Sam Altman is the king of generative artificial intelligence. But is he the person we should trust to guide our explorations into AI? This week, we do a deep dive on Sam Altman, from his Midwest roots to his early startup days, his time in venture capital, and his rise and fall and rise again at OpenAI. You can follow Michael Calore on Mastodon at @snackfight, Lauren Goode on Threads and @laurengoode, and Zoë Schiffer on Threads @reporterzoe. Write to us at uncannyvalley@wired.com.

The increasing frequency and sophistication of cybersecurity vulnerabilities in software systems underscore the urgent need for robust and effective methods of vulnerability assessment. However, existing approaches often rely on highly technical and abstract frameworks, which hinders understanding and increases the likelihood of exploitation, resulting in severe cyberattacks. Given the growing adoption of Large Language Models (LLMs) across diverse domains, this paper explores their potential application in cybersecurity, specifically for enhancing the assessment of software vulnerabilities. We propose ChatNVD, an LLM-based cybersecurity vulnerability assessment tool leveraging the National Vulnerability Database (NVD) to provide context-rich insights and streamline vulnerability analysis for cybersecurity professionals, developers, and non-technical users. We develop three variants of ChatNVD, utilizing three prominent LLMs: GPT-4o mini by OpenAI, Llama 3 by Meta, and Gemini 1.5 Pro by Google. To evaluate their efficacy, we conduct a comparative analysis of these models using a comprehensive questionnaire comprising common security vulnerability questions, assessing their accuracy in identifying and analyzing software vulnerabilities. This study provides valuable insights into the potential of LLMs to address critical challenges in understanding and mitigation of software vulnerabilities.

With the approach of the High Luminosity Large Hadron Collider (HL-LHC) era set to begin particle collisions by the end of this decade, it is evident that the computational demands of traditional collision simulation methods are becoming increasingly unsustainable. Existing approaches, which rely heavily on first-principles Monte Carlo simulations for modeling event showers in calorimeters, are projected to require millions of CPU-years annually -- far exceeding current computational capacities. This bottleneck presents an exciting opportunity for advancements in computational physics by integrating deep generative models with quantum simulations. We propose a quantum-assisted hierarchical deep generative surrogate founded on a variational autoencoder (VAE) in combination with an energy conditioned restricted Boltzmann machine (RBM) embedded in the model's latent space as a prior. By mapping the topology of D-Wave's Zephyr quantum annealer (QA) into the nodes and couplings of a 4-partite RBM, we leverage quantum simulation to accelerate our shower generation times significantly. To evaluate our framework, we use Dataset 2 of the CaloChallenge 2022. Through the integration of classical computation and quantum simulation, this hybrid framework paves way for utilizing large-scale quantum simulations as priors in deep generative models.

This paper argues that we should perceive LLMs as machines of extrapolation. Extrapolation is a statistical function for predicting the next value in a series. Extrapolation contributes to both GPT successes and controversies surrounding its hallucination. The term hallucination implies a malfunction, yet this paper contends that it in fact indicates the chatbot efficiency in extrapolation, albeit an excess of it. This article bears a historical dimension: it traces extrapolation to the nascent years of cybernetics. In 1941, when Norbert Wiener transitioned from missile science to communication engineering, the pivotal concept he adopted was none other than extrapolation. Soviet mathematician Andrey Kolmogorov, renowned for his compression logic that inspired OpenAI, had developed in 1939 another extrapolation project that Wiener later found rather like his own. This paper uncovers the connections between hot war science, Cold War cybernetics, and the contemporary debates on LLM performances.

