World Model is A Waiting Room
Welcome back, AI Enthusiasts! $2.3B went into companies calling themselves world models this year. Yann LeCun and Fei-Fei Li raised a billion dollars each on the term, and still cannot agree
Read the storyYann LeCun
Executive Chairman, AMI Labs; Professor, NYU
Yann LeCun is a deep learning researcher associated with convolutional networks, visual recognition, and predictive approaches to machine intelligence. After research roles at Bell Labs and leadership at Facebook and Meta, he now serves as executive chairman of AMI Labs and a professor at NYU. His current agenda emphasizes world models, memory, planning, and learning abstract representations of real-world data.
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At a glance
Yann LeCun is a deep learning researcher associated with convolutional networks, visual recognition, and predictive approaches to machine intelligence. After research roles at Bell Labs and leadership at Facebook and Meta, he now serves as executive chairman of AMI Labs and a professor at NYU. His current agenda emphasizes world models, memory, planning, and learning abstract representations of real-world data.
- Organizations
- AMI Labs; New York University
- Research
- Deep learning; world models
- Recognition
- 2018 ACM A.M. Turing Award
Sources checked . Selected career background and milestones.
Career, in context.
Selected research, leadership and career milestones, newest first.
AMI chair and NYU professor
NYU’s September seminar biography identifies LeCun as AMI Labs executive chairman and Jacob T. Schwartz Professor, while listing his Meta chief scientist tenure as 2018–2025.
Source: New York University ↗Co-authors I-JEPA research
LeCun and collaborators introduced an image-based joint-embedding predictive architecture that learns by predicting representations of missing image regions, rather than reconstructing their individual pixels.
Source: arXiv / paper authors ↗Named a Turing Award recipient
ACM named LeCun, Geoffrey Hinton, and Yoshua Bengio recipients of its 2018 Turing Award, recognizing their contributions to the development and practical use of deep networks.
Source: Association for Computing Machinery ↗Founds Facebook AI Research
LeCun joined Facebook and became the founding director of its AI research organization, serving in that position before his later chief AI scientist role.
Source: New York University ↗Joins New York University
LeCun joined NYU as a professor after his industrial research career, establishing a long-running academic base for work in machine learning, perception, and artificial intelligence.
Source: New York University ↗Publishes document-recognition work
LeCun and collaborators described gradient-based learning for document recognition, including convolutional network methods applied to handwritten character recognition and practical document-processing systems.
Source: IEEE paper / co-author Léon Bottou ↗Joins AT&T Bell Labs
After postdoctoral work in Toronto, LeCun joined AT&T Bell Labs. He later moved to AT&T Labs in 1996 to head image processing research.
Source: New York University ↗Completes doctorate in Paris
LeCun earned his PhD in 1987 after an engineering diploma at ESIEE, laying the academic foundation for his later work on neural networks and perception.
Source: New York University ↗
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World Labs, founded by Fei-Fei Li, has valued at over 1 billion USD in less than six months. The company focuses on spatial intelligence, which involves AI's perception and interaction in three-dimensional space. Following its announcement, Li and co-founder Justin Johnson discussed various AI topics in an exclusive a16z interview.
- The last decade focused on interpreting existing data, while the upcoming decade will emphasize the comprehension of new data.
- Language is described as a generated signal, indicating that the input data leads to predictable outputs that generalize the same information.
- Wisdom enables intelligent beings to interact with their environment, build civilizations, and perform tasks autonomously.
- Converting cognitive abilities into three-dimensional technology is essential for maximizing AI applications. Real-time understanding of our three-dimensional surroundings could reduce our dependence on physical devices.
- Robots rely on spatial intelligence to translate learned data into real-world actions. Their digital brains necessitate this capability for effective interaction.
- The greatest danger in the new AI era is ignorance, which extends beyond a lack of basic knowledge to include the potential for knowledgeable individuals to misrepresent AI complexities.
- It is crucial for humans to take responsibility for controlling and managing AI technology. There is ample time and authority to maintain this responsibility without relinquishing it easily.
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- Apple's latest iOS 18 update introduces AI recipe generation features, sparking concerns among food bloggers about safety and the impact on their livelihoods.
- Yann LeCun criticizes Elon Musk for repeatedly misleading about the arrival of fully-automated Teslas.
- Constellation CEO urges the US to mimic China's approach by building data centers near power plants to meet rising AI energy demands.
- OpenAI announced that one of its X accounts was compromised, leading to unauthorized posts about a fake crypto token.
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