Enlarge (credit: Caiaimage/Chris Ryan)

“Since the rise of large language models like ChatGPT there have been lots of anecdotal reports about students submitting AI-generated work as their exam assignments and getting good grades. So, we stress-tested our university’s examination system against AI cheating in a controlled experiment,” says Peter Scarfe, a researcher at the School of Psychology and Clinical Language Sciences at the University of Reading.

His team created over 30 fake psychology student accounts and used them to submit ChatGPT-4-produced answers to examination questions. The anecdotal reports were true—the AI use went largely undetected, and, on average, ChatGPT scored better than human students.

Rules of engagement

Scarfe’s team submitted AI-generated work in five undergraduate modules, covering classes needed during all three years of study for a bachelor’s degree in psychology. The assignments were either 200-word answers to short questions or more elaborate essays, roughly 1,500 words long. “The markers of the exams didn’t know about the experiment. In a way, participants in the study didn’t know they were participating in the study, but we’ve got necessary permissions to go ahead with that”, Scarfe claims.

Enlarge / Ligeia Mare, the second-largest body of liquid hydrocarbons on Titan. (credit: NASA/JPL-Caltech/ASI/Cornell)

During its T85 Titan flyby on July 24, 2012, the Cassini spacecraft registered an unexpectedly bright reflection on the surface of the lake Kivu Lacus. Its Visual and Infrared Mapping Spectrometer (VIMS) data was interpreted as a roughness on the methane-ethane lake, which could have been a sign of mudflats, surfacing bubbles, or waves.

“Our landscape evolution models show that the shorelines on Titan are most consistent with Earth lakes that have been eroded by waves,” says Rose Palermo, a coastal geomorphologist at St. Petersburg Coastal and Marine Science Center, who led the study investigating signatures of wave erosion on Titan. The evidence of waves is still inconclusive, but future crewed missions to Titan should probably pack some surfboards just in case.

Troubled seas

While waves have been considered the most plausible explanation for reflections visible in Cassini’s VIMS imagery for quite some time, other studies aimed to confirm their presence found no wave activity at all. “Other observations show that the liquid surfaces have been very still in the past, very flat,” Palermo says. “A possible explanation for this is at the time we were observing Titan, the winds were pretty low, so there weren’t many waves at that time. To confirm waves, we would need to have better resolution data,” she adds.

Enlarge (credit: OLE-CNX)

High-assay low-enriched uranium (HALEU) has been touted as the go-to fuel for powering next-gen nuclear reactors, which include the sodium-cooled TerraPower or the space-borne system powering Demonstration Rocket for Agile Cislunar Operations (DRACO). That’s because it was supposed to offer higher efficiency while keeping uranium enrichment “well below the threshold needed for weapons-grade material,” according to the US Department of Energy.

This justified huge government investments in HALEU production in the US and UK, as well as relaxed security requirements for facilities using it as fuel. But now, a team of scientists has published an article in Science that argues that you can make a nuclear bomb using HALEU.

“I looked it up and DRACO space reactor will use around 300 kg of HALEU. This is marginal, but I would say you could make one a weapon with that much,” says Edwin Lyman, the director of Nuclear Power Safety at the Union of Concerned Scientists and co-author of the paper.

Enlarge (credit: Witthaya Prasongsin)

Elon Musk, back in October 2021, tweeted that “humans drive with eyes and biological neural nets, so cameras and silicon neural nets are only way to achieve generalized solution to self-driving.” The problem with his logic has been that human eyes are way better than RGB cameras at detecting fast-moving objects and estimating distances. Our brains have also surpassed all artificial neural nets by a wide margin at general processing of visual inputs.

To bridge this gap, a team of scientists at the University of Zurich developed a new automotive object-detection system that brings digital camera performance that’s much closer to human eyes. “Unofficial sources say Tesla uses multiple Sony IMX490 cameras with 5.4-megapixel resolution that [capture] up to 45 frames per second, which translates to perceptual latency of 22 milliseconds. Comparing [these] cameras alone to our solution, we already see a 100-fold reduction in perceptual latency,” says Daniel Gehrig, a researcher at the University of Zurich and lead author of the study.

Replicating human vision

When a pedestrian suddenly jumps in front of your car, multiple things have to happen before a driver-assistance system initiates emergency braking. First, the pedestrian must be captured in images taken by a camera. The time this takes is called perceptual latency—it’s a delay between the existence of a visual stimuli and its appearance in the readout from a sensor. Then, the readout needs to get to a processing unit, which adds a network latency of around 4 milliseconds.