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Every time a new AI model demonstrates an ability to manipulate or generate media, it's celebrated as if we're witnessing these capabilities for the first time. This framing misses a crucial point: most of these capabilities have existed for decades. We just used different technology to accomplish them. What's... changing now is that AI is allowing media generation and editing to be more accessible to many more - both in terms of cost and ease of use. Take David Fincher's The Social Network from 2010. The Winklevoss twins were played by two different actors, but Armie Hammer's face was digitally placed onto Josh Pence's body. What we call deepfakes today was just traditional VFX pipelines then. The process involved high-resolution facial scanning, detailed 3D modeling, precise facial rigging, and frame-by-frame tracking. The VFX team created photorealistic digital doubles, mapped accurate skin textures, and manually refined each transformation until the result was imperceptible. Most viewers never noticed - which is exactly the point. The best CGI is invisible CGI. This wasn't unique. Hollywood has been digitally transforming actors for decades through well-established technical pipelines: photogrammetry, facial capture, advanced compositing, and physics-based rendering. The question isn't whether we can do it - that has already been answered. Previously, two factors kept this technology contained: technical complexity and cost. Traditional graphics pipelines required specialized infrastructure - from high-end capture equipment to render farms - and deep technical expertise across multiple disciplines. "Fix it in post" meant teams of technical artists working with proprietary tools and complex workflows. More importantly, it was expensive - often millions per shot. Digital effects at this level are reserved for big-budget productions. AI isn't changing what's possible - it's changing the implementation stack. The same transformations that once required extensive hardware, specialized software, and teams of technical artists are being consolidated by generative and world models. The technology is moving from complex production pipelines to end-to-end solutions that anyone can use. Like Act-One (who said Act-Two?). What becomes possible when these capabilities are democratized? When sophisticated effects and graphics become accessible to many more filmmakers? When actors will be able to do more, in more languages, for more audiences? What happens when the technical and financial barriers to high-end content creation disappear?show more

Cristóbal Valenzuela

44,514 subscribers

30,561 просмотров • 1 год назад •via X (Twitter)

Наука и технологии Искусство Образование

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Комментарии: 9

Фото профиля Bilawal Sidhu

Bilawal Sidhu1 год назад

In other words: this has never happened before, yet has happened time and time again

Фото профиля Cristóbal Valenzuela

Cristóbal Valenzuela1 год назад

exactly

Фото профиля Tonio

Tonio1 год назад

The illegal data scrape angle is what you're missing - artists didn't sign up for their art to be taken to be mimic'd. In the VFX model artist got paid $800/day at times. New model = I took ur old rendes, now I only need you to retouch once in a while.

Фото профиля J. Vortex

J. Vortex1 год назад

Democratized means of creation = more art, more healthy expression, and a happier more communicative world overall. I think this is all so much more important than just film! An amazing time to be alive!

Фото профиля Julian Harris

Julian Harris1 год назад

From a text/NLP point of view, there have been some breakthroughs that were genuinely science-fiction beforehand. For instance “the trophy didn’t fit into the suitcase because it was too big”. Most LLMs will tell you “it” was the trophy. Impossible before.

Фото профиля @gatscape

@gatscape1 год назад

nice, central point: problem space is the same, solution space is different. What are the consequences of art creation methods going from a million $ to a dollar

Фото профиля Cristóbal Valenzuela

Cristóbal Valenzuela1 год назад

more art

Фото профиля Dᴀᴛᴀ Sᴀᴄᴋs

Dᴀᴛᴀ Sᴀᴄᴋs1 год назад

This is why Ben Aflac is so mad.

Фото профиля Christopher Moonlight Productions

Christopher Moonlight Productions1 год назад

Thank you. This is something I've been telling people for ages. It's the difference between having a shovel or a trencher. The result is the same but now a technology can handle the lift more efficiently for us and at much less cost. The human artists still ultimately drives.

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I had to do this of course - test out the new Google Omni Flash model with my favorite 3d art sandbox - Dreams. Just a quick test for now.. I'll be sharing more examples and techniques soon but wanted to show you this one. There's something very fitting about combining "handmade" 3d models and animations sculpted from scratch in software that runs on 2013 hardware, with some of the most advanced AI technology in the world. As part of my work for Google, I've used Google V2V models on a few different projects now - Ancestra, Dear Upstairs Neighbors and most recently one of the IO films (I'll share more about that project soon) 🥰 - and video continues to be my favorite form of input for Generative Ai workflows. If an image says more than a thousand words, a video says more than a million. And knowing that these capabilities are now in the hands of all of you, makes me very excited to see the new workflows and projects that will come out of it. What do you think of Omni so far?

