Chris

@chatgpt21 • 43,224 subscribers

Agi 2029 - AI Insider / Reporter as featured in The Information • NYT • Techcrunch

Shorts

Frame mogged to oblivion 💀 This is GPT 5.4 not even pro.. In all seriousness these are videos of older models — this video was readily available so I thought it would be fun to compare how much we’ve improved in less than a year!

Frame mogged to oblivion 💀 This is GPT 5.4 not even pro.. In all seriousness these are videos of older models — this video was readily available so I thought it would be fun to compare how much we’ve improved in less than a year!

250,557 views

First Sora 2 Pro video after Sora Launch This is max performance on every setting. “A professional gymnast performance” Render time 7-10 minutes

First Sora 2 Pro video after Sora Launch This is max performance on every setting. “A professional gymnast performance” Render time 7-10 minutes

213,732 views

Sora 2, “ family guy dark humor” My personal thoughts: This is clearly the best AI video model for replicating animated shows. This truly gives credence to the fact that within the decade AI generated short films/shows is looking like a real possibility. My important caveats. Model trained only on video can get visually indistinguishable for most viewers most of the time. It can match texture, lighting, motion, and camera language so well that only careful inspection gives it away. However For sustained quality at the level of a full scene or an episode, video alone hits a ceiling IMO. Pure video likelihood drives the model toward what is frequent, not toward the rare timing and payoff choices that make the best jokes land. It has weak grasp of long arc causality, character memory, and joke structure. It also does not see intent, off screen context, or prosody unless you give it those signals. So you get something that looks right but drifts on beats that matter. I don’t know what the potential solution would be other than to have an AGI just animate the show for me. Any others ? Credit for the sora clip: figure

Sora 2, “ family guy dark humor” My personal thoughts: This is clearly the best AI video model for replicating animated shows. This truly gives credence to the fact that within the decade AI generated short films/shows is looking like a real possibility. My important caveats. Model trained only on video can get visually indistinguishable for most viewers most of the time. It can match texture, lighting, motion, and camera language so well that only careful inspection gives it away. However For sustained quality at the level of a full scene or an episode, video alone hits a ceiling IMO. Pure video likelihood drives the model toward what is frequent, not toward the rare timing and payoff choices that make the best jokes land. It has weak grasp of long arc causality, character memory, and joke structure. It also does not see intent, off screen context, or prosody unless you give it those signals. So you get something that looks right but drifts on beats that matter. I don’t know what the potential solution would be other than to have an AGI just animate the show for me. Any others ? Credit for the sora clip: figure

150,286 views

Holy sh!t ! OpenAI will have their custom inference chips ready in just a few months and deployed at scale by the end of the year! 🤯 Training chip = The heavy lifters that require massive amounts of data and power to build and teach the AI models from scratch. Inference chip = The specialized, highly efficient chips that actually run the AI and generate the answers in real-time when you use it. This is going to help OpenAI drastically cut down their massive compute costs, speed up model reasoning times, and finally break free from relying entirely on Nvidia to scale their operations.

Holy sh!t ! OpenAI will have their custom inference chips ready in just a few months and deployed at scale by the end of the year! 🤯 Training chip = The heavy lifters that require massive amounts of data and power to build and teach the AI models from scratch. Inference chip = The specialized, highly efficient chips that actually run the AI and generate the answers in real-time when you use it. This is going to help OpenAI drastically cut down their massive compute costs, speed up model reasoning times, and finally break free from relying entirely on Nvidia to scale their operations.

60,278 views

“Family guy Star Wars joke” Were actually so close 2-4 more good iterations and no lawsuits and I’m generating all of my entertainment

“Family guy Star Wars joke” Were actually so close 2-4 more good iterations and no lawsuits and I’m generating all of my entertainment

67,371 views

Gpt 5 vs Grok 4 SVG animation, (same prompt)

Gpt 5 vs Grok 4 SVG animation, (same prompt)

24,459 views

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🚨 GREG BROCKMAN JUST EXPLAINED THE NEXT LEAP WITH SPUD (GPT 5.5) Greg Brockman: "I think of Spud as a new base, as a new pre-train... I'd say it's like we have maybe two years worth of research that is coming to fruition in this model." Greg says: "There's this thing called 'big model smell'... when these models are just actually much smarter, much more capable, that they bend to you much more, and you feel it." Here is exactly what we are getting with the upcoming GPT 5.5 rollout: • "Big Model Smell": A massive qualitative shift. The models stop being rigid and start intuitively bending to what you actually want them to do. • Unlocking New Abilities: It can just do things it wasn’t able to before. The frustrating moments where the AI "doesn't quite get it" and needs you to over-explain are going away. • Longer Time Horizons: The ceiling is being completely raised. The new models will be able to autonomously solve complex, open-ended problems over much longer periods of time. • A New Pre-Train Base: This is not an incremental fine-tune. Spud is a completely new foundation built to accelerate the entire economy.

