37.509 --> 00:16:40.730 because that day might never come. Leverage your 00:16:40.730 --> 00:16:43.730 existing network. Who do you know? Small business 00:16:43.730 --> 00:16:46.970 owner. Someone at a nonprofit. Offer a small, 00:16:47.129 --> 00:16:50.450 very low -risk pilot project. Maybe even offer 00:16:50.450 --> 00:16:52.929 to create one free sample video from one of their 00:16:52.929 --> 00:16:55.570 existing blog posts or reports. Lower the barrier 00:16:55.570 --> 00:16:57.769 to entry for them. Exactly. It removes their 00:16:57.769 --> 00:17:00.190 risk, lets them see the magic firsthand, and 00:17:00.190 --> 00:17:02.710 gives you a real -world case study and valuable 00:17:02.710 --> 00:17:05.930 feedback. Okay. Pilot client secured. Step four. 00:17:06.109 --> 00:17:09.279 Step four. Price with confidence. This is important. 00:17:09.400 --> 00:17:10.779 Remember what you're selling. You're not selling 00:17:10.779 --> 00:17:12.839 a cheap AI trick that takes you five minutes. 00:17:13.240 --> 00:17:15.420 You're selling a solution to significant, often 00:17:15.420 --> 00:17:18.380 costly, problem -saving time, ensuring consistency, 00:17:18.759 --> 00:17:20.859 boosting professionalism, providing peace of 00:17:20.859 --> 00:17:23.839 mind, delivering measurable ROI. So anchor your 00:17:23.839 --> 00:17:25.740 price to the value you create for the client, 00:17:26.079 --> 00:17:28.079 not just the time it takes you. Value -based 00:17:28.079 --> 00:17:31.000 pricing. Got it. And the final step. Step five. 00:17:32.019 --> 00:17:35.210 Systematize and scale. Once you land that first 00:17:35.210 --> 00:17:37.109 client and hopefully knock it out of the park, 00:17:37.950 --> 00:17:40.089 immediately document your entire process. What 00:17:40.089 --> 00:17:42.049 steps did you take? What prompts worked best? 00:17:42.569 --> 00:17:44.670 This becomes your standard operating procedure 00:17:44.670 --> 00:17:47.910 or SOP. It allows you to deliver consistent quality 00:17:47.910 --> 00:17:51.009 much faster next time and always ask for a testimonial 00:17:51.009 --> 00:17:54.529 and ask for a referral. Happy clients are your 00:17:54.529 --> 00:17:57.109 absolute best marketing engine. Okay, so recapping 00:17:57.109 --> 00:18:00.240 that path. Pick a focus area, really learn the 00:18:00.240 --> 00:18:02.480 tools, get that first pilot client on board, 00:18:02.640 --> 00:18:04.920 price based on the value you deliver, and then 00:18:04.920 --> 00:18:06.960 build a system to scale it. That's the roadmap 00:18:06.960 --> 00:18:10.200 right there. Focus, learn, pilot, value price, 00:18:10.500 --> 00:18:12.759 then systematize. All right, let's just quickly 00:18:12.759 --> 00:18:15.259 recap the big picture here. This deep dive, we've 00:18:15.259 --> 00:18:17.619 really explored how Google's Notebook LM, especially 00:18:17.619 --> 00:18:20.339 with its grounded AI approach and its new pretty 00:18:20.339 --> 00:18:22.480 elegant video capabilities, how it's unlocking 00:18:22.480 --> 00:18:25.019 a really significant and still very early stage 00:18:25.019 --> 00:18:27.720 opportunity. Yeah, it's about becoming almost 00:18:27.720 --> 00:18:31.359 like a digital artisan. You're using this reliable 00:18:31.359 --> 00:18:34.380 AI not just to automate, but to craft highly 00:18:34.380 --> 00:18:37.660 valuable customized content. Content that solves 00:18:37.660 --> 00:18:40.559 real, often expensive problems for clients. You're 00:18:40.559 --> 00:18:42.759 creating tangible assets incredibly quickly. 00:18:43.180 --> 00:18:45.859 And we looked at five powerful ways to do that. 00:18:46.119 --> 00:18:48.819 Daily intelligence briefings, ghost thought leadership. 00:18:49.259 --> 00:18:52.619 Evergreen brand education, nonprofit story mining, 00:18:53.180 --> 00:18:55.720 and extending the life and value of event content. 00:18:56.160 --> 00:18:58.940 Each one taps into a proven market need and offers 00:18:58.940 --> 00:19:01.339 clear value. And it feels like the timing is 00:19:01.339 --> 00:19:03.759 critical here. It really is. Think about that 00:19:03.759 --> 00:19:06.630 technology adoption curve model. We are squarely 00:19:06.630 --> 00:19:08.569 in the innovator and early adopter phase right 00:19:08.569 --> 00:19:10.390 now for this kind of application. That means 00:19:10.390 --> 00:19:13.190 there's still minimal direct competition. And 00:19:13.190 --> 00:19:15.109 clients are often genuinely amazed by the results 00:19:15.109 --> 00:19:17.890 because it's new to them. But that window, it's 00:19:17.890 --> 00:19:20.349 definitely closing as awareness grows. So looking 00:19:20.349 --> 00:19:22.789 ahead, maybe a year from now, you listening will 00:19:22.789 --> 00:19:24.549 probably be in one of two positions. You'll either 00:19:24.549 --> 00:19:26.950 be glad you decided to jump in and start experimenting 00:19:26.950 --> 00:19:29.269 today, or you'll likely wish you had. Yeah, the 00:19:29.269 --> 00:19:31.930 choice ultimately is yours. The technology is 00:19:31.930 --> 00:19:35.109 here. It works, and the market need is clearly 00:19:35.109 --> 00:19:37.730 waiting. So if any of these five methods or just 00:19:37.730 --> 00:19:40.069 the potential of this tool resonated with you 00:19:40.069 --> 00:19:41.809 today, our advice is pretty straightforward. 00:19:42.269 --> 00:19:45.430 Pick one method that excites you. Find one potential 00:19:45.430 --> 00:19:48.190 pilot client, even just for a small test. Start 00:19:48.190 --> 00:19:50.349 today. Thank you for joining us on this deep 00:19:50.349 --> 00:19:53.289 dive. Until next time, keep digging, keep learning. 00:19:53.589 --> 00:19:54.450 UT Row Music.