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The most prominent example of a film that was financially viable because of generative AI was “Here” by Robert Zemeckis. Starring Tom Hanks and Robin Wright, it shows a couple living through multiple decades. The film’s budget was ~$50m and wouldn’t be able to cover traditional process for de-aging: ▫️Make-up: Takes hour to put on and can make actors look 10 years younger (but not 50 as the film requires) ▫️CGI: Expensive and long (per NYT, “Persuading us that we’re watching Hanks and Wright in their 20s would have required hundreds of VFX artists, tens of millions of dollars and months of postproduction work.”) Zemeckis says “Here” was able to be made in 2024 but not in 2021 (due to CGI costs). Also by using generative AI, Hanks and Wright could act more naturally without thick make-up (or those CGI dots) on their face. The AI effects were done by Metaphysics (the company’s content head is Ed Ulbrich, the former CEO of Digital Domain, James Cameron’s FX firm). Metaphysics AI tools were particularly useful because of how much video and images there are of Hanks and Wright over the decades (won’t be the case for all actors). Some of those images include 1994’s “Forrest Gump”, which was also directed by Zemeckis starring Hanks and Wright. That banger used a lot of advanced aging effects for the time and won the 1995 Best Visual Effects Oscar. A best case scenario might be instead of a studio spending $200m for a single blockbuster, it could finance and staff up 4 films at $50m (which could reach same visual quality bar using new tech). *** More from NYT: “Here” featurette:

The most prominent example of a film that was financially viable because of generative AI was “Here” by Robert Zemeckis. Starring Tom Hanks and Robin Wright, it shows a couple living through multiple decades. The film’s budget was ~$50m and wouldn’t be able to cover traditional process for de-aging: ▫️Make-up: Takes hour to put on and can make actors look 10 years younger (but not 50 as the film requires) ▫️CGI: Expensive and long (per NYT, “Persuading us that we’re watching Hanks and Wright in their 20s would have required hundreds of VFX artists, tens of millions of dollars and months of postproduction work.”) Zemeckis says “Here” was able to be made in 2024 but not in 2021 (due to CGI costs). Also by using generative AI, Hanks and Wright could act more naturally without thick make-up (or those CGI dots) on their face. The AI effects were done by Metaphysics (the company’s content head is Ed Ulbrich, the former CEO of Digital Domain, James Cameron’s FX firm). Metaphysics AI tools were particularly useful because of how much video and images there are of Hanks and Wright over the decades (won’t be the case for all actors). Some of those images include 1994’s “Forrest Gump”, which was also directed by Zemeckis starring Hanks and Wright. That banger used a lot of advanced aging effects for the time and won the 1995 Best Visual Effects Oscar. A best case scenario might be instead of a studio spending $200m for a single blockbuster, it could finance and staff up 4 films at $50m (which could reach same visual quality bar using new tech). *** More from NYT: “Here” featurette:

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677,857 просмотров • 8 месяцев назад

