It’s New Year’s Eve, so I thought it would be fun to review the 10 most popular stories by page views on shellypalmer.com. Obviously, 2023 was the year of Generative AI, with this past November 30 marking 1 GE (Generative Era). These stories reflect this year’s trends, although some of the topics may surprise you.
1. Generative Synthetic Media: The Future of the Creative Process
Synthetic media, sometimes referred to as “deepfake” technology, is the use of AI and machine learning to generate realistic, digital media such as images, videos, and audio. This technology is already revolutionizing the creative process as both artists and artisans conscript AI-coworkers for production assistance. But in the coming months, we are likely to see this technology evolve into Generative Synthetic Media (GSM) which we will define (for this essay) as data-driven synthetic media (created in near real time and surfaced in place of traditional media). When fully achieved, GSM will revolutionize human communication. This is a bold claim, so it requires bold evidence. Let’s review. Read more.
2. Will Conversational AI Kill Web Traffic?
After dinner last night, three generations of my family were sitting in the living room discussing the possibility of finding a movie we could all watch together. While this passionate debate about which movies won an Oscar and which were just fan favorites was heating up and heading nowhere, I asked ChatGPT to “list some great movies that would be appropriate for kids 12-14, parents 32-46, and grandparents.” In just under 30 seconds, it helped us find our movie. Amazing! Except… we didn’t visit any websites to accomplish our search. As someone who writes and publishes 5,000-7,500 original words each week, the ramifications of this new workflow are profound. Read more.
3. Near-AGI Technology Is Already Transforming the World
Unlike existing, but newly popular, artificial intelligence (AI) systems which are designed to perform specific tasks such as image recognition, speech recognition, and natural language processing, artificial general intelligence (AGI) systems will be super-AI systems that will be able to learn anything and perform intellectual tasks at a level of expertise comparable to or exceeding that of human beings. Read more.
4. AI and Copyright Law and Creators
The human creative community, the U.S. Copyright Office, and AI-enabled creators all have different ideas about where copyrightable human creativity begins. Are you entitled to royalties if your work is used to help train a model? If a model is prompted to create something that is inspired by a bunch of different styles is that work “original?” If a human uses what they’ve learned to craft a prompt is the result of that prompt “original?” Humans learn by mimicking. In fact, human beings are the most successful mimics on the planet. “Watch Mommy!” or “Daddy will show you how to do it,” or “Repeat after me” are phrases we have heard all of our lives. You will learn about this subject by mimicking the words, acronyms and concepts written here – that’s why you are reading. Generative AI learns in a very similar way. Has it crossed a line? If it has, we’ve been walking up to the edge for decades. Let’s explore. Read more.
5. Default to Distrust: A New Paradigm for Engaging with Generative AI Models
For reasons that are theorized – but not fully understood – human beings “default-to-trust.” In other words, it is more evolutionarily stable to trust someone than it is to begin from a place of distrust. We don’t always default-to-trust when we meet a stranger, especially if we’re in a new or uncomfortable environment, but when we are not under a perceived threat, almost all of us default-to-trust because the benefits of doing so outweigh the consequences of acting like a cynical, pessimistic jerk. Read more.
6. Help Draft The US National AI Strategy
The Office of Science and Technology Policy (OSTP) is asking for your help. The Biden-Harris Administration is developing a National Artificial Intelligence (AI) Strategy that will chart a path for the United States to harness the benefits and mitigate the risks of AI. This strategy will build on the actions that the Federal Government has already taken to responsibly advance the development and use of AI. To inform this strategy, OSTP requests public comments to help update U.S. national priorities and future actions on AI. Read more.
7. Adapting to the AI Revolution: Don’t Just Hand Over the Tools, Rework the Workflow
Welcome to the brave new world of generative AI, where the machines are no longer just number crunchers, they’re word crunchers, image crunchers, audio and video crunchers. But here’s the catch: If we’re to ride the wave of this technological revolution, we need to rethink not just the tools we use, but also how we use them. Read more.
8. AI Can Hum a Tune. But Is It Music or Just Notes?
Meta AI has introduced AudioCraft, a text-to-music AI model that does an impressive job of composing, arranging, orchestrating, and playing in a wide range of musical styles. Not only can it create or mimic a melody, but it also engineers and produces fully finished work, some of which is already suitable for commercial use – and this is only V1. Imagine where the state-of-the-art will be a year from now. Read more.
9. Talking to Data: The Real Power of Generative AI
A prevailing misconception suggests that generative AI platforms, such as ChatGPT, possess an almost mystical ability to provide answers to intricate business queries. “How can I sell more widgets in Wyoming?” seems like a simple question, but without the right data, even the most advanced AI systems won’t help you. At the heart of this misconception is an overestimation of AI’s capabilities. While generative AI is undeniably powerful, it cannot conjure insights from thin air. The adage “Garbage in, garbage out” remains as relevant as ever. In the context of AI, this translates to “You can’t analyze data you don’t have.” Read more.
10. The Dual Realities of AI: A Balance of Wonder and Caution
Recent developments at OpenAI, marked by the abrupt departure of CEO Sam Altman, have stirred the AI community. Speculations suggest internal disagreements over the pace of AI development, particularly around commercialization, hinting at deeper issues within the field. Read more.
Author’s note: This is not a sponsored post. I am the author of this article and it expresses my own opinions. I am not, nor is my company, receiving compensation for it. This work was created with the assistance of various generative AI models.