As usage of generative AI tools skyrockets, the amount of sensitive information being exposed to these models and centralized model providers is alarming. For example, confidential source code from Samsung suffered a data leak as the text prompt to ChatGPT encountered data leakage. An increasing number of companies are restricting the use of LLMs (Apple, Verizon, JPMorgan Chase, etc.) due to data leakage or confidentiality issues. Also, an increasing number of centralized generative model providers are restricting, filtering, aligning, or censoring what can be used. Midjourney and RunwayML, two of the major image generation platforms, restrict the prompts to their system via prompt filtering. Certain political figures are restricted from image generation, as well as words associated with women's health care, rights, and abortion. In our research, we present a secure and private methodology for generative artificial intelligence that does not expose sensitive data or models to third-party AI providers. Our work modifies the key building block of modern generative AI algorithms, e.g. the transformer, and introduces confidential and verifiable multiparty computations in a decentralized network to maintain the 1) privacy of the user input and obfuscation to the output of the model, and 2) introduce privacy to the model itself. Additionally, the sharding process reduces the computational burden on any one node, enabling the distribution of resources of large generative AI processes across multiple, smaller nodes. We show that as long as there exists one honest node in the decentralized computation, security is maintained. We also show that the inference process will still succeed if only a majority of the nodes in the computation are successful. Thus, our method offers both secure and verifiable computation in a decentralized network.

We propose a novel framework that leverages Visual Question Answering (VQA) models to automate the evaluation of LLM-generated data visualizations. Traditional evaluation methods often rely on human judgment, which is costly and unscalable, or focus solely on data accuracy, neglecting the effectiveness of visual communication. By employing VQA models, we assess data representation quality and the general communicative clarity of charts. Experiments were conducted using two leading VQA benchmark datasets, ChartQA and PlotQA, with visualizations generated by OpenAI's GPT-3.5 Turbo and Meta's Llama 3.1 70B-Instruct models. Our results indicate that LLM-generated charts do not match the accuracy of the original non-LLM-generated charts based on VQA performance measures. Moreover, while our results demonstrate that few-shot prompting significantly boosts the accuracy of chart generation, considerable progress remains to be made before LLMs can fully match the precision of human-generated graphs. This underscores the importance of our work, which expedites the research process by enabling rapid iteration without the need for human annotation, thus accelerating advancements in this field.

This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, including computer science, mathematics, natural sciences, medicine, linguistics, and social sciences. Through rigorous testing, o1-preview demonstrated remarkable capabilities, often achieving human-level or superior performance in areas ranging from coding challenges to scientific reasoning and from language processing to creative problem-solving. Key findings include: -83.3% success rate in solving complex competitive programming problems, surpassing many human experts. -Superior ability in generating coherent and accurate radiology reports, outperforming other evaluated models. -100% accuracy in high school-level mathematical reasoning tasks, providing detailed step-by-step solutions. -Advanced natural language inference capabilities across general and specialized domains like medicine. -Impressive performance in chip design tasks, outperforming specialized models in areas such as EDA script generation and bug analysis. -Remarkable proficiency in anthropology and geology, demonstrating deep understanding and reasoning in these specialized fields. -Strong capabilities in quantitative investing. O1 has comprehensive financial knowledge and statistical modeling skills. -Effective performance in social media analysis, including sentiment analysis and emotion recognition. The model excelled particularly in tasks requiring intricate reasoning and knowledge integration across various fields. While some limitations were observed, including occasional errors on simpler problems and challenges with certain highly specialized concepts, the overall results indicate significant progress towards artificial general intelligence.

This paper explores the potential of AI-powered tools to reshape data analysis, focusing on design considerations and challenges. We explore how the emergence of large language and multimodal models offers new opportunities to enhance various stages of data analysis workflow by translating high-level user intentions into executable code, charts, and insights. We then examine human-centered design principles that facilitate intuitive interactions, build user trust, and streamline the AI-assisted analysis workflow across multiple apps. Finally, we discuss the research challenges that impede the development of these AI-based systems such as enhancing model capabilities, evaluating and benchmarking, and understanding end-user needs.

