正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Babies learn gravity and physics by 9 months. Before they speak. "We're never going to get human-level AI unless systems learn by observing the world." Companies building video-first AI will leapfrog text-based systems. Here's what Meta is secretly building:

Karl Mehta

143,679 subscribers

119,114 次观看 • 10 个月前 •via X (Twitter)

科学技术教育

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Chief Al Scientist at Meta, Yann LeCun, believes we're never going to get to human level AI by text:

Chief Al Scientist at Meta, Yann LeCun, believes we're never going to get to human level AI by text:

ₕₐₘₚₜₒₙ

867,687 次观看 • 1 年前

Yann LeCun: "We're never going to get to human level AI by just training on text"

Yann LeCun: "We're never going to get to human level AI by just training on text"

Lior Alexander

66,881 次观看 • 1 年前

"we will not get to human-level AI by just scaling up LLMs... it's not going to happen" Meta AI chief scientist, Yann LeCun: scaling up LLMs alone will not lead to human-level AI ...what we’ll have instead are systems with huge memory and retrieval abilities, but still not able to invent solutions to new problems

"we will not get to human-level AI by just scaling up LLMs... it's not going to happen" Meta AI chief scientist, Yann LeCun: scaling up LLMs alone will not lead to human-level AI ...what we’ll have instead are systems with huge memory and retrieval abilities, but still not able to invent solutions to new problems

Haider.

123,655 次观看 • 1 年前

Yann LeCun -- Meta's chief AI scientist and a Turing Award winner -- explains why scaling up LLMs will never reach human-level AI, and names the four things today's systems still can't do: "If you think that we're going to get to human-level AI by just training on more data and scaling up LLMs, you're making a mistake." "If you're an investor and you invest in a company that told you we're going to get to human-level AI and PhD level by just training on more data and with a few tricks... that was probably not a good idea." "There are ideas about how to go forward and have systems that are capable of doing what every intelligent animal and human are capable of doing, and that current AI systems are not capable of doing." "Understanding the physical world, having persistent memory, and being able to reason and plan. Those are the four characteristics that need to be there." "That requires systems that can acquire common sense, that can learn from natural sensors like video, as opposed to just text." The entire market is priced on a straight line from bigger models to AGI. One of the people who invented deep learning is telling you the line doesn't reach -- and that the real bottleneck isn't compute, it's world models. If he's right, the winner isn't whoever stacks the most GPUs. It's whoever teaches a machine to learn from video the way a child does.

Yann LeCun -- Meta's chief AI scientist and a Turing Award winner -- explains why scaling up LLMs will never reach human-level AI, and names the four things today's systems still can't do: "If you think that we're going to get to human-level AI by just training on more data and scaling up LLMs, you're making a mistake." "If you're an investor and you invest in a company that told you we're going to get to human-level AI and PhD level by just training on more data and with a few tricks... that was probably not a good idea." "There are ideas about how to go forward and have systems that are capable of doing what every intelligent animal and human are capable of doing, and that current AI systems are not capable of doing." "Understanding the physical world, having persistent memory, and being able to reason and plan. Those are the four characteristics that need to be there." "That requires systems that can acquire common sense, that can learn from natural sensors like video, as opposed to just text." The entire market is priced on a straight line from bigger models to AGI. One of the people who invented deep learning is telling you the line doesn't reach -- and that the real bottleneck isn't compute, it's world models. If he's right, the winner isn't whoever stacks the most GPUs. It's whoever teaches a machine to learn from video the way a child does.

Karl Mehta

34,577 次观看 • 9 天前

We're helping businesses scale their AI infrastructure like never before. Watch as Lisa Su explains cutting-edge innovations from Lenovo + AMD built to power the most demanding AI systems in the world. Learn more:

We're helping businesses scale their AI infrastructure like never before. Watch as Lisa Su explains cutting-edge innovations from Lenovo + AMD built to power the most demanding AI systems in the world. Learn more:

Lenovo

13,038,925 次观看 • 6 个月前

Yann LeCun says we're never gonna get to human-level intelligence by just training on text AI must learn from high-bandwidth sensory data like video to build true world models Current models look PhD-smart but mostly regurgitate, with no real understanding "even a cat understands the physical world better"

Yann LeCun says we're never gonna get to human-level intelligence by just training on text AI must learn from high-bandwidth sensory data like video to build true world models Current models look PhD-smart but mostly regurgitate, with no real understanding "even a cat understands the physical world better"

Haider.

138,265 次观看 • 8 个月前

Babies learn by watching long before they can speak. 💛

Babies learn by watching long before they can speak. 💛

Skye

17,107 次观看 • 7 天前

What powers the world’s most advanced AI systems? Supermicro Data Center Building Block Solutions provide AI and compute systems, powered by NVIDIA, AMD, and Intel. From GPU-dense servers to petascale storage, liquid cooling helps optimize performance.

What powers the world’s most advanced AI systems? Supermicro Data Center Building Block Solutions provide AI and compute systems, powered by NVIDIA, AMD, and Intel. From GPU-dense servers to petascale storage, liquid cooling helps optimize performance.

Supermicro

50,670,998 次观看 • 2 个月前

How are world models changing enterprise systems? Here the founders of Skyfall AI tell me how. Don't have time to watch this video? Click the Grok button and ask it "what will I learn by watching this video?" (I'll post a link below).

