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.Ilya Sutskever on why OpenAI gave up on robotics: "Progress comes from the combination of compute and data. There was no path to data from robotics. I'd say that now it is possible to create a path forward, but one needs to really commit. You could imagine a gradual... show more

Dwarkesh Patel

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325,857 görüntüleme • 2 yıl önce •via X (Twitter)

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Richard profil fotoğrafı

Richard2 yıl önce

@ilyasut Sounds like the path being created by Tesla autopilot. The cars are essentially robots on wheel. Now, they’re creating humanoid robots.

Bilal profil fotoğrafı

Bilal2 yıl önce

@ilyasut Good chance he moves to Tesla

wannabe futurist profil fotoğrafı

wannabe futurist2 yıl önce

@ilyasut @elonmusk - all the more reason you got to bring Ilya to @Tesla

Soon Yeow Lee profil fotoğrafı

Soon Yeow Lee2 yıl önce

@WholeMarsBlog @ilyasut Ilya’s comment was really eye-opening! OpenAI can only handle LLMs (like ChatGPT), practical AIs (like FSD) are really tough, especially robots (like Optimus). Yet, ironically, these toughest parts are where Elon's projects excel the most. Tesla is truly the big brother of AI.

Tim profil fotoğrafı

Tim2 yıl önce

@ilyasut Talking about @Tesla without talking about Tesla.

Pawel Pachniewski profil fotoğrafı

Pawel Pachniewski2 yıl önce

@ilyasut With some paradigm shifts and insights into say, why Moravec's Paradox was ever an issue, we could have made more progress.

Cache Money profil fotoğrafı

Cache Money2 yıl önce

@ilyasut always so insightful whenever Ilya speaks

joswiseman profil fotoğrafı

joswiseman2 yıl önce

@ilyasut This is naive from people who define robotics as transformed movie or terminators. Robots should be any devices.....phones, cars, buses, laptops, planes...trains...if only you can imagine.

Nodir profil fotoğrafı

Nodir2 yıl önce

@ilyasut Maybe you need a really good physics engine to generate synthetic data

Triyansha profil fotoğrafı

Triyansha2 yıl önce

the logistical challenges of building even a low cost robotics startup are truly a nightmare. a mentor once told me that while algorithms win software, business model innovation will win hardware wars. if anyone is writing more about this, would love to read more on the topic...DM

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wild! Sam Altman said OpenAI are trying to figure out robotics: “If you could pick one thing to make the US competitive at manufacturing, you would say we need robots that can build a lot more robots”

wild! Sam Altman said OpenAI are trying to figure out robotics: “If you could pick one thing to make the US competitive at manufacturing, you would say we need robots that can build a lot more robots”

Damian Player

161,922 görüntüleme • 3 ay önce

So many robotics companies trying to solve everything at once… Last year I talked to Nima Gard, Director of AI at Path Robotics about this… Doing one thing really really well. They went after welding. Today they’re introducing Rove™, which embodies Obsidian™ (Path's physical AI model for manufacturing) on a legged mobile platform. The result is the intelligence to autonomously weld with the mobility to bring the worker to the work. Path Robotics (Columbus, Ohio) has raised more than $300 million in venture capital to build autonomous AI-powered welding cells. I think the tech is pretty impressive and video really cool. Congrats guys! Credit: Path Robotics

So many robotics companies trying to solve everything at once… Last year I talked to Nima Gard, Director of AI at Path Robotics about this… Doing one thing really really well. They went after welding. Today they’re introducing Rove™, which embodies Obsidian™ (Path's physical AI model for manufacturing) on a legged mobile platform. The result is the intelligence to autonomously weld with the mobility to bring the worker to the work. Path Robotics (Columbus, Ohio) has raised more than $300 million in venture capital to build autonomous AI-powered welding cells. I think the tech is pretty impressive and video really cool. Congrats guys! Credit: Path Robotics

Ilir Aliu

23,488 görüntüleme • 3 ay önce

We asked Angus about the future of robotics and AI training. “I built an industrial-grade kinematic solver for 6 degrees of freedom motion, with full path planning and joint control." "You can stream AI model outputs into it, or run it like a traditional industrial robot." "The benefit of that is all of that information you can stream and record from those joints… you can use that as the training data." "Frankly, moving a robot with a lever is really crap data for training robots. But this gives you smooth, high-quality motion, without needing two robots.”

