Top Mathematics discussions

NishMath

@machinelearning.apple.com //
Apple researchers have released a new study questioning the capabilities of Large Reasoning Models (LRMs), casting doubt on the industry's pursuit of Artificial General Intelligence (AGI). The research paper, titled "The Illusion of Thinking," reveals that these models, including those from OpenAI, Google DeepMind, Anthropic, and DeepSeek, experience a 'complete accuracy collapse' when faced with complex problems. Unlike existing evaluations primarily focused on mathematical and coding benchmarks, this study evaluates the reasoning traces of these models, offering insights into how LRMs "think".

Researchers tested various models, including OpenAI's o3-mini, DeepSeek-R1, and Claude 3.7 Sonnet, using puzzles like the Tower of Hanoi, Checker Jumping, River Crossing, and Blocks World. These environments allowed for the manipulation of complexity while maintaining consistent logical structures. The team discovered that standard language models surprisingly outperformed LRMs in low-complexity scenarios, while LRMs only demonstrated advantages in medium-complexity tasks. However, all models experienced a performance collapse when faced with highly complex tasks.

The study suggests that the so-called reasoning of LRMs may be more akin to sophisticated pattern matching, which is fragile and prone to failure when challenged with significant complexity. Apple's research team identified three distinct performance regimes: low-complexity tasks where standard models outperform LRMs, medium-complexity tasks where LRMs show advantages, and high-complexity tasks where all models collapse. Apple has begun integrating powerful generative AI into its own apps and experiences. The new Foundation Models framework gives app developers access to the on-device foundation language model.

Recommended read:
References :
  • THE DECODER: LLMs designed for reasoning, like Claude 3.7 and Deepseek-R1, are supposed to excel at complex problem-solving by simulating thought processes.
  • machinelearning.apple.com: Apple machine learning discusses Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
  • PPC Land: PPC Land reports on Apple study exposes fundamental limits in AI reasoning models through puzzle tests.
  • the-decoder.com: The Decoder covers Apple's study, highlighting the limitation in thinking abilities of reasoning models.
  • felloai.com: In a breakthrough paper, Apple researchers reveal the uncomfortable truth about large reasoning models (LRMs): their internal “thought processes” might be nothing more than performative illusions.
  • Gadgets 360: Apple Claims AI Reasoning Models Suffer From ‘Accuracy Collapse’ When Solving Complex Problems
  • futurism.com: Apple Researchers Just Released a Damning Paper That Pours Water on the Entire AI Industry
  • The Register - Software: Apple AI boffins puncture AGI hype as reasoning models flail on complex planning
  • www.theguardian.com: Advanced AI suffers ‘complete accuracy collapse’ in face of complex problems, study finds
  • chatgptiseatingtheworld.com: Apple researchers cast doubt on AI reasoning models of other companies
  • www.livescience.com: AI reasoning models aren’t as smart as they were cracked up to be, Apple study claims
  • www.computerworld.com: Apple warns: GenAI still isn’t very smart
  • Fello AI: Apple's research paper, "The Illusion of Thinking," argues that large reasoning models face a complete accuracy collapse beyond certain complexities, highlighting limitations in their reasoning capabilities.
  • WIRED: Apple's research paper challenges the claims of significant reasoning capabilities in current AI models, particularly those relying on pattern matching instead of genuine understanding.
  • Analytics Vidhya: Apple Exposes Reasoning Flaws in o3, Claude, and DeepSeek-R1
  • www.itpro.com: ‘A complete accuracy collapse’: Apple throws cold water on the potential of AI reasoning – and it's a huge blow for the likes of OpenAI, Google, and Anthropic
  • www.tomshardware.com: Apple says generative AI cannot think like a human - research paper pours cold water on reasoning models
  • Digital Information World: Apple study questions AI reasoning models in stark new report
  • www.theguardian.com: A research paper by Apple has taken the AI world by storm, all but eviscerating the popular notion that large language models (LLMs, and their newest variant, LRMs, large reasoning models) are able to reason reliably.
  • AI Alignment Forum: Researchers at Apple released a paper provocatively titled “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexityâ€, which “challenge[s] prevailing assumptions about [language model] capabilities and suggest that current approaches may be encountering fundamental barriers to generalizable reasoningâ€.
  • Ars OpenForum: New Apple study challenges whether AI models truly “reason†through problems

@www.linkedin.com //
Nvidia's Blackwell GPUs have achieved top rankings in the latest MLPerf Training v5.0 benchmarks, demonstrating breakthrough performance across various AI workloads. The NVIDIA AI platform delivered the highest performance at scale on every benchmark, including the most challenging large language model (LLM) test, Llama 3.1 405B pretraining. Nvidia was the only vendor to submit results on all MLPerf Training v5.0 benchmarks, highlighting the versatility of the NVIDIA platform across a wide array of AI workloads, including LLMs, recommendation systems, multimodal LLMs, object detection, and graph neural networks.

The at-scale submissions used two AI supercomputers powered by the NVIDIA Blackwell platform: Tyche, built using NVIDIA GB200 NVL72 rack-scale systems, and Nyx, based on NVIDIA DGX B200 systems. Nvidia collaborated with CoreWeave and IBM to submit GB200 NVL72 results using a total of 2,496 Blackwell GPUs and 1,248 NVIDIA Grace CPUs. The GB200 NVL72 systems achieved 90% scaling efficiency up to 2,496 GPUs, improving time-to-convergence by up to 2.6x compared to Hopper-generation H100.

The new MLPerf Training v5.0 benchmark suite introduces a pretraining benchmark based on the Llama 3.1 405B generative AI system, the largest model to be introduced in the training benchmark suite. On this benchmark, Blackwell delivered 2.2x greater performance compared with the previous-generation architecture at the same scale. Furthermore, on the Llama 2 70B LoRA fine-tuning benchmark, NVIDIA DGX B200 systems, powered by eight Blackwell GPUs, delivered 2.5x more performance compared with a submission using the same number of GPUs in the prior round. These performance gains highlight advancements in the Blackwell architecture and software stack, including high-density liquid-cooled racks, fifth-generation NVLink and NVLink Switch interconnect technologies, and NVIDIA Quantum-2 InfiniBand networking.

