DeepLearning.AI

Kai-Fu Lee — AI Everywhere: The expanding business possibilities for AI

Artificial intelligence has moved from the age of discovery to the age of implementation. Among our invested portfolios, primarily in China, we see flourishing applications using AI and automation in banking, finance, transportation, logistics, supermarkets, restaurants, warehouses, factories...

Interviews & Essays

Yann LeCun — Learning From Observation: The power of self-supervised learning

How is it that many people learn to drive a car fairly safely in 20 hours of practice, while current imitation learning algorithms take hundreds of thousands of hours, and reinforcement learning algorithms take millions of hours? Clearly we’re missing something big.

Interviews & Essays

Yann LeCun — Learning From Observation: The power of self-supervised learning

How is it that many people learn to drive a car fairly safely in 20 hours of practice, while current imitation learning algorithms take hundreds of thousands of hours, and reinforcement learning algorithms take millions of hours? Clearly we’re missing something big.

Interviews & Essays

Chelsea Finn — Robots That Generalize: Generalization for robotics through reinforcement learning

Many people in the AI community focus on achieving flashy results, like building an agent that can win at Go or Jeopardy. This kind of work is impressive in terms of complexity.

Interviews & Essays

Chelsea Finn — Robots That Generalize: Generalization for robotics through reinforcement learning

Many people in the AI community focus on achieving flashy results, like building an agent that can win at Go or Jeopardy. This kind of work is impressive in terms of complexity.

Interviews & Essays

Oren Etzioni — Tools For Equality: How AI can help improve accessibility

In 2020, I hope the AI community will grapple with issues of fairness in ways that tangibly and directly benefit disadvantaged populations.

Interviews & Essays

Oren Etzioni — Tools For Equality: How AI can help improve accessibility

In 2020, I hope the AI community will grapple with issues of fairness in ways that tangibly and directly benefit disadvantaged populations.

Interviews & Essays

Anima Anandkumar — The Power of Simulation: How simulation can be useful for supervised learning

We’ve had great success with supervised deep learning on labeled data. Now it’s time to explore other ways to learn: training on unlabeled data, lifelong learning, and especially letting models explore a simulated environment before transferring what they learn to the real world.

Interviews & Essays

Anima Anandkumar — The Power of Simulation: How simulation can be useful for supervised learning

We’ve had great success with supervised deep learning on labeled data. Now it’s time to explore other ways to learn: training on unlabeled data, lifelong learning, and especially letting models explore a simulated environment before transferring what they learn to the real world.

Kai-Fu Lee — AI Everywhere: The expanding business possibilities for AI

Yann LeCun — Learning From Observation: The power of self-supervised learning

Yann LeCun — Learning From Observation: The power of self-supervised learning

Chelsea Finn — Robots That Generalize: Generalization for robotics through reinforcement learning

Chelsea Finn — Robots That Generalize: Generalization for robotics through reinforcement learning

Oren Etzioni — Tools For Equality: How AI can help improve accessibility

Oren Etzioni — Tools For Equality: How AI can help improve accessibility

Anima Anandkumar — The Power of Simulation: How simulation can be useful for supervised learning

Anima Anandkumar — The Power of Simulation: How simulation can be useful for supervised learning

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