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AI made creation effortless. But that also made creation worthless. Here’s what actually matters now 👇 Every decade, a new technology resets the playing field. AI just did that. Now anyone can code, design, or produce in seconds. What used to take teams, agencies, and budgets, now takes a...

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Will Deane

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21,343 просмотров • 10 месяцев назад •via X (Twitter)

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Geoffrey Hinton, who is known as the godfather of AI, used his 2024 Nobel Prize acceptance speech not to celebrate his creation but to warn humanity of its risks: “AI is already being used by authoritarian governments for mass surveillance. In the near future, AI will be used to create new viruses and lethal weapons that decide by themselves who to kill or maim. There is also a long-term existential threat that will arise…We now have evidence that AI created by companies motivated by short-term profits will not prioritize the safety of humanity. We need research on how to prevent these AI beings from taking control. They are no longer science fiction.” When the pioneer of AI is warning humanity about the existential dangers of his own creation it’s time not just to listen, but to take action by stopping the one thing the billionaires need to power the dystopian AI world they’re trying to create: Data Centers.
1:15

Geoffrey Hinton, who is known as the godfather of AI, used his 2024 Nobel Prize acceptance speech not to celebrate his creation but to warn humanity of its risks: “AI is already being used by authoritarian governments for mass surveillance. In the near future, AI will be used to create new viruses and lethal weapons that decide by themselves who to kill or maim. There is also a long-term existential threat that will arise…We now have evidence that AI created by companies motivated by short-term profits will not prioritize the safety of humanity. We need research on how to prevent these AI beings from taking control. They are no longer science fiction.” When the pioneer of AI is warning humanity about the existential dangers of his own creation it’s time not just to listen, but to take action by stopping the one thing the billionaires need to power the dystopian AI world they’re trying to create: Data Centers.

Power to the People ☭🕊

61,682 просмотров • 3 месяцев назад

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)
0:59

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 просмотров • 3 месяцев назад

I think we're entering a new era of AI creation. The best tools won't just generate content. They'll help you discover what to create. Dreamina Octo is one of the first tools that made me feel that shift. 🧵👇
0:41

I think we're entering a new era of AI creation. The best tools won't just generate content. They'll help you discover what to create. Dreamina Octo is one of the first tools that made me feel that shift. 🧵👇

Md Riyazuddin

47,689 просмотров • 2 месяцев назад

DAVID SACKS: “I understand that there is a lot of concern about [AI] job disruption or job loss. That's not what we're seeing in the data so far. What we're actually seeing is job creation … We have a 4% GDP growth number right now, and half of that is attributable to AI.”
1:05

DAVID SACKS: “I understand that there is a lot of concern about [AI] job disruption or job loss. That's not what we're seeing in the data so far. What we're actually seeing is job creation … We have a 4% GDP growth number right now, and half of that is attributable to AI.”

Chief Nerd

206,382 просмотров • 8 месяцев назад

higgsfield DROPPED this and it just made ai filmmaking easier than ever. they open-sourced their originals. every flagship video they produced in-house, the entire prompt is now public. the references, the generation settings, the model, the resolution, all of it sitting right there on the project page. for anyone making ai video this is the part that actually matters. the hardest thing was never the tool, it was knowing how to prompt it. what to write to get cinematic lighting, character consistency across shots, real physics, camera movement that doesn't look ai. that knowledge stayed locked inside studios and a few people who figured it out early. now it's just open. open one of their best clips, read the exact prompt that built it, copy it, download the video, rebuild the whole thing yourself.
0:39

higgsfield DROPPED this and it just made ai filmmaking easier than ever. they open-sourced their originals. every flagship video they produced in-house, the entire prompt is now public. the references, the generation settings, the model, the resolution, all of it sitting right there on the project page. for anyone making ai video this is the part that actually matters. the hardest thing was never the tool, it was knowing how to prompt it. what to write to get cinematic lighting, character consistency across shots, real physics, camera movement that doesn't look ai. that knowledge stayed locked inside studios and a few people who figured it out early. now it's just open. open one of their best clips, read the exact prompt that built it, copy it, download the video, rebuild the whole thing yourself.

