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$CRWV The CoreWeave Canary My first cut at using NotebookLM (new product launched by Google). Used a single Jag research note (pdf) that I issued to clients last week, and asked AI to generate a video without diving into deep thinking. Intentionally kept very basic. Result 👇

JaguarAnalytics

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62,614 views • 8 months ago •via X (Twitter)

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One of my best use cases for Google NotebookLM is using it to break down AI research papers. I asked it to create a video overview of DeepSeek's new mHC (mHC: Manifold-Constrained Hyper-Connections) paper, and it made the concepts incredibly simple to understand.

One of my best use cases for Google NotebookLM is using it to break down AI research papers. I asked it to create a video overview of DeepSeek's new mHC (mHC: Manifold-Constrained Hyper-Connections) paper, and it made the concepts incredibly simple to understand.

AshutoshShrivastava

52,360 views • 7 months ago

NotebookLM just became a custom AI tool builder. Most people are still using it like a note app. Here’s the new workflow: → Upload your docs first (PDFs, Drive links, Sheets, Word). → Set a 10,000-character persona (rules, formats, constraints). → Ask for data tables → export straight to Google Sheets. → Run Deep Research → plan + web crawl + cited report. → Generate mind maps to see how ideas connect. Save this video, you’ll build your first “AI specialist” in 10 minutes. Want the SOP? DM me. 💬

NotebookLM just became a custom AI tool builder. Most people are still using it like a note app. Here’s the new workflow: → Upload your docs first (PDFs, Drive links, Sheets, Word). → Set a 10,000-character persona (rules, formats, constraints). → Ask for data tables → export straight to Google Sheets. → Run Deep Research → plan + web crawl + cited report. → Generate mind maps to see how ideas connect. Save this video, you’ll build your first “AI specialist” in 10 minutes. Want the SOP? DM me. 💬

Julian Goldie SEO

18,534 views • 6 months ago

I asked Kling 3.0 to create a short film from just a single image... and the result blew my mind! here's how I made this video using Multi-Shot 👇

I asked Kling 3.0 to create a short film from just a single image... and the result blew my mind! here's how I made this video using Multi-Shot 👇

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77,788 views • 6 months ago

I just built a $DOG video game using AI 🤯 I asked ChatGPT 5.5 Thinking to design the gameplay and create the visual assets then fed them into Codex 5.5 Extra High and this was the result!

I just built a $DOG video game using AI 🤯 I asked ChatGPT 5.5 Thinking to design the gameplay and create the visual assets then fed them into Codex 5.5 Extra High and this was the result!

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Really impressed with the new video feature in @NotebookLM. I asked for a history of Disneyland. It kicked off a deep search, pulled 58 sources, used them to write a script, and generated a 5 minute video with a mix of real and AI visuals. How it works + a clip 👇

Really impressed with the new video feature in @NotebookLM. I asked for a history of Disneyland. It kicked off a deep search, pulled 58 sources, used them to write a script, and generated a 5 minute video with a mix of real and AI visuals. How it works + a clip 👇

Justine Moore

59,991 views • 5 months ago

At #GoogleIO, Google launched a pile of product under a pile of product names: Antigravity, Gemini, AI Studio, Flow, Omni, Stitch, Pomelli...and that's not even half of it. I recap my favorite launches for eng + designers, and try (and sometimes fail!) to try the new stuff 👇

At #GoogleIO, Google launched a pile of product under a pile of product names: Antigravity, Gemini, AI Studio, Flow, Omni, Stitch, Pomelli...and that's not even half of it. I recap my favorite launches for eng + designers, and try (and sometimes fail!) to try the new stuff 👇

claire vo 🖤

18,638 views • 2 months ago

NotebookLM is the most powerful automation engine hidden in plain sight. No more wasting hours on manual research. No more hiring expensive designers for slide decks. Here’s the new play 👇 → Deep Research: Scan hundreds of websites for a single report instantly. → Video Overviews: Turn any PDF into a narrated video in minutes. → Smart Tables: Extract structured data from messy transcripts automatically. → Visual Studio: Auto-generate infographics and professional slides. → Knowledge Hub: Build a custom AI expert trained on your own documents. Save this post. Google is shipping updates faster than you can keep up. Want the full guide? DM me.

NotebookLM is the most powerful automation engine hidden in plain sight. No more wasting hours on manual research. No more hiring expensive designers for slide decks. Here’s the new play 👇 → Deep Research: Scan hundreds of websites for a single report instantly. → Video Overviews: Turn any PDF into a narrated video in minutes. → Smart Tables: Extract structured data from messy transcripts automatically. → Visual Studio: Auto-generate infographics and professional slides. → Knowledge Hub: Build a custom AI expert trained on your own documents. Save this post. Google is shipping updates faster than you can keep up. Want the full guide? DM me.

