“The human genome is made of about 3 billion base pairs of DNA — but much of it remains a mystery. Scientists understand the 2% of the human genome that codes for proteins relatively well, but have only limited knowledge of the remaining 98%. Our AlphaGenome model has already shown how single changes in these non-coding DNA regions can disrupt molecular processes like protein production, but the bigger picture remained unclear.

Today, we're introducing AlphaGenome Atlas, a database that predicts the effects of every possible single nucleotide variant in the human genome. We used the AlphaGenome AI model to pre-calculate the regulatory impact of all 9 billion single-letter genetic changes, resulting in a massive, 1-petabyte dataset. Our new Atlas helps scientists rapidly query this vast information.

To help researchers rapidly navigate this, the Atlas introduces the AlphaGenome Variant Impact (AVI) score. This single, easy-to-use score combines predictions for both coding and non-coding regions, allowing researchers to quickly prioritize the most promising avenues for research without sifting through thousands of data points.”

From The Keyword.

“Mr. Fryer raised the alarm about suppression of inconvenient findings in a November 2024 Wall Street Journal essay. He called for something like a MacArthur Fellowship or an X Prize for academic truth-telling. The prize should be large enough to matter, prestigious enough to serve as a public credential for scholars who were right when it was costly to be right. Shortly after that piece ran, we found each other and decided to launch the Carob Trust Prize for Academic Courage.

The prize awards $1 million each to as many as five social scientists a year who have demonstrated intellectual independence, published findings that were attacked rather than answered, and been validated by the evidence—despite the professional cost. The selection criteria are designed to distinguish courage from contrarianism: Nominees must show a sustained commitment to following logic and evidence regardless of pressure, a willingness to ask questions others avoid, and work that has shifted academic debate, public discourse or policy—often despite being misread, mischaracterized or vilified at the time of publication.

The inaugural prize is limited to the social sciences; in future years we hope to broaden it to additional disciplines and to add a category for institutional leadership. Nominations are open through Nov. 1, and the first winners will be announced in early 2027.”

From Wall Street Journal.

“We’re sharing a solution to the Navier–Stokes existence and smoothness problem, one of the Millennium Prize Problems. This proof, produced by an internal OpenAI system, shows that the dynamics of the Navier-Stokes equations for fluid motion can develop a singularity in finite time. We’re sharing both a writeup of the proof and a formalization in Lean.

The Millennium Prize Problems⁠(opens in a new window) represent some of the deepest questions at the frontier of mathematics. The question of whether smooth three-dimensional fluid motion can break down has remained unresolved for roughly 90 years.

A major goal of our work is to empower scientists to advance research and technology that benefits all of humanity. To solve the Navier–Stokes problem, we used an internal model that is significantly more capable than GPT‑6 Astra. We believe it is important to inform the world about the pace of AI progress and what to expect from upcoming models.”

From OpenAI.

“From helping doctors detect cancer to guiding self-driving cars through traffic, many modern imaging systems rely on near-infrared light, producing a crisp picture when visible light would scatter and yield a blurry picture. But near-infrared systems struggle when light passes through materials like deep tissue or dense fog, succumbing to the same scattering effect where photons deviate from their path. Existing near-infrared imaging systems also rely on specialized detectors made from expensive materials, limiting their affordability and widespread use.

University of Rochester researchers have now developed a lower-cost imaging system that overcomes both challenges. Using inexpensive silicon-based detectors, the system quickly converts near-infrared light to visible light while producing clearer images through these difficult environments. The technology, outlined in a recent Nature Communications paper, uses a technique called time-gating that the laboratory of Robert Boyd, the William F. Krupke Distinguished Professor in Optics, has spent more than a decade refining."”

From University of Rochester.