Generative AI is rapidly reshaping creative work, raising critical questions about its beneficiaries and societal implications. This study challenges prevailing assumptions by exploring how generative AI interacts with diverse forms of human capital in creative tasks. Through two random controlled experiments in flash fiction writing and song composition, we uncover a paradox: while AI democratizes access to creative tools, it simultaneously amplifies cognitive inequalities. Our findings reveal that AI enhances general human capital (cognitive abilities and education) by facilitating adaptability and idea integration but diminishes the value of domain-specific expertise. We introduce a novel theoretical framework that merges human capital theory with the automation-augmentation perspective, offering a nuanced understanding of human-AI collaboration. This framework elucidates how AI shifts the locus of creative advantage from specialized expertise to broader cognitive adaptability. Contrary to the notion of AI as a universal equalizer, our work highlights its potential to exacerbate disparities in skill valuation, reshaping workplace hierarchies and redefining the nature of creativity in the AI era. These insights advance theories of human capital and automation while providing actionable guidance for organizations navigating AI integration amidst workforce inequalities.

OpenAI has partnered with defense startup Anduril Industries to develop AI for the Pentagon. The companies said on Wednesday that they'll combine OpenAI's models, including GPT-4o and OpenAI o1, with Anduril's systems and software to improve the US military's defenses against unpiloted aerial attacks. The deal comes less than a year after OpenAI softened its stance on using its models for military purposes. Although the ChatGPT maker's policies still prohibit its models from developing or using weapons, it deleted a line in January that explicitly banned integrating its tech into "military and warfare" use. The company said at the time it was already working with DARPA on cybersecurity tools.

OpenAI, maker of ChatGPT and one of the most prominent artificial intelligence companies in the world, said today that it has entered a partnership with Anduril, a defense startup that makes missiles, drones, and software for the United States military. It marks the latest in a series of similar announcements made recently by major tech companies in Silicon Valley, which has warmed to forming closer ties with the defense industry. "OpenAI builds AI to benefit as many people as possible, and supports US-led efforts to ensure the technology upholds democratic values," Sam Altman, OpenAI's CEO, said in a statement Wednesday. OpenAI's AI models will be used to improve systems used for air defense, Brian Schimpf, co-founder and CEO of Anduril, said in the statement. "Together, we are committed to developing responsible solutions that enable military and intelligence operators to make faster, more accurate decisions in high-pressure situations," he said.

Today, OpenAI is announcing that its technology will be deployed directly on the battlefield. The company says it will partner with the defense-tech company Anduril, a maker of AI-powered drones, radar systems, and missiles, to help US and allied forces defend against drone attacks. OpenAI will help build AI models that "rapidly synthesize time-sensitive data, reduce the burden on human operators, and improve situational awareness" to take down enemy drones, according to the announcement. Specifics have not been released, but the program will be narrowly focused on defending US personnel and facilities from unmanned aerial threats, according to Liz Bourgeois, an OpenAI spokesperson. "This partnership is consistent with our policies and does not involve leveraging our technology to develop systems designed to harm others," she said.

OpenAI will start announcing new features and demos tomorrow for 12 days through livestreams. Sources familiar with the matter told The Verge that these new products will allegedly include OpenAI's long-awaited text-to-video tool, Sora, and a new reasoning model. The announcement for "12 Days of OpenAI", as the company puts it, was made public on X yesterday. The first livestream will broadcast tomorrow, but the announcements themselves remain unconfirmed That said, in addition to the sources that spoke more recently with The Verge, the Wall Street Journal previously reported Sora was likely to come out before the end of 2024. Sora was revealed early this year, and shared with a small group of testers. But 20 or so of those artists leaked the model to the public in protest of "unpaid labor," The Washington Post reported.

MAMMO MISHAP: A U.K. woman is thanking artificial intelligence for saving her life. The technology picked up cancer cells in the patient's screening that were undetectable by the human eye, according to SWNS. READY AND WILLING: Sam Altman, CEO of OpenAI, the creator of ChatGPT, on Sunday said he is looking forward to working with the incoming Trump administration, adding that he thinks President-elect Trump will succeed at helping to make America a world-leading force in artificial intelligence infrastructure. SEEING IS REPEATING: In a groundbreaking development, researchers at Johns Hopkins University and Stanford University have successfully trained a robotic surgical system to perform complex tasks with the skill of human doctors. "Like all technology, there's the potential for incredible innovation and a real threat and obviously needs to be highly regulated," she told Fox News Digital.