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- 🧠 Judge rules that AI generated art can't be copyrighted
🧠 Judge rules that AI generated art can't be copyrighted
PLUS: MIT and Harvard researchers innovate in AI robotics
Alan Buxbaum & Alex Valaitis
August 21, 2023
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Happy Monday Everyone!
This week is off to another hot start with major rulings around AI art & breakthroughs in AI robotics.
Today's AI spotlights:
Judge rules that AI-generated art can’t be copyrighted 👩⚖️
MIT and Harvard researchers innovate in AI robotics 🙌
How do businesses measure the success of AI? 🧐
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NEWS
Even with AI's painting up a storm, is it even able to snag a copyright? Judge Beryl A. Howell says it's a no-go.
The case itself involves Stephen Thaler, the genius behind Creativity Machine, and him trying to get AI art copyrighted.
So what was the judge's reasoning? If it doesn't have that human element, it doesn't get the stamp.
That being said, it may not be so simple. After all, we're diving deep into uncharted copyright waters here. How involved do humans really need to be?
Thaler's not done yet, given that he's appealing the decision.
As the world of AI and copyright intertwines, it's clear that things are just getting started.
NEWS
Introducing "Follow Anything" (FAn) - a monster AI move to bridge computer vision and robotics.
Current robot sidekicks are limited by a number of obstacles. FAn does away with a variety of them when it comes to tracking.
It’s like the Swiss Army knife of object tracking: spot, segment, chase, repeat. And get this: it adapts to new objects via text, pics, or clicks.
FAn’s also got re-detection tricks up its sleeve. It can deploy stuff like the Vision Transformer (ViT) & the sassy Segment Anything Model (SAM).
📰 OTHER HEADLINES & STORIES
💡AI CAREER INSIGHT
AI is all the rage these days. But measuring its success? That's the million-dollar question!
Generative AI, with stars like ChatGPT, is unpredictable by nature. Same input, different output – like a box of chocolates, you never know what you’re gonna get.
But here's the catch: how do we gauge if the tech’s hit the mark? Traditional metrics don't quite do the trick.
Enter probabilistic success metrics – think confidence intervals and probability distributions.
And don't forget to consider user-centric evaluations, 'cause if users ain't happy, your AI's not gonna make it.
So in summary, business must balance rigorous model validations with real user feedback. Do that and you're golden.
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