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AI is all about "knowing what you don't know" Here's an interactive exploration of the Andromeda: - React Three Fiber + Three.js - 600k particles (my m4 gets rly hot) - GSAP for smooth camera animations - Bloom post-processing for realistic stellar glow The more impressive piece here is...

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matt palmer

41,472 subscribers

17,327 次观看 • 9 个月前 •via X (Twitter)

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A little sneak peak at what I am building with Brayden Levangie using the X API. A new kind of personalized X is now possible. And it comes with many side benefits I haven’t yet shown here. Like feeds for your OpenClaw🦞 And reports that go way being what you can make with AIs that aren’t cognitive architectures. This is how I keep up now on the AI industry here on X. Looking for help to turn this into a business. Sponsors and customers who need much better reports on what is happening right now. What do you wish this effort would show you? By the way. I did ask this without writing a line of code. Brayden’s agents did it all.
6:16

A little sneak peak at what I am building with Brayden Levangie using the X API. A new kind of personalized X is now possible. And it comes with many side benefits I haven’t yet shown here. Like feeds for your OpenClaw🦞 And reports that go way being what you can make with AIs that aren’t cognitive architectures. This is how I keep up now on the AI industry here on X. Looking for help to turn this into a business. Sponsors and customers who need much better reports on what is happening right now. What do you wish this effort would show you? By the way. I did ask this without writing a line of code. Brayden’s agents did it all.

Robert Scoble

67,675 次观看 • 5 个月前

Whole Earth AI is a project-based learning tool. I built it to explore two questions: 1. what new ux patterns do LLMs make possible? 2. what might the montessori method applied to software for adults look like? here's what I learned,
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Whole Earth AI is a project-based learning tool. I built it to explore two questions: 1. what new ux patterns do LLMs make possible? 2. what might the montessori method applied to software for adults look like? here's what I learned,

kasey

50,106 次观看 • 1 年前

📝 AI/ML for Biology & Healthcare: A Learning Path This blog is highly inspired by my experience and exploration in the field of ML for biology and healthcare. Everything that I've been studying for the past years and a more structured way to learn the foundational knowledge to tackle problems in this impactful field. Here's what I covered in the blog: — Programming & Engineering — AI & Machine Learning — Mathematics for ML — Healthcare — Biology & Biolomedicine This is what I hoped to have when I first started learning all this. 🔗 link:
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📝 AI/ML for Biology & Healthcare: A Learning Path This blog is highly inspired by my experience and exploration in the field of ML for biology and healthcare. Everything that I've been studying for the past years and a more structured way to learn the foundational knowledge to tackle problems in this impactful field. Here's what I covered in the blog: — Programming & Engineering — AI & Machine Learning — Mathematics for ML — Healthcare — Biology & Biolomedicine This is what I hoped to have when I first started learning all this. 🔗 link:

TK • 木下

26,889 次观看 • 8 个月前

Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO Brian Armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛.
1:16

Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO Brian Armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛.

The All-In Podcast

80,524 次观看 • 6 个月前

when ai meets cryptocurrency = HeyElsa in this video i explain what the ai is all about and the features i did a step by step guide on how to get started on Heyelsaai.
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when ai meets cryptocurrency = HeyElsa in this video i explain what the ai is all about and the features i did a step by step guide on how to get started on Heyelsaai.

Confido

91,440 次观看 • 6 个月前

Coinbase CEO, Brian Armstrong: Some great insights on how they are using internally hosted AI Agents. "It’s connected to every Slack message, every Google Doc, and every Salesforce data confluence. Now, this is all linked up and the data is all aggregated, so you can ask these agents questions. Every team is using it—legal, finance, everything. It’s like the "Oracle of Coinbase." I’ve started to ask it things that go beyond just simple prompting, like "Hey, can you write this kind of memo for me?" I’m asking these AI agents now, as CEO, "What should I be aware of in the company that I might not be aware of?" It will tell me, "Did you know that there’s actually disagreement on this team about the strategy?" I realized I didn't know that, but the AI does because it can read every Slack message and every Google Doc. Tobi, who is on my board, calls this "reverse prompting." Instead of telling the AI agent what you want to do, you ask it what you should be thinking more about." --- From The All-In Podcast YT channel (link in comment)
1:20