OpenAI, the developer of the groundbreaking ChatGPT chatbot, is preparing to overhaul its corporate structure and become a for-profit business. The startup's chief executive, Sam Altman, acknowledged on Thursday that it was "not a normal company" after another surprising development at OpenAI this week when its its chief technology officer, Mira Murati, resigned. Her departure was quickly followed by the announcement that two other executives had quit. The company is synonymous with an artificial intelligence boom triggered by the emergence, in 2022, of OpenAI's signature product, a chatbot that stunned users with its ability to craft convincing, human-like responses to an array of prompts. Altman, in turn, has become the poster child for a technology that is advancing rapidly and is being developed by the world's largest tech companies, including Microsoft – OpenAI's biggest backer – Google, the Facebook owner Meta and Amazon.

For years now, generative AI has been used to conjure all sorts of realities--dazzling paintings and startling animations of worlds and people, both real and imagined. This power has brought with it a tremendous dark side that many experts are only now beginning to contend with: AI is being used to create nonconsensual, sexually explicit images and videos of children. And not just in a handful of cases--perhaps millions of kids nationwide have been affected in some way by the emergence of this technology, either directly victimized themselves or made aware of other students who have been. This morning, the Center for Democracy and Technology, a nonprofit that advocates for digital rights and privacy, released a report on the alarming prevalence of nonconsensual intimate imagery (or NCII) in American schools. In the past school year, the center's polling found, 15 percent of high schoolers reported hearing about a "deepfake"--or AI-generated image--that depicted someone associated with their school in a sexually explicit or intimate manner.

There's a story about Sam Altman that has been repeated often enough to become Silicon Valley lore. In 2012, Paul Graham, a co-founder of the famed start-up accelerator Y Combinator and one of Altman's biggest mentors, sat Altman down and asked if he wanted to take over the organization. The decision was a peculiar one: Altman was only in his late 20s, and at least on paper, his qualifications were middling. He had dropped out of Stanford to found a company that ultimately hadn't panned out. After seven years, he'd sold it for roughly the same amount that his investors had put in.

In the decade-long fight to control CRISPR, the super-tool for modifying DNA, it's been common for lawyers to try to overturn patents held by competitors. But now, in a surprise twist, the team that earned the Nobel Prize in chemistry for developing CRISPR is asking to cancel two of their own seminal patents, MIT Technology Review has learned. The request to withdraw the pair of European patents, by lawyers for Emmanuelle Charpentier and Jennifer Doudna, comes after a damaging August opinion from a European technical appeals board, which ruled that the duo's earliest patent filing didn't explain CRISPR well enough for other scientists to use it and doesn't count as a proper invention. The decision could have major ramifications regarding who gets to collect the lucrative licensing fees on using the technology.Read the full story. What's new: The Allen Institute for Artificial Intelligence (Ai2), a research nonprofit, is releasing a family of open-source multimodal language models, called Molmo, that it says perform as well as top proprietary models from OpenAI, Google, and Anthropic.

OpenAI is reportedly pushing ahead with plans to become a for-profit company, as more senior figures left the ChatGPT developer after the surprise exit of its chief technology officer, Mira Murati. The San Francisco-based startup is preparing to change its corporate structure as it seeks 6.5bn ( 4.9bn) of new funding, according to reports. Under the changes, OpenAI will become a for-profit benefit corporation – an entity that makes profits but is committed to the social and public good – that will no longer be controlled by its nonprofit board, Reuters reported. OpenAI declined to comment on the details of the reports but a spokesperson said the nonprofit entity would continue to exist. "We remain focused on building AI that benefits everyone, and we're working with our board to ensure that we're best positioned to succeed in our mission. The nonprofit is core to our mission and will continue to exist," said the spokesperson.

A high-ranking executive at OpenAI who served a few days as its interim CEO during a period of turmoil last year said she's leaving the artificial intelligence company. Mira Murati, OpenAI's chief technology officer, said in a written statement Wednesday that, after much reflection, she has "made the difficult decision to leave OpenAI." "I'm stepping away because I want to create the time and space to do my own exploration," she said. Two other top executives are also on their way out, CEO Sam Altman announced later Wednesday. The decisions by Murati, as well as OpenAI's Chief Research Officer Bob McGrew and another research leader, Barret Zoph, were made "independently of each other and amicably," Altman said in a note to employees he shared on social media.