In this episode:
A newly developed method that can rapidly identify the type of bacteria causing a blood infection, and the correct antibiotics to treat it, could save clinicians time, and patient lives. Blood infections are serious, and can lead to the life-threatening condition sepsis, but conventional diagnostic methods can take days to identify the causes. This new method does away with some of the time-consuming steps, and the researchers behind it say that if it can be fully automated, it could provide results in less than a day.
Research Article: Kim et al.
The discovery of a connection between three star-forming interstellar clouds could help explain how these giant structures form, and evidence of the largest accidental methane leak ever recorded.
Research Highlight: Found: the hidden link between star-forming molecular clouds
Research Highlight: Blowout! Satellites reveal one of the largest methane leaks on record
When artificial intelligences are fed data that has itself been AI-generated, these systems quickly begin to spout nonsense responses, according to new research. Typically, large language model (LLM) AI’s are trained on human-produced text found online. However, as an increasing amount of online content is AI-generated, a team wanted to know how these systems would cope. They trained an AI to produce Wikipedia-like entries, then trained new iterations on the model on the text produced by its predecessor. Quickly the outputs descended into gibberish, which highlights the dangers of the Internet becoming increasingly full of AI-generated text.
Research Article: Shumailov et al.
How psilocybin — the hallucinogenic compound found in magic mushrooms — resets communication between brain regions, and the surprise cancellation of a NASA Moon mission.