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From Eric Vishria on how the top AI founders are building products completely opposite of the SaaS era: "One of the things that is really different in the AI world versus the SaaS world, is that in the SaaS world, over and over again, you had people who really understood the customer. And the problem. And then they understood a domain. They understood what the technology was more or less capable of. But it wasn't a real question of if you could build something or not. For example, take Salesforce, Workday, and ServiceNow. CRM existed before Salesforce. HR management existed before Workday. Same thing with ServiceNow. So in every case, Salesforce followed Siebel. Workday followed Peoplesoft. ServiceNow followed Peregrine and Remedy, and others. So they were just kind of, cloud SaaS versions of the prior generation product. They just understood the customers. They understood the problem. And they were just like, here's a better version. And that evolved a little bit over time in SaaS land. But that's what it is. And so product development in that way was done by people who really understood the customer and the problems. And then just took advantage of the next wave. And this is almost diametrically opposite of product development in the AI era. When I look at the teams that are having the most success today, they have intimate knowledge of the models. They are right on the frontier of understanding which models are better at what, and why, and when. And what they're going to be good at and what they're not going to be good at. And what they're spending their time on, is figuring out how do I apply this capability of this model to this domain or to this user. So they're actually working inside out or technology out, versus customer problem in. And of course, they understand the customer problem. And a lot of times they have firsthand knowledge of it. But they're really close to the metal and capability, and they're applying it. And I think this is a really different way to develop products than in SaaS. I started my career as a product manager a long time ago, and it's almost the complete opposite of everything you learned. "Listen to the customer, understand it, then bring it back to the engineering and product teams." If you did that right now, ask a bunch of customers what they want out of AI, and you brought it back, for the most part, it may not be possible today with today's technology. Whereas the teams that are winning right now really understand the technology and are applying it out. And so I think this reversal matters. I think it's a big difference in terms of how companies are getting built. And maybe even the types of entrepreneurs that will be successful. I'm not sure. You're seeing some real change there. Look at the Bret Taylor's at Sierra. That's a super, super technical founder who really gets it. Brett and Clay really get it. You look at Michael and his co-founders at Cursor. They're super technical founders and they get it. They all really understand what these things can and can't do. And that's a pretty different dynamic relative to the way the best SaaS companies got built." Link in bio for the full conversation going deep on the current class of startups going from zero to $100m+ in ARR within 12 months.

The Peel

209,752 просмотров • 1 год назад

For generative AI to become an interesting art tool, we need much more control over the output. The slot-machine-like nature of pure text-to-image leaves too much to chance. Using the "Real-time Latent Consistency Model" that I'm using in the example here, is the first time I truly got a glimpse of a future where we'll be able to use our artistic skills and sensibility, to get control over AI image gen. Systems like these will never be able to match the quality or originality of a skilled artist, it won't surprise us in the same way an artist can. Things are a mess in terms of the training data these models are based on, and the questions about copyright concerns and about a time when everything will look the same are very valid. At some point capabilities like these will be embedded in photoshop, and anyone will be able to generate a pretty picture. But to create interesting designs, to tell original stories and to surprise us, we need creatives and artists with something on their mind. We'll be able to create immersive worlds, by making brush-strokes and sculpt marks, without needing to worry about all the dials, plugins, wires of our 3d and 2d tools today. I love to sculpt, I love to draw, and I love to explore new mediums and new ways to create. The Gen AI tools we have today are far from perfect, and things need to be steered in a better direction. For that we need artists to help point the way. Gen AI isn't going away.. it's too powerful and has the potential to allow us to tell stories like never before. Like all other big technological shifts, tech like this will come at a cost, but it will also open up new opportunities and empower a new generation of storytellers. I might be naive, but I believe that human ingenuity and creativity will persevere in this new world ♥️ #art #ai

For generative AI to become an interesting art tool, we need much more control over the output. The slot-machine-like nature of pure text-to-image leaves too much to chance. Using the "Real-time Latent Consistency Model" that I'm using in the example here, is the first time I truly got a glimpse of a future where we'll be able to use our artistic skills and sensibility, to get control over AI image gen. Systems like these will never be able to match the quality or originality of a skilled artist, it won't surprise us in the same way an artist can. Things are a mess in terms of the training data these models are based on, and the questions about copyright concerns and about a time when everything will look the same are very valid. At some point capabilities like these will be embedded in photoshop, and anyone will be able to generate a pretty picture. But to create interesting designs, to tell original stories and to surprise us, we need creatives and artists with something on their mind. We'll be able to create immersive worlds, by making brush-strokes and sculpt marks, without needing to worry about all the dials, plugins, wires of our 3d and 2d tools today. I love to sculpt, I love to draw, and I love to explore new mediums and new ways to create. The Gen AI tools we have today are far from perfect, and things need to be steered in a better direction. For that we need artists to help point the way. Gen AI isn't going away.. it's too powerful and has the potential to allow us to tell stories like never before. Like all other big technological shifts, tech like this will come at a cost, but it will also open up new opportunities and empower a new generation of storytellers. I might be naive, but I believe that human ingenuity and creativity will persevere in this new world ♥️ #art #ai