Sulfur

31,111 просмотров • 1 месяц назад

We've built a massive verification bottleneck: • 72% of developers use AI to generate code every day • 96% of them don't fully trust it Writing code is now free. All the work now is verifying that the code does what it's supposed to. According to a new State of Code Survey, almost half of the respondents believe the number one skill that will matter most in the coming years is "reviewing and validating AI-generated code for quality and security". Not prompt engineering or vibe-coding, but checking AI's work.
3:44

We've built a massive verification bottleneck: • 72% of developers use AI to generate code every day • 96% of them don't fully trust it Writing code is now free. All the work now is verifying that the code does what it's supposed to. According to a new State of Code Survey, almost half of the respondents believe the number one skill that will matter most in the coming years is "reviewing and validating AI-generated code for quality and security". Not prompt engineering or vibe-coding, but checking AI's work.

Santiago

16,299 просмотров • 7 месяцев назад

Strauss Zelnick, the CEO behind Grand Theft Auto 6, is skeptical of AI creating new, original, hit video games: “What AI is, despite the fact that there are people in Silicon Valley who don't want you to believe this, is big data sets, lots of compute, and a large language model mushed together. Data sets by their very nature are backward-looking. Creativity by its very nature is forward-looking. Right now with AI we can more efficiently create a completely derivative property. Derivative properties don't work. Where the thread has been lost is that AI so far is really great at asset creation. But hit creation isn't asset creation. Asset creation is a necessary but insufficient condition for hit creation. I would love to say that AI will make it easier and quicker and better to make hits because who would benefit more than we? We're in that business already. We own IP that you know. Creating new IP is really really hard to do—with or without AI. Getting someone to buy a new video game is incredibly hard. Getting them to buy GTA 6? Not so hard by comparison. So it's not that I take lightly the potential benefits of new technology. It's just that when our stock goes down by 50 points because people are like: "With AI anyone can make a video game.” It's like anyone could make a video game last week. Anyone could make a video game five years ago. The technology's readily available. It's been commoditized. You know how many mobile games get put out a year? Thousands. You know how many hits are made in a year? Zero to five. You know who makes them? We do thank you very much.”
2:17

Strauss Zelnick, the CEO behind Grand Theft Auto 6, is skeptical of AI creating new, original, hit video games: “What AI is, despite the fact that there are people in Silicon Valley who don't want you to believe this, is big data sets, lots of compute, and a large language model mushed together. Data sets by their very nature are backward-looking. Creativity by its very nature is forward-looking. Right now with AI we can more efficiently create a completely derivative property. Derivative properties don't work. Where the thread has been lost is that AI so far is really great at asset creation. But hit creation isn't asset creation. Asset creation is a necessary but insufficient condition for hit creation. I would love to say that AI will make it easier and quicker and better to make hits because who would benefit more than we? We're in that business already. We own IP that you know. Creating new IP is really really hard to do—with or without AI. Getting someone to buy a new video game is incredibly hard. Getting them to buy GTA 6? Not so hard by comparison. So it's not that I take lightly the potential benefits of new technology. It's just that when our stock goes down by 50 points because people are like: "With AI anyone can make a video game.” It's like anyone could make a video game last week. Anyone could make a video game five years ago. The technology's readily available. It's been commoditized. You know how many mobile games get put out a year? Thousands. You know how many hits are made in a year? Zero to five. You know who makes them? We do thank you very much.”

David Senra

42,986 просмотров • 3 месяцев назад

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.
0:35

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.