Coinbase CEO, Brian Armstrong: Some great insights on how they are using internally hosted AI Agents. "It’s connected to every Slack message, every Google Doc, and every Salesforce data confluence. Now, this is all linked up and the data is all aggregated, so you can ask these agents questions. Every team is using it—legal, finance, everything. It’s like the "Oracle of Coinbase." I’ve started to ask it things that go beyond just simple prompting, like "Hey, can you write this kind of memo for me?" I’m asking these AI agents now, as CEO, "What should I be aware of in the company that I might not be aware of?" It will tell me, "Did you know that there’s actually disagreement on this team about the strategy?" I realized I didn't know that, but the AI does because it can read every Slack message and every Google Doc. Tobi, who is on my board, calls this "reverse prompting." Instead of telling the AI agent what you want to do, you ask it what you should be thinking more about." --- From The All-In Podcast YT channel (link in comment)

Rohan Paul

174,884 次观看 • 4 个月前

Caitlin Clark on how she gets covered by the media: "I think there's just like a false characterization of who I am sometimes. And I get it like as a reporter or as a blogger, like you can write an opinion piece and that's your job and whatever. But at the same time, like you don't know me. Like we've never had a conversation. I get people have a job to do. But at the same time, like don't make accusations about my character and who I am when you don't know me. I understand this is your job and this is your profession, and this is what you get to do. And basketball is my profession, what I get to do. And the reason I play it is when I step in between the lines, I love it. And that's what's so fun about it for me is like, I get to compete. This was always my dream. And nobody should ever try to take that away from me"
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Caitlin Clark on how she gets covered by the media: "I think there's just like a false characterization of who I am sometimes. And I get it like as a reporter or as a blogger, like you can write an opinion piece and that's your job and whatever. But at the same time, like you don't know me. Like we've never had a conversation. I get people have a job to do. But at the same time, like don't make accusations about my character and who I am when you don't know me. I understand this is your job and this is your profession, and this is what you get to do. And basketball is my profession, what I get to do. And the reason I play it is when I step in between the lines, I love it. And that's what's so fun about it for me is like, I get to compete. This was always my dream. And nobody should ever try to take that away from me"

Oh No He Didn't

260,899 次观看 • 16 天前

There's so much focus on "how can AI do my work for me?" I think the more important question is "what work can I now do with AI that I would have never attempted before?" Earlier this year I wrote freestiler, a vector tiling engine for R and Python, with the help of Claude and Codex. I knew what the ideal engine looked like and how it would work at a high level. I didn't know how to put it together, and I don't know Rust, the language I wanted under the hood. Previously I would never have attempted this project as the ROI wasn't there. It would have taken me a year or more to learn the internals of a vector tiling engine and enough Rust to implement one. With Opus-level models, I could take it on. freestiler now powers all my vector tiling pipelines, including the map below rendering 143 million jobs from LODES, and it has 114 GitHub stars. Building this way has required a different set of skills. I don't review the code line by line. I set up adversarial agents to do that and write the test suites. What I review is the architecture, the behavior, and the results. Agent teams surface findings and explain their reasoning; I evaluate and critique. My job isn't to stress over code formatting, but instead to focus on questions like whether the engine is designed right, whether the output is correct, and if the UX makes sense. This means that I haven't "replaced my work." I've taken on entirely new work, with the help of agents, that I would have never done otherwise. It has taken some getting used to shipping code I haven't personally typed. In the old way of working, I built understanding through writing that code. Now I build understanding through managing the project - writing a spec, reviewing structure, evaluating UX. And that's helped me think a whole lot bigger in terms of what I can now do.
1:00

