- The Hidden Layer
- Posts
- Amazon Mandates AI Material Disclosure for Authors
Amazon Mandates AI Material Disclosure for Authors
PLUS: Meta's Next-Gen AI System
The Hidden Layer
September 11, 2023
Diving into Edition #08 of "The Hidden Layer." Continuing our journey, we'll further explore the profound ways AI is reshaping the landscape of business and society, uncovering layer after layer.
Today's AI Headlines:
Meta's Next-Gen AI System
Top 20 Free AI Courses on edX
Amazon Mandates AI Material Disclosure for Authors
5 Skills AI Can't Replace
Australia Demands Removal of AI-Generated Abusive Content
Amazon to require some authors to disclose the use of AI material
After pressure from the Authors Guild, Amazon now requires authors to disclose if their books contain AI-generated content when publishing on its platform. This policy aims to increase transparency and prevent an influx of computer-generated books crowding out human-written works. While a positive first step, the impact may be limited since Amazon isn't yet labeling which books use AI. The Authors Guild hopes public disclosure will eventually be required. This change comes amid broader concerns about the rise of AI-generated content and its implications for creativity, originality, and copyright. The new rules differentiate between AI-assisted and AI-generated content, with only the latter requiring disclosure.
Why Does This Matter?
This issue is relevant in the context of the ongoing debate around AI creativity and the potential disruption of AI to industries like writing and publishing. As AI capabilities advance, policies and norms will need to adapt to balance innovation and responsible development. Issues like disclosure and copyright will continue to be discussed regarding AI-generated content across platforms.
FROM OUR PARTNERS
AI Tool of the Day: Speechify
Introducing Speechify: Transform the way you consume content by listening instead of reading. Available on Chrome, iOS, Android, and Mac, this tool swiftly converts documents, articles, and even photographed pages into high-quality audio. With AI voices that read up to 9x faster than average, immerse in your favorite texts or learn on-the-go. From books to emails, experience reading redefined, anywhere and anytime.
Meta is developing a new, more powerful AI system
Meta is working on a new artificial intelligence system meant to match the most advanced AI model from OpenAI, according to a Wall Street Journal report. The system, slated for completion in 2023, would be several times more powerful than Meta's current Llama 2 model. This AI is expected to help other companies build sophisticated text and analysis outputs. Meta plans to start training the large language model in early 2024. The move shows Meta's ambitions to be a leader in generative AI amid the rapid growth in demand for chatbots and advanced natural language processing. With tech giants like Apple, Google, and Microsoft also investing heavily in AI, the field is seeing intense competition.
Why Does This Matter?
This matters because it highlights the massive investments being made by Big Tech companies to advance AI capabilities, particularly in natural language processing. The progress in generative AI has significant implications for industries like marketing, customer service, and content creation. As these systems grow more sophisticated, it also raises important questions around ethics, bias, and misuse that society will need to grapple with.
FROM OUR PARTNERS
AI Spotlight
Prompt of the Day:
Transform the given [text] into an email with a [tone] style. Ensure the email remains succinct and integrate appropriate placeholders.
Text: [Specify here]
Tone: [Specify here]
Decoding AI: Your Questions Answered
What is an activation function?
An activation function is a crucial component in artificial neural networks. It determines the output of a neuron based on its input, essentially deciding whether the neuron should be activated or not. The primary purpose of the activation function is to introduce non-linearity into the network, allowing it to learn from the error and make necessary corrections. This non-linearity enables the neural network to model complex relationships and patterns that linear equations cannot. Common examples of activation functions include the sigmoid, hyperbolic tangent (tanh), and rectified linear unit (ReLU).
Thank you for accompanying us through Edition #08 of The Hidden Layer. Eager to understand more about AI's role in business and society? Your insights and queries might just pave the way for our upcoming edition. Stay curious!
Until next time,
Best,
The Hidden Layer Team
Finding value in the newsletter? Share the knowledge with a friend—it takes just a moment. Your referral supports the hours we invest in bringing you this content. They can sing up below.
