Michael Huppe is President & CEO of SoundExchange, an adjunct music law professor, published author, frequent contributor and lecturer. In the not-too-distance future, when a new recording artist seizes the spotlight with hit songs, a huge social media following and sold-out venues, it won't be a human being. It'll be a performer whose lyrics, melodies and voice are solely created by artificial intelligence (AI). We're already seeing hints of this with virtual artists such as metaverse avatars, hybrid performers that rely on a combination of AI and human talent. Beyond music, there's also been the emergence of AI products that create realistic digital images based on a natural language sentence provided by the user.

Can a machine be an inventor? After the courts said no, a computer scientist is once more trying to have an artificial intelligence considered an inventor in the eyes of the law. In August, the U.S. Federal Circuit Court of Appeals issued a decision that AI cannot be listed as the inventor on a patent registration. The case before the court--Thaler v. Vidal--was either a gimmick that could be dismissed with a simple reading of U.S. patent law or one that strikes at the heart of a metaphysical question with crucial implications for the future of innovation. In Thaler v. Vidal, Stephen Thaler challenged the refusal of the U.S. Patent and Trademark Office to issue a patent registration for an invention Thaler claims was created by an artificial intelligence device called Device for Autonomous Bootstrapping of Unified Sentience, or DABUS.

You may have heard that, on Monday, Silicon Valley startup Cerebras Systems unveiled the world's biggest chip, called the WSE, or "wafer-scale engine," pronounced "wise." It is going to be built into complete computing systems sold by Cerebras. What you may not know is that the WSE and the systems it makes possible have some fascinating implications for deep learning forms of AI, beyond merely speeding up computations. Cerebras co-founder and chief executive Andrew Feldman talked with ZDNet a bit about what changes become possible in deep learning. There are three immediate implications that can be seen in what we know of the WSE so far.