Happy Friday!

With CES going on this week we expected a lot of splashes to be made but the biggest news to come out is the Senate hearing around the use of Media and Journalism to train AI models. Last week, the New York Times dropped a lawsuit on Microsoft and OpenAI. This week, Congress is jumping into the fray to discuss fair use of media and if there should be licensing in effect for Big Tech to utilize it. This will be an interesting topic as we move forward in 2024.

In this edition:

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Ian Goodfellow is an American computer scientist, engineer, and executive, most noted for his work on artificial neural networks and deep learning. He was previously employed as a research scientist at Google Brain, Director of Machine Learning at Apple and has made several important contributions to the field of deep learning including the invention of the Generative Adversarial Network (GAN). Goodfellow co-wrote, as the first author, the textbook Deep Learning (2016) and wrote the chapter on deep learning in the authoritative textbook of the field of artificial intelligence, Artificial Intelligence: A Modern Approach (used in more than 1,500 universities in 135 countries).

There is a growing concern among news organizations about the impact of generative artificial intelligence on the media industry, with lawmakers signaling potential changes ahead.

Over a decade ago, the media industry began grappling with the challenges posed by tech companies using their content without direct payment, leading to a decline in readership and ad revenue. Now, with the advent of generative AI, these firms threaten to further disrupt the balance of power between Big Tech and news organizations.

A recent Senate Judiciary Committee hearing focused on the need for legislation to prevent the exploitation of content by Big Tech. Lawmakers, including Richard Blumenthal and Josh Hawley, supported proposals requiring AI companies to strike licensing deals with news organizations. They emphasized learning from past failures to oversee social media and the necessity of adopting standards for AI.

The legality of AI firms using content from news organizations without consent or compensation is currently a subject of debate. One camp argues that this practice is protected under the “fair use” doctrine, while others view it as copyright infringement. The courts are yet to provide a definitive answer, but in the interim, AI companies continue to use copyrighted content as training materials, jeopardizing the financial viability of media outlets.

During the hearing, Roger Lynch, CEO of Condé Nast, urged Congress to clarify that using journalistic content for AI training is not fair use. Josh Hawley supported this view, suggesting a broader regime for compensation. However, Jeff Jarvis, a journalism professor, advocated for a broader interpretation of fair use and opposed protectionist legislation.

The New York Times recently filed a lawsuit that sheds light on the negotiations over licensing content with AI companies like OpenAI and Microsoft. This case highlights the dilemma faced by news organizations: accept low offers to license their content or engage in costly legal battles.

Lawmakers have expressed concerns about the creation of deepfakes and voice clones, leading to a bill prohibiting the unauthorized publication and distribution of digital replicas. This bill aims to confer intellectual property rights on individuals for the use of their image, voice, and likeness.

There is an need for legislative action to address the challenges posed by AI to the news industry. As AI continues to evolve, the balance between innovation and the protection of intellectual property rights remains a critical issue.

This week we found an interesting article that highlights the narrowing performance gap between open-source and private AI models. A graph from the article is below, but it’s well worth a quick read if you want to see what Open Source vs. Private Model is looking like. The full article can be found here.

Prompt: Neon Colored Bonsai Tree

Prompt: a water droplet encapsulates the majestic magnificence of a towering mountain