Martin Nebelong

1,660,343 просмотров • 2 лет назад

Billions CEO Evin McMullen evin interviewed by HoC Founder Diederick Jacobs at House of Chimera Spaces Event Dec 3, 2025 Diederick: There's a lot of privacy issues with AI. Your data obviously is being used, that's one. But more importantly it can be used against you and that is very scary. How do we determine who we can trust and who we cannot trust? Because across history, sometimes parties switch. Evin: How do we determine roots of trust? Who are the entities who we trust? That is not really a technical question, that is more of a social and philosophical question. But as the basis for roots of trust, one of the most expressive and specific entities who we look to are the issuers of government documents. With Billions Network, we have integrated with more than 100 different government ID systems around the world to make it easy for citizens to do things like take their passport, tap it to their phone, pull the data out of the NFC chip in their passport, and be able to represent that in a privacy preserving and compliant way to different applications onchain and online.

Billions CEO Evin McMullen evin interviewed by HoC Founder Diederick Jacobs at House of Chimera Spaces Event Dec 3, 2025 Diederick: There's a lot of privacy issues with AI. Your data obviously is being used, that's one. But more importantly it can be used against you and that is very scary. How do we determine who we can trust and who we cannot trust? Because across history, sometimes parties switch. Evin: How do we determine roots of trust? Who are the entities who we trust? That is not really a technical question, that is more of a social and philosophical question. But as the basis for roots of trust, one of the most expressive and specific entities who we look to are the issuers of government documents. With Billions Network, we have integrated with more than 100 different government ID systems around the world to make it easy for citizens to do things like take their passport, tap it to their phone, pull the data out of the NFC chip in their passport, and be able to represent that in a privacy preserving and compliant way to different applications onchain and online.

Billions Network

65,208 просмотров • 8 месяцев назад

Jensen to AI Leaders: “We have to be far more thoughtful” when communicating to the public Jensen Huang: “(AI) is not a biological being. It is not alien. It is not conscious. It is computer software.” “We say things like, ‘We don't understand it at all.’ It is not true. We understand a lot of things about this technology.” Chamath: “If you were in the seat in the boardroom of Anthropic over that whole scuttlebutt with the Department of War, what do you think you would've told Dario and that team to do, maybe, differently to try to change some of this outcome and some of this perception?” Jensen: “The first thing that I would say about Anthropic is, first of all, the technology is incredible. We are a large consumer of Anthropic technology.” “The desire to warn people about the capability of the technology is also really terrific.” “We just have to make sure that we understand that the world has a spectrum, and that warning is good, scaring is less good because this technology is too important to us.” “I think that it is fine to predict the future, but we need to be a little bit more circumspect. We need to have a little bit more humility, that, in fact, we can't completely predict the future.” “And to say things that are quite extreme, quite catastrophic, that there's no evidence of it happening, could be more damaging than people think.” “And of course we are technology leaders.” “There was a time when nobody listened to us, but now because technology is so important in the social fabric, such an important industry, so important to national security, our words do matter.” “And I think we have to be much more circumspect, we have to be more moderate, we have to be more balanced, we have to be far more thoughtful.”

Jensen to AI Leaders: “We have to be far more thoughtful” when communicating to the public Jensen Huang: “(AI) is not a biological being. It is not alien. It is not conscious. It is computer software.” “We say things like, ‘We don't understand it at all.’ It is not true. We understand a lot of things about this technology.” Chamath: “If you were in the seat in the boardroom of Anthropic over that whole scuttlebutt with the Department of War, what do you think you would've told Dario and that team to do, maybe, differently to try to change some of this outcome and some of this perception?” Jensen: “The first thing that I would say about Anthropic is, first of all, the technology is incredible. We are a large consumer of Anthropic technology.” “The desire to warn people about the capability of the technology is also really terrific.” “We just have to make sure that we understand that the world has a spectrum, and that warning is good, scaring is less good because this technology is too important to us.” “I think that it is fine to predict the future, but we need to be a little bit more circumspect. We need to have a little bit more humility, that, in fact, we can't completely predict the future.” “And to say things that are quite extreme, quite catastrophic, that there's no evidence of it happening, could be more damaging than people think.” “And of course we are technology leaders.” “There was a time when nobody listened to us, but now because technology is so important in the social fabric, such an important industry, so important to national security, our words do matter.” “And I think we have to be much more circumspect, we have to be more moderate, we have to be more balanced, we have to be far more thoughtful.”