Recommended read:
References :
  • NVIDIA Newsroom: NVIDIA Blackwell Delivers Breakthrough Performance in Latest MLPerf Training Results
  • NVIDIA Technical Blog: NVIDIA Blackwell Delivers up to 2.6x Higher Performance in MLPerf Training v5.0
  • IEEE Spectrum: Nvidia’s Blackwell Conquers Largest LLM Training Benchmark
  • NVIDIA Technical Blog: Reproducing NVIDIA MLPerf v5.0 Training Scores for LLM Benchmarks
  • AI News | VentureBeat: Nvidia says its Blackwell chips lead benchmarks in training AI LLMs
  • MLCommons: New MLCommons MLPerf Training v5.0 Benchmark Results Reflect Rapid Growth and Evolution of the Field of AI
  • www.aiwire.net: MLPerf Training v5.0 results show Nvidia’s Blackwell GB200 accelerators sprinting through record time-to-train scores.
  • blogs.nvidia.com: NVIDIA is working with companies worldwide to build out AI factories — speeding the training and deployment of next-generation AI applications that use the latest advancements in training and inference. The NVIDIA Blackwell architecture is built to meet the heightened performance requirements of these new applications. In the latest round of MLPerf Training — the
  • mlcommons.org: New MLCommons MLPerf Training v5.0 Benchmark Results Reflect Rapid Growth and Evolution of the Field of AI
  • NVIDIA Newsroom: NVIDIA RTX Blackwell GPUs Accelerate Professional-Grade Video Editing
  • ServeTheHome: The new MLPerf Training v5.0 are dominated by NVIDIA Blackwell and Hopper results, but we also get AMD Instinct MI325X on a benchmark as well
  • AIwire: This is a news article on nvidia Blackwell GPUs lift Nvidia to the top of MLPerf Training Rankings
  • www.servethehome.com: MLPerf Training v5.0 is Out
  • IEEE Spectrum: Nvidia’s Blackwell Conquers Largest LLM Training Benchmark

Emilia David@AI News | VentureBeat //
References: bsky.app , the-decoder.com , Maginative ...
OpenAI has recently launched its newest reasoning model, o3-pro, making it available to ChatGPT Pro and Team subscribers, as well as through OpenAI’s API. Enterprise and Edu subscribers will gain access the following week. The company touts o3-pro as a significant upgrade, emphasizing its enhanced capabilities in mathematics, science, and coding, and its improved ability to utilize external tools.

OpenAI has also slashed the price of o3 by 80% and o3-pro by 87%, positioning the model as a more accessible option for developers seeking advanced reasoning capabilities. This price adjustment comes at a time when AI providers are competing more aggressively on both performance and affordability. Experts note that evaluations consistently prefer o3-pro over the standard o3 model across all categories, especially in science, programming, and business tasks.

O3-pro utilizes the same underlying architecture as o3, but it’s tuned to be more reliable, especially on complex tasks, with better long-range reasoning. The model supports tools like web browsing, code execution, vision analysis, and memory. While the increased complexity can lead to slower response times, OpenAI suggests that the tradeoff is worthwhile for the most challenging questions "where reliability matters more than speed, and waiting a few minutes is worth the tradeoff.”

Recommended read:
References :
  • bsky.app: The OpenAI API is back to running at 100% again, plus we dropped o3 prices by 80% and launched o3-pro - enjoy!
  • the-decoder.com: OpenAI lowered the price of its o3 language model by 80 percent, CEO Sam Altman said.
  • AI News | VentureBeat: OpenAI released the latest in its o-series of reasoning model that promises more reliable and accurate responses for enterprises.
  • Maginative: OpenAI’s new o3-pro model is now available in ChatGPT and the API, offering top-tier performance in math, science, and coding—at a dramatically lower price.
  • THE DECODER: OpenAI has lowered the price of its o3 language model by 80 percent, CEO Sam Altman said. The article appeared first on The Decoder.
  • AI News | VentureBeat: OpenAI's most powerful reasoning model, o3, is now 80% cheaper, making it more affordable for businesses, researchers, and individual developers.
  • www.cnbc.com: The figure includes sales from the company’s consumer products, ChatGPT business products and its application programming interface, or API.
  • Latent.Space: OpenAI just dropped the price of their o3 model by 80% today and launched o3-pro.
  • Simon Willison's Weblog: OpenAI's Adam Groth explained that the engineers have optimized inference, allowing a significant price reduction for the o3 model.
  • Sam Altman: We are past the event horizon; the takeoff has started. Humanity is close to building digital superintelligence, and at least so far it’s much less weird than it seems like it should be.
  • siliconangle.com: OpenAI’s newest reasoning model o3-pro surpasses rivals on multiple benchmarks, but it’s not very fast
  • SiliconANGLE: Silicon Angle reports on OpenAI’s newest reasoning model o3-pro surpassing rivals.
  • bsky.app: the OpenAI API is back to running at 100% again, plus we dropped o3 prices by 80% and launched o3-pro - enjoy!
  • bsky.app: OpenAI has launched o3-pro. The new model is available to ChatGPT Pro and Team subscribers and in OpenAI’s API now, while Enterprise and Edu subscribers will get access next week. If you use reasoning models like o1 or o3, try o3-pro, which is much smarter and better at using external tools.
  • The Algorithmic Bridge: OpenAI o3-Pro Is So Good That I Can’t Tell How Good It Is

Carl Franzen@AI News | VentureBeat //
Mistral AI has launched its first reasoning model, Magistral, signaling a commitment to open-source AI development. The Magistral family features two models: Magistral Small, a 24-billion parameter model available with open weights under the Apache 2.0 license, and Magistral Medium, a proprietary model accessible through an API. This dual release strategy aims to cater to both enterprise clients seeking advanced reasoning capabilities and the broader AI community interested in open-source innovation.

Mistral's decision to release Magistral Small under the permissive Apache 2.0 license marks a significant return to its open-source roots. The license allows for the free use, modification, and distribution of the model's source code, even for commercial purposes. This empowers startups and established companies to build and deploy their own applications on top of Mistral’s latest reasoning architecture, without the burdens of licensing fees or vendor lock-in. The release serves as a powerful counter-narrative, reaffirming Mistral’s dedication to arming the open community with cutting-edge tools.