Dustin

82,823 просмотров • 5 месяцев назад

The CEO of Take-Two, the company behind GTA, just said something the entire AI industry doesn't want to hear. And he said it without being anti-AI. Strauss Zelnick's argument is precise. AI is built on datasets. Datasets are backward-looking. Creativity is forward-looking. A model trained on everything that already exists cannot, by definition, produce something genuinely unexpected. And all hits, by their very nature, are unexpected. Asset creation and hit creation are not the same thing. AI is getting very good at the first one. The second one is what actually makes money, builds franchises, and changes culture. Nobody has shown AI can do that yet. The derivative property problem is real. You can clone GTA with existing technology. You could do it before AI. It would take 3 years and look identical. It still wouldn't sell. Because it isn't GTA. It's a clone of GTA. And consumers, despite what the industry occasionally pretends, can feel the difference between something genuinely new and something assembled from the residue of things that already worked. Thousands of mobile games ship every year. 0 to 5 hits get made. The same studios make them every time. The technology to make more games has been commoditized for years. It didn't democratize hit creation. It just flooded the market with more forgettable product. The Silicon Valley thesis that AI unlocks game creation for everyone is true in the same way that cheap cameras unlocked filmmaking for everyone. They did. And the same 5 studios still make the movies everyone watches. What Zelnick is saying, without quite saying it, is that the thing AI cannot replicate is taste. The instinct for what hasn't been done yet. The cultural antenna that detects the gap in the market before the data can see it. Data tells you what people wanted. Hits tell people what they want next. Those are different jobs.
3:16

The CEO of Take-Two, the company behind GTA, just said something the entire AI industry doesn't want to hear. And he said it without being anti-AI. Strauss Zelnick's argument is precise. AI is built on datasets. Datasets are backward-looking. Creativity is forward-looking. A model trained on everything that already exists cannot, by definition, produce something genuinely unexpected. And all hits, by their very nature, are unexpected. Asset creation and hit creation are not the same thing. AI is getting very good at the first one. The second one is what actually makes money, builds franchises, and changes culture. Nobody has shown AI can do that yet. The derivative property problem is real. You can clone GTA with existing technology. You could do it before AI. It would take 3 years and look identical. It still wouldn't sell. Because it isn't GTA. It's a clone of GTA. And consumers, despite what the industry occasionally pretends, can feel the difference between something genuinely new and something assembled from the residue of things that already worked. Thousands of mobile games ship every year. 0 to 5 hits get made. The same studios make them every time. The technology to make more games has been commoditized for years. It didn't democratize hit creation. It just flooded the market with more forgettable product. The Silicon Valley thesis that AI unlocks game creation for everyone is true in the same way that cheap cameras unlocked filmmaking for everyone. They did. And the same 5 studios still make the movies everyone watches. What Zelnick is saying, without quite saying it, is that the thing AI cannot replicate is taste. The instinct for what hasn't been done yet. The cultural antenna that detects the gap in the market before the data can see it. Data tells you what people wanted. Hits tell people what they want next. Those are different jobs.

Mario Nawfal

1,638,984 просмотров • 3 месяцев назад

AI spend is now one of the fastest-growing line items at every company, but here's the problem: it's invisible to traditional spend management. We experienced this firsthand at Brex, so we built Magpie: an internal tool that sources and normalizes AI spend across every vendor so we can break it down by model, customer, employee, and workflow. What Magpie has already unlocked: → ~85% cost reduction on an audit agent through prompt caching → Real customer cost-to-serve numbers that inform pricing and margin → Model routing governance we couldn't enforce before → A surprise: operational AI is much cheaper than we assumed So why is AI spend so hard to track? Because each one exposes usage data differently (some not at all). At Brex, tool-use costs weren't tracked alongside tokens, customer attribution was inconsistent, and a meaningful chunk of our daily AI spend was unattributable. Now with Magpie, we have reliable visibility. AI spend is more complex than anything finance teams have had to manage before, and it's exactly the kind of problem Brex is built to solve, shaping how we think about the future of our platform. More below.
1:56

AI spend is now one of the fastest-growing line items at every company, but here's the problem: it's invisible to traditional spend management. We experienced this firsthand at Brex, so we built Magpie: an internal tool that sources and normalizes AI spend across every vendor so we can break it down by model, customer, employee, and workflow. What Magpie has already unlocked: → ~85% cost reduction on an audit agent through prompt caching → Real customer cost-to-serve numbers that inform pricing and margin → Model routing governance we couldn't enforce before → A surprise: operational AI is much cheaper than we assumed So why is AI spend so hard to track? Because each one exposes usage data differently (some not at all). At Brex, tool-use costs weren't tracked alongside tokens, customer attribution was inconsistent, and a meaningful chunk of our daily AI spend was unattributable. Now with Magpie, we have reliable visibility. AI spend is more complex than anything finance teams have had to manage before, and it's exactly the kind of problem Brex is built to solve, shaping how we think about the future of our platform. More below.