There's so much focus on "how can AI do my work for me?" I think the more important question is "what work can I now do with AI that I would have never attempted before?" Earlier this year I wrote freestiler, a vector tiling engine for R and Python, with the help of Claude and Codex. I knew what the ideal engine looked like and how it would work at a high level. I didn't know how to put it together, and I don't know Rust, the language I wanted under the hood. Previously I would never have attempted this project as the ROI wasn't there. It would have taken me a year or more to learn the internals of a vector tiling engine and enough Rust to implement one. With Opus-level models, I could take it on. freestiler now powers all my vector tiling pipelines, including the map below rendering 143 million jobs from LODES, and it has 114 GitHub stars. Building this way has required a different set of skills. I don't review the code line by line. I set up adversarial agents to do that and write the test suites. What I review is the architecture, the behavior, and the results. Agent teams surface findings and explain their reasoning; I evaluate and critique. My job isn't to stress over code formatting, but instead to focus on questions like whether the engine is designed right, whether the output is correct, and if the UX makes sense. This means that I haven't "replaced my work." I've taken on entirely new work, with the help of agents, that I would have never done otherwise. It has taken some getting used to shipping code I haven't personally typed. In the old way of working, I built understanding through writing that code. Now I build understanding through managing the project - writing a spec, reviewing structure, evaluating UX. And that's helped me think a whole lot bigger in terms of what I can now do.

Kyle Walker

13,740 次观看 • 1 个月前

"I was at home on a ladder changing a light fixture when I took the call [about auditioning for Superman] and they were like 'Well, David... we think you know what this call is about and I was like 'I really don't know what this is about. I'm on a ladder. Please talk faster.'"
0:36

"I was at home on a ladder changing a light fixture when I took the call [about auditioning for Superman] and they were like 'Well, David... we think you know what this call is about and I was like 'I really don't know what this is about. I'm on a ladder. Please talk faster.'"

david corenswet archive

353,099 次观看 • 1 年前

What does OpenAI GPT 5.4 (just released this morning) mean for developers? You talked about it. My AI agents read it. Wrote a report. Sent it over to NotebookLM. Which made this video. Using the new cinematic quality released yesterday. This was all built with your posts from X. Damn, I wish I had this decades ago. Do you all get how insane this is for learning about new things?
7:14

What does OpenAI GPT 5.4 (just released this morning) mean for developers? You talked about it. My AI agents read it. Wrote a report. Sent it over to NotebookLM. Which made this video. Using the new cinematic quality released yesterday. This was all built with your posts from X. Damn, I wish I had this decades ago. Do you all get how insane this is for learning about new things?

Robert Scoble

27,728 次观看 • 5 个月前

The response to the Marketing Skills for Claude Code repo I shared was unreal 🤯 BUT, I realized that most marketers still don't even know what a Terminal is. So I made a step-by-step guide to get up and running with agentic AI tools like Claude Code.
0:23

The response to the Marketing Skills for Claude Code repo I shared was unreal 🤯 BUT, I realized that most marketers still don't even know what a Terminal is. So I made a step-by-step guide to get up and running with agentic AI tools like Claude Code.

Corey Haines

30,236 次观看 • 6 个月前

I invest in a lot of entrepreneurs that I don't like but I respect. I respect them and the only thing I care about is executional skills. The ability to say, "All right this is what I'm going to achieve this month" and then execute on it. When they hit their bumps which they all do, because whatever their plan was is not going to work, they have the ability to pivot. That what I look for.
0:31

I invest in a lot of entrepreneurs that I don't like but I respect. I respect them and the only thing I care about is executional skills. The ability to say, "All right this is what I'm going to achieve this month" and then execute on it. When they hit their bumps which they all do, because whatever their plan was is not going to work, they have the ability to pivot. That what I look for.