Magistral Medium demonstrates competitive performance in the reasoning arena, according to internal benchmarks released by Mistral. The model was tested against its predecessor, Mistral-Medium 3, and models from Deepseek. Furthermore, Mistral's Agents API's Handoffs feature facilitates smart, multi-agent workflows, allowing different agents to collaborate on complex tasks. This enables modular and efficient problem-solving, as demonstrated in systems where agents collaborate to answer inflation-related questions.

Recommended read:
References :
  • Simon Willison: Mistral's first reasoning LLM - Magistral - was released today and is available in two sizes, an open weights (Apache 2) 24B model called Magistral Small and an API/hosted only model called Magistral Medium. My notes here, including running Small locally with Ollama and accessing Medium via my llm-mistral plugin
  • Simon Willison's Weblog: Mistral's first reasoning model is out today, in two sizes. There's a 24B Apache 2 licensed open-weights model called Magistral Small (actually Magistral-Small-2506), and a larger API-only model called Magistral Medium.
  • THE DECODER: Mistral launches Europe's first reasoning model Magistral but lags behind competitors
  • AI News | VentureBeat: The company is signaling that the future of reasoning AI will be both powerful and, in a meaningful way, open to all.
  • www.marktechpost.com: How to Create Smart Multi-Agent Workflows Using the Mistral Agents API’s Handoffs Feature
  • TestingCatalog: Mistral AI debuts Magistral models focused on advanced reasoning
  • the-decoder.com: The French start-up Mistral is launching its first reasoning model on the market with Magistral. It is designed to enable logical thinking in European languages.
  • www.artificialintelligence-news.com: Mistral AI has pulled back the curtain on Magistral, their first model specifically built for reasoning tasks.
  • www.infoworld.com: Mistral AI unveils Magistral reasoning model
  • AI News: Mistral AI has pulled back the curtain on Magistral, their first model specifically built for reasoning tasks.
  • Simon Willison: Mistral's first reasoning LLM - Magistral - was released today and is available in two sizes, an open weights (Apache 2) 24B model called Magistral Small and an API/hosted only model called Magistral Medium. My notes here, including running Small locally with Ollama and accessing Medium via my llm-mistral plugin
  • SiliconANGLE: Mistral AI debuts new Magistral series of reasoning LLMs.
  • siliconangle.com: Mistral AI SAS today introduced Magistral, a new lineup of reasoning-optimized large language models. The LLM series includes two algorithms on launch.
  • MarkTechPost: Mistral AI Releases Magistral Series: Advanced Chain-of-Thought LLMs for Enterprise and Open-Source Applications
  • www.marktechpost.com: Mistral AI Releases Magistral Series: Advanced Chain-of-Thought LLMs for Enterprise and Open-Source Applications
  • WhatIs: What differentiates Mistral AI reasoning model Magistral

@thecyberexpress.com //
A critical security vulnerability has been discovered in OpenPGP.js, a widely used JavaScript library that implements the OpenPGP standard for email and data encryption. Tracked as CVE-2025-47934, the flaw allows attackers to spoof both signed and encrypted messages, effectively undermining the trust inherent in public key cryptography. Security researchers from Codean Labs, Edoardo Geraci and Thomas Rinsma, discovered that the vulnerability stems from the `openpgp.verify` and `openpgp.decrypt` functions, and it essentially undermines the core purpose of using public key cryptography to secure communications.

The vulnerability impacts versions 5.0.1 to 5.11.2 and 6.0.0-alpha.0 to 6.1.0 of the OpenPGP.js library. According to an advisory posted on the library's GitHub repository, a maliciously modified message can be passed to one of these functions, and the function may return a result indicating a valid signature, even if the message has not been legitimately signed. This flaw affects both inline signed messages and signed-and-encrypted messages. The advisory also states that to spoof a message, an attacker needs a single valid message signature along with the plaintext data that was legitimately signed. They can then construct a fake message that appears legitimately signed.

Users are strongly advised to upgrade to versions 5.11.3 or 6.1.1 as soon as possible to mitigate the risk. Versions 4.x are not affected by the vulnerability. While a full write-up and proof-of-concept exploit are expected to be released soon, the current advisory offers enough details to highlight the severity of the issue. The underlying problem is that OpenPGP.js trusts the signing process without properly verifying it, leaving users open to having signed and encrypted messages spoofed. This vulnerability allows message signature verification to be spoofed.

Recommended read:
References :
  • The Register - Software: Freshly discovered bug in OpenPGP.js undermines whole point of encrypted comms
  • thecyberexpress.com: A flaw has been discovered in OpenPGP.js, a widely used JavaScript library for OpenPGP encryption. Tracked as CVE-2025-47934, the vulnerability allows threat actors to spoof both signed and encrypted messages, effectively undermining the very foundation of trust in public key cryptography.
  • Security Affairs: A critical flaw in OpenPGP.js, tracked as CVE-2025-47934, lets attackers spoof message signatures; updates have been released to address the flaw. OpenPGP.js is an open-source JavaScript library that implements the OpenPGP standard for email and data encryption.
  • www.csoonline.com: Critical flaw in OpenPGP.js raises alarms for encrypted email services
  • www.techradar.com: Researchers found a bug that allowed malicious actors to spoof messages. Users are advised to patch up.
  • securityaffairs.com: A critical flaw in OpenPGP.js lets attackers spoof message signatures; updates have been released to address the flaw.
  • securityaffairs.com: A critical flaw in OpenPGP.js lets attackers spoof message signatures

@www.quantamagazine.org //
Recent breakthroughs have significantly advanced the "Core of Fermat's Last Theorem," a concept deeply rooted in number theory. Four mathematicians have extended the key insight behind Fermat's Last Theorem, which states there are no three positive integers that, when raised to a power greater than two, can be added together to equal another number raised to the same power. Their work involves applying this concept to other mathematical objects, notably elliptic curves. This extension represents a major step towards building a "grand unified theory" of mathematics, a long-sought goal in the field.

