A new method combines machine learning and cell-free systems to design powerful enzymes faster than ever—no living cells needed.
Scientists will finally be able to simulate the chemistry that drives our bodies, our environment, and our technologies.
This leads us to perhaps the hardest change of all: seeing a longer life as an opportunity and overcoming deeply engrained ageist assumptions. Currently, we underestimate the capacity of older people and the promise of our own later years.
David Bowie, a man who knew a thing or two about transitions, described ageing as “an extraordinary process whereby you become the person you always should have been”. If we can make life not just longer, but healthier, productive and engaged for longer, what’s not to like?
For most of human history, only a minority of the young and middle-aged became old. The result is that we underinvest in our later years and fail to provide the required support that a long healthy, productive and engaged life requires. Given how many of us alive can expect to become 80, have a shot at 90, and might even make it to 100, that is a problem which demands change.
Insight, involving representational change, can boost long-term memory. Here, in an fMRI study, the authors show that insight triggers stronger conceptual shifts in solution relevant brain regions and enhanced network integration, improving memory retention.
Large language models (LLMs) are remarkably versatile. They can summarize documents, generate code or even brainstorm new ideas. And now we’ve expanded these capabilities to target fundamental and highly complex problems in mathematics and modern computing.
Today, we’re announcing AlphaEvolve, an evolutionary coding agent powered by large language models for general-purpose algorithm discovery and optimization. AlphaEvolve pairs the creative problem-solving capabilities of our Gemini models with automated evaluators that verify answers, and uses an evolutionary framework to improve upon the most promising ideas.
AlphaEvolve enhanced the efficiency of Google’s data centers, chip design and AI training processes — including training the large language models underlying AlphaEvolve itself. It has also helped design faster matrix multiplication algorithms and find new solutions to open mathematical problems, showing incredible promise for application across many areas.
NASA’s Perseverance rover recently captured a photo of green auroras shining in the Martian sky for the first time. The alien light show, previously assumed to be impossible, could be visible to future astronauts.
A common assumption is that AGI won’t need any further training by humans. The reality is that AGI will surely need to further tap into human knowledge. Here’s why.
Light is all around us, essential for one of our primary senses (sight) as well as life on Earth itself. It underpins many technologies that affect our daily lives, including energy harvesting with solar cells, light-emitting-diode (LED) displays and telecommunications through fiber optic networks.
The smartphone is a great example of the power of light. Inside the box, its electronic functionality works because of quantum mechanics. The front screen is an entirely photonic device: liquid crystals controlling light. The back too: white light-emitting diodes for a flash, and lenses to capture images.
We use the word photonics, and sometimes optics, to capture the harnessing of light for new applications and technologies. Their importance in modern life is celebrated every year on 16 May with the International Day of Light.
On March 15, 2024, near the peak of the current solar cycle, the sun produced a solar flare and an accompanying coronal mass ejection (CME), a massive explosion of gas and magnetic energy that carries with it large amounts of solar energetic particles. This solar activity led to stunning auroras across the solar system, including at Mars, where NASA’s Perseverance Mars rover made history by detecting them for the first time from the surface of another planet.
“This exciting discovery opens up new possibilities for auroral research and confirms that auroras could be visible to future astronauts on Mars’ surface,” said Elise Knutsen, a postdoctoral researcher at the University of Oslo in Norway and lead author of the Science Advances study, which reported the detection.
Engineers at NASA’s Jet Propulsion Laboratory in Southern California have revived a set of thrusters aboard the Voyager 1 spacecraft that had been considered inoperable since 2004. Fixing the thrusters required creativity and risk, but the team wants to have them available as a backup to a set of active thrusters whose fuel tubes are experiencing a buildup of residue that could cause them to stop working as early as this fall.
In addition, the mission needed to ensure the availability of the long-dormant thrusters before May 4, when the Earth-bound antenna that sends commands to Voyager 1 and its twin Voyager 2 went offline for months of upgrades.