Kevin O'Leary aka Mr. Wonderful

31,216 次观看 • 1 年前

Chamath: US AI Startups Can Learn A Lot from DeepSeek "This is a case where necessity was the mother of invention." On E213, Chamath Palihapitiya explained how, even if the $6M number is inaccurate, DeepSeek still had some impressive breakthroughs: GRPO > PPO for reinforcement learning "These guys were like, 'Well, how am I going to do this reinforcement learning thing?' They invented a totally different algorithm." "It uses a lot less computer memory and it's highly performant." PTX > CUDA to build the model "And then the second thing that was crazy is everybody is used to building models and compiling through CUDA, which is NVIDIA's proprietary language." "And these guys worked totally around CUDA and they did something called PTX, which goes right to the bare metal." What US AI startups can learn from this: "We, meaning the West, with all the money that we've had, didn't come up with these ideas." "And I think part of why we didn't come up is not that we're not smart enough to do it, but we weren't forced to because the constraints didn't exist." "And so I just wonder how we make sure we learn this principle, meaning, when the AI company wakes up and rolls out of bed and some VC gives them $200M, maybe that's not the right answer for a Series A or a Seed." "And maybe the right answer is $2M so that they do these DeepSeek-like innovations."
0:55

Chamath: US AI Startups Can Learn A Lot from DeepSeek "This is a case where necessity was the mother of invention." On E213, Chamath Palihapitiya explained how, even if the $6M number is inaccurate, DeepSeek still had some impressive breakthroughs: GRPO > PPO for reinforcement learning "These guys were like, 'Well, how am I going to do this reinforcement learning thing?' They invented a totally different algorithm." "It uses a lot less computer memory and it's highly performant." PTX > CUDA to build the model "And then the second thing that was crazy is everybody is used to building models and compiling through CUDA, which is NVIDIA's proprietary language." "And these guys worked totally around CUDA and they did something called PTX, which goes right to the bare metal." What US AI startups can learn from this: "We, meaning the West, with all the money that we've had, didn't come up with these ideas." "And I think part of why we didn't come up is not that we're not smart enough to do it, but we weren't forced to because the constraints didn't exist." "And so I just wonder how we make sure we learn this principle, meaning, when the AI company wakes up and rolls out of bed and some VC gives them $200M, maybe that's not the right answer for a Series A or a Seed." "And maybe the right answer is $2M so that they do these DeepSeek-like innovations."

The All-In Podcast

108,815 次观看 • 1 年前

I built an agent that answers machine-learning questions. It's autonomous, and the best part is that I built the whole thing without writing a single line of Python code. Here is what I did and how I did it: Over a year ago, a friend and I built a site that publishes multi-choice questions. You get a new one every day. I decided to have GPT-3.5 answer questions. Here is what I needed to build: 1. Connect to the site's API to retrieve today's question 2. Extract the question and the potential choices 3. Connect to OpenAI's API and ask GPT-3.5 to answer the question 4. Parse the answer from the model 5. Submit the answer back to the API to get the score Not difficult. Likely several hours of work. But I didn't have to write any code. I built the whole thing by dragging and dropping components using Vellum is a YC-backed platform for developers to build LLM applications. They are the only ones I've seen offering this functionality. They sponsored this post, and their team helped me with all my questions while I built this. I created a workflow. The platform supports several node types to build whatever you have in mind. I show how I put the whole thing together in the attached video. The only code I had to write was a few lines of Jinja to parse and transform the API and the LLM results. There are three lessons I want to share from this experience: First, the best possible code is the one you didn't write. I'm a big fan of no-code tools because they help me materialize my ideas fast. They help product people, designers, and no coders collaborate on the solution. Second, Large Language Models are sensitive to how you prompt them. Small changes to prompts can make a big difference in results. This is more pronounced when you are building a multi-step workflow. Third, automated testing and evaluation for prompts is critical. There aren't many companies thinking about this. They'll have a hard time moving from a demo phase. The attached video will show you what I did.
3:46

