Jan 01, 2020

11 Posts

Andrew Ng with his grandfather
Jan 01, 2020

Hopes for AI in 2020: Yann LeCun, Kai-Fu Lee, Anima Anandkumar, Richard Socher

Happy New Year! Every winter holiday, I pursue a learning goal around a new topic. In between visits with family, I end up reading a lot. About a decade ago, my holiday topic was pedagogy — I still remember lugging a heavy suitcase of books through the airport — and this...
Andrew Ng with his grandfather
Jan 01, 2020

The Key to Longevity

Happy New Year!Every winter holiday, I pursue a learning goal around a new topic. In between visits with family, I end up reading a lot.
Zhi-Hua Zhou
Jan 01, 2020

Zhi-Hua Zhou: Fresh Methods, Clear Guidelines

I have three hopes for 2020.
Dawn Song
Jan 01, 2020

Dawn Song: Taking Responsibility for Data

Datasets are critical to AI and machine learning, and they are becoming a key driver of the economy. Collection of sensitive data is increasing rapidly, covering almost every aspect of people’s lives.
Richard Socher
Jan 01, 2020

Richard Socher: Boiling the Information Ocean

Ignorance is a choice in the Internet age. Virtually all of human knowledge is available for the cost of typing a few words into a search box.
David Patterson
Jan 01, 2020

David Patterson: Faster Training and Inference

Billions of dollars invested to create novel AI hardware will bear their early fruit in 2020. Google unleashed a financial avalanche with its tensor processing unit in 2017.
Kai-Fu Lee
Jan 01, 2020

Kai-Fu Lee: AI Everywhere

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...
Yann LeCun
Jan 01, 2020

Yann LeCun: Learning From Observation

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.
Chelsea Finn
Jan 01, 2020

Chelsea Finn: Robots That Generalize

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.
Oren Etzioni
Jan 01, 2020

Oren Etzioni: Tools For Equality

In 2020, I hope the AI community will grapple with issues of fairness in ways that tangibly and directly benefit disadvantaged populations.
Anima Anandkumar
Jan 01, 2020

Anima Anandkumar: The Power of Simulation

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.

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