The All-In Podcast

57,581 просмотров • 5 месяцев назад

In our $KGN earnings call today, it sounded like it's David Shafer and I presenting but it wasn't. Our voices were AI generated and read the script. We uploaded several hours of our prior talks to train our voice model and the results were pretty incredible. This saved us a few hours preparation - valuable time we could spend working on other areas of the business. This is an example of the many one percenters across our business where AI is making us more efficient and helping the team be more productive. Our marketing team uses it to improve our content and make it more enaging. Our Engineering team uses it to get more context of our entire code base quicker and produce production ready code more rapidly. Our purchasing teams are using it for data and trend analysis to bring the latest products to our customers at even better prices. The list goes on. While the productivity gains are exciting, what's even more exciting is the pace at which things are changing and the technology is getting better!

In our $KGN earnings call today, it sounded like it's David Shafer and I presenting but it wasn't. Our voices were AI generated and read the script. We uploaded several hours of our prior talks to train our voice model and the results were pretty incredible. This saved us a few hours preparation - valuable time we could spend working on other areas of the business. This is an example of the many one percenters across our business where AI is making us more efficient and helping the team be more productive. Our marketing team uses it to improve our content and make it more enaging. Our Engineering team uses it to get more context of our entire code base quicker and produce production ready code more rapidly. Our purchasing teams are using it for data and trend analysis to bring the latest products to our customers at even better prices. The list goes on. While the productivity gains are exciting, what's even more exciting is the pace at which things are changing and the technology is getting better!

Ruslan Kogan

814,106 просмотров • 1 год назад

Build and customize complex AI applications with a flexible framework in this new short course, Building AI Applications with Haystack. Created in collaboration with deepset, makers of Haystack, and taught by Tuana, who is the developer relations lead for Haystack at deepset. Generative AI technology is changing rapidly and it can be challenging to integrate APIs from different LLMs, vector databases, and various tools such as web search. In this course, you will learn how to use the Haystack framework to make your development process more modular, allowing you to manage complexity and focus more on building your application. In detail, you’ll: - Build a RAG pipeline using Haystack’s main building blocks – components, pipelines, and document stores. - Create custom components in your pipeline by building a Hacker News summarizer that extends your app’s ability to access APIs. - Use conditional routing to create a branching pipeline with a fallback to web search mechanism when the LLM does not have the necessary context to respond to the user's query. - Build a self-reflecting agent for named entity recognition that loops using an output validator custom component. - Create a chat agent using OpenAI's function-calling capabilities which allow you to provide Haystack pipelines as tools to the LLM, enhancing that agent's capabilities. By the end of this course, you will learn a high-level orchestration framework that can help make your applications flexible, extendible, and maintainable, even as the technology stack changes, new user needs arise, and you add new features to your application. Please sign up here:

Build and customize complex AI applications with a flexible framework in this new short course, Building AI Applications with Haystack. Created in collaboration with deepset, makers of Haystack, and taught by Tuana, who is the developer relations lead for Haystack at deepset. Generative AI technology is changing rapidly and it can be challenging to integrate APIs from different LLMs, vector databases, and various tools such as web search. In this course, you will learn how to use the Haystack framework to make your development process more modular, allowing you to manage complexity and focus more on building your application. In detail, you’ll: - Build a RAG pipeline using Haystack’s main building blocks – components, pipelines, and document stores. - Create custom components in your pipeline by building a Hacker News summarizer that extends your app’s ability to access APIs. - Use conditional routing to create a branching pipeline with a fallback to web search mechanism when the LLM does not have the necessary context to respond to the user's query. - Build a self-reflecting agent for named entity recognition that loops using an output validator custom component. - Create a chat agent using OpenAI's function-calling capabilities which allow you to provide Haystack pipelines as tools to the LLM, enhancing that agent's capabilities. By the end of this course, you will learn a high-level orchestration framework that can help make your applications flexible, extendible, and maintainable, even as the technology stack changes, new user needs arise, and you add new features to your application. Please sign up here:

