Self-driving labs can perform experiments thousands of times faster than a human and they don’t need to sleep. That means more science in less time, but many questions remain, says Alex Wilkins
By Alex Wilkins
According to Candy, the rise of AI would instead put a premium on soft skills like critical and creative thinking.
“Questioning, creativity skills, and innovation are going to be hugely important because I think AI’s going to free up more capacity for creative thought processes,” he told Fortune earlier.
It’s not just jobs in tech, though. Candy said that advances in AI image-generation technology could also affect those working in the arts.
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Continue reading “The Attribute of Light Science Still Can’t Explain” »
This chapter gives an overview of the projects facing a science of consciousness. Such a science must integrate third-person data about behavior and brain processes with first-person data about conscious experience. Empirical projects for integrating these data include those of contrasting conscious and unconscious processes, investigating the contents of consciousness, finding neural correlates of consciousness, and eventually inferring underlying principles connecting consciousness with physical processes. These projects are discussed with reference to current experimental research on consciousness. Some obstacles that a science of consciousness faces are also discussed.
The Paulding Light, a perplexing glow in the Michigan sky, has fueled folklore with its eerie nightly appearances since the 1960s. What was once thought to be a ghostly signal has turned into a case study for scientific inquiry. A team of Michigan Tech students, led by Jeremy Bos, a PhD candidate in electrical engineering, undertook a methodical investigation to expose the truth behind the spectral luminance that intrigued both locals and visitors in Michigan’s Upper Peninsula.
Their rigorous scientific approach involved telescopes, spectrographs, and atmospheric modeling, which demystified the paranormal claims. By observing the phenomenon through a telescope, the researchers identified the lights as nothing more than the headlights and taillights of vehicles on a distant stretch of US Highway 45. This was further supported by spectral analysis, confirming the automotive origin of the lights. The team’s findings pointed to atmospheric conditions and the geography of the Paulding area, which caused the vehicle lights to refract and create the illusion of the unexplained Paulding Light.
Despite the logical explanations provided by these dedicated students, the Paulding Light’s allure remains undiminished. The legend continues to attract those drawn to the supernatural, demonstrating the human fascination with mystery over the mundane. The Paulding Light stands as a symbol of our enduring attraction to the unexplained, a reminder that sometimes, even when the truth is revealed, the legend never dies.
Quanta Magazine’s full list of the major computer science discoveries from 2023.
In 2023, artificial intelligence dominated popular culture — showing up in everything from internet memes to Senate hearings. Large language models such as those behind ChatGPT fueled a lot of this excitement, even as researchers still struggled to pry open the “black box” that describes their inner workings. Image generation systems also routinely impressed and unsettled us with their artistic abilities, yet these were explicitly founded on concepts borrowed from physics.
Continue reading “The Biggest Discoveries in Computer Science in 2023” »
Occam’s razor—the principle that when faced with competing explanations, we should choose the simplest that fits the facts—is not just a tool of science. Occam’s razor is science, insists a renowned molecular geneticist from the University of Surrey.
In a paper published in the Annals of the New York Academy of Sciences, Professor Johnjoe McFadden argues Occam’s razor—attributed to the Surrey-born Franciscan friar William of Occam (1285–1347)—is the only feature that differentiates science from superstition, pseudoscience or fake news.
Professor McFadden said, “What is science? The rise of issues such as vaccine hesitancy, climate skepticism, alternative medicine, and mysticism reveals significant levels of distrust or misunderstanding of science among the general public. The ongoing COVID inquiry also highlights how scientific ignorance extends into the heart of government. Part of the problem is that most people, even most scientists, have no clear idea of what science is actually about.”
The discovery of stars with their outer layers of hydrogen stripped by companions fills a glaring hole in our understanding of supernovas and binary systems with colliding neutron stars.
A research team has revealed that ultrashort laser pulses can magnetize iron alloys, a discovery with significant potential for applications in magnetic sensor technology, data storage, and spintronics.
To magnetize an iron nail, one simply has to stroke its surface several times with a bar magnet. Yet, there is a much more unusual method: A team led by the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) discovered some time ago that a certain iron alloy can be magnetized with ultrashort laser pulses. The researchers have now teamed up with the Laserinstitut Hochschule Mittweida (LHM) to investigate this process further. They discovered that the phenomenon also occurs with a different class of materials – which significantly broadens potential application prospects. The working group presents its findings in the scientific journal Advanced Functional Materials.
Breakthrough Discovery in Magnetization.
A team of computer scientists at Google’s DeepMind project in the U.K., working with a colleague from the University of Wisconsin-Madison and another from Université de Lyon, has developed a computer program that combines a pretrained large language model (LLM) with an automated “evaluator” to produce solutions to problems in the form of computer code.
In their paper published in the journal Nature, the group describes their ideas, how they were implemented and the types of output produced by the new system.
Researchers throughout the scientific community have taken note of the things people are doing with LLMs, such as ChatGPT, and it has occurred to many of them that LLMs might be used to help speed up the process of scientific discovery. But they have also noted that for that to happen, a method is required to prevent confabulations, answers that seem reasonable but are wrong—they need output that is verifiable. To address this problem, the team working in the U.K. used what they call an automated evaluator to assess the answers given by an LLM.
