Earlier this week, the Republican National Committee released a video that it claims was “built entirely with AI imagery.” The content of the ad isn’t especially novel—a dystopian vision of America under a second term with President Joe Biden—but the deliberate emphasis on the technology used to create it stands out: It’s a “Daisy” moment for the 2020s.
We should expect more of this kind of thing. The applications of AI to political advertising have not escaped campaigners, who are already “pressure testing” possible uses for the technology. In the 2024 presidential election campaign, you can bank on the appearance of AI-generated personalized fundraising emails, text messages from chatbots urging you to vote, and maybe even some deepfaked campaign avatars. Future candidates could use chatbots trained on data representing their views and personalities to approximate the act of directly connecting with people. Think of it like a whistle-stop tour with an appearance in every living room. Previous technological revolutions—railroad, radio, television, and the World Wide Web—transformed how candidates connect to their constituents, and we should expect the same from generative AI. This isn’t science fiction: The era of AI chatbots standing in as avatars for real, individual people has already begun, as the journalist Casey Newton made clear in a 2016 feature about a woman who used thousands of text messages to create a chatbot replica of her best friend after he died. Read More
Daily Archives: May 5, 2023
There Is No Turning Back on AI
The only question is: will we learn how to live in moving history?
ChatGPT has been around for about two seconds and it’s already changing how people work, how they write, how they research, how they cheat on tests, how they profess their love, and what they make for dinner.
We didn’t have to talk about theoretical “use cases,” as people still do with cryptocurrency. ChatGPT, which 100 million people use every day, showed us its uses right away.
That is really exciting. And also really unnerving. Read More
Are Emergent Abilities of Large Language Models a Mirage?
Recent work claims that large language models display emergent abilities, abilities not present in smaller-scale models that are present in larger-scale models. What makes emergent abilities intriguing is two-fold: their sharpness, transitioning seemingly instantaneously from not present to present, and their unpredictability, appearing at seemingly unforeseeable model scales. Here, we present an alternative explanation for emergent abilities: that for a particular task and model family, when analyzing fixed model outputs, one can choose a metric which leads to the inference of an emergent ability or another metric which does not. Thus, our alternative suggests that existing claims of emergent abilities are creations of the researcher’s analyses, not fundamental changes in model behavior on specific tasks with scale. We present our explanation in a simple mathematical model, then test it in three complementary ways: we (1) make, test and confirm three predictions on the effect of metric choice using the InstructGPT/GPT-3 family on tasks with claimed emergent abilities, (2) make, test and confirm two predictions about metric choices in a meta-analysis of emergent abilities on BIG-Bench; and (3) show how similar metric decisions suggest apparent emergent abilities on vision tasks in diverse deep network architectures (convolutional, autoencoder, transformers). In all three analyses, we find strong supporting evidence that emergent abilities may not be a fundamental property of scaling AI models. Read More
Rick's Cafe AI 