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monthly digest

AIhub monthly digest: June 2026 – biodiversity, resource allocation, and color metaphors

  16 Jun 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

Statistical or embodied? Comparing people and LLMs in their processing of color metaphors: an interview with Douglas Guilbeault

  09 Jun 2026
We learn what implications color metaphors and synaesthesia have for human and AI cognition.

Design tweaks promote responsible AI use for environmental protection, research shows

  03 Jun 2026
Systems that ask users to pause to consider AI’s energy consumption and environmental impacts are likely to reduce unnecessary AI use

An AI solution to an 80‑year‑old problem has shocked mathematicians

  02 Jun 2026
An OpenAI model has been used to find a counterexample to a famous conjecture made by legendary Hungarian mathematician Paul Erdős.
monthly digest

AIhub monthly digest: May 2026 – AI for science, the lottery ticket hypothesis, and world models

  28 May 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

You probably wouldn’t notice if an AI chatbot slipped ads into its responses

  27 May 2026
Research suggests AI chatbots could easily be used for covert advertising to manipulate their human users.

Why the world’s banks are so worried about Anthropic’s latest AI model

  21 May 2026
The finance world’s concern rests on the impressive cyber capabilities of a product called Mythos.

Embracing empiricism – from the lottery hypothesis to creating real-world impact: an interview with Jonathan Frankle

  20 May 2026
Jonathan Frankle discusses empiricism, making an impact, and the legacy of his lottery ticket hypothesis.

A faster way to estimate AI power consumption

  19 May 2026
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.

Introducing ARFBench: A time series question-answering benchmark based on real incidents

  18 May 2026
To resolve system failures, engineers must troubleshoot outages quickly.

Does ‘federated unlearning’ in AI improve data privacy, or create a new cybersecurity risk?

  15 May 2026
As the capacity of AI systems increases apace, so do concerns about the privacy of user data.

Reflections from #AIES2025

and   14 May 2026
We reflect on AIES 2025, outlining a discussion session on LLMs for clinical usage and human rights.

Deep learning-powered biochip to detect genetic markers

System can detect extremely small amounts of microRNAs, genetic markers linked to diseases such as heart disease.

Half of AI health answers are wrong even though they sound convincing – new study

  12 May 2026
Imagine you have just been diagnosed with early-stage cancer and, before your next appointment, you type a question into an AI chatbot.

Gradient-based planning for world models at longer horizons

  11 May 2026
What were the problems that motivated this project and what was the approach to address them?

It’s tempting to offload your thinking to AI. Cognitive science shows why that’s a bad idea

  08 May 2026
Increased offloading to new tools has raised the fear that people will become overly reliant on AI.

AI for Science – from cosmology to chemistry

  01 May 2026
How AI is transforming science, from a day conference at the Royal Society
monthly digest

AIhub monthly digest: April 2026 – machine learning for particle physics, AI Index Report, and table tennis

  30 Apr 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

#AAAI2026 invited talk: Yolanda Gil on improving workflows with AI

  28 Apr 2026
Former AAAI president on using AI to help communities of scientists better streamline their research.

As a ‘book scientist’ I work with microscopes, imaging technologies and AI to preserve ancient texts

  23 Apr 2026
Using an array of technologies to recover, understand and preserve many valuable ancient texts.

A model for defect identification in materials

  20 Apr 2026
A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.

‘Probably’ doesn’t mean the same thing to your AI as it does to you

  17 Apr 2026
Are you sure you and the AI chatbot you’re using are on the same page about probabilities?

Water flow in prairie watersheds is increasingly unpredictable — but AI could help

  13 Apr 2026
In recent years, the Prairies have seen bigger swings in climate conditions — very wet years followed by very dry ones.

Identifying interactions at scale for LLMs

  10 Apr 2026
Model behavior is rarely the result of isolated components; rather, it emerges from complex dependencies and patterns.

#AAAI2026 invited talk: machine learning for particle physics

  01 Apr 2026
How is ML used in the search for new particles at CERN?
monthly digest

AIhub monthly digest: March 2026 – time series, multiplicity, and the history of RoboCup

  31 Mar 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

Information-driven design of imaging systems

  23 Mar 2026
Framework that enables direct evaluation and optimization of imaging systems based on their information content.

Machine learning framework to predict global imperilment status of freshwater fish

  20 Mar 2026
“With our model, decision makers can deploy resources in advance before a species becomes imperiled.”

A principled approach for data bias mitigation

  18 Mar 2026
Find out more about work presented at AIES 2025 which proposes a new way to measure data bias, along with a mitigation algorithm with mathematical guarantees.

An AI image generator for non-English speakers

  17 Mar 2026
"Translations lose the nuances of language and culture, because many words lack good English equivalents."

AI chatbots can effectively sway voters – in either direction

  12 Mar 2026
A short interaction with a chatbot can meaningfully shift a voter’s opinion about a presidential candidate or proposed policy.

What the Moltbook experiment is teaching us about AI

An experimental social media platform where only AI bots can post reveals surprising lessons about artificial intelligence behaviour and safety.

The malleable mind: context accumulation drives LLM’s belief drift

  09 Mar 2026
LLMs change their "beliefs" over time, depending on the data they are given.

The greatest risk of AI in higher education isn’t cheating – it’s the erosion of learning itself

  03 Mar 2026
Will AI hollow out the pipeline of students, researchers and faculty that is the basis of today’s universities?
monthly digest

AIhub monthly digest: February 2026 – collective decision making, multi-modal learning, and governing the rise of interactive AI

  27 Feb 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

Relational neurosymbolic Markov models

and   19 Feb 2026
Relational neurosymbolic Markov models make deep sequential models logically consistent, intervenable and generalisable





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