This is the third in my annual series reviewing everything that happened in the LLM space over the past 12 months. For previous years see Stuff we figured out about AI in 2023 and Things we learned about LLMs in 2024.
It’s been a year filled with a lot of different trends.
2026 (Nature Neuroscience)
• AstroREG, a resource of enhancer–gene interactions in human primary astrocytes, generated by combining CRISPR inhibition (CRISPRi), single-cell RNA-seq and machine learning.
This study reveals how distal DNA ‘switches’ control gene activity in human astrocytes. Using CRISPRi screens and single-cell RNA-seq, we map enhancer–gene links, highlight Alzheimer’s disease-related targets and introduce a model that predicts additional regulatory interactions.
Goodrich admits that when his group first proposed the strategy, “everyone said we were crazy.” Researchers have been trying to develop vaccines that contain whole cancer cells for more than 50 years, and although some formulations made it to clinical trials, they produced a poor immune response. None of the vaccines has been approved for humans, although one is available for pets.
The harsh methods previously used to stop cancer cells from reproducing, such as radiation, also caused them to shed their neoantigens, Goodrich says. He argues that the UV-based approach should work better because it preserves these potential immune stimulants.
The new clinical trial, launching this month at City of Hope in California and sponsored by PhotonPharma, aims to recruit eight patients with relapsed ovarian cancer. They will first undergo surgery to remove their tumors. Researchers will then expose the tumor cells to riboflavin and UV light and combine them with an immune-boosting additive known as an adjuvant to produce a custom vaccine. Participants will receive three doses of the vaccine, and researchers will check for side effects and measure immune responses.
Thanks to their work from the 1980s and onward, John Hopfield and Geoffrey Hinton have helped lay the foundation for the machine learning revolution that started around 2010.
The development we are now witnessing has been made possible through access to the vast amounts of data that can be used to train networks, and through the enormous increase in computing power. Today’s artificial neural networks are often enormous and constructed from many layers. These are called deep neural networks and the way they are trained is called deep learning.
A quick glance at Hopfield’s article on associative memory, from 1982, provides some perspective on this development. In it, he used a network with 30 nodes. If all the nodes are connected to each other, there are 435 connections. The nodes have their values, the connections have different strengths and, in total, there are fewer than 500 parameters to keep track of. He also tried a network with 100 nodes, but this was too complicated, given the computer he was using at the time. We can compare this to the large language models of today, which are built as networks that can contain more than one trillion parameters (one million millions).
Humans have the remarkable ability to remember the same person or object in completely different situations. We can easily distinguish between dinner with a friend and a business meeting with the same friend. “We already know that deep in the memory centers of the brain, specific cells, called concept neurons, respond to this friend, regardless of the environment in which he appears,” says Prof. Florian Mormann from the Clinic for Epileptology at the UKB, who is also a member of the Transdisciplinary Research Area (TRA) Life & Health at the University of Bonn.
However, the brain must be able to combine this content with the context in order to form a useful memory. In rodents, individual neurons often mix these two pieces of information. “We asked ourselves: Does the human brain function fundamentally differently here? Does it map content and context separately to enable a more flexible memory? And how do these separate pieces of information connect when we need to remember specific content according to context?” says Dr. Marcel Bausch, working group leader at the Department of Epileptology and member of TRA Life & Health at the University of Bonn.
Past research has found that exposure to bright lights and high levels of noise can alter both physiological processes and human behavior. For instance, an elevated or limited exposure to bright lights and noise has been found to influence people’s sleeping patterns, circadian rhythm, mood, metabolism, stress levels and mental performance.
Researchers at Jinan University and other institutes in China recently carried out a new study involving mice, exploring the possibility that the exposure to bright lights also influences eating behavior and body weight. Their findings, published in Nature Neuroscience, suggest that bright light exposure suppresses food consumption in mice and can lead to weight loss, while also identifying neural processes that could support these light-induced changes in feeding behavior.
“Environmental light regulates nonimage-forming functions like feeding, and bright light therapy shows anti-obesity potential, yet its neural basis remains unclear,” wrote Wen Li, Xiaodan Huang and their colleagues in their paper. “We show that bright light treatment effectively reduces food intake and mitigates weight gain in mice through a visual circuit involving the lateral hypothalamic area (LHA).”
You can’t see, feel, hear, taste or smell them, but tiny particles from space are constantly raining down on us.
They come from cosmic rays—high-energy particles that can originate from exploding stars and other extreme astrophysical events far beyond our solar system. When the rays collide with atoms high in Earth’s protective atmosphere, they trigger a cascade of secondary particles. Among the most important of these new particles are muons, which can pass through the atmosphere and even penetrate into the ground.
An invention by University of Delaware physics professor Spencer Axani called CosmicWatch is putting the science of muons in the palms of experienced scientists and high school students alike.