Extending single-minus amplitudes to gravitons
A new preprint extends single-minus amplitudes to gravitons, with GPT-5. 2 Pro helping derive and verify nonzero graviton tree amplitudes in quantum gravity.
A new preprint shows GPT-5. 2 proposing a new formula for a gluon amplitude, later formally proved and verified by OpenAI and academic collaborators.
A new preprint extends single-minus amplitudes to gravitons, with GPT-5. 2 Pro helping derive and verify nonzero graviton tree amplitudes in quantum gravity.
GPT-5. 2 is OpenAI’s strongest model yet for math and science, setting new state-of-the-art results on benchmarks like GPQA Diamond and FrontierMath.
GPT-5. 1 is now available in the API, bringing faster adaptive reasoning, extended prompt caching, improved coding performance, and new apply_patch and shell tools.
The coupled ghost and gluon Dyson--Schwinger equations (DSEs) of four-dimensional Landau-gauge Yang--Mills (YM) theory are solved with a neural representation trained only from renormalized equation residuals. The neural and fixed-point solutions agree at the percent level and remain stable under changes of initialization, network size, integration grid, and infrared boundary condition.
arXiv:2607. 21548v1 Announce Type: cross Abstract: The coupled ghost and gluon Dyson--Schwinger equations (DSEs) of four-dimensional Landau-gauge Yang--Mills (YM) theory are solved with a neural representation trained only from renormalized equation residuals.
As the final model release of GPT-2’s staged release, we’re releasing the largest version (1. 5B parameters) of GPT-2 along with code and model weights to facilitate detection of outputs of GPT-2 models.
See how a group of leading developers use GPT-5 for the first time.
arXiv:2603. 02984v2 Announce Type: replace-cross Abstract: Normalizing flows can be used to construct unbiased, reduced-variance estimators for lattice field theory observables that are defined by a derivative with respect to action parameters.
Introducing GPT-4. 1 in the API—a new family of models with across-the-board improvements, including major gains in coding, instruction following, and long-context understanding.
More intelligence from every token, stronger performance per dollar, and more capability on demand for your hardest work.
UCLA Professor Ernest Ryu and GPT-5 solved a key question in optimization theory, showcasing AI’s role in accelerating mathematical discovery.
We’re releasing a research preview of OpenAI GPT‑4. 5, our largest and most knowledgeable model yet.