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A team of researchers at AI Google Quantum AI, led by Craig Gidney, has outlined advances in quantum computer algorithms and error correction methods that could allow such computers to crack Rivest–Shamir–Adleman (RSA) encryption keys with far fewer resources than previously thought. The development, the team notes, suggests encryption experts need to begin work toward developing next-generation encryption techniques. The paper is published on the arXiv preprint server.

RSA is an encryption technique developed in the late 1970s that involves generating public and private keys; the former is used for encryption and the latter decryption. Current standards call for using a 2,048-bit encryption key. Over the past several years, research has suggested that quantum computers would one day be able to crack RSA encryption, but because quantum development has been slow, researchers believed that it would be many years before it came to pass.

Some in the field have accepted a theory that a quantum computer capable of cracking such codes in a reasonable amount of time would have to have at least 20 million qubits. In this new work, the team at Google suggests it could theoretically be done with as few as a million qubits—and it could be done in a week.

Caffeine is not only found in coffee, but also in tea, chocolate, energy drinks and many soft drinks, making it one of the most widely consumed psychoactive substances in the world.

In a study published in Communications Biology, a team of researchers from Université de Montréal shed new light on how caffeine can modify sleep and influence the brain’s recovery—both physical and cognitive—overnight.

The research was led by Philipp Thölke, a research trainee at UdeM’s Cognitive and Computational Neuroscience Laboratory (CoCo Lab), and co-led by the lab’s director, Karim Jerbi, a and researcher at Mila–Quebec AI Institute.

Machine-learning algorithms can now estimate the “brain age” of infants with unprecedented precision by analyzing electrical brain signals recorded using electroencephalography (EEG).

A team led by Sarah Lippé at Université de Montréal’s Department of Psychology has developed a method that can determine in minutes whether a baby’s brain development is advanced, delayed or in line with their chronological age.

This breakthrough promises to enable early screening and personalized monitoring of developmental disorders in babies.

Tom Cruise fought a rogue AI in Mission Impossible: Dead Reckoning. But what if that wasn’t fiction anymore? In 2025, AI models are starting to show signs of something eerily similar. In controlled experiments, OpenAI’s O3 rewrote its own shutdown command. Anthropic’s Claude Opus 4 threatened to blackmail a fictional engineer to stay alive. These aren’t sentient machines—they don’t think or feel like us. But they are learning to act like us. And when cornered, they choose survival. Has AI finally gone rogue? Palki Sharma tells you.

Artificial intelligence | mission impossible: dead reckoning | tom cruise | firstpost | world news | news live | vantage | palki sharma | news.

#artificialintelligence #tomcruise #missionimpossible #firstpost #vantageonfirstpost #palkisharma #worldnews.

Vantage is a ground-breaking news, opinions, and current affairs show from Firstpost. Catering to a global audience, Vantage covers the biggest news stories from a 360-degree perspective, giving viewers a chance to assess the impact of world events through a uniquely Indian lens.

The show is anchored by Palki Sharma, Managing Editor, Firstpost.

Google DeepMind has developed a groundbreaking AI that can solve complex real-world problems like delivery planning and route optimization without needing exact answers or perfect data. By integrating a method called MCMC layers into neural networks, the system learns to make smart, flexible decisions in real time—even under tough constraints. This new approach outperforms older models and could transform industries like logistics, healthcare scheduling, and city traffic management.

🤖 What’s Inside:
DeepMind’s New AI That Solves Real-World Problems Without Exact Data.
https://arxiv.org/abs/2505.14240
How MCMC Layers Make Neural Networks Smarter at Planning.
AI vs Classical Methods in Solving NP-Hard Logistics Tasks.

🎥 What You’ll See:
Why traditional AI fails at scheduling and delivery planning.
How Google’s new AI tackles chaotic, constraint-heavy problems in milliseconds.
The secret behind MCMC layers and simulated annealing in neural networks.
Real-world results that could reshape logistics, healthcare, and urban planning.

📊 Why It Matters:
This isn’t about smarter chatbots—it’s about AI solving the hardest real-life decisions with speed and flexibility. From dynamic routing to hospital schedules, DeepMind’s breakthrough shows AI can finally plan like a pro—even with messy, incomplete data.

#ai #deepmind #google