I built an agent that answers machine-learning questions. It's autonomous, and the best part is that I built the whole thing without writing a single line of Python code. Here is what I did and how I did it: Over a year ago, a friend and I built a site that publishes multi-choice questions. You get a new one every day. I decided to have GPT-3.5 answer questions. Here is what I needed to build: 1. Connect to the site's API to retrieve today's question 2. Extract the question and the potential choices 3. Connect to OpenAI's API and ask GPT-3.5 to answer the question 4. Parse the answer from the model 5. Submit the answer back to the API to get the score Not difficult. Likely several hours of work. But I didn't have to write any code. I built the whole thing by dragging and dropping components using Vellum is a YC-backed platform for developers to build LLM applications. They are the only ones I've seen offering this functionality. They sponsored this post, and their team helped me with all my questions while I built this. I created a workflow. The platform supports several node types to build whatever you have in mind. I show how I put the whole thing together in the attached video. The only code I had to write was a few lines of Jinja to parse and transform the API and the LLM results. There are three lessons I want to share from this experience: First, the best possible code is the one you didn't write. I'm a big fan of no-code tools because they help me materialize my ideas fast. They help product people, designers, and no coders collaborate on the solution. Second, Large Language Models are sensitive to how you prompt them. Small changes to prompts can make a big difference in results. This is more pronounced when you are building a multi-step workflow. Third, automated testing and evaluation for prompts is critical. There aren't many companies thinking about this. They'll have a hard time moving from a demo phase. The attached video will show you what I did.

Santiago

309,825 次观看 • 2 年前

I made tons of money building websites for people and small companies. Most of that is now gone. You can now generate, customize, and deploy a website using natural language. I recorded myself building a site from scratch using 10Web.io. 4 minutes later, I had a full website generated just for me. Crazy! That's mostly how I paid rent when I graduated college: I'd either build you a new site or make changes to an existing one. It's nuts anyone can do that today by just asking. But this doesn't stop with generating a website. 10Web also released an AI Copilot that you can use to edit a website with a chat-based AI assistant. Here is what you can do with the AI Copilot: 1. You can edit individual elements and widgets on your site by selecting them and describing the changes you want. 2. You can generate new images, create sections, and generate or edit text. 3. You can also add any new elements to the site. The best way to understand how much progress we've made is by looking at the AI Copilot in action: And the funny part is that we are just figuring out how to use AI models. 2025 will be crazy.
4:17

I made tons of money building websites for people and small companies. Most of that is now gone. You can now generate, customize, and deploy a website using natural language. I recorded myself building a site from scratch using 10Web.io. 4 minutes later, I had a full website generated just for me. Crazy! That's mostly how I paid rent when I graduated college: I'd either build you a new site or make changes to an existing one. It's nuts anyone can do that today by just asking. But this doesn't stop with generating a website. 10Web also released an AI Copilot that you can use to edit a website with a chat-based AI assistant. Here is what you can do with the AI Copilot: 1. You can edit individual elements and widgets on your site by selecting them and describing the changes you want. 2. You can generate new images, create sections, and generate or edit text. 3. You can also add any new elements to the site. The best way to understand how much progress we've made is by looking at the AI Copilot in action: And the funny part is that we are just figuring out how to use AI models. 2025 will be crazy.

Santiago

57,917 次观看 • 1 年前

What if any post on 𝕏 could become a playable game? I built it. 𝕏 Games takes any post on this platform and turns it into a real, playable canvas game — generated in real-time by Grok and Grok Imagine. Pick a post. Any post. Grok reads it, designs a game around it, generates the art, and builds the whole thing in seconds. Leaderboards, score sharing, all native to X. Here's the thing that still blows my mind — I didn't write a single line of code. The entire app was built by AI through Pokee AI and PokeeClaw. The games are generated live by Grok. Every pixel, every mechanic, every asset. All AI. This is what's possible right now. Not in some future demo. Right now, today, on 𝕏. I built this because I wanted to show what Grok can really do when you push it beyond chatbot Q&A. It can create. It can build entire interactive experiences from a tweet. Hey xAI — if you ever want someone to build this for real, into the platform... I'm right here. 👀 Try it yourself: 🎮 walkthrough below ⬇️
2:34