Julian Goldie SEO

32,335 views • 7 months ago

$LUNR Intuitive Machines -- I usually reserve notes like this exclusively for Jag clients, but I'm in good mood, so it's your lucky day 😀 Extensive research here. Conclusion: I don't own enough shares! Jag research: Slide deck:

$LUNR Intuitive Machines -- I usually reserve notes like this exclusively for Jag clients, but I'm in good mood, so it's your lucky day 😀 Extensive research here. Conclusion: I don't own enough shares! Jag research: Slide deck:

JaguarAnalytics

32,048 views • 6 months ago

I used NotebookLM to study Google new breakthrough with TurboQuant and used Video overview to study the subject, best learning tool in the world at the moment. TurboQuant: Redefining AI Efficiency with Extreme Compression Google Research has introduced TurboQuant, a suite of advanced algorithms designed to dramatically compress the data used by large language models and search engines. By utilizing specialized techniques like PolarQuant and Quantized Johnson-Lindenstrauss, the system transforms complex information into a compact "shorthand" that requires significantly less memory. This innovation specifically addresses the key-value cache bottleneck, allowing AI models to process massive amounts of text faster without losing accuracy. Testing demonstrates that these methods can shrink data size by six times while actually increasing operational speed on high-end hardware. Ultimately, these theoretical advancements enable more efficient semantic search and high-performance AI applications at a global scale.

I used NotebookLM to study Google new breakthrough with TurboQuant and used Video overview to study the subject, best learning tool in the world at the moment. TurboQuant: Redefining AI Efficiency with Extreme Compression Google Research has introduced TurboQuant, a suite of advanced algorithms designed to dramatically compress the data used by large language models and search engines. By utilizing specialized techniques like PolarQuant and Quantized Johnson-Lindenstrauss, the system transforms complex information into a compact "shorthand" that requires significantly less memory. This innovation specifically addresses the key-value cache bottleneck, allowing AI models to process massive amounts of text faster without losing accuracy. Testing demonstrates that these methods can shrink data size by six times while actually increasing operational speed on high-end hardware. Ultimately, these theoretical advancements enable more efficient semantic search and high-performance AI applications at a global scale.

Emily

14,648 views • 4 months ago

Google's AI strategy is intriguing. They are building AI tools that target real use-cases. I am finding myself using NotebookLM (to read stuff), Gemini (to analyze images and videos), Google Lens (to find stuff without links), NotebookLM (to create video explainers), Gemini (for generating mini apps), Collab (for data science), Deep Research (for gathering info), Antigravity (vibe coding), Nanobanna (for image editing), veo (for video gen), aistudio (mini apps). You also get all this under a wireless subscription with GoogleFi! That's insane! What else am I missing?

Google's AI strategy is intriguing. They are building AI tools that target real use-cases. I am finding myself using NotebookLM (to read stuff), Gemini (to analyze images and videos), Google Lens (to find stuff without links), NotebookLM (to create video explainers), Gemini (for generating mini apps), Collab (for data science), Deep Research (for gathering info), Antigravity (vibe coding), Nanobanna (for image editing), veo (for video gen), aistudio (mini apps). You also get all this under a wireless subscription with GoogleFi! That's insane! What else am I missing?

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55,478 views • 8 months ago

Was very excited when Last Week Tonight asked Четыреста Четыре.co to help out with research/fact checking for an AI Slop segment that ran last night. I thought it turned out very good! Here's a few mentions of our reporting, and the full segment:

Was very excited when Last Week Tonight asked Четыреста Четыре.co to help out with research/fact checking for an AI Slop segment that ran last night. I thought it turned out very good! Here's a few mentions of our reporting, and the full segment:

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18,020 views • 1 year ago

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I'm about to piss off a 13 billion dollar industry - the OCR market. Here's why: Monday: I optimized my PDF-to-Excel converter landing page for SEO. Tuesday: I started ranking #1 organically for "pdf to excel ai", a phrase with 8K+ monthly searches and growing. The Google Ads competition is insane. Wednesday: I was previously using a basic OCR API and I replaced it with the Gemini 2.0 Flash model, which is insanely good at PDF parsing. Thursday: I bought the domain pdftoexcelai[dot]com.

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A FREE Master Class On Competitive Research Using AI... 🤯🤯🤯 I dive into 👇👇👇 ➡️ How to do DEEP competitive research ➡️ Version 1 of my prompts ➡️ Live example + Breakdown ➡️ How to use this for your own brand And yes... I'm giving this for free. Want the prompts doc used in the video? 👉 Like this post 👉 Comment "Prompts" Special S/O to Professor Charley T | The Meta Ads Guy for sharing this plugin, you just turned my research process into a MACHINE. Forever grateful! 🙌

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33,703 views • 2 years ago

The AI power trio of NotebookLM, Perplexity, and Gemini 3 just killed manual research. No more spending hours digging through articles. No more manually building slide decks from scratch. Here’s the new play 👇 → Perplexity pulls real-time facts with verified source citations. → NotebookLM processes 1M tokens to synthesize massive data. → Gemini 3 adds multimodal reasoning for text, audio, and video. → Auto-generate full presentations and video overviews instantly. → Transform days of research into a 20-minute automated system. Save this workflow. Google is shipping these AI updates quietly and fast. Want the full guide? DM me.

