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Category: mathematics – Page 32

Google Launches Gemini 2.0 Pro LLM

In today’s AI news, Google launched its much-anticipated new flagship AI model, Gemini 2.0 Pro Experimental, on Wednesday. The announcement was part of a series of other AI model releases. The company is also making its reasoning model, Gemini 2.0 Flash Thinking, available in the Gemini app.

In other advancements, LinkedIn is testing a new job-hunting tool that uses a custom large language model to comb through huge quantities of data to help people find prospective roles. The company believes that artificial intelligence will help users unearth new roles they might have missed in the typical search process.

S Deep Research feature, which can autonomously browse the web and create research reports. ‘ + s up from hitting $50 million ARR, or the yearly value of last month s case for why they are the best positioned to take over TikTok And, in this episode, a16z Partner Marc Andrusko chats with Mastercard’s Chief AI and Data Officer Greg Ulrich about Mastercard’s long history of using AI, the opportunities (and potential risks) associated with integrating generative AI into fraud detection, determining what tech to employ based on use cases, and the best advice he’s ever gotten.

Then, power your AI transformation with an insightful keynote from Scott Guthrie, Executive Vice President, Cloud + AI Group at Microsoft, and other industry experts. Watch this keynote presentation from NYC stop on Microsoft’s AI Tour.

We close out with this insightful discussion with Malcolm Gladwell and Ric Lewis, SVP of Infrastructure at IBM. Learn how hardware capabilities enable the matrix math behind large language models and how AI is transforming industries—from banking to your local coffee shop.

Thats all for today, but AI is moving fast — like, comment, and subscribe for more AI news! Please vote for me in the Entrepreneur of Impact Competition today! Thank you for supporting my partners and I — it’s how I keep Neural News Network free.

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New AI Tool Detects Fake News with 99% Accuracy

A tool developed by Keele University researchers has been shown to help detect fake news with an impressive 99% level of accuracy, offering a vital resource in combating online misinformation.

The researchers Dr. Uchenna Ani, Dr. Sangeeta Sangeeta, and Dr. Patricia Asowo-Ayobode from Keele’s School of Computer Science and Mathematics, used a number of different machine learning techniques to develop their model, which can scan news content to give a judgment of whether a news source is trustworthy and genuine or not.

The method developed by the researchers uses an “ensemble voting” technique, which combines the predictions of multiple different machine learning models to give an overall score.

Barbecue grill approach helps researchers understand puzzling Rayleigh–Bloch waves

So-called Rayleigh–Bloch waves can release an enormous amount of energy that can damage technical systems under certain circumstances. They only exist below a precisely defined cut-off frequency; above this, they disappear abruptly. Strangely enough, however, there are isolated high frequencies at which they can also be detected.

Mathematicians from the Universities of Augsburg and Adelaide have recently proposed an explanation for this puzzling phenomenon. Together with researchers from the University of Exeter, they have now been able to prove experimentally that their theory is indeed correct. The study has just been published in the journal Communications Physics.

Suppose you had a gigantic barbecue grill that could easily accommodate several hundreds of sausages. Then, you could not only use it to invite your children’s entire school to a barbecue. The numerous stainless steel struts aligned parallel to each other are also ideal for generating Rayleigh–Bloch waves.

Quantum Systems Obey Second Law Of Thermodynamics

The fundamental principles of thermodynamics have long been a cornerstone of our understanding of the physical world, with the second law of thermodynamics standing as a testament to the inexorable march towards disorder and entropy that governs all closed systems. However, the realm of quantum physics has traditionally appeared to defy this notion, with mathematical formulations suggesting that entropy remains constant in these systems.

Recent research has shed new light on this seeming paradox, revealing that the apparent contradiction between quantum mechanics and thermodynamics can be reconciled through a nuanced understanding of entropy itself. By adopting a definition of entropy that is compatible with the principles of quantum physics, specifically the concept of Shannon entropy, scientists have demonstrated that even isolated quantum systems will indeed evolve towards greater disorder over time, their entropy increasing as the uncertainty of measurement outcomes grows.

This breakthrough insight has far-reaching implications for our comprehension of the interplay between quantum theory and thermodynamics, and is poised to play a pivotal role in the development of novel quantum technologies that rely on the manipulation of complex many-particle systems.

The Potential Existence of Paraparticles, Once Considered “Impossible,” Now Mathematically Proven

For decades, the realm of particle physics has been governed by two major categories: fermions and bosons. Fermions, like quarks and leptons, make up matter, while bosons, such as photons and gluons, act as force carriers. These classifications have long been thought to be the limits of particle behavior. However, a breakthrough has recently changed this understanding.

Researchers have mathematically proven the existence of paraparticles, a theoretical type of particle that doesn’t fit neatly into the traditional fermion or boson categories. These exotic particles were once deemed impossible, defying the conventional laws of physics. Now, thanks to advanced mathematical equations, scientists have demonstrated that paraparticles can exist without violating known physical constraints.

The implications of this discovery could be far-reaching, especially in areas like quantum computing. Paraparticles could offer new possibilities in how we understand the universe at its most fundamental level. While the discovery is still in its early stages, it provides a new tool for physicists to explore more complex systems, potentially unlocking new technologies in the future.

How To Solve Any Problem Using Enrico Fermi’s Back-Of-The-Envelope Math (And Some Common Sense)

The real magic of Fermi problems lies in their imperfection. They remind us that it’s okay to be wrong — as long as you’re thoughtfully wrong. “There are no wrong answers,” says Funk. “It’s about the process.”

No single formula exists. Yet each problem invites the same approach: break it down, make realistic (or at least consistent) assumptions, and trust your critical thinking. “No Wrong Answers” is a common Fermi problem refrain because even if your math arrives at a slightly off result, you’ve shown how you reason. And that, ultimately, is the real answer.

So, the next time you’re faced with a seemingly impossible question — whether it’s How many grains of sand are on all the world’s beaches? or How long would it take to drive to the moon? — grab a napkin and a pen. Start breaking it down. Make some guesses. Do some math. You might just surprise yourself with how close you can get.

Scientists map the mathematics behind how we create and innovate

A new study in Nature Communications explores the dynamics of higher-order novelties, identifying fascinating patterns in how we combine existing elements to create novelty, potentially reshaping our understanding of human creativity and innovation.

Novelties—a common part of human life—refer to one of two things. The first is the discovery of a single item, like a place, song, or an artist. The second covers discoveries new to everyone, such as technological developments or drug discoveries.

The researchers in this study aimed to understand how both kinds of novelties emerge. The team was led by Prof. Vito Latora from the Queen Mary University of London, who spoke to Phys.org about the work.

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