🚨 GREG BROCKMAN JUST EXPLAINED THE NEXT LEAP WITH SPUD (GPT 5.5) Greg Brockman: "I think of Spud as a new base, as a new pre-train... I'd say it's like we have maybe two years worth of research that is coming to fruition in this model." Greg says: "There's this thing called 'big model smell'... when these models are just actually much smarter, much more capable, that they bend to you much more, and you feel it." Here is exactly what we are getting with the upcoming GPT 5.5 rollout: • "Big Model Smell": A massive qualitative shift. The models stop being rigid and start intuitively bending to what you actually want them to do. • Unlocking New Abilities: It can just do things it wasn’t able to before. The frustrating moments where the AI "doesn't quite get it" and needs you to over-explain are going away. • Longer Time Horizons: The ceiling is being completely raised. The new models will be able to autonomously solve complex, open-ended problems over much longer periods of time. • A New Pre-Train Base: This is not an incremental fine-tune. Spud is a completely new foundation built to accelerate the entire economy.

201,638 views • 5 months ago

This week we’re getting GPT 5.5 and I couldn’t be more excited to see the first new pre train base in a while Before Spud releases, here’s the last video you need to watch - Greg Brockman perfectly indicated to us 3 important things that perfectly encapsulate the lineage of OpenAI and the mission. 1.This is the culmination of 2 years of research and is a fresh base pre-train that we haven’t gotten for a long time. 2.This is an “exciting release” and it will bring new capabilities (sort of a given but still very grateful nonetheless) & that it is AN EARLY VERSION of what we have coming - meaning they have a lot of RL to do to make this model even better since it’s a fresh pre-train. 3.THIS IS THE BEGINNING OF THE FLYWHEEL. As he said toward the end, “we have this engine of progress that just moves faster and faster and Spud is just one step along the way.” Depending on the capabilities we see this week from Spud, we may be able to map out if AGI will be sooner rather than later, judging by how much recursive work can exist within this model and the harness. In other words, the flywheel.

This week we’re getting GPT 5.5 and I couldn’t be more excited to see the first new pre train base in a while Before Spud releases, here’s the last video you need to watch - Greg Brockman perfectly indicated to us 3 important things that perfectly encapsulate the lineage of OpenAI and the mission. 1.This is the culmination of 2 years of research and is a fresh base pre-train that we haven’t gotten for a long time. 2.This is an “exciting release” and it will bring new capabilities (sort of a given but still very grateful nonetheless) & that it is AN EARLY VERSION of what we have coming - meaning they have a lot of RL to do to make this model even better since it’s a fresh pre-train. 3.THIS IS THE BEGINNING OF THE FLYWHEEL. As he said toward the end, “we have this engine of progress that just moves faster and faster and Spud is just one step along the way.” Depending on the capabilities we see this week from Spud, we may be able to map out if AGI will be sooner rather than later, judging by how much recursive work can exist within this model and the harness. In other words, the flywheel.

103,198 views • 4 months ago

OpenAI researcher Noam Brown on hallucination with the new IMO reasoning model: > Mathematicians used to comb through model solutions because earlier systems would quietly flip an inequality or tuck in a wrong step, creating hallucinated answers. > Brown says the updated IMO reasoning model now tends to say “I’m not sure” whenever it lacks a valid proof, which sharply cuts down on those hidden errors. TLDR, the model shows a clear shift away from hallucinations and toward reliable, self‑aware reasoning.

OpenAI researcher Noam Brown on hallucination with the new IMO reasoning model: > Mathematicians used to comb through model solutions because earlier systems would quietly flip an inequality or tuck in a wrong step, creating hallucinated answers. > Brown says the updated IMO reasoning model now tends to say “I’m not sure” whenever it lacks a valid proof, which sharply cuts down on those hidden errors. TLDR, the model shows a clear shift away from hallucinations and toward reliable, self‑aware reasoning.

230,471 views • 1 year ago

How is this AI 🤯 if you showed this to any millennial they’d think this is a new season of “curb your enthusiasm”

How is this AI 🤯 if you showed this to any millennial they’d think this is a new season of “curb your enthusiasm”

58,638 views • 6 months ago

Francois Chollet says his AGI timelines have dropped from 10 years to about 5 years, I wonder if he internally tested Open AIs new reasoning system that won gold at IMO

Francois Chollet says his AGI timelines have dropped from 10 years to about 5 years, I wonder if he internally tested Open AIs new reasoning system that won gold at IMO

83,501 views • 1 year ago

Sam Altman, when asked what he admires most about Elon Musk: "He’s extremely good at physical engineering and also extremely good at getting people to perform incredibly well at their jobs." Many people focused on Sam Altman ’s quotes regarding AGI here and I’m also at fault for that. However, watching this whole interview back, I’m genuinely surprised that despite OpenAI being the front runner in the AI race he seemed to talk a lot about democratization, saying no country. No one company should own the means of super intelligence even “in the name of safety.” It’s very rare to hear a CEO who’s number one in a field, saying that everybody should have the technology and it shouldn’t be condensed into one company. There were just many parts that seem selfless even when the interviewer had mistakenly said OpenAI was ahead of Google 10 years ago and then Sam Altman corrected him saying that they’ve only been ahead for the past three years.

