February 2026

Federated Learning (FL) aims to train a collaborative model while preserving data privacy. However, the distributed nature of this approach still raises privacy and security issues, such as the exposure of sensitive data due to inference attacks and the influence of Byzantine behaviors on the trained model. In particular, achieving both secure aggregation and Byzantine resilience remains challenging, as existing solutions often address these aspects independently. In this work, we propose to address these challenges through a novel […]

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Federated Learning (FL) aims to train a collaborative model while preserving data privacy. However, the distributed nature of this approach still raises privacy and security issues, such as the exposure of sensitive data due to inference attacks and the influence of Byzantine behaviors on the trained model. In particular, achieving both secure aggregation and Byzantine resilience remains challenging, as existing solutions often address these aspects independently. In this work, we propose to address these challenges through a novel […]

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As Large Language Models (LLMs) achieve remarkable empirical success through scaling model and data size, pretraining has become increasingly critical yet computationally prohibitive, hindering rapid development. Despite the availability of numerous pretrained LLMs developed at significant computational expense, a fundamental real-world question remains underexplored: textit{Can we leverage existing small pretrained models to accelerate the training of larger models?} In this paper, we propose a Late-to-Early Training (LET) paradigm that enables LLMs to explicitly learn later knowledge in earlier […]

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How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## The SEPA Instant Deadlines Have Passed. But Did Europe Really Go Instant? By @noda [ 4 Min read ] The major SEPA instant payments deadlines have passed, but adoption varies by country. Noda analysis reviews whether Europe has really gone instant. Read More. The […]

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Many approximate machine unlearning methods demonstrate strong logit-level forgetting — such as near-zero accuracy on the forget set — yet continue to preserve substantial information within their internal feature representations. We refer to this discrepancy as superficial forgetting. Recent studies indicate that most existing unlearning approaches primarily alter the final classifier, leaving intermediate representations largely unchanged and highly similar to those of the original model. To address this limitation, we introduce the Erase at the Core (EC), a […]

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The app sec community was happy to see that OWASP is considering making a move in their Top 10 update: “Security Logging and Alerting Failures” from position #10 to position #9, and highlighted in the 2025 release with a new name emphasizing a critical component that was often overlooked—alerting. “Security Logging & Alerting Failures” represents more than a simple reordering of priorities. It signals a shift in how organizations will approach application security in