This achievement builds upon the groundwork laid by Andrew Wiles's famous 1994 proof of Fermat's Last Theorem. Wiles, with assistance from Richard Taylor, demonstrated that elliptic curves and modular forms, seemingly distinct mathematical entities, are interconnected. This discovery revealed a surprising "modularity," where these realms mirror each other in a distorted way. Mathematicians can now leverage this connection, translating problems about elliptic curves into the language of modular forms, solving them, and then applying the results back to the original problem.

This new research goes beyond elliptic curves, extending the modularity connection to more complicated mathematical objects. This breakthrough defies previous expectations that such extensions would be impossible. The Langlands program, a set of conjectures aiming to develop a grand unified theory of mathematics, hinges on such correspondences. The team's success provides strong support for the Langlands program and opens new avenues for solving previously intractable problems in various areas of mathematics, solidifying the power and reach of the "Core of Fermat's Last Theorem."

Recommended read:
References :
  • Computational Complexity: The research discussed in this cluster is part of a broader effort to build a unified theory of mathematics, and it involves the extension of the key insight behind Fermat's Last Theorem to include the study of other mathematical objects, such as elliptic curves.
  • Terence Tao: The research discussed in this cluster is part of a broader effort to build a unified theory of mathematics, and it involves the extension of the key insight behind Fermat's Last Theorem to include the study of other mathematical objects, such as elliptic curves.
  • nLab: The research discussed in this cluster is part of a broader effort to build a unified theory of mathematics, and it involves the extension of the key insight behind Fermat's Last Theorem to include the study of other mathematical objects, such as elliptic curves.
  • Quanta Magazine: The research discussed in this cluster is part of a broader effort to build a unified theory of mathematics, and it involves the extension of the key insight behind Fermat's Last Theorem to include the study of other mathematical objects, such as elliptic curves.

Sophia Chen@technologyreview.com //
IBM has announced ambitious plans to construct a large-scale, error-corrected quantum computer, aiming for completion by 2028. This initiative, known as IBM Quantum Starling, represents a significant step forward in quantum computing technology. The project involves a modular architecture, with components being developed at a new IBM Quantum Data Center in Poughkeepsie, New York. IBM hopes to make the computer available to users via the cloud by 2029.

The company's approach to fault tolerance involves a novel architecture using quantum low-density parity check (qLDPC) codes. This method is projected to drastically reduce the number of physical qubits required for error correction, potentially cutting overhead by around 90% compared to other leading codes. IBM says it's cracked the code to quantum error correction and this will significantly enhance the computational capability of the new machine compared to existing quantum computers. IBM also released two technical papers outlining how qLDPC codes can improve instruction processing and operational efficiency, and describes how error correction and decoding can be handled in real-time using classical computing resources.

IBM anticipates that Starling will be capable of executing 100 million quantum operations using 200 logical qubits. This lays the foundation for a follow-up system, IBM Quantum Blue Jay, which will operate with 2,000 logical qubits and run 1 billion operations. According to IBM, storing the computational state of Starling would require memory exceeding that of a quindecillion (10⁴⁸) of today’s most powerful supercomputers. This project aims to solve real-world challenges and unlock immense possibilities for business in fields such as drug development, materials science, chemistry, and optimisation.

Recommended read:
References :
  • Analytics India Magazine: IBM Plans ‘World’s First’ Fault-Tolerant Quantum Computer by 2029
  • www.technologyreview.com: IBM announced detailed plans today to build an error-corrected quantum computer with significantly more computational capability than existing machines by 2028.
  • ComputerWeekly.com: IBM updates path to fault-tolerant quantum computing
  • www.cxoinsightme.com: IBM unveiled its path to build the world’s first large-scale, fault-tolerant quantum computer, setting the stage for practical and scalable quantum computing.
  • www.newscientist.com: New Scientist reports IBM will build a practical quantum supercomputer by 2029.

@medium.com //
Google Quantum AI has published a study that dramatically lowers the estimated quantum resources needed to break RSA-2048, one of the most widely used encryption standards. The study, authored by Craig Gidney, indicates that RSA cracking may be possible with fewer qubits than previously estimated, potentially impacting digital security protocols used in secure web browsing, email encryption, VPNs, and blockchain systems. This breakthrough could significantly accelerate the timeline for "Q-Day," the point at which quantum computers can break modern encryption.

Previous estimates, including Gidney's 2019 study, suggested that cracking RSA-2048 would require around 20 million qubits and 8 hours of computation. However, the new analysis reveals it could be done in under a week using fewer than 1 million noisy qubits. This reduction in hardware requirements is attributed to several technical innovations, including approximate residue arithmetic, magic state cultivation, optimized period finding with Ekerå-Håstad algorithms, and yoked surface codes & sparse lookups. These improvements minimize the overhead in fault-tolerant quantum circuits, enabling better scaling.

Google's researchers have discovered that, thanks to new error correction tricks and smarter algorithms, the encryption could be broken with under 1 million qubits and in less than a week, given favorable assumptions like a 0.1% gate error rate and a 1-microsecond gate time. This significantly faster encryption breaking capability, potentially 20x faster than previously anticipated, raises concerns about the security of Bitcoin wallets and other financial systems that rely on RSA encryption. The findings could potentially make Bitcoin wallets and financial systems vulnerable much sooner than expected.

Recommended read:
References :
  • medium.com: Last week, Craig Gidney from Google Quantum AI published a breakthrough study that redefines the landscape of cryptographic security. His 
  • www.theguardian.com: Google working on AI email tool that can ‘answer in your style’
  • The Official Google Blog: We’re investing for a cleaner energy future with TAE Technologies, a leading nuclear fusion company.
  • medium.com: Google’s quantum leap just changed everything: They can now break encryption 20x faster than 

@www.marktechpost.com //
Google LLC has announced the development of a new AI model designed to improve tropical cyclone forecasting. The model, created through collaboration between Google Research and DeepMind, aims to predict both the path and intensity of these storms days in advance, offering a significant advancement over traditional forecasting methods. This AI-driven approach is accessible through a newly launched website called Weather Lab, providing researchers and experts with access to cutting-edge predictions. According to Google, the algorithm was trained using two datasets. The first described the path, intensity and other key properties of nearly 5,000 cyclones from the past 45 years. The other dataset included information about past weather conditions that was distilled from millions of observations.