We asked Angus about the future of robotics and AI training. “I built an industrial-grade kinematic solver for 6 degrees of freedom motion, with full path planning and joint control." "You can stream AI model outputs into it, or run it like a traditional industrial robot." "The benefit of that is all of that information you can stream and record from those joints… you can use that as the training data." "Frankly, moving a robot with a lever is really crap data for training robots. But this gives you smooth, high-quality motion, without needing two robots.”

TBPN

18,811 görüntüleme • 1 yıl önce

“There are more companies than ideas by quite a bit. Compute is large enough such that it's not obvious that you need that much more compute to prove some idea. AlexNet was built on 2 GPUs. The transformer was built on 8 to 64 GPUs. Which would be, what, 2 GPUs of today? You could argue that o1 reasoning was not the most compute heavy thing in the world. For research, you definitely need some amount of compute, but it's far from obvious that you need the absolutely largest amount of compute. If everyone is within the same paradigm, then compute becomes one of the big differentiators.” Ilya Sutskever

“There are more companies than ideas by quite a bit. Compute is large enough such that it's not obvious that you need that much more compute to prove some idea. AlexNet was built on 2 GPUs. The transformer was built on 8 to 64 GPUs. Which would be, what, 2 GPUs of today? You could argue that o1 reasoning was not the most compute heavy thing in the world. For research, you definitely need some amount of compute, but it's far from obvious that you need the absolutely largest amount of compute. If everyone is within the same paradigm, then compute becomes one of the big differentiators.” Ilya Sutskever

Dwarkesh Patel

203,605 görüntüleme • 7 ay önce

Data centers in space are a "no brainer." SpaceX's 1st employee Tom Mueller (Tom Mueller) on Elon Musk's plan to move compute into space: "It makes the most sense of anything to move to space. All you need as an input is power, and all you have as an output is data." "You move it to space, you have all the power you would ever need, and you transmit that data back down on a terawatt laser beam—it's solved. It's just so simple."

Data centers in space are a "no brainer." SpaceX's 1st employee Tom Mueller (Tom Mueller) on Elon Musk's plan to move compute into space: "It makes the most sense of anything to move to space. All you need as an input is power, and all you have as an output is data." "You move it to space, you have all the power you would ever need, and you transmit that data back down on a terawatt laser beam—it's solved. It's just so simple."

Molly O’Shea

357,424 görüntüleme • 1 ay önce

"We're not a consumer company, we're the shortest path to artificial labor." - Bernt Bornich, founder of 1X "It just happens to be that the shortest path is through consumer, because you need to live and learn among people." "Model intelligence comes from the diversity of your AI dataset. There isn't enough variance (if you are just) in a factory." "We want to deploy robots there (in homes), where we get data through a truly intelligent machine that doesn't just repeat a motion."

"We're not a consumer company, we're the shortest path to artificial labor." - Bernt Bornich, founder of 1X "It just happens to be that the shortest path is through consumer, because you need to live and learn among people." "Model intelligence comes from the diversity of your AI dataset. There isn't enough variance (if you are just) in a factory." "We want to deploy robots there (in homes), where we get data through a truly intelligent machine that doesn't just repeat a motion."

TBPN

15,742 görüntüleme • 1 yıl önce

Crypto meets robotics. Superteam Georgia member's CrowdBrain on building on Solana and becoming the Colosseum grand champion: "When I started at Solana, I knew no one. We became hackathon winners in 2021, and we built one of the biggest gaming projects on Solana ever. You have to manifest it and put the work in, and everything's gonna happen." "Crypto allows you to create network effects and coordinate on a decentralized network. Robotics is missing the human layer. Robotics companies need humans to train robots, control them remotely, and collect real world data. Crowdbrain gives them trained operators and the infrastructure to do that at scale."

Crypto meets robotics. Superteam Georgia member's CrowdBrain on building on Solana and becoming the Colosseum grand champion: "When I started at Solana, I knew no one. We became hackathon winners in 2021, and we built one of the biggest gaming projects on Solana ever. You have to manifest it and put the work in, and everything's gonna happen." "Crypto allows you to create network effects and coordinate on a decentralized network. Robotics is missing the human layer. Robotics companies need humans to train robots, control them remotely, and collect real world data. Crowdbrain gives them trained operators and the infrastructure to do that at scale."