Andrew Ng

53,788 просмотров • 2 лет назад

Announcing Innovative Dreams, a new production company by Luma and Wonder Project built by filmmakers for filmmakers, and our first production — Moses starring Sir Ben Kingsley, coming this Spring on Prime Video. AI is a fundamental change to the craft and business of filmmaking, and through ID, we are building a new production process for this era — one that brings Humans and AI together to enable great storytelling. We call it Hybrid Production — actors, artists, and generative AI working together in Luma. In real time. Innovative Dreams is a production services company where seasoned filmmakers from Director Jon Erwin's team and Luma's creative technologists work with great studios and filmmakers to help them realize ambitious ideas. It's a liberating force. Hybrid Production enables actors, directors, and artists to work together in real time. Creative teams collaborate with Luma Agents live and make changes to sets, props, lighting, and bring in performance capture from human actors. This is a significant improvement over the current virtual production and performance capture processes where things come together only in post. This is the leverage of AI — not just faster or cheaper, but better than what came before. We have built the first Hybrid Filmmaking studio at Manhattan Beach Studios where Moses is being shot. ID is significantly oversubscribed with demand and is actively growing the team to extend its services to more studios and filmmakers. Read more:

Announcing Innovative Dreams, a new production company by Luma and Wonder Project built by filmmakers for filmmakers, and our first production — Moses starring Sir Ben Kingsley, coming this Spring on Prime Video. AI is a fundamental change to the craft and business of filmmaking, and through ID, we are building a new production process for this era — one that brings Humans and AI together to enable great storytelling. We call it Hybrid Production — actors, artists, and generative AI working together in Luma. In real time. Innovative Dreams is a production services company where seasoned filmmakers from Director Jon Erwin's team and Luma's creative technologists work with great studios and filmmakers to help them realize ambitious ideas. It's a liberating force. Hybrid Production enables actors, directors, and artists to work together in real time. Creative teams collaborate with Luma Agents live and make changes to sets, props, lighting, and bring in performance capture from human actors. This is a significant improvement over the current virtual production and performance capture processes where things come together only in post. This is the leverage of AI — not just faster or cheaper, but better than what came before. We have built the first Hybrid Filmmaking studio at Manhattan Beach Studios where Moses is being shot. ID is significantly oversubscribed with demand and is actively growing the team to extend its services to more studios and filmmakers. Read more:

Luma

95,747 просмотров • 4 месяцев назад

Decades of hardware development led to strong, fast, and precise robot arms. The moment we can put in general intelligence in these things, we can leverage the full spectra of capabilities that they were always meant to capture. We’re betting on a future where robot hardware will continue to improve, and we intend to build the best models on top of the best hardware to push the frontier of capabilities and reliability. Here’s an old video from TossingBot that I think helps make this point extra clear. Industrial-grade repeatability started out as a crutch for dumb software -- but if you pair it with the right AI models, then it becomes an advantage that is superhuman. There are factories where the same UR robot arms are still being used to precisely and repeatably build the same car parts, operating for 10 yrs straight without a single failure or shutdown. Humanoids will get there too (among other form factors). Not yet today, but eventually. And our models will be ready to meet them when they do.

Decades of hardware development led to strong, fast, and precise robot arms. The moment we can put in general intelligence in these things, we can leverage the full spectra of capabilities that they were always meant to capture. We’re betting on a future where robot hardware will continue to improve, and we intend to build the best models on top of the best hardware to push the frontier of capabilities and reliability. Here’s an old video from TossingBot that I think helps make this point extra clear. Industrial-grade repeatability started out as a crutch for dumb software -- but if you pair it with the right AI models, then it becomes an advantage that is superhuman. There are factories where the same UR robot arms are still being used to precisely and repeatably build the same car parts, operating for 10 yrs straight without a single failure or shutdown. Humanoids will get there too (among other form factors). Not yet today, but eventually. And our models will be ready to meet them when they do.

Andy Zeng

19,174 просмотров • 3 месяцев назад

David Friedberg: The AI Jobs Panic Is a Crock of Sh*t Why? The revenue potential outweighs the cost savings by 100x. “There is no job loss with AI. I've said it a thousand times, and I will say it again, and again, and again. What I see on the ground, and what I've seen at dozens of companies, including my company that I run, there are two sides to a business. There is revenue and there’s costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money, to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do 100x or 1000x what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products, or boats and ships, or software for companies, or clothing, or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side 100x more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago, and they're like, ‘We want to add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do.’ So we are going to hire more people. And to Sacks' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of sh*t.”