Pedro Franceschi

28,580 просмотров • 3 месяцев назад

A lot of people want to learn AI video creation but get discouraged by how expensive the tools can be. The truth is, you don’t need every platform to start creating good work. That’s one of the things I’ll be covering in AI VIDEO MONETIZATION BOOTCAMP. You can join the waitlist here -
1:53

A lot of people want to learn AI video creation but get discouraged by how expensive the tools can be. The truth is, you don’t need every platform to start creating good work. That’s one of the things I’ll be covering in AI VIDEO MONETIZATION BOOTCAMP. You can join the waitlist here -

UI x AI by Christabel

11,836 просмотров • 4 месяцев назад

Jensen Huang: What if I told you that in the last decade, we’ve made AI computing 100,000 times more efficient? Imagine if your car could become 100,000 times faster or use 100,000 times less energy. That’s what we’ve achieved with AI. In just 10 years, the energy required to run AI will be minimal, making it accessible in everything – from smartphones to homes – all the time. The future of AI means it will power our daily lives without draining resources or creating environmental impact. This is happening now, and the potential is limitless.
1:25

Jensen Huang: What if I told you that in the last decade, we’ve made AI computing 100,000 times more efficient? Imagine if your car could become 100,000 times faster or use 100,000 times less energy. That’s what we’ve achieved with AI. In just 10 years, the energy required to run AI will be minimal, making it accessible in everything – from smartphones to homes – all the time. The future of AI means it will power our daily lives without draining resources or creating environmental impact. This is happening now, and the potential is limitless.

Ian Miles Cheong

35,071 просмотров • 9 месяцев назад

Humanity will split into two. They are already aiding the rise of a new human race, and the steps were eerily and accurately described in 1983 by Michio Kushi. From ultra-psychonotization and controlling the population with chemicals from 2000 to 2020, to the creation of artificial intelligence and robotic workers, to merging humans with AI, controlling emotions through waves, satellites, and technology, and ultimately to the creation of a new human race. The artificial spirit versus natural creation. It is Biblical. Now do you understand the concept of Neuralink and Starlink? Do you see what is happening?
3:20

Humanity will split into two. They are already aiding the rise of a new human race, and the steps were eerily and accurately described in 1983 by Michio Kushi. From ultra-psychonotization and controlling the population with chemicals from 2000 to 2020, to the creation of artificial intelligence and robotic workers, to merging humans with AI, controlling emotions through waves, satellites, and technology, and ultimately to the creation of a new human race. The artificial spirit versus natural creation. It is Biblical. Now do you understand the concept of Neuralink and Starlink? Do you see what is happening?

Open Minded Approach

477,441 просмотров • 1 месяц назад

NVIDIA CEO Jensen Huang just gave us a glimpse into the future of AI, and it's far bigger than text and images. He asked: "If you can understand worlds, is it possible that you understand proteins and chemicals that have structure?” This is the quiet revolution happening in AI right now. We're moving from an AI that understands human language to an AI that understands the language of nature itself. The "letters" are atoms. The "words" are molecules. The "sentences" are the complex structures of life, networks, and reality. The same foundational models that generate video are now being used to: *Decode proteins to fight disease *Design new materials at the atomic level *Simulate complex systems in quantum computing These were once the domain of supercomputers and Nobel laureates. Now, they're becoming solvable problems for a new generation of startups. AI is transitioning from a tool for communication to a tool for creation and discovery in the physical world. This is where the next wave of generational companies will be built. The "hard-to-solve" problems are now within reach.
2:14

NVIDIA CEO Jensen Huang just gave us a glimpse into the future of AI, and it's far bigger than text and images. He asked: "If you can understand worlds, is it possible that you understand proteins and chemicals that have structure?” This is the quiet revolution happening in AI right now. We're moving from an AI that understands human language to an AI that understands the language of nature itself. The "letters" are atoms. The "words" are molecules. The "sentences" are the complex structures of life, networks, and reality. The same foundational models that generate video are now being used to: *Decode proteins to fight disease *Design new materials at the atomic level *Simulate complex systems in quantum computing These were once the domain of supercomputers and Nobel laureates. Now, they're becoming solvable problems for a new generation of startups. AI is transitioning from a tool for communication to a tool for creation and discovery in the physical world. This is where the next wave of generational companies will be built. The "hard-to-solve" problems are now within reach.

