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Enhancing AI-Powered Computer Vision Through Physics-Awareness

Unite.AI

In a significant breakthrough, the UCLA study intends to combine the deep understanding from data and the real-world know-how of physics, thereby creating a hybrid AI with augmented capabilities.

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AI is just a bad student.

Towards AI

An analogy to explain how deep learning works… This member-only story is on us. link] When we talk about artificial intelligence, or AI, we tend to mean deep learning. Let’s begin by imagining a group of computer scientists and a very large elephant in the same room… Read the full blog for free on Medium.

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AI Everywhere, All at Once

Flipboard

For instance, Google has applied deep-reinforcement learning to optimize placement of logic and memory on chips, as Senior Editor Samuel K. However, a recent article in The New Yorker by the computer scientist Jaron Lanier directly takes on provenance and traceability in generative AI systems.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

IBM computer scientist Arthur Samuel coined the phrase “machine learning” in 1952. In 1962, a checkers master played against the machine learning program on an IBM 7094 computer, and the computer won. Python is the most common programming language used in machine learning.

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MLOps and the evolution of data science

IBM Journey to AI blog

The advancement of computing power over recent decades has led to an explosion of digital data, from traffic cameras monitoring commuter habits to smart refrigerators revealing how and when the average family eats. Both computer scientists and business leaders have taken note of the potential of the data.

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Top AI Influencers To Follow In 2023

Dlabs.ai

He also runs his own YouTube channel , where he explains basic concepts of AI, shows how to use them, and talks through technological trends for the coming years. She was the leading scientist and co-creator of ImageNet , a visual object recognition database. To find out more about deep learning, check this Dlabs.AI

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Getting ready for artificial general intelligence with examples

IBM Journey to AI blog

Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. Most importantly, no matter the strength of AI (weak or strong), data scientists, AI engineers, computer scientists and ML specialists are essential for developing and deploying these systems.