The traditional reliance on physics-based weather prediction models often faces limitations, struggling to accurately predict both a cyclone's track and its intensity simultaneously. Google claims its AI model overcomes this hurdle, achieving state-of-the-art accuracy in forecasting both aspects of cyclone behavior. Furthermore, the model can predict other vital details, including a cyclone's formation, size, and shape. In internal tests, Google successfully used the algorithm to predict the paths of four recent cyclones, generating accurate forecasts nearly a week ahead of time for two of the storms, with the capability to predict storms up to 15 days in advance by generating 50 possible scenarios.

The Weather Lab platform allows users to explore and compare predictions from various AI and physics-based models, potentially enhancing the ability of weather agencies and emergency services to anticipate cyclone paths and intensities. DeepMind has also announced a partnership with the U.S. National Hurricane Center, which will incorporate the AI predictions into its operational forecasting workflow for the first time. The company claims this is a major breakthrough in hurricane forecasting, introducing an artificial intelligence system that can predict both the path and intensity of tropical cyclones with unprecedented accuracy which has eluded traditional weather models for decades.

Recommended read:
References :
  • siliconangle.com: Google develops AI model for forecasting tropical cyclones
  • AI News | VentureBeat: Google DeepMind just changed hurricane forecasting forever with new AI model
  • MarkTechPost: Google AI Unveils a Hybrid AI-Physics Model for Accurate Regional Climate Risk Forecasts with Better Uncertainty Assessment

@www.marktechpost.com //
A new framework called AlphaOne, developed by researchers at the University of Illinois Urbana-Champaign and the University of California, Berkeley, offers AI developers a novel method to modulate the reasoning processes of large language models (LLMs). This test-time scaling technique improves model accuracy and efficiency without requiring costly retraining. AlphaOne essentially provides a new "dial" to control LLM 'thinking,' allowing developers to boost performance on complex tasks in a more controlled and cost-effective manner compared to existing approaches. The framework dynamically manages slow-to-fast reasoning transitions, optimizing accuracy on real-world datasets like AMC23 and LiveCodeBench.

One persistent issue with large reasoning models is their inability to self-regulate shifts between fast and slow thinking, leading to either premature conclusions or excessive processing. AlphaOne addresses this by providing a universal method for modulating the reasoning process of advanced LLMs. Previous solutions, such as parallel scaling (running a model multiple times) or sequential scaling (modulating thinking during a single run), often lack synchronization between the duration of reasoning and the scheduling of slow-to-fast thinking transitions. AlphaOne aims to overcome these limitations by effectively adapting reasoning processes.

In addition to AlphaOne, Amazon Nova provides a solution for data consistency in generative AI through Text-to-SQL. Businesses rely on precise, real-time insights to make critical decisions, and Text-to-SQL bridges the gap by generating precise, schema-specific queries that empower faster decision-making and foster a data-driven culture. Unlike Retrieval Augmented Generation (RAG) which is better suited for extracting insights from unstructured data and Generative Business Intelligence, Text-to-SQL excels in querying structured organizational data directly from relational schemas and provides deterministic, reproducible results for specific, schema-dependent queries.

Recommended read:
References :
  • learn.aisingapore.org: Build a Text-to-SQL solution for data consistency in generative AI using Amazon Nova
  • AI News | VentureBeat: AlphaOne gives AI developers a new dial to control LLM ‘thinking’ and boost performance
  • www.marktechpost.com: ALPHAONE: A Universal Test-Time Framework for Modulating Reasoning in AI Models
  • MarkTechPost: ALPHAONE: A Universal Test-Time Framework for Modulating Reasoning in AI Models

@www.quantamagazine.org //
References: StartsWithABang , Ray Lee , Ray Lee ...
Fermilab has announced the final results from its Muon g-2 experiment, aiming to resolve a long-standing anomaly regarding the magnetic moment of muons. This experiment delves into the quantum realm, exploring how short-lived particles popping in and out of existence influence the magnetic properties of muons. The initial results from this experiment suggested that the Standard Model of physics might be incomplete, hinting at the presence of undiscovered particles or forces.

The experiment's findings continue to show a discrepancy between experimental measurements and the predictions of the Standard Model. However, the statistical significance of this discrepancy has decreased due to improvements in theoretical calculations. This implies that while the Standard Model may not fully account for the behavior of muons, the evidence for new physics is not as strong as previously thought. The result is at 4.2σ (standard deviations) away from what's calculated using the Standard Model, which is a bit short of the 5 sigma normally used to declare a discovery. There's about a 1 in 40,000 chance that this is a fluke.

Despite the reduced statistical significance, the results remain intriguing and motivate further research. The possibility of undiscovered particles influencing muons still exists, pushing physicists to explore new theoretical models and conduct additional experiments. Fermilab shared first results from their "g-2" experiment showing the Standard Model of physics is even more incomplete than we thought. If the universe includes particles we don't yet know about, these too will show up as fluctuations around particles, influencing the properties we can measure.

Recommended read:
References :
  • StartsWithABang: Anomaly no more! “Muon g-2†puzzle resolved at last Can theory and experiment agree on the magnetic moment of the muon? At last, a new theory initiative paper coupled with final, world's best experimental results point to the resolution.
  • Ray Lee: Fermilab is announcing final results from the muon g-2 experiment today! I'm heading out the door, but the results will be at 10am CT. Quoting myself from April 7th, 2021: Fermilab shared first results from their "g-2" experiment showing the Standard Model of physics is even more incomplete than we thought.
  • bigthink.com: Anomaly no more! “Muon g-2†puzzle resolved at last Can theory and experiment agree on the magnetic moment of the muon? At last, a new theory initiative paper coupled with final, world's best experimental results point to the resolution.
  • Ray Lee: I should add, there have been various papers since this announcement back in 2021 that claim the calculations were incomplete and newer methods, such as brute-forcing the calculation via SM lattice methods on supercomputers, has pushed the discrepancy with experiment down to less than 2 sigma. Today we'll learn more! 3/3
  • physics.aps.org: Link to the stream: A rather nice cartoon explainer of all this by Jorge Cham: An accessible and slightly more scientific walkthrough over at Quanta Magazine from 2021: And the below graphic, showing how one particle physicist (who's name escapes me), viewed the tension in the results, four years ago. 2/3

@www.microsoft.com //
Microsoft is taking a proactive approach to future cybersecurity threats by integrating post-quantum cryptography (PQC) into its Windows and Linux systems. This move is designed to protect against the potential for quantum computers to break current encryption methods like RSA, which secure online communications, banking transactions, and sensitive data. Quantum computers, leveraging quantum mechanics, can solve complex problems far faster than classical computers, posing a significant threat to existing cryptographic schemes. Microsoft's initiative aims to safeguard data from a "harvest now, decrypt later" scenario, where hackers steal encrypted data today with the intent of decrypting it once quantum technology becomes advanced enough.

