Toggle light / dark theme

Amid heated debates about the potential pitfills of artificial intelligence, the technology has finally taken a form we can probably all get behind — an “AI granny” created expressly to waste scammers’ time.

British telecom company Virgin Media O2 on Thursday introduced Daisy, a custom-made human-like chabot that answers calls in real time, keeping fraudsters on the phone as long as possible in a bid to annoy and frustrate them, just as they do to consumers worldwide. Daisy (that’s “dAIsy”) automates the practice of “scambaiting,” which involves people posing as potential victims to squander scammers’ time and resources, publicly expose their wily ways, gather information useful to law enforcement and even confuse the con artists’ devices.

Daisy, newly dubbed O2’s “head of scammer relations,” impersonates an older adult, making her part of a demographic that’s particularly vulnerable to scams. Unlike human scambaiters who need to sleep and shower once in a while, Daisy can spend all day and night on the phone with swindlers. “While they’re busy talking to me they can’t be scamming you, and let’s face it, dear, I’ve got all the time in the world,” Daisy says in the introductory video from O2 embedded below. The video personifies her as a photorealistic AI-generated woman with gray hair, glasses and pearls talking on a pink landline.

A team of astrophysicists, led by our Institute for Computational Cosmology, have developed a new model that could estimate how likely it is for intelligent life to emerge in our Universe and beyond.

In the 1960s, American astronomer Dr Frank Drake came up with an equation to calculate the number of detectable extraterrestrial civilisations in our Milky Way galaxy.

More than 60 years on, researchers at Durham, the University of Edinburgh and the Université de Genève, have produced a new model based on the conditions created by the acceleration of the Universe’s expansion and the amount of stars formed instead.

Join us at ploutos.dev.

#AI #topology #language #computation #neuroscience


Researchers have long observed that neurons in the brain tend to be organized in clusters, with neighboring neurons often sharing similar functions. This phenomenon is also seen in the brain’s language system, where certain areas respond to different aspects of language, such as syntax (sentence structure) or semantics (meaning). However, the exact mechanisms behind this organization remain a mystery.

In an attempt to better understand how the brain organizes language processing, the researchers developed TopoLM, a new type of AI language model inspired by the brain’s spatial layout. Unlike traditional language models, TopoLM arranges its processing units in a two-dimensional space, mimicking how neurons are arranged in the brain. It combines a standard language task (predicting the next word in a sentence) with an additional goal: encouraging units that are close together in space to also have similar functions, creating clusters of units that process similar linguistic information.

The risk for thrombosis on equipment within coronary arteries during PCI – and the potential dangerous complications – has led to nearly 50 years of targeted research on the mechanisms of normal and pathologic thrombosis. This research has in turn led to the development of blood-thinning drug treatments to prevent thrombosis during and after PCI. However, the blood thinning (‘anti-thrombotic’) therapies can also lead to life-threatening excessive bleeding. Research to identify the optimal balance of anti-thrombotic drugs that minimises both pathologic thrombosis and excessive bleeding continues through today.

Dr Scott Denardo at Duke University Medical Center in the USA has modelled the behaviour of platelets inside blood vessels and near medical device surfaces. Some of his observations are just now entering the contemporary understanding of thrombosis. Denardo believes that applying these observations can refine existing anti-thrombotic therapies to improve their safety (less bleeding) while not compromising their effectiveness (preventing thrombosis on PCI equipment, including stents).

Team develops simulation algorithms for safer, greener, and more aerodynamic aircraft.


Ice buildup on aircraft wings and fuselage occurs when atmospheric conditions conducive to ice formation are encountered during flight, presenting a critical area of focus for their research endeavors.

Ice accumulation on an aircraft during flight poses a significant risk, potentially impairing its performance and, in severe cases, leading to catastrophic consequences.

Fernández’s laboratory is dedicated to the development of algorithms and software tools aimed at comprehensively understanding these processes and leveraging this knowledge to enhance future aircraft designs, thereby mitigating potential negative outcomes.