The AI power trio of NotebookLM, Perplexity, and Gemini 3 just killed manual research. No more spending hours digging through articles. No more manually building slide decks from scratch. Here’s the new play 👇 → Perplexity pulls real-time facts with verified source citations. → NotebookLM processes 1M tokens to synthesize massive data. → Gemini 3 adds multimodal reasoning for text, audio, and video. → Auto-generate full presentations and video overviews instantly. → Transform days of research into a 20-minute automated system. Save this workflow. Google is shipping these AI updates quietly and fast. Want the full guide? DM me.

Julian Goldie SEO

29,354 views • 7 months ago

NotebookLM is one of the most delightful, inspiring, and viral AI products out there right now, and I got a chance to chat with the PM behind the product, Raiza Martin (@raiza_abubakar). In our conversation, we cover: 🔸 The origin story of NotebookLM 🔸 The future road map for NotebookLM 🔸 How Google Labs operates differently from the rest of Google 🔸 The development of the “Audio Overviews” feature 🔸 Key metrics and growth of NotebookLM 🔸 Stories about collaborating with author Steven Johnson 🔸 Navigating potential misuse of AI technology 🔸 More Listen now 👇 - YouTube: - Spotify: - Apple: Raiza is a senior product manager for AI at Google Labs for AI at Google Labs, where she leads the team behind NotebookLM, an AI-powered research tool that includes a mind-blowing podcast-on-demand feature called “Audio Overviews.” NotebookLM started as a 20% project and has grown into a product that’s spreading across social media and has a Discord server with over 60,000 users. Raiza previously worked on AI Test Kitchen and has a background in startups, payments, and ads. Thank you to our wonderful sponsors for supporting the podcast: 🏆 Explo — Embed customer-facing analytics in your product: 🏆 Sprig — Build products for people, not data points: 🏆 Sidebar — Accelerate your career by surrounding yourself with extraordinary peers: Some key takeaways: 1. Embrace a startup mentality within large organizations: Google Labs operates with fewer processes and more agility than typical Google teams. This allows them to move faster and iterate quickly, much like a startup. 2. Often, powerful technology is already available; the magic lies in how you interact with it. For instance, by integrating powerful audio models with existing LLMs, NotebookLM created an innovative way for users to interact with content. Look for unique applications of the tools you already have. 3. Don’t wait for a perfect launch. Start with a working version of your product and use user feedback to iterate and improve. This approach can reveal unexpected insights and user preferences, helping you shape the final product.

NotebookLM is one of the most delightful, inspiring, and viral AI products out there right now, and I got a chance to chat with the PM behind the product, Raiza Martin (@raiza_abubakar). In our conversation, we cover: 🔸 The origin story of NotebookLM 🔸 The future road map for NotebookLM 🔸 How Google Labs operates differently from the rest of Google 🔸 The development of the “Audio Overviews” feature 🔸 Key metrics and growth of NotebookLM 🔸 Stories about collaborating with author Steven Johnson 🔸 Navigating potential misuse of AI technology 🔸 More Listen now 👇 - YouTube: - Spotify: - Apple: Raiza is a senior product manager for AI at Google Labs for AI at Google Labs, where she leads the team behind NotebookLM, an AI-powered research tool that includes a mind-blowing podcast-on-demand feature called “Audio Overviews.” NotebookLM started as a 20% project and has grown into a product that’s spreading across social media and has a Discord server with over 60,000 users. Raiza previously worked on AI Test Kitchen and has a background in startups, payments, and ads. Thank you to our wonderful sponsors for supporting the podcast: 🏆 Explo — Embed customer-facing analytics in your product: 🏆 Sprig — Build products for people, not data points: 🏆 Sidebar — Accelerate your career by surrounding yourself with extraordinary peers: Some key takeaways: 1. Embrace a startup mentality within large organizations: Google Labs operates with fewer processes and more agility than typical Google teams. This allows them to move faster and iterate quickly, much like a startup. 2. Often, powerful technology is already available; the magic lies in how you interact with it. For instance, by integrating powerful audio models with existing LLMs, NotebookLM created an innovative way for users to interact with content. Look for unique applications of the tools you already have. 3. Don’t wait for a perfect launch. Start with a working version of your product and use user feedback to iterate and improve. This approach can reveal unexpected insights and user preferences, helping you shape the final product.

Lenny Rachitsky

75,439 views • 1 year ago

I decided to make a short film using Google DeepMind Veo 2 (via fal) a one minute piece about life in the city. SFX and voice are . It costs a lot more than other AI video tools but I only needed to generate 18 clips to get the 11 I used. That is a much better ratio than normal. I used roughly $50 in FAL credits to make this.

I decided to make a short film using Google DeepMind Veo 2 (via fal) a one minute piece about life in the city. SFX and voice are . It costs a lot more than other AI video tools but I only needed to generate 18 clips to get the 11 I used. That is a much better ratio than normal. I used roughly $50 in FAL credits to make this.

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