Microsoft's PQC implementation includes the addition of two key algorithms: ML-KEM (Module Lattice-Based Key Encapsulation Mechanism) and ML-DSA (Module Lattice-Based Digital Signature Algorithm). ML-KEM, also known as CRYSTALS-Kyber, secures key exchanges and prevents attacks by protecting the start of secure connections. ML-DSA, formerly CRYSTALS-Dilithium, ensures data integrity and authenticity through digital signatures. These algorithms are being introduced in Windows Insider builds (Canary Build 27852+) and Linux via SymCrypt-OpenSSL v1.9.0, allowing developers and organizations to begin testing and preparing for a quantum-secure future.

This update to Windows 11 is a critical step in what Microsoft views as a major technological transition. By making quantum-resistant algorithms available through SymCrypt, the core cryptographic code library in Windows, and updating SymCrypt-OpenSSL, Microsoft is enabling the widely used OpenSSL library to leverage SymCrypt for cryptographic operations. The new algorithms, selected by the National Institute of Standards and Technology (NIST), represent a move towards replacing vulnerable cryptosystems like RSA and elliptic curves. This signifies a broader effort to bolster cybersecurity against the emerging threat of quantum computing.

Recommended read:
References :
  • www.microsoft.com: FrodoKEM: A conservative quantum-safe cryptographic algorithm
  • medium.com: Welcome to the Quantum Era, where even the strongest locks we use to protect our digital lives might soon be breakable. However, don’t…
  • arstechnica.com: Here’s how Windows 11 aims to make the world safe in the post-quantum era
  • medium.com: Quantum Computing and Encryption Breakthroughs in 2025: A New Era of Innovation
  • medium.com: Cracking RSA with Fewer Qubits: What Google’s New Quantum Factoring Estimate Means for…
  • medium.com: Google’s quantum leap just changed everything: They can now break encryption 20x faster than…
  • medium.com: On August 13, 2024, the U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) announced the approval of…
  • medium.com: As our world becomes increasingly interconnected, the Internet of Things (IoT) is transforming industries, homes, and entire cities. From…
  • Quantum Computing Report: Post-Quantum Cryptography Coalition (PQCC) Publishes Comprehensive Roadmap for Post-Quantum Cryptography Migration
  • www.techradar.com: Breaking encryption with quantum computers may be easier than we thought

@www.microsoft.com //
References: cyberinsider.com , Dan Goodin , medium.com ...
Microsoft is taking a significant step towards future-proofing cybersecurity by integrating post-quantum cryptography (PQC) into Windows Insider builds. This move aims to protect data against the potential threat of quantum computers, which could render current encryption methods vulnerable. The integration of PQC is a critical step toward quantum-resilient cybersecurity, ensuring that Windows systems can withstand attacks from more advanced computing power in the future.

Microsoft announced the availability of PQC support in Windows Insider Canary builds (27852 and above). This release allows developers and organizations to begin experimenting with PQC in real-world environments, assessing integration challenges, performance trade-offs, and compatibility. This is being done in an attempt to jump-start what’s likely to be the most formidable and important technology transition in modern history.

The urgency behind this transition stems from the "harvest now, decrypt later" threat, where malicious actors store encrypted communications today, with the intent to decrypt them once quantum computers become capable. These captured secrets, such as passwords, encryption keys, or medical data, could remain valuable to attackers for years to come. By adopting PQC algorithms, Microsoft aims to safeguard sensitive information against this future risk, emphasizing the importance of starting the transition now.

Recommended read:
References :
  • cyberinsider.com: Microsoft has begun integrating post-quantum cryptography (PQC) into Windows Insider builds, marking a critical step toward quantum-resilient cybersecurity. Microsoft announced the availability of PQC support in Windows Insider Canary builds (27852 and above). This release allows developers and organizations to begin experimenting with PQC in real-world environments, assessing integration challenges, performance trade-offs, and compatibility with …
  • Dan Goodin: Microsoft is updating Windows 11 with a set of new encryption algorithms that can withstand future attacks from quantum computers in an attempt to jump-start what’s likely to be the most formidable and important technology transition in modern history.
  • Red Hat Security: In their article on post-quantum cryptography, Emily Fox and Simo Sorce explained how Red Hat is integrating post-quantum cryptography (PQC) into our products. PQC protects confidentiality, integrity and authenticity of communication and data against quantum computers, which will make attacks on existing classic cryptographic algorithms such as RSA and elliptic curves feasible. Cryptographically relevant quantum computers (CRQCs) are not known to exist yet, but continued advances in research point to a future risk of successful attacks. While the migration to algorithms resistant against such
  • medium.com: Post-Quantum Cryptography Is Arriving on Windows & Linux
  • www.microsoft.com: The recent advances in quantum computing offer many advantages—but also challenge current cryptographic strategies. Learn how FrodoKEM could help strengthen security, even in a future with powerful quantum computers. The post first appeared on .
  • arstechnica.com: For the first time, new quantum-safe algorithms can be invoked using standard Windows APIs.

Haden Pelletier@Towards Data Science //
Recent discussions in statistics highlight significant concepts and applications relevant to data science. A book review explores seminal ideas and controversies in the field, focusing on key papers and historical perspectives. The review mentions Fisher's 1922 paper, which is credited with creating modern mathematical statistics, and discusses debates around hypothesis testing and Bayesian analysis.