Solana

91,296 görüntüleme • 13 gün önce

Here’s Elon Musk explaining that SpaceX could launch up to one terawatt per year of AI compute capacity into Earth orbit — equivalent to the power output of roughly 1,000 nuclear power plants. “The next step beyond Earth data centers is our Earth orbital data centers. And we'll be launching with SpaceX orbital data centers at the 100-to-200-gigawatt-per-year level. Not cumulative, per year. And ultimately, we see a path to maybe launching as much as a terawatt per year of compute from Earth. But what if you want to go beyond a mere terawatt per year? In order to do that, you have to go to the Moon. So by having factories on the Moon, building AI satellites, and having a mass driver, which is the kind of thing you really only learn about in or read about in science fiction, but we're going to make it real. We're actually going to have a mass driver on the Moon. And if you do that, you can go several orders of magnitude greater. You can go to 1,000 gigawatts or more per year and ultimately get to maybe a millionth and then a thousandth and maybe even a few percent of the Sun's energy.” xAI All-Hands, February 10, 2026

Here’s Elon Musk explaining that SpaceX could launch up to one terawatt per year of AI compute capacity into Earth orbit — equivalent to the power output of roughly 1,000 nuclear power plants. “The next step beyond Earth data centers is our Earth orbital data centers. And we'll be launching with SpaceX orbital data centers at the 100-to-200-gigawatt-per-year level. Not cumulative, per year. And ultimately, we see a path to maybe launching as much as a terawatt per year of compute from Earth. But what if you want to go beyond a mere terawatt per year? In order to do that, you have to go to the Moon. So by having factories on the Moon, building AI satellites, and having a mass driver, which is the kind of thing you really only learn about in or read about in science fiction, but we're going to make it real. We're actually going to have a mass driver on the Moon. And if you do that, you can go several orders of magnitude greater. You can go to 1,000 gigawatts or more per year and ultimately get to maybe a millionth and then a thousandth and maybe even a few percent of the Sun's energy.” xAI All-Hands, February 10, 2026

ELON CLIPS

21,962 görüntüleme • 4 ay önce

ELON MUSK: "With Robotics and AI, this is really the path to abundance for all. If you say people often talk about solving global poverty, essentially, how do we make give everyone a very high standard of living? I think the only way to do this is AI and robotics. I mean this, we need to be very careful with AI. We need to be very careful with robotics. We don't want to find ourselves in a James Cameron movie. We don't want to be a Terminator, obviously. But if you have ubiquitous AI that is essentially free or close to it, and ubiquitous robotics, then you will have an explosion in the global economy and expansion the global economy that is truly beyond all precedent."

ELON MUSK: "With Robotics and AI, this is really the path to abundance for all. If you say people often talk about solving global poverty, essentially, how do we make give everyone a very high standard of living? I think the only way to do this is AI and robotics. I mean this, we need to be very careful with AI. We need to be very careful with robotics. We don't want to find ourselves in a James Cameron movie. We don't want to be a Terminator, obviously. But if you have ubiquitous AI that is essentially free or close to it, and ubiquitous robotics, then you will have an explosion in the global economy and expansion the global economy that is truly beyond all precedent."

DogeDesigner

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Q: "What made you say, 'I want to be a member of Congress now...'?" A: "Because I felt I wasn't doing enough. ... It's sort of unfair to be saying to Democratic office holders, 'You need to do more! You need to do more!,' It's easy to lob stuff in from the sidelines. And so, I'm putting it all on the line."

Q: "What made you say, 'I want to be a member of Congress now...'?" A: "Because I felt I wasn't doing enough. ... It's sort of unfair to be saying to Democratic office holders, 'You need to do more! You need to do more!,' It's easy to lob stuff in from the sidelines. And so, I'm putting it all on the line."

George Conway ⚖️🇺🇸

113,932 görüntüleme • 6 ay önce

.Anish Acharya says the future of AI isn’t one model to rule them all—and explains why platforms that integrate multiple models will benefit the most: "I think we're going to need and rely on all of the models." "It's sort of like if you have a team of people... if you have five people, they could all do a basic set of things pretty capably." "But then they all have their specializations. Maybe one of them is really good at closing a customer who doesn't want to sign the deal, and one of them is really good at culture and getting the best out of the team." "There are some areas in which they are going to build apps, and that will be a threat to app companies. But there are many areas in which app companies are advantaged. Cursor and Krea are great examples of this—products where you benefit from being multi-model." "When you actually use a creative tool, you don't want to just use Nano Banana, you want to have access to OpenAI, Nano Banana, Kling—all of them—Qwen, you name it. So using a single interface to access all the models is powerful." Anish Acharya on BILLIONS with Guillaume Moubeche

