What's Next For AI?

Pascal Bernard | Data Scientist, AI Thinker

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Sunday Reading: The Rise of Artificial Intelligence

“As the field expands, many philosophers and academics are raising questions about what A.I. means for the future of human intelligence.”... Article from : https://www.newyorker.com/books/double-take/sunday-reading-the-rise-of-artificial-intelligence

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Policy Gradient methods and Proximal Policy Optimization (PPO): diving into Deep RL!

Fantastic short video where Xander introduces Policy Gradient methods for Deep Reinforcement Learning. After a general overview, he dives into Proximal Policy Optimization: an algorithm designed at OpenAI that tries to find a balance between sample efficiency and code complexity. PPO is the algorithm used to train the OpenAI Five system and is also used in a wide range of other challenges like Atari and robotic control tasks.

[pascal-bernard]

Artificial Intelligence Could Be a $14 Trillion Boon to the Global Economy—If It Can Overcome These Obstacles

https://fortune.com/2019/10/09/artificial-intelligence-14-trillion-boon-only-if-overcome-one-thing/

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An achievable view of artificial intelligence.

“Artificial intelligence has been the holy grail of computing for half a century. And like the mythical cup, it always remains just out of reach But there are ways to deploy a measure of real artificial intelligence that yields tangible benefits.”

https://www.cio.com/article/3442727/an-achievable-view-of-artificial-intelligence.html

[pascal-bernard]

What’s Next For AI? Enter: Deep Reasoning.

Deep Reasoning is the field of enabling machines to understand implicit relationships between different things. For example, consider the following: “all animals drink water. Cats are animals”.

full article here:

https://towardsdatascience.com/whats-next-for-ai-enter-deep-reasoning-fae8b131962a