Stephen Senn's guest post addresses the concept of "relevant significance" in statistical testing, cautioning against misinterpreting statistical significance as proof of a genuine effect. Senn points out that rejecting a null hypothesis does not necessarily mean it is false, emphasizing the importance of careful interpretation of statistical results.

Furthermore, aspiring data scientists are advised to familiarize themselves with essential statistical concepts for job interviews. These include understanding p-values, Z-scores, and outlier detection methods. A p-value is crucial for hypothesis testing, and Z-scores help identify data points that deviate significantly from the mean. These concepts form a foundation for analyzing data and drawing meaningful conclusions in data science applications.

Recommended read:
References :
  • errorstatistics.com: Stephen Senn (guest post): “Relevant significance? Be careful what you wish for”
  • Towards Data Science: 5 Statistical Concepts You Need to Know Before Your Next Data Science Interview
  • Xi'an's Og: Seminal ideas and controversies in Statistics [book review]
  • medium.com: Statistics for Data Science and Machine Learning
  • medium.com: Why Data Science Needs Statistics

@www.microsoft.com //
References: mfesgin.github.io , IACR News , medium.com ...
IACR News has highlighted recent advancements in post-quantum cryptography, essential for safeguarding data against future quantum computer attacks. A key area of focus is the development of algorithms and protocols that remain secure even when classical cryptographic methods become vulnerable. Among these efforts, FrodoKEM stands out as a conservative quantum-safe cryptographic algorithm, designed to provide strong security guarantees in the face of quantum computing threats.

The adaptive security of key-unique threshold signatures is also under scrutiny. Research presented by Elizabeth Crites, Chelsea Komlo, and Mary Mallere, investigates the security assumptions required to prove the adaptive security of threshold signatures. Their work reveals impossibility results that highlight the difficulty of achieving adaptive security for key-unique threshold signatures, particularly for schemes compatible with standard, single-party signatures like BLS, ECDSA, and Schnorr. This research aims to guide the development of new assumptions and properties for constructing adaptively secure threshold schemes.

In related news, Muhammed F. Esgin is offering PhD and Post-Doc positions in post-quantum cryptography, emphasizing the need for candidates with a strong mathematical and cryptography background. Students at Monash University can expect to work on their research from the beginning, supported by competitive stipends and opportunities for teaching assistant roles. These academic opportunities are crucial for training the next generation of cryptographers who will develop and implement post-quantum solutions.

Recommended read:
References :
  • mfesgin.github.io: PhD and Post-Doc in Post-Quantum Cryptography
  • IACR News: Zero-Trust Post-quantum Cryptography Implementation Using Category Theory
  • medium.com: Post-Quantum Cryptography Is Arriving on Windows & Linux
  • medium.com: NIST Approves Three Post-Quantum Cryptography Standards: A Milestone for Digital Security
  • medium.com: Should Post-Quantum Cryptography Start Now? The Clock Is Ticking

@medium.com //
References: medium.com , medium.com , medium.com ...
Medium is currently hosting a series of articles that delve into the core concepts and practical applications of cryptography. These articles aim to demystify complex topics such as symmetric key cryptography, also known as secret key or private key cryptography, where a single shared key is used for both encryption and decryption. This method is highlighted for its speed and efficiency, making it suitable for bulk data encryption, though it primarily provides confidentiality and requires secure key distribution. The resources available are designed to cater to individuals with varying levels of expertise, offering accessible guides to enhance their understanding of secure communication and cryptographic systems.

The published materials offer detailed explorations of cryptographic techniques, including AES-256 encryption and decryption. AES-256, which stands for Advanced Encryption Standard with a 256-bit key size, is a symmetric encryption algorithm renowned for its high level of security. Articles break down the internal mechanics of AES-256, explaining the rounds of transformation and key expansion involved in the encryption process. These explanations are presented in both technical terms for those with a deeper understanding and in layman's terms to make the concepts accessible to a broader audience.

In addition to theoretical explanations, the Medium articles also showcase the practical applications of cryptography. One example provided is the combination of OSINT (Open Source Intelligence), web, crypto, and forensics techniques in CTF (Capture The Flag) challenges. These challenges offer hands-on experience in applying cryptographic principles to real-world scenarios, such as identifying the final resting place of historical figures through OSINT techniques. The series underscores the importance of mastering cryptography in the evolving landscape of cybersecurity, equipping readers with the knowledge to secure digital communications and protect sensitive information.

Recommended read:
References :
  • medium.com: Understanding AES-256 Encryption and Decryption: A Detailed Guide for All Levels
  • medium.com: Understanding Cryptography: The Art of Secure Communication
  • mraviteja9949.medium.com: Symmetric Key Cryptography
  • medium.com: Zero-knowledge proofs (ZKPs) let a saver prove that funds follow a rule — such as “stay locked for six monthsâ€â€Šâ€” without showing the 
  • medium.com: Article on how cryptographic hash functions actually work.
  • medium.com: Quantum-Resistant Cryptography: Preparing Your Code for Post-Quantum Era
  • medium.com: News story about Demystifying ECC, Web3 Cryptography and Their Evolving Threats
  • medium.com: Hello everyone! I’m a pen tester and today we will discuss about cryptography.
  • renanikeda.medium.com: The Diffie-Hellman Key Exchange is one of the most interesting mathematical techniques to guarantee that both parties share the same…

@quantumcomputingreport.com //
References: medium.com , medium.com , medium.com ...
The rapid advancement of quantum computing poses a significant threat to current encryption methods, particularly RSA, which secures much of today's internet communication. Google's recent breakthroughs have redefined the landscape of cryptographic security, with researchers like Craig Gidney significantly lowering the estimated quantum resources needed to break RSA-2048. A new study indicates that RSA-2048 could be cracked in under a week using fewer than 1 million noisy qubits, a dramatic reduction from previous estimates of around 20 million qubits and eight hours of computation. This shift accelerates the timeline for "Q-Day," the hypothetical moment when quantum computers can break modern encryption, impacting everything from email to financial transactions.