.Anish Acharya says the future of AI isn’t one model to rule them all—and explains why platforms that integrate multiple models will benefit the most: "I think we're going to need and rely on all of the models." "It's sort of like if you have a team of people... if you have five people, they could all do a basic set of things pretty capably." "But then they all have their specializations. Maybe one of them is really good at closing a customer who doesn't want to sign the deal, and one of them is really good at culture and getting the best out of the team." "There are some areas in which they are going to build apps, and that will be a threat to app companies. But there are many areas in which app companies are advantaged. Cursor and Krea are great examples of this—products where you benefit from being multi-model." "When you actually use a creative tool, you don't want to just use Nano Banana, you want to have access to OpenAI, Nano Banana, Kling—all of them—Qwen, you name it. So using a single interface to access all the models is powerful." Anish Acharya on BILLIONS with Guillaume Moubeche

a16z

33,175 görüntüleme • 4 ay önce

jiwoong is officially debuting in zerobaseone, its been a really long journey for you , but you never gave up trying to chase your dream , and now you make it after years of tying , i hope you'll always walk on the flowery path from now on , lets shine more idol jiwoong

jiwoong is officially debuting in zerobaseone, its been a really long journey for you , but you never gave up trying to chase your dream , and now you make it after years of tying , i hope you'll always walk on the flowery path from now on , lets shine more idol jiwoong

Vio || jiwoong

19,862 görüntüleme • 3 yıl önce

Unreal Engine 5 is becoming the go-to platform for robotics teams, not just as a simulator but as a synthetic data factory powering the next generation of robotics systems🦾 From synthetic data to sim-to-real transfer, read our piece on how UE5 is quietly reshaping how robots learn to see, move, and act in the real world:

Unreal Engine 5 is becoming the go-to platform for robotics teams, not just as a simulator but as a synthetic data factory powering the next generation of robotics systems🦾 From synthetic data to sim-to-real transfer, read our piece on how UE5 is quietly reshaping how robots learn to see, move, and act in the real world:

Unreal Engine

61,187 görüntüleme • 3 ay önce

Greg Brockman talks about when OpenAI first realized that AGI can't be achieved with "Non-Profit" status and the decided to abandon its Non-Profit roots. "In 2017, we started to think very hard about, first of all, how do we really achieve the mission? How do we actually build an AGI? What will that look like? And we started to do the math on compute. You start to realize that it is going to take a big computer. We came across a company called Cerebras, which was building a unique piece of computing hardware. The kind of computer that they were promising, we realized, was going to be far advanced from where our compute calculations looked. As you start to realize, if we could buy a lot of those computers, we could actually probably succeed at building an AGI. If we could get exclusive access to Cerebras, that could give us an overwhelming advantage. If we could buy very large data centers, that could be something unique as well. The thing about nonprofit fundraising is that I think there is essentially a cap to what is possible there. And so Elon, Sam, Ilya, and I all agreed that the only path forward for OpenAI, and the only path to achieve the mission, was to create a for-profit entity associated with OpenAI in some form. And so, we were committed to that direction. That is something that we knew was the only way to achieve the mission." --- From "The Knowledge Project Podcast" YT Channel (link in comment)

Greg Brockman talks about when OpenAI first realized that AGI can't be achieved with "Non-Profit" status and the decided to abandon its Non-Profit roots. "In 2017, we started to think very hard about, first of all, how do we really achieve the mission? How do we actually build an AGI? What will that look like? And we started to do the math on compute. You start to realize that it is going to take a big computer. We came across a company called Cerebras, which was building a unique piece of computing hardware. The kind of computer that they were promising, we realized, was going to be far advanced from where our compute calculations looked. As you start to realize, if we could buy a lot of those computers, we could actually probably succeed at building an AGI. If we could get exclusive access to Cerebras, that could give us an overwhelming advantage. If we could buy very large data centers, that could be something unique as well. The thing about nonprofit fundraising is that I think there is essentially a cap to what is possible there. And so Elon, Sam, Ilya, and I all agreed that the only path forward for OpenAI, and the only path to achieve the mission, was to create a for-profit entity associated with OpenAI in some form. And so, we were committed to that direction. That is something that we knew was the only way to achieve the mission." --- From "The Knowledge Project Podcast" YT Channel (link in comment)

Rohan Paul

10,311 görüntüleme • 2 ay önce

Larry Ellison—owner of Oracle, CBS, and now TikTok—tells Tony Blair about his plan to use digital ID to "unify" all data on each country's citizens "so it can be consumed and used by" his AI models. "We have to take all of this data... and move it into a single, if you will, unified data platform." "When we want to ask a question, we've provided that AI model with all the data they need to understand our country." "We need to unify all of the national data, put it into a database where it's easily consumable by the AI model, and then ask whatever question you like."