Konstantine Buhler

13,014 просмотров • 10 месяцев назад

🚨BREAKING: The AI film era has officially begun. The Dzine × Pixverse AI Short Film Challenge proved one thing: You don’t need cameras, actors, or editors to make a film anymore. Anyone can tell great stories now. This is the future of content creation↓
1:24

🚨BREAKING: The AI film era has officially begun. The Dzine × Pixverse AI Short Film Challenge proved one thing: You don’t need cameras, actors, or editors to make a film anymore. Anyone can tell great stories now. This is the future of content creation↓

Hasan Toor

71,128 просмотров • 1 год назад

Nobel Prize winner and Google DeepMind CEO Demis Hassabis just revealed the real AI skill gap: “The next generation will do things that used to take teams of 10, 20, 30, 50 people” Most people heard that and thought: “Cool, AI makes me faster” Wrong. AI does not just make people faster. It changes what one person can become. A startup used to need: > researcher > designer > developer > marketer > analyst > support team > ops manager Now one AI-native person can wire all of that into workflows. > Agents that research. > Tools that write. > Workflows that test. > Automations that publish. > Memory that compounds. This is not prompt engineering. This is leverage. The next 5 years will not belong to people who write better prompts. They will belong to people who build better workflows. Watch the full interview. Bookmark this. It is one of the most important ideas of the decade.
22:54

Nobel Prize winner and Google DeepMind CEO Demis Hassabis just revealed the real AI skill gap: “The next generation will do things that used to take teams of 10, 20, 30, 50 people” Most people heard that and thought: “Cool, AI makes me faster” Wrong. AI does not just make people faster. It changes what one person can become. A startup used to need: > researcher > designer > developer > marketer > analyst > support team > ops manager Now one AI-native person can wire all of that into workflows. > Agents that research. > Tools that write. > Workflows that test. > Automations that publish. > Memory that compounds. This is not prompt engineering. This is leverage. The next 5 years will not belong to people who write better prompts. They will belong to people who build better workflows. Watch the full interview. Bookmark this. It is one of the most important ideas of the decade.

spect

132,349 просмотров • 2 месяцев назад

I've been responding to hundreds of people who have been writing me "Merry Christmas" this morning. And a new little app that shipped one day ago has been helping me. Typeless Free app for iPhones. Way faster than I can type and I wrote eight books and type faster than anyone else I know. And now that we are in the AI age it's way faster to use your voice to work with AI agents than to type. Thought I'd do a little video. It's way faster to respond to everything now due to it. But the big message is Merry Christmas!
3:15

I've been responding to hundreds of people who have been writing me "Merry Christmas" this morning. And a new little app that shipped one day ago has been helping me. Typeless Free app for iPhones. Way faster than I can type and I wrote eight books and type faster than anyone else I know. And now that we are in the AI age it's way faster to use your voice to work with AI agents than to type. Thought I'd do a little video. It's way faster to respond to everything now due to it. But the big message is Merry Christmas!

Robert Scoble

20,069 просмотров • 8 месяцев назад

🇺🇸 ZUCK: META AI IS THE BIGGEST, BEST, IN THE WORLD!! Has anyone ever used it?... “Meta AI now has nearly 600 million monthly actives and as promised is on track to be the most used AI assistant in the world by the end of the year. Llama 3.3 is a new 70 billion parameter text model that performs about as well as our 405 billion parameter model but now it is easier and more efficient to run. So that is the last Lama 3.0 release. The next stop is Lama 4.0.” Source: Instagram
1:26

🇺🇸 ZUCK: META AI IS THE BIGGEST, BEST, IN THE WORLD!! Has anyone ever used it?... “Meta AI now has nearly 600 million monthly actives and as promised is on track to be the most used AI assistant in the world by the end of the year. Llama 3.3 is a new 70 billion parameter text model that performs about as well as our 405 billion parameter model but now it is easier and more efficient to run. So that is the last Lama 3.0 release. The next stop is Lama 4.0.” Source: Instagram

Mario Nawfal

482,099 просмотров • 1 год назад