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Three Key Takeaways from Meta's Galactica AI
From ACM Opinion

Three Key Takeaways from Meta's Galactica AI

We should look at Galactica's initial failure as another scientific experiment, one that can bring us one step closer to success.

How to Solve AI's 'Common-Sense' Problem
From ACM Opinion

How to Solve AI's 'Common-Sense' Problem

AI systems without common sense will make mistakes when they reach the limits of where they've been trained.

Intro to Model-Free and Model-Based Reinforcement Learning
From ACM Opinion

Intro to Model-Free and Model-Based Reinforcement Learning

Neuroscientist and author Daeyeol Lee talks reinforcement learning in humans and animals, AI and natural intelligence, and more.

'Sentience' Is the Wrong Discussion to Have on AI Right Now
From ACM Opinion

'Sentience' Is the Wrong Discussion to Have on AI Right Now

A more important conversation would be one about human compatibility and trust.

Can Large Language Models Be Democratized?
From ACM Opinion

Can Large Language Models Be Democratized?

The very nature of large language models is undemocratic and in favor of the companies that publicize them.

The AI in a Jar
From ACM Opinion

The AI in a Jar

Exploring a metaphysical argument against artificial intelligence.

Democratize Machine Learning with No-Code AI
From ACM Opinion

Democratize Machine Learning with No-Code AI

Organizations lacking skilled data scientists and ML engineers can create and deploy ML models, too.

Meta's Yann LeCun on His Vision for Human-level AI
From ACM Opinion

Meta's Yann LeCun on His Vision for Human-level AI

Rather than try to replace natural intelligence, create AI that is compatible with human intelligence

DeepMind AlphaCode Does Not Compare to Human Programmers
From ACM Opinion

DeepMind AlphaCode Does Not Compare to Human Programmers

Human programmers are in control but they must learn to harness the power and limits of AI-generated code
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