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Symbolic ai

Moonlake: Multimodal, Interactive, and Efficient World Models — with Fan-yun Sun and Chris Manning

Moonlake: Multimodal, Interactive, and Efficient World Models — with Fan-yun Sun and Chris Manning

Moonlake AI presents a distinctive approach to world modeling, prioritizing interactive, action-conditioned environments built on symbolic representations and game engines over purely pixel-based generative models. This method focuses on causal reasoning, long-term consistency, and programmable rendering (via their 'Reverie' diffusion model) to create dynamic, multiplayer worlds, positioning itself as a platform for training embodied AI and revolutionizing game development.

François Chollet: ARC-AGI-3, Beyond Deep Learning & A New Approach To ML

François Chollet: ARC-AGI-3, Beyond Deep Learning & A New Approach To ML

François Chollet discusses his contrarian approach to AI, moving beyond scaling LLMs to understand intelligence from first principles. He explains his work on the ARC benchmark series, including the new ARC-AGI V3, designed to measure 'agentic intelligence' and skill acquisition efficiency. He also introduces his lab, Ndea, which is developing a new ML paradigm based on symbolic models, and shares his perspective on the limits of current systems and the future path to AGI.

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Pedro Domingos introduces Tensor Logic, a new programming language designed to be the fundamental language for AI. It unifies the two major paradigms: the learning capabilities of deep learning (neural networks) and the transparent, verifiable reasoning of symbolic AI (logic programming), aiming to solve critical issues like hallucination and the opacity of current models.

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Pedro Domingos introduces Tensor Logic, a new programming language designed to be the fundamental language for AI. It unifies the two major paradigms: the data-driven learning of deep learning and the verifiable reasoning of symbolic AI. By treating logical rules and tensor operations as the same underlying construct, Tensor Logic enables systems that can learn logical structures and perform transparent, deductive reasoning, directly addressing critical issues like model opacity and hallucination.

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Tensor Logic "Unifies" AI Paradigms [Pedro Domingos]

Pedro Domingos introduces Tensor Logic, a new programming language designed to unify the two major paradigms of AI—deep learning's ability to learn from data and symbolic AI's power of logical reasoning—into a single, elegant framework.