David Friedberg: The AI Jobs Panic Is a Crock of Sht Why? The revenue potential outweighs the cost savings by 100x. “There is no job loss with AI. I've said it a thousand times, and I will say it again, and again, and again. What I see on the ground, and what I've seen at dozens of companies, including my company that I run, there are two sides to a business. There is revenue and there’s costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money, to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do 100x or 1000x what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products, or boats and ships, or software for companies, or clothing, or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side 100x more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago, and they're like, ‘We want to add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do.’ So we are going to hire more people. And to Sacks' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of sht.”

The All-In Podcast

152,394 просмотров • 2 месяцев назад

Generative AI is fundamentally changing how decisions are made. At its core, AI collapses the distance between a question and a confident answer. Throughout my journey, I have always been interested in how machine intelligence can simplify complexity, from shortening design cycles earlier to now making wealth creation more intuitive. Today, we are taking a step in that direction with 𝗔𝘀𝗸 𝗔𝗻𝗴𝗲𝗹. We have built it to be a true "financial co-pilot" that lives exactly where you need it. If you’re on a stock page, Ask Angel will help break down fundamentals or the latest news. If you’re navigating an IPO, it will help you parse through the data without you ever having to leave the page. And for everyday tasks like checking balances or withdrawals, it gives you instant, clear answers. To make this even more seamless, we’ve integrated intuitive "helpful pills", which suggest prompts that help you articulate complex queries and get to the right outcome, faster. Under the hood, Ask Angel is powered by a curated “Golden Dataset” across multiple research categories, ensuring that responses are fast, accurate, safe, and compliant. This is just the beginning. Over time, we will continue to deepen its capabilities from technical insights to more contextual, decision-oriented guidance. Incredibly proud of what the team has built, and even more excited about what comes next. Angel One #AskAngel #GenerativeAI #FinTech #AngelOne

Generative AI is fundamentally changing how decisions are made. At its core, AI collapses the distance between a question and a confident answer. Throughout my journey, I have always been interested in how machine intelligence can simplify complexity, from shortening design cycles earlier to now making wealth creation more intuitive. Today, we are taking a step in that direction with 𝗔𝘀𝗸 𝗔𝗻𝗴𝗲𝗹. We have built it to be a true "financial co-pilot" that lives exactly where you need it. If you’re on a stock page, Ask Angel will help break down fundamentals or the latest news. If you’re navigating an IPO, it will help you parse through the data without you ever having to leave the page. And for everyday tasks like checking balances or withdrawals, it gives you instant, clear answers. To make this even more seamless, we’ve integrated intuitive "helpful pills", which suggest prompts that help you articulate complex queries and get to the right outcome, faster. Under the hood, Ask Angel is powered by a curated “Golden Dataset” across multiple research categories, ensuring that responses are fast, accurate, safe, and compliant. This is just the beginning. Over time, we will continue to deepen its capabilities from technical insights to more contextual, decision-oriented guidance. Incredibly proud of what the team has built, and even more excited about what comes next. Angel One #AskAngel #GenerativeAI #FinTech #AngelOne

Ambarish Kenghe

48,077 просмотров • 4 месяцев назад

Steve Jobs talking about Pixar and storytelling. Says "no amount of technology will turn a bad story into a good story" and that Pixar's early films had to prioritize a good story because the cost of animating was so high: ◻️ "In a live action movie, the director goes out and shoots a lot of film — typically 10x to 100x more footage than will end up on the screen. Then they take it all into the editing room and that's why sometimes you see a movie and you go 'that stunk, didn't they know?' Well, the answer is 'yes' but they knew it too late in the editing room and...by the time they knew it, the actors were gone and the sets were down and they were out of money.” "In animation, it is so expensive that you can't afford to animate more than a few % more than it's going to end up on screen. You could never afford to animate 10x more. Walt Disney solved the problem decades ago and the way he solved it was to edit films before making them: you get your story team together and you do storyboards." "In Hollywood, one of the most popular sayings is 'story is King' but it turns out it really isn't. Because when push comes to shove...when a movie is in production and there's a lot of mouths to feed — and they're waiting for stuff to make and the story is not working — almost everybody says 'we will just have to make the movie'. And one of the things that I'm proudest of about Pixar is we have a story crisis on every movie...and we stop [everything to] fix the story." *** D3 Conference in 2005:

