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Large language models such as OpenAI’s o1 have electrified the debate over achieving artificial general intelligence, or AGI. But they are unlikely to reach this milestone on their own. [ABSTRACT FROM AUTHOR]

Proportional representation or winner takes all? Here’s how researchers compare the merits of contrasting voting methods. [ABSTRACT FROM AUTHOR]

The advent of LLMs has reopened a debate about the limits of machine intelligence — and requires new benchmarks of what reasoning consists of. [ABSTRACT FROM AUTHOR]

Roger Penrose, now 93, never shied away from wild ideas and the ensuring debates. The first full-length biography reveals more about the mathematician and the man. [ABSTRACT FROM AUTHOR]

Scientists worry that ill-informed use of artificial intelligence is driving a deluge of unreliable or useless research. [ABSTRACT FROM AUTHOR]

Researchers, educators and companies are experimenting with ways to turn flawed but famous large language models into trustworthy, accurate ‘thought partners’ for learning. [ABSTRACT FROM AUTHOR]

Survey highlights disparity between academic and industry scientists’ access to computing power needed to train machine-learning models. [ABSTRACT FROM AUTHOR]

Deceptive videos and images created using generative AI could sway elections, crash stock markets and ruin reputations. Researchers are developing methods to limit their harm. [ABSTRACT FROM AUTHOR]

A Nature survey finds that scientists are concerned, as well as excited, by the increasing use of artificial-intelligence tools in research. [ABSTRACT FROM AUTHOR]

Large language models mimic human chatter, but scientists disagree on their ability to reason. [ABSTRACT FROM AUTHOR]

Cryptographers are preparing for new quantum computers that will break their ciphers. [ABSTRACT FROM AUTHOR]

As generative AI models grow larger and more powerful, some scientists advocate for leaner, more energy-efficient systems. [ABSTRACT FROM AUTHOR]

Mathematicians leading decolonization efforts say that building knowledge-sharing partnerships with communities is key. [ABSTRACT FROM AUTHOR]

Mathematicians and their collaborators discuss the joys and challenges of working together on projects in science and the arts. [ABSTRACT FROM AUTHOR]

Fifty years ago, an equation called the Black–Scholes formula revolutionized finance, leading to a rapid growth of markets and stimulating quantitatively oriented minds. But, with time, its simplicity became a liability — and yet its legacy persists. Fifty years of the Black–Scholes equation. [ABSTRACT FROM AUTHOR]

To avert privacy breaches, scams and environmental damage, governments and central banks need to know how best to regulate this financial frontier. [ABSTRACT FROM AUTHOR]

Researchers are excited but apprehensive about the latest advances in artificial intelligence. [ABSTRACT FROM AUTHOR]

The quantum computer revolution could break encryption — but more-secure algorithms can safeguard privacy. [ABSTRACT FROM AUTHOR]

As the FIFA tournament kicks off, researchers are showing their skills to help soccer coaches develop players and tactics. [ABSTRACT FROM AUTHOR]

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.