Lifeboat Foundation

Proteins are molecular machines, with flexible pieces and moving parts. Understanding how these parts move helps scientists unravel the function a protein plays in living things—and potentially how to change its effects. Biochemists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and colleagues at DOE’s Pacific Northwest National Laboratory (PNNL) have published a new example of how one such molecular machine works.

Two-dimensional materials such as graphene promise to form the basis of incredibly small and fast technologies, but this requires a detailed understanding of their electronic properties. New research demonstrates that fast electronic processes can be probed by irradiating the materials with ions first.

A molecular biologist at the USC Dornsife College of Letters, Arts and Sciences may have found a new “rule of biology.”

Floating photovoltaics (FPV), also known as floating solar farms, are photovoltaic systems that can be deployed on the sea’s surface or on other bodies of water. While their environmental impact is still the topic of debate worldwide, these systems could be highly advantageous for generating renewable energy, particularly in warm regions where available land is scarce or costly.

For quantum computers to go from research curiosities to practically useful devices, researchers need to get their errors under control. New research from Microsoft and Quantinuum has now taken a major step in that direction.

Today’s quantum computers are stuck firmly in the “noisy intermediate-scale quantum” (NISQ) era. While companies have had some success stringing large numbers of qubits together, they are highly susceptible to noise which can quickly degrade their quantum states. This makes it impossible to carry out computations with enough steps to be practically useful.

While some have claimed that these noisy devices could still be put to practical use, the consensus is that quantum error correction schemes will be vital for the full potential of the technology to be realized. But error correction is difficult in quantum computers because reading the quantum state of a qubit causes it to collapse.

AlphaFold 3 models all life’s molecules—proteins, DNA, RNA, and small molecules—and their interactions. The work could speed up science and drug discovery.

In March, we saw the launch of a “ChatGPT for music” called Suno, which uses generative AI to produce realistic songs on demand from short text prompts. A few weeks later, a similar competitor— Udio — arrived on the scene.

I’ve been working with various creative computational tools for the past 15 years, both as a researcher and a producer, and the recent pace of change has floored me. As I’ve argued elsewhere, the view that AI systems will never make “real” music like humans do should be understood more as a claim about social context than technical capability.

The argument “sure, it can make expressive, complex-structured, natural-sounding, virtuosic, original music which can stir human emotions, but AI can’t make proper music” can easily begin to sound like something from a Monty Python sketch.

Genomics is revolutionizing medicine and science, but current approaches still struggle to capture the breadth of human genetic diversity. Pangenomes that incorporate many people’s DNA could be the answer, and a new project thinks quantum computers will be a key enabler.

When the Human Genome Project published its first reference genome in 2001, it was based on DNA from just a handful of humans. While less than one percent of our DNA varies from person to person, this can still leave important gaps and limit what we can learn from genomic analyses.

That’s why the concept of a pangenome has become increasingly popular. This refers to a collection of genomic sequences from many different people that have been merged to cover a much greater range of human genetic possibilities.

If you use the web for more than just browsing (that’s pretty much everyone), chances are you’ve had your fair share of “CAPTCHA rage,” the frustration stemming from trying to discern a marginally legible string of letters aimed at verifying that you are a human. CAPTCHA, which stands for “Completely Automated Public Turing test to tell Computers and Humans Apart,” was introduced to the Internet a decade ago and has seen widespread adoption in various forms — whether using letters, sounds, math equations, or images — even as complaints about their use continue.

A large-scale Stanford study a few years ago concluded that “CAPTCHAs are often difficult for humans.” It has also been reported that around 1 in 5 visitors will leave a website rather than complete a CAPTCHA.

Continue reading “Artificial Intelligence Will Defeat CAPTCHA — How Will We Prove We’re Human Then?” »