This vulnerability stems from the ability of quantum computers to utilize Shor's algorithm for factoring large numbers, a task prohibitively difficult for classical computers. Google's innovation involves several technical advancements, including approximate residue arithmetic, magic state cultivation, optimized period finding with Ekerå-Håstad algorithms, and yoked surface codes with sparse lookups. These improvements streamline modular arithmetic, reduce the depth of quantum circuits, and minimize overhead in fault-tolerant quantum circuits, collectively reducing the physical qubit requirement to under 1 million while maintaining a relatively short computation time.

In response to this threat, post-quantum cryptography (PQC) is gaining momentum. PQC refers to cryptographic algorithms designed to be secure against both classical and quantum attacks. NIST has already announced the first set of quantum-safe algorithms for standardization, including FrodoKEM, a key encapsulation protocol offering a simple design and strong security guarantees. The urgency of transitioning to quantum-resistant cryptographic systems is underscored by ongoing advances in quantum computing. While the digital world relies on encryption, the evolution to AI and quantum computing is challenging the security. Professionals who understand both cybersecurity and artificial intelligence will be the leaders in adapting to these challenges.

Recommended read:
References :
  • medium.com: Should Post-Quantum Cryptography Start Now? The Clock Is Ticking
  • medium.com: Google’s quantum leap just changed everything: They can now break encryption 20x faster than…
  • quantumcomputingreport.com: Significant Theoretical Advancement in Factoring 2048 Bit RSA Integers
  • medium.com: Last week, Craig Gidney from Google Quantum AI published a breakthrough study that redefines the landscape of cryptographic security.
  • www.microsoft.com: The recent advances in quantum computing offer many advantages—but also challenge current cryptographic strategies. Learn how FrodoKEM could help strengthen security, even in a future with powerful quantum computers.
  • medium.com: Securing the Internet of Things: Why Post-Quantum Cryptography Is Critical for IoT’s Future
  • medium.com: Quantum Resilience Starts Now: Building Secure Infrastructure with Hybrid Cryptography
  • medium.com: Quantum-Resistant Cryptography: Preparing Your Code for Post-Quantum Era

@aasnova.org //
JWST is currently being used to study exoplanets, particularly sub-Neptunes, providing valuable data on their atmospheric composition. A recent study utilized JWST spectroscopy to analyze the atmosphere of the sub-Neptune GJ 3090b. This planet orbits a late-type, low-mass star and its radius places it at the outer edge of the radius valley. Sub-Neptunes are the most common type of planet in the Milky Way, however their formation and composition are not well understood, making these studies especially important.

The JWST's observations of GJ 3090b revealed a low-amplitude helium signature, suggesting a metal-enriched atmosphere. The presence of heavy molecules like water, carbon dioxide, and sulfur further contributes to the understanding of the planet's atmospheric properties. These atmospheric observations help clarify how hydrogen and helium may be escaping the planet’s atmosphere, with the presence of metals slowing down mass loss and weakening the helium signature.

While JWST is making significant contributions to exoplanet research, it won't find the very first stars. Other telescopes will be needed to make those observations. JWST however contains some of the latest discoveries, including the new cosmic record-holder for the most distant galaxy, MoM-z14.

Recommended read:
References :
  • StartsWithABang: Earlier this week, I gave a talk about JWST to the RASC Toronto audience through York University, and it has the latest and greatest of its discoveries inside, including the new cosmic record-holder for most distant galaxy: MoM-z14. Check it out!
  • aasnova.org: Abundant but Ambiguous: Understanding the Atmospheres of Sub-Neptunes with JWST

@thequantuminsider.com //
The quantum computing industry is experiencing a surge in activity, marked by significant acquisitions and technological advancements. IonQ has announced its intent to acquire UK-based Oxford Ionics for $1.075 billion in stock and cash, uniting two leaders in trapped-ion quantum computing. This deal aims to accelerate the development of scalable and reliable quantum systems, targeting 256 high-fidelity qubits by 2026 and over 10,000 physical qubits by 2027. The acquisition combines IonQ's quantum computing stack with Oxford Ionics' semiconductor-compatible ion-trap technology, strengthening IonQ's technical capabilities and expanding its European presence. CEO of IonQ, Niccolo de Masi, highlighted the strategic importance of this acquisition, uniting talent from across the world to become the world’s best quantum computing, quantum communication and quantum networking ecosystem.

Recent advancements also include the activation of Europe’s first room-temperature quantum accelerator by Fraunhofer IAF, featuring Quantum Brilliance’s diamond-based QB-QDK2.0 system. This system utilizes nitrogen-vacancy (NV) centers and operates without cryogenic requirements, seamlessly integrating into existing high-performance computing environments. It's co-located with classical processors and NVIDIA GPUs to support hybrid quantum-classical workloads. Moreover, IBM has announced plans to build the world’s first large-scale, error-corrected quantum computer named Starling, aiming for completion by 2028 and cloud availability by 2029. IBM claims it has cracked the code for quantum error correction, moving from science to engineering.

Further bolstering the industry's growth, collaborative projects are demonstrating the potential of quantum computing in various applications. IonQ, in partnership with AstraZeneca, AWS, and NVIDIA, has showcased a quantum-accelerated drug discovery workflow that drastically reduces simulation time for key pharmaceutical reactions. Their hybrid system, integrating IonQ’s Forte quantum processor with NVIDIA CUDA-Q and AWS infrastructure, achieved over a 20-fold improvement in time-to-solution for the Suzuki-Miyaura reaction. Additionally, the Karnataka State Cabinet has approved the second phase of the Quantum Research Park at the Indian Institute of Science (IISc) in Bengaluru, allocating ₹48 crore ($5.595 million USD) to expand the state’s quantum technology infrastructure and foster collaboration between academia, startups, and industry.

Recommended read:
References :
  • thequantuminsider.com: IonQ has announced the results of a collaborative quantum computing project that could accelerate pharmaceutical research timelines by orders of magnitude.
  • Quantum Computing Report: Fraunhofer IAF Activates Europe’s First Room-Temperature Quantum Accelerator from Quantum Brilliance
  • thequantuminsider.com: IonQ Acquires UK-based Oxford Ionics For $1.075 Billion