Larry Ellison—owner of Oracle, CBS, and now TikTok—tells Tony Blair about his plan to use digital ID to "unify" all data on each country's citizens "so it can be consumed and used by" his AI models. "We have to take all of this data... and move it into a single, if you will, unified data platform." "When we want to ask a question, we've provided that AI model with all the data they need to understand our country." "We need to unify all of the national data, put it into a database where it's easily consumable by the AI model, and then ask whatever question you like."

Wide Awake Media

144,324 görüntüleme • 6 ay önce

Saying "NO AI data centers" won't end in victory. They'll just build them anyways. If you truly want to make a difference, you need to say, "No data centers, UNLESS..." Turn it into a negotiation instead of a war, so we can fight over what really matters. No data centers UNLESS they're not draining our energy. In fact, you could say, "you want 10 gigawatts of power? Ok, YOU pay for it. And because we’re allowing you to do it, you have to produce 15 gigawatts of power and give the excess to the grid." It's a win-win and YOU control the terms.

Saying "NO AI data centers" won't end in victory. They'll just build them anyways. If you truly want to make a difference, you need to say, "No data centers, UNLESS..." Turn it into a negotiation instead of a war, so we can fight over what really matters. No data centers UNLESS they're not draining our energy. In fact, you could say, "you want 10 gigawatts of power? Ok, YOU pay for it. And because we’re allowing you to do it, you have to produce 15 gigawatts of power and give the excess to the grid." It's a win-win and YOU control the terms.

Glenn Beck

70,593 görüntüleme • 1 ay önce

Perplexity CEO Aravind Srinivas on the biggest threat to the data center industry: It's not competition. It's not regulation. It's decentralisation. "The biggest threat to a data center is if the intelligence can be packed locally on a chip that's running on the device and then there's no need to inference all of it on like one centralized data center." He outlines how this could work in practice. Personalisation doesn't necessarily require on-device model training. Retrieval augmented generation, tool calls, and local data can already tailor AI to individual users. But the real unlock? Test time training. Aravind Srinivas describes a future where AI lives on your device, watches how you work and gradually automates your repetitive tasks. "Imagine we crack test time training where the AI watches tasks you repeatedly do on your local system, adapts to you over time and starts automating a lot of the things you do." The key insight: in this model, the intelligence belongs to you. It's your data, your device, your personalised AI brain. And if that future arrives, the economics of centralised infrastructure start to collapse. "That really disrupts the whole data center industry. It doesn't make sense to spend all this money, 500 billion, 5 trillion, whatever on building all the centralized data centers across the world that do a lot of the intelligence workloads for people." The companies spending trillions on centralised infrastructure may want to rethink where intelligence actually needs to live.

Perplexity CEO Aravind Srinivas on the biggest threat to the data center industry: It's not competition. It's not regulation. It's decentralisation. "The biggest threat to a data center is if the intelligence can be packed locally on a chip that's running on the device and then there's no need to inference all of it on like one centralized data center." He outlines how this could work in practice. Personalisation doesn't necessarily require on-device model training. Retrieval augmented generation, tool calls, and local data can already tailor AI to individual users. But the real unlock? Test time training. Aravind Srinivas describes a future where AI lives on your device, watches how you work and gradually automates your repetitive tasks. "Imagine we crack test time training where the AI watches tasks you repeatedly do on your local system, adapts to you over time and starts automating a lot of the things you do." The key insight: in this model, the intelligence belongs to you. It's your data, your device, your personalised AI brain. And if that future arrives, the economics of centralised infrastructure start to collapse. "That really disrupts the whole data center industry. It doesn't make sense to spend all this money, 500 billion, 5 trillion, whatever on building all the centralized data centers across the world that do a lot of the intelligence workloads for people." The companies spending trillions on centralised infrastructure may want to rethink where intelligence actually needs to live.