What if any post on 𝕏 could become a playable game? I built it. 𝕏 Games takes any post on this platform and turns it into a real, playable canvas game — generated in real-time by Grok and Grok Imagine. Pick a post. Any post. Grok reads it, designs a game around it, generates the art, and builds the whole thing in seconds. Leaderboards, score sharing, all native to X. Here's the thing that still blows my mind — I didn't write a single line of code. The entire app was built by AI through Pokee AI and PokeeClaw. The games are generated live by Grok. Every pixel, every mechanic, every asset. All AI. This is what's possible right now. Not in some future demo. Right now, today, on 𝕏. I built this because I wanted to show what Grok can really do when you push it beyond chatbot Q&A. It can create. It can build entire interactive experiences from a tweet. Hey xAI — if you ever want someone to build this for real, into the platform... I'm right here. 👀 Try it yourself: 🎮 walkthrough below ⬇️

Mike

39,558 次观看 • 4 个月前

This is amazing: Gay American shows up to Charlie Kirk vigil to show support, this was his experience “I'm just leaving the Charlie Kirk vigil in Philly. And let me tell you, I'm now knowing that the Republican Party is full of the most inclusive people” “For all of you asking — whether I was going to show up in full makeup, I did. This is what the right does, we come together for the greater good. — I was a little hesitant on coming because I was like, I don't know what to expect. I don't know who's gonna be here. I don't know, you know, anything. But then I thought about something that Charlie Kirk said, and he always used to say, never surrender. And that's what we did. We're never gonna surrender. — You have no idea what you guys just started, because now's the time we're gonna speak louder. That was confirmation for me.”
1:04

This is amazing: Gay American shows up to Charlie Kirk vigil to show support, this was his experience “I'm just leaving the Charlie Kirk vigil in Philly. And let me tell you, I'm now knowing that the Republican Party is full of the most inclusive people” “For all of you asking — whether I was going to show up in full makeup, I did. This is what the right does, we come together for the greater good. — I was a little hesitant on coming because I was like, I don't know what to expect. I don't know who's gonna be here. I don't know, you know, anything. But then I thought about something that Charlie Kirk said, and he always used to say, never surrender. And that's what we did. We're never gonna surrender. — You have no idea what you guys just started, because now's the time we're gonna speak louder. That was confirmation for me.”

Wall Street Apes

5,525,599 次观看 • 11 个月前

There are three areas where every developer should focus on right now: 1. Learning how to use AI as a copilot 2. Learning how to be a copilot for AI 3. Learning how to build tooling for the future of AI Reality check: AI is here. AI isn't going anywhere. You either adapt, or somebody who does will send you to a shoelace factory for the rest of your career. I recorded a video to discuss this.
13:23

There are three areas where every developer should focus on right now: 1. Learning how to use AI as a copilot 2. Learning how to be a copilot for AI 3. Learning how to build tooling for the future of AI Reality check: AI is here. AI isn't going anywhere. You either adapt, or somebody who does will send you to a shoelace factory for the rest of your career. I recorded a video to discuss this.

Santiago

28,690 次观看 • 1 年前

LeBron James reveals he didn't know what a pantry was until high school “I went to my high school coach's house and I asked him, ‘Can I get a snack or some chips or whatever?’ He was like, ‘Yeah, just go in the pantry.’ I'm like, ‘What the fuck is the pantry?’” “Where I grew up, everything is on top of the refrigerator. The bread, the chips, the cereal, everything is on top of the refrigerator. I don't know what the hell a pantry is” “That was my motivation right there. I'm like I got to give my mama a pantry”
0:43

LeBron James reveals he didn't know what a pantry was until high school “I went to my high school coach's house and I asked him, ‘Can I get a snack or some chips or whatever?’ He was like, ‘Yeah, just go in the pantry.’ I'm like, ‘What the fuck is the pantry?’” “Where I grew up, everything is on top of the refrigerator. The bread, the chips, the cereal, everything is on top of the refrigerator. I don't know what the hell a pantry is” “That was my motivation right there. I'm like I got to give my mama a pantry”

Jack

3,768,795 次观看 • 1 个月前