Unlearning is also proposed as a way to prevent a model from generating targeted types of information in its outputs, e.g., generations that closely resemble a particular individual's data or reflect the concept of Spiderman. Both of these goals--the targeted removal of information from a model and the targeted suppression of information from a model's outputs--present various technical and substantive challenges. We provide a framework for ML researchers and policymakers to think rigorously about these challenges, identifying several mismatches between the goals of unlearning and feasible implementations. These mismatches explain why unlearning is not a general-purpose solution for circumscribing generative-AI model behavior in service of broader positive impact.

Mother sues OpenAI in US after daughter's death linked to ChatGPT use Alice Carrier had recently started playing the guitar again, a hobby she enjoyed in high school but had set aside during college. It was one of several pursuits she filled her free time with as she interviewed for new jobs, spent time with her dog and enjoyed activities, including gaming. By all appearances, at least to her mother, Kristie Carrier, things were going well. Alice was working as a web developer in Montreal, Canada, fulfilling a dream she had carried since growing up in the small town of Lawrence, New Brunswick. But what Carrier did not know was how much her daughter was struggling in silence.

GOP lawmakers, tech investors, and even OpenAI have tied the anti-data-center movement in the US to Chinese interference. Experts say it's much more complicated than that. Right-wing officials and data center investors are increasingly claiming that data center protests are being funded and influenced by the Chinese government. OpenAI added to the discourse on Wednesday when it released a report describing a cluster of accounts originating in China that, the company said, had been spreading anti-data-center messages on social media. Experts who spoke to WIRED, however, are skeptical of the funding claims.

While Generative AI rapidly advances in various domains, generating truly creative, aesthetic, and counter-intuitive outputs remains a challenge. This paper presents an approach to tackle these difficulties in the domain of chess puzzles. We start by benchmarking Generative AI architectures, and then introduce an RL framework with novel rewards based on chess engine search statistics to overcome some of those shortcomings. The rewards are designed to enhance a puzzle's uniqueness, counter-intuitiveness, diversity, and realism. Our RL approach dramatically increases counter-intuitive puzzle generation by 10x, from 0.22\% (supervised) to 2.5\%, surpassing existing dataset rates (2.1\%) and the best Lichess-trained model (0.4\%). Our puzzles meet novelty and diversity benchmarks, retain aesthetic themes, and are rated by human experts as more creative, enjoyable, and counter-intuitive than composed book puzzles, even approaching classic compositions. Our final outcome is a curated booklet of these novel AI-generated puzzles, which is acknowledged for creativity by three world-renowned experts.

OpenAI is in the midst of overhauling ChatGPT . The goal is to transform the chatbot's simple interface into a personalized AI agent that can handle tasks in every facet of your personal and professional life. The company has taken to calling this new product, privately and publicly, a "super app." The all-in-one platform represents one of the biggest bets OpenAI has ever made, and one engineering leader now holds enormous sway over whether it pays off: Thibault Sottiaux. Last month, Sottiaux was appointed OpenAI's head of core products, overseeing both ChatGPT and Codex, as well as combining them into the future super app.

The tension between OpenAI CEO Sam Altman and Anthropic CEO Dario Amodei is the driving force in today's biggest technological revolution. SAN FRANCISCO/NEW YORK - If not for the intense rivalry between Anthropic and OpenAI, the generative AI boom might not have arrived so quickly. In late 2022, OpenAI caught wind that Anthropic was working on an AI-powered chatbot. OpenAI CEO Sam Altman immediately directed employees to fast-track a competing product, four people familiar with the matter said. Two weeks later, the company released ChatGPT, sparking a technological revolution that promises to overhaul the global economy and the way humans interact.

The company has published a report about China-linked influence campaigns that used ChatGPT. OpenAI has published a report about ChatGPT users, who it says were likely based in China, that used the chatbot to plan a campaign designed to sway Americans' opinions about AI data centers. It divided the users into two clusters, the first of which it had designated the Data Center Bandwagon group. Accounts categorized in the group allegedly asked ChatGPT to generate English-language talking points and images, such as comic strips, which focus on how AI data centers drive up demand in electricity and how that leads to higher bills for consumers. The company says these users posed as Americans from a variety of backgrounds on social media, where they had posted the text and image output they got from ChatGPT.

China-based actors are likely behind the use of ChatGPT for "covert influence operations" aimed at stoking opposition to data centres in the United States, OpenAI has said. In a research report released on Wednesday, the company behind the world's most popular AI chatbot said it had banned a cluster of accounts likely based in China for attempting to "manipulate a legitimate debate about American AI". Among other content, the accounts generated a comic strip showing a cigar-chomping businessman holding bags marked with dollar signs as a family reacted in shock to their electricity bill, according to the San Francisco-based company. OpenAI said a second cluster of accounts had generated content casting US tariffs as an effort to "dominate technological competition" with China, and specified that the material should not mention Chinese leader Xi Jinping. While the campaign sought to "exploit and amplify existing public concerns" about energy prices, OpenAI found no evidence that it had a "meaningful" influence, the company said.

We introduce BikeBench, an engineering design benchmark for evaluating generative models on problems with multiple real-world objectives and constraints. As generative AI's reach continues to grow, evaluating its capability to understand physical laws, human guidelines, and hard constraints grows increasingly important. Engineering product design lies at the intersection of these difficult tasks, providing new challenges for AI capabilities. BikeBench evaluates AI models' capabilities to generate bicycle designs that not only resemble the dataset, but meet specific performance objectives and constraints. To do so, BikeBench quantifies a variety of human-centered and multiphysics performance characteristics, such as aerodynamics, ergonomics, structural mechanics, human-rated usability, and similarity to subjective text or image prompts. Supporting the benchmark are several datasets of simulation results, a dataset of 10,000 human-rated bicycle assessments, and a synthetically generated dataset of 1.6M designs, each with a parametric, CAD/XML, SVG, and PNG representation. BikeBench is uniquely configured to evaluate tabular generative models, large language models (LLMs), design optimization, and hybrid algorithms side-by-side. Our experiments indicate that LLMs and tabular generative models fall short of hybrid GenAI+optimization algorithms in design quality, constraint satisfaction, and similarity scores, suggesting significant room for improvement. We hope that BikeBench, a first-of-its-kind benchmark, will help catalyze progress in generative AI for constrained multi-objective engineering design problems.

SoftBank's attempt to get $6 billion OpenAI margin loan stalls SoftBank Group's efforts to secure at least $6 billion through a margin loan backed by its OpenAI stake have stalled after the company lowered its fundraising target. SoftBank Group's talks with potential creditors to raise at least $6 billion from a margin loan backed by its OpenAI stake have stalled, people familiar with the matter said, just weeks after the Japanese conglomerate cut its initial target from $10 billion. The company is considering various fundraising options, according to the people, who asked not to be identified discussing private matters. It could still move forward with the margin loan at a later stage, they added. It's unclear why the margin loan discussions stalled. Borrowers and creditors can pause and revisit fundraising discussions for various reasons, and SoftBank hasn't elaborated on its plans, the people said.