Doing Vibe Physics — Alex Lupsasca, OpenAI
A Latent Space podcast/essay featuring Alex Lupsasca of OpenAI recounts how GPT-5.x was used to derive new results in theoretical physics and quantum gravity. The piece documents a concrete case of frontier LLMs contributing to original scientific research rather than merely assisting with literature review or code. It represents an early data point on AI-driven discovery in hard sciences.
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Early experiments in accelerating science with GPT-5
OpenAI has published initial research cases demonstrating GPT-5's application to scientific discovery across mathematics, physics, biology, and computer science. The examples highlight human-AI collaboration in generating mathematical proofs and uncovering novel insights. This represents OpenAI's first public documentation of GPT-5's scientific research capabilities beyond general benchmarks.
GPT-5.2 derives a new result in theoretical physics
A new preprint demonstrates GPT-5.2 proposing a novel formula for a gluon amplitude in theoretical physics, which was subsequently formally proved and verified by OpenAI researchers and academic collaborators. This represents a claimed instance of an AI system producing a genuinely new scientific result rather than reproducing known work. The result was published as a preprint and announced via the OpenAI blog.
GPT-5 and the future of mathematical discovery
UCLA Professor Ernest Ryu collaborated with GPT-5 to solve an open problem in optimization theory, representing a concrete example of AI-assisted mathematical research. The announcement highlights GPT-5's capability in formal reasoning and scientific discovery beyond standard benchmarks. This is an OpenAI blog post showcasing a real-world research outcome involving a frontier model.
Advancing science and math with GPT-5.2
OpenAI has released GPT-5.2, described as its strongest model for mathematics and science, achieving state-of-the-art results on GPQA Diamond and FrontierMath benchmarks. The announcement highlights practical research applications including solving an open theoretical problem and generating verified mathematical proofs. The post positions GPT-5.2 as a meaningful step toward AI-assisted scientific discovery.
Latent Space profiles Axiom Math on verified generation and compounding intelligence
Latent Space interviews Carina Hong of Axiom Math, a company focused on formal verification applied to AI-generated mathematics. The discussion centers on 'verified generation' and 'compounding intelligence' as frameworks for scaling AI reasoning beyond informal, unverified outputs. The piece is relevant to the growing intersection of formal methods, mathematical reasoning, and AI capability development.
Answering quantum physics questions with OpenAI o1
OpenAI published a case study featuring quantum physicist Mario Krenn using the o1 model to assist with complex quantum physics research questions. The piece highlights o1's reasoning capabilities applied to a frontier scientific domain. This is a capability demonstration framed around a real researcher's workflow rather than a benchmark result.
Data Points: GPT-5.4 Pro, Luma Uni-1, Phi-4-reasoning-vision-15B, Yuan 3.0 Ultra, OpenAI hardware chief resignation
The Batch's weekly roundup covers several significant AI developments: OpenAI released GPT-5.4 and GPT-5.4 Pro with computer-use agent capabilities, 1M token context, and strong benchmark gains on GDPval and OSWorld-Verified; Luma AI released Uni-1, a unified autoregressive model for visual understanding and generation; Microsoft released Phi-4-reasoning-vision-15B, an open-weights multimodal model trained on 200B tokens; Yuan Lab AI released Yuan 3.0 Ultra, a 1T-parameter MoE model with SOTA on document retrieval benchmarks. Additionally, OpenAI hardware chief Caitlin Kalinowski resigned over the company's Pentagon deal, citing concerns about surveillance and autonomous weapons governance.
Introducing GPT-5.2
OpenAI has released GPT-5.2, described as their most advanced frontier model for professional use, featuring state-of-the-art reasoning, long-context understanding, coding, and vision capabilities. The model is available through ChatGPT and the OpenAI API. It is positioned to support faster and more reliable agentic workflows.