Sam Altman, when asked what he admires most about Elon Musk: "He’s extremely good at physical engineering and also extremely good at getting people to perform incredibly well at their jobs." Many people focused on Sam Altman ’s quotes regarding AGI here and I’m also at fault for that. However, watching this whole interview back, I’m genuinely surprised that despite OpenAI being the front runner in the AI race he seemed to talk a lot about democratization, saying no country. No one company should own the means of super intelligence even “in the name of safety.” It’s very rare to hear a CEO who’s number one in a field, saying that everybody should have the technology and it shouldn’t be condensed into one company. There were just many parts that seem selfless even when the interviewer had mistakenly said OpenAI was ahead of Google 10 years ago and then Sam Altman corrected him saying that they’ve only been ahead for the past three years.

35,029 views • 6 months ago

Sam Altman on GPT 6: “There will be a chance that it will be a GPT 3-4 style leap” in terms of science problems, where with GPT 5 it has these tiny glimmers and “GPT 6 it can really do it”

Sam Altman on GPT 6: “There will be a chance that it will be a GPT 3-4 style leap” in terms of science problems, where with GPT 5 it has these tiny glimmers and “GPT 6 it can really do it”

42,684 views • 9 months ago

🚨 Two really important Figure robotics updates. - 1st, they will be announcing two new commercial customers in the next 60 days. This means Figure will probably be the first humanoid robotics company in the United States after Digit (Agility Robotics) to hit true commercial deployment. It puts them in an extremely elite group alongside the very few other humanoid companies actually gaining real-world commercial revenue right now, like Apptronik. That's really exciting. Second, Brett Adcock confirmed they are now making a robot every 90 minutes. Let's do the math on that production line: • At one robot every 90 minutes, they are building 16 robots per day. • That translates to roughly 480 robots per month. • Which equals over 5,840 robots per year! That means Figure by the end of 2026 should have nearly 6,000 humanoids produced and ready to enter the workforce. They might be Tesla this year we will have to see 👀

🚨 Two really important Figure robotics updates. - 1st, they will be announcing two new commercial customers in the next 60 days. This means Figure will probably be the first humanoid robotics company in the United States after Digit (Agility Robotics) to hit true commercial deployment. It puts them in an extremely elite group alongside the very few other humanoid companies actually gaining real-world commercial revenue right now, like Apptronik. That's really exciting. Second, Brett Adcock confirmed they are now making a robot every 90 minutes. Let's do the math on that production line: • At one robot every 90 minutes, they are building 16 robots per day. • That translates to roughly 480 robots per month. • Which equals over 5,840 robots per year! That means Figure by the end of 2026 should have nearly 6,000 humanoids produced and ready to enter the workforce. They might be Tesla this year we will have to see 👀

18,392 views • 4 months ago

Sam Altman: “I didn’t think Elon was gonna unfairly abuse his power to compete” 😮

Sam Altman: “I didn’t think Elon was gonna unfairly abuse his power to compete” 😮

36,005 views • 1 year ago

🚨 FRANCOIS CHOLLET SAYS THE CURRENT LLM STACK IS THE WRONG PATH TO AGI Interviewer: “When will we accomplish the first definition of AGI?” Chollet confirms we are already on that exact trajectory, pointing out that: "Current technology can fully automate at human level or beyond any domain where you have verifiable rewards, right? And code... code being the first one." He then brings up the problem with LLMs, stating that: "It's possible in principle to build something that looks a lot like AGI on top of the LLM stack... I do believe, however, this would be the wrong thing to do because it would be very inefficient." Looking ahead to what the final architecture will actually require, he explains that: "AI research will have to trend towards not just efficiency, but in fact optimality over time. And for this reason, future AI in a few decades... it's not going to be this harness on top of a reasoning model on top of a base LLM."

🚨 FRANCOIS CHOLLET SAYS THE CURRENT LLM STACK IS THE WRONG PATH TO AGI Interviewer: “When will we accomplish the first definition of AGI?” Chollet confirms we are already on that exact trajectory, pointing out that: "Current technology can fully automate at human level or beyond any domain where you have verifiable rewards, right? And code... code being the first one." He then brings up the problem with LLMs, stating that: "It's possible in principle to build something that looks a lot like AGI on top of the LLM stack... I do believe, however, this would be the wrong thing to do because it would be very inefficient." Looking ahead to what the final architecture will actually require, he explains that: "AI research will have to trend towards not just efficiency, but in fact optimality over time. And for this reason, future AI in a few decades... it's not going to be this harness on top of a reasoning model on top of a base LLM."

15,578 views • 4 months ago

Very Boston dynamics coded, increasingly becoming clear that this is the future of warfare

Very Boston dynamics coded, increasingly becoming clear that this is the future of warfare

18,726 views • 9 months ago

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