OpenAI has notched a victory in its ongoing legal fight against publishers over how its AI tools use creative work. OpenAI argued that the publishers had no legal standing to bring this claim, stating they failed to offer proof that ChatGPT was trained on their material, let alone that the training was harmful. Judge Colleen McMahon of the US Southern District of New York agreed with OpenAI's argument, dismissing the case for lack of standing. "We build our AI models using publicly available data, in a manner protected by fair use and related principles, and supported by long-standing and widely accepted legal precedents," says OpenAI spokesperson Jason Deutrom. Although this is a major setback for Alternet and Raw Story, it's not necessarily the end.

We introduce Brain-Artificial Intelligence Interfaces (BAIs) as a new class of Brain-Computer Interfaces (BCIs). Unlike conventional BCIs, which rely on intact cognitive capabilities, BAIs leverage the power of artificial intelligence to replace parts of the neuro-cognitive processing pipeline. BAIs allow users to accomplish complex tasks by providing high-level intentions, while a pre-trained AI agent determines low-level details. This approach enlarges the target audience of BCIs to individuals with cognitive impairments, a population often excluded from the benefits of conventional BCIs. We present the general concept of BAIs and illustrate the potential of this new approach with a Conversational BAI based on EEG. In particular, we show in an experiment with simulated phone conversations that the Conversational BAI enables complex communication without the need to generate language. Our work thus demonstrates, for the first time, the ability of a speech neuroprosthesis to enable fluent communication in realistic scenarios with non-invasive technologies.

This paper introduces a notation of $\varepsilon$-weakened robustness for analyzing the reliability and stability of deep neural networks (DNNs). Unlike the conventional robustness, which focuses on the "perfect" safe region in the absence of adversarial examples, $\varepsilon$-weakened robustness focuses on the region where the proportion of adversarial examples is bounded by user-specified $\varepsilon$. Smaller $\varepsilon$ means a smaller chance of failure. Under such robustness definition, we can give conclusive results for the regions where conventional robustness ignores. We prove that the $\varepsilon$-weakened robustness decision problem is PP-complete and give a statistical decision algorithm with user-controllable error bound. Furthermore, we derive an algorithm to find the maximum $\varepsilon$-weakened robustness radius. The time complexity of our algorithms is polynomial in the dimension and size of the network. So, they are scalable to large real-world networks. Besides, We also show its potential application in analyzing quality issues.

In March 2020, game creators at Ubisoft's Toronto studio had just finished wrapping up the "primo moments" of Far Cry 6's scenes with Breaking Bad's villain Giancarlo Esposito and Coco's young dreamer Anthony Gonzalez when Covid-19 became very real, very quickly. The borders between the US and Canada were about to shut down, and the team was anxious to bag the footage they needed before getting the American actors safely and quickly on a plane back home. The first-person shooter game hinged on performances of the A-list actors, Esposito and Gonzalez, who play Anton and Diego Castillo, a president-dictator and his son from Yara, "a tropical paradise frozen in time." Esposito and Gonzalez made it out of Canada just before the first lockdown, but Ubisoft was still facing a dilemma. The game's release was set for less than a year away, and the whole opening scene--arguably the most important sequence of the entire game--hadn't yet been shot.

When you decide to write a story set in the near future, or speculating about things that might happen, you're running the risk of looking like a jackass. Nobody expects a science fiction story to predict the actual future--not if they know anything about science fiction, anyway. But given how slowly publishing can move and how fast the world changes, your story can look outdated before it even sees print. I ran into this a bunch of times with my novel All the Birds in the Sky. Because this novel took so long to write, and then had another two years between getting a book deal and actually getting published, there was tons of stuff in there that I had a queasy feeling would be just completely wrong by the time this book saw the light of day.

List of Tables Table 4-1: Status determined based on the ''alues returned by selection rules 13 ACKNOWLEDGMENTS 1 would like to thank

A wide range of problems, from contingent and multiagent planning to process/service orchestration, can be viewed as games. In many of these, it is natural to spec- ify the possible behaviors procedurally. In this paper, we develop a logical framework for specifying these types of problems/games based on the situation calculus and ConGolog. The framework incorporates game-theoretic path quantifiers as in ATL. We show that the framework can be used to model such problems in a natural way. We also show how verification/synthesis techniques can be used to solve problems expressed in the framework. In particular, we develop a method for dealing with infinite state settings using fixpoint approximation and “characteristic graphs”.