Big Brain AI

90,102 görüntüleme • 4 ay önce

John: "Over in China, they’re doing robot Olympics. They’re doing marathons and all sorts of stuff." Figure founder Brett Adcock: “We look at the distribution of what humans do that is useful, and we [designed our humanoid] to do as much of that as possible.” “These things where we run marathons, or we do backflips, or we do karate moves—they’re not in the main part of the distribution. They don’t matter. And if you really want to size for those, you’re going to build a really expensive and unsafe robot that’s hard to manufacture.” “People want the $10,000 humanoid that can do general-purpose work. We want it to do laundry and dishes and be a companion. I want to ship robots at scale into the workforce to do logistics and healthcare, and build buildings and data centers.” "I don't need [our humanoid] to do backflips to do any of that work. I want robots building other robots."

John: "Over in China, they’re doing robot Olympics. They’re doing marathons and all sorts of stuff." Figure founder Brett Adcock: “We look at the distribution of what humans do that is useful, and we [designed our humanoid] to do as much of that as possible.” “These things where we run marathons, or we do backflips, or we do karate moves—they’re not in the main part of the distribution. They don’t matter. And if you really want to size for those, you’re going to build a really expensive and unsafe robot that’s hard to manufacture.” “People want the $10,000 humanoid that can do general-purpose work. We want it to do laundry and dishes and be a companion. I want to ship robots at scale into the workforce to do logistics and healthcare, and build buildings and data centers.” "I don't need [our humanoid] to do backflips to do any of that work. I want robots building other robots."

TBPN

15,419 görüntüleme • 5 ay önce

Flapping Airplanes co-founder Asher Spector explains why data efficiency is the greatest bottleneck to AI adoption: "To the extent that AI has been hard to integrate into the economy, I really think it's because models are much less data-efficient than humans. If you want it to learn a new task, or put it in a new vertical, it takes thousands of times more effort than it does to just tell a human what to do." "If you can make a model a million times more data-efficient, it's a million times easier to put into the economy. There's a ton of cool stuff that you can do in really data-constrained regimes. For example, whether it's robotics, or scientific discovery, or even something like trading, these problems have very limited data, and existing AI systems aren't quite as good at them as they are at other things. I think that learning to learn with less data is just tremendously valuable in all of these domains."

Flapping Airplanes co-founder Asher Spector explains why data efficiency is the greatest bottleneck to AI adoption: "To the extent that AI has been hard to integrate into the economy, I really think it's because models are much less data-efficient than humans. If you want it to learn a new task, or put it in a new vertical, it takes thousands of times more effort than it does to just tell a human what to do." "If you can make a model a million times more data-efficient, it's a million times easier to put into the economy. There's a ton of cool stuff that you can do in really data-constrained regimes. For example, whether it's robotics, or scientific discovery, or even something like trading, these problems have very limited data, and existing AI systems aren't quite as good at them as they are at other things. I think that learning to learn with less data is just tremendously valuable in all of these domains."

TBPN

90,711 görüntüleme • 5 ay önce

Mack Brown shares a can't miss message on habits and success. "If your habits do not lead to your dreams - change your habits." "If I'm not doing the things that I need to do to be successful out here, figure out why and do it. You wanna do it. It's easy to do." Then he delivered the real truth: "It's not what you're capable of doing. It's what you're willing to do." "You are all capable or you wouldn't be here. Every one of you. All of you are really good or they wouldn't have brought you in." "But what are you willing to do?" Many are capable, few are COMMITTED. "Now you should make the choice to be the best you can be and do what you were brought here to do and be a great teammate." You win through your habits and how you show up. The first choice is to show up. The next choice is to commit. Commit, show up, do the work, and stack the days. (🎥Texas Women's Swimming & Diving)

Mack Brown shares a can't miss message on habits and success. "If your habits do not lead to your dreams - change your habits." "If I'm not doing the things that I need to do to be successful out here, figure out why and do it. You wanna do it. It's easy to do." Then he delivered the real truth: "It's not what you're capable of doing. It's what you're willing to do." "You are all capable or you wouldn't be here. Every one of you. All of you are really good or they wouldn't have brought you in." "But what are you willing to do?" Many are capable, few are COMMITTED. "Now you should make the choice to be the best you can be and do what you were brought here to do and be a great teammate." You win through your habits and how you show up. The first choice is to show up. The next choice is to commit. Commit, show up, do the work, and stack the days. (🎥Texas Women's Swimming & Diving)

Coach AJ 🎯 Mental Fitness

73,752 görüntüleme • 2 ay önce