Steve Jobs talking about Pixar and storytelling. Says "no amount of technology will turn a bad story into a good story" and that Pixar's early films had to prioritize a good story because the cost of animating was so high: ◻️ "In a live action movie, the director goes out and shoots a lot of film — typically 10x to 100x more footage than will end up on the screen. Then they take it all into the editing room and that's why sometimes you see a movie and you go 'that stunk, didn't they know?' Well, the answer is 'yes' but they knew it too late in the editing room and...by the time they knew it, the actors were gone and the sets were down and they were out of money.” "In animation, it is so expensive that you can't afford to animate more than a few % more than it's going to end up on screen. You could never afford to animate 10x more. Walt Disney solved the problem decades ago and the way he solved it was to edit films before making them: you get your story team together and you do storyboards." "In Hollywood, one of the most popular sayings is 'story is King' but it turns out it really isn't. Because when push comes to shove...when a movie is in production and there's a lot of mouths to feed — and they're waiting for stuff to make and the story is not working — almost everybody says 'we will just have to make the movie'. And one of the things that I'm proudest of about Pixar is we have a story crisis on every movie...and we stop [everything to] fix the story." *** D3 Conference in 2005:

Trung Phan

308,105 просмотров • 2 лет назад

The AI business model is undergoing a transformation. For the last few years, the playbook was simple: put an AI wrapper on a SaaS product and sell it by the seat. That era is ending. The new wave of AI companies are moving beyond simple subscriptions and embracing a more sophisticated approach tied directly to value creation. Here’s what’s changing: 💰 From Seats to Spend: The most forward-thinking companies are shifting to usage-based and outcome-driven pricing. Think less about how many people use the AI and more about what the AI does. This includes new revenue streams like "agentic checkout" on ChatGPT, where AI agents complete purchases and transactions directly within a chat interface. The closer the AI is to the dollar, the more value it captures. 🎙️ From Text to Voice & Video: The interface for AI is becoming more human. Voice is mainstream (Sierra for support, Listen Labs for market research). The next frontier is video, where AI will see, understand, and interact with the world in real-time. The keyboard is no longer the only way to talk to a machine. 🤖 From Advisors to Actors: Early AI copilots gave advice. The next generation takes action. These agents aren't just suggesting what to do; they are executing complex workflows that directly impact the metrics that matter: boosting conversion, reducing average handle time (AHT), improving NPS, and cutting churn. This is about moving from passive assistance to active problem-solving. The common thread? A relentless focus on tangible ROI. We’re incredibly bullish on founders who understand this shift and are building companies that align their success with the success of their customers. The future of AI isn't just about intelligence; it's about impact.

The AI business model is undergoing a transformation. For the last few years, the playbook was simple: put an AI wrapper on a SaaS product and sell it by the seat. That era is ending. The new wave of AI companies are moving beyond simple subscriptions and embracing a more sophisticated approach tied directly to value creation. Here’s what’s changing: 💰 From Seats to Spend: The most forward-thinking companies are shifting to usage-based and outcome-driven pricing. Think less about how many people use the AI and more about what the AI does. This includes new revenue streams like "agentic checkout" on ChatGPT, where AI agents complete purchases and transactions directly within a chat interface. The closer the AI is to the dollar, the more value it captures. 🎙️ From Text to Voice & Video: The interface for AI is becoming more human. Voice is mainstream (Sierra for support, Listen Labs for market research). The next frontier is video, where AI will see, understand, and interact with the world in real-time. The keyboard is no longer the only way to talk to a machine. 🤖 From Advisors to Actors: Early AI copilots gave advice. The next generation takes action. These agents aren't just suggesting what to do; they are executing complex workflows that directly impact the metrics that matter: boosting conversion, reducing average handle time (AHT), improving NPS, and cutting churn. This is about moving from passive assistance to active problem-solving. The common thread? A relentless focus on tangible ROI. We’re incredibly bullish on founders who understand this shift and are building companies that align their success with the success of their customers. The future of AI isn't just about intelligence; it's about impact.

Konstantine Buhler

24,887 просмотров • 10 месяцев назад