What mathematicians call ‘disordered collections’ can help engineers explore real-world worst-case scenarios. The simple card game Set illustrates how to predict internet and electrical grid failures.
Rigor académico, oficio periodístico
Artículos sobre AI model
Mostrando 1 - 20 de 33 artículos
People have been battling tuberculosis for thousands of years, and drug-resistant strains are on the rise. Analyzing large datasets with AI can help humanity gain a crucial edge over the disease.
From making journeys more fuel-efficient to reducing food waste.
As far back as the dawn of the internet, scholars have discussed how AI might serve to replace (or supplement) human relationships.
Microsoft Copilot can summarise meetings and even formulate arguments. But as good as that sounds, we shouldn’t blindly trust its accuracy.
The chatbot has been released to a small group of testers and some of X’s Premium+ subscribers – many of them have shared their initial thoughts.
When it comes to training high-performing AI models, the quality of the data is just as important as the quantity.
President Joe Biden has issued an executive order to regulate AI. The directives could help avoid AI doom – but they miss some key points.
AI tools are becoming increasingly personalised to cater to our every need. Will outsourcing the handling of information to AI make us ‘dumber’?
AI could kill our creativity by making us think too alike. It also forces us to question what “creativity” is, and the different forms it can take.
AI systems with deceptive capabilities could be misused in numerous ways by bad actors. Or, they may become prone to behaving in ways their creators never intended.
Media articles and influencers have helped give the impression that prompt engineering could be a ticket to a six-figure salary. The reality, as always, is a different story.
Snapchat’s AI-powered chatbot malfunctioned this week, raising questions of “sentience” among users. As AI becomes increasingly human-like, society must become AI-literate.
Creating bias-free AI systems is easier said than done. A computer scientist explains how controlling bias could lead to fairer AI.
Regardless of the input, AI image generators will have a tendency to return certain kinds of results. This is where the potential for bias arises.
Large language models have been shown to ‘hallucinate’ entirely false information, but aren’t humans guilty of the same thing? So what’s the difference between both?
I study artificial general intelligence, and I believe the ongoing fearmongering is at least partially attributable to large AI developers’ financial interests.
Dubbed the ‘godfather of AI’, Hinton’s early work helped pioneer many of the methods underlying the AI systems we see today.
if a machine can ascribe intent to the events and experiences befalling it, this raises the question of identity and what it means to be aware of oneself and others
The new tools are expected to free up space for workers by helping out with tedious and repetitive task. Here’s how it will work.
Principales colaboradores
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Professor of AI, Research Group Leader, UNSW Sydney
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Lecturer in Business Analytics, University of Sydney
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Research Scientist, Responsible Innovation, Data61, CSIRO
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Professor of Cyber Security Practice, Edith Cowan University
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PhD Student, School of Computing, Australian National University
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Sessional Academic and Visitor, School of Information Systems, Queensland University of Technology
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Monash University
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Senior Lecturer, Management, University of Tasmania
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Associate Professor in Law, UNSW Sydney
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Associate Professor – Information & Communication Technology (ICT), CQUniversity Australia
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Associate Professor of Biomedical Engineering, University of Michigan
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Philosopher, University of New England
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Professor of Mathematics, Arts & Sciences at Washington University in St. Louis
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Senior Lecturer of Computing and Security, Edith Cowan University
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Lead AI for Missions, CSIRO