How are world models changing enterprise systems? Here the founders of Skyfall AI tell me how. Don't have time to watch this video? Click the Grok button and ask it "what will I learn by watching this video?" (I'll post a link below).

Robert Scoble

10,490 次观看 • 6 个月前

We learn to speak before we learn to read. Voice is the most natural interface we have. We just raised a $100M to make building voice AI as easy as a web app.

We learn to speak before we learn to read. Voice is the most natural interface we have. We just raised a $100M to make building voice AI as easy as a web app.

LiveKit

223,818 次观看 • 5 个月前

🧠 Just dropped: Our first Chromia | Power to the Public AI Agent tutorial is LIVE! Learn to build AI Agent Brains right on the blockchain - with memory systems that mirror human cognition 👇🧵

🧠 Just dropped: Our first Chromia | Power to the Public AI Agent tutorial is LIVE! Learn to build AI Agent Brains right on the blockchain - with memory systems that mirror human cognition 👇🧵

superoo7

14,617 次观看 • 1 年前

They try to avoid mistakes instead of building systems to learn from them. They chase perfection instead of progress. But here's what 25 years in Silicon Valley taught me: The best founders embrace the Kaizen mindset:

They try to avoid mistakes instead of building systems to learn from them. They chase perfection instead of progress. But here's what 25 years in Silicon Valley taught me: The best founders embrace the Kaizen mindset:

Terry Kim

131,674 次观看 • 1 年前

Cognitive scientist Joscha Bach: "at the moment, we are not building systems that are minds — we are building systems that predict text and visual patterns made for human consumption" True machine perception has never been tried, but once it is, it may surpass human reasoning

Cognitive scientist Joscha Bach: "at the moment, we are not building systems that are minds — we are building systems that predict text and visual patterns made for human consumption" True machine perception has never been tried, but once it is, it may surpass human reasoning

Haider.

61,017 次观看 • 9 天前

Anthropic co-founder Jack Clark: We're building systems that may be able to invent their own successors as soon as 2028 No researchers required. Just compute and data "after that, the progress of AI and science is no longer defined by humans alone" That's never happened before

Anthropic co-founder Jack Clark: We're building systems that may be able to invent their own successors as soon as 2028 No researchers required. Just compute and data "after that, the progress of AI and science is no longer defined by humans alone" That's never happened before

Haider.

27,706 次观看 • 19 天前

"What happens to everyone else?" New pod with Fernando Nikolić 🇦🇷 🟠 where we discuss the systems we're building with AI and the profound impact this is having. - 1 person companies - What happens to work - Software's printing press moment Full show below 👇

"What happens to everyone else?" New pod with Fernando Nikolić 🇦🇷 🟠 where we discuss the systems we're building with AI and the profound impact this is having. - 1 person companies - What happens to work - Software's printing press moment Full show below 👇

Peter McCormack 🏴‍☠️🇬🇧🇮🇪

13,306 次观看 • 23 天前

today we're introducing Levangie Laboratories (by: Brayden Levangie) they are building the first *causal trajectory learning architecture* giving AI the ability to learn continuously the result: autonomous intelligences that don't just deploy into a company; they grow into it LLABS is already working with some of the largest companies in the world, building agents that solve problems impacting thousands of lives every day autonomy designed for the next generation of humanity's challenges

today we're introducing Levangie Laboratories (by: Brayden Levangie) they are building the first causal trajectory learning architecture giving AI the ability to learn continuously the result: autonomous intelligences that don't just deploy into a company; they grow into it LLABS is already working with some of the largest companies in the world, building agents that solve problems impacting thousands of lives every day autonomy designed for the next generation of humanity's challenges

the residency

20,795 次观看 • 2 个月前

Low trust. High accountability. manadia is building the backbone for verifiable data settlement and AI coordination — where execution is secure, private, and provable. Finance. Digital assets. AI systems. All connected. Here’s what we’re building 👇

Low trust. High accountability. manadia is building the backbone for verifiable data settlement and AI coordination — where execution is secure, private, and provable. Finance. Digital assets. AI systems. All connected. Here’s what we’re building 👇

manadia

50,723 次观看 • 4 个月前

"The Sniper Code" The best way to learn AI animation is by creating 1-minute concept videos. It will level up your skills insanely fast. Here's why👇

"The Sniper Code" The best way to learn AI animation is by creating 1-minute concept videos. It will level up your skills insanely fast. Here's why👇

Framer 🇱🇹

21,360 次观看 • 1 个月前

AI Is Replacing Programmers and Mathematicians—Fast Eric Schmidt predicts that within one year, the majority of programmers will be replaced by AI agents, and graduate-level mathematicians will be rivaled by models trained on mathematical reasoning. Why? Because both code and math follow structured languages, which AI can learn to manipulate with extreme precision using techniques like word prediction and proof systems like Lean.

AI Is Replacing Programmers and Mathematicians—Fast Eric Schmidt predicts that within one year, the majority of programmers will be replaced by AI agents, and graduate-level mathematicians will be rivaled by models trained on mathematical reasoning. Why? Because both code and math follow structured languages, which AI can learn to manipulate with extreme precision using techniques like word prediction and proof systems like Lean.

Wes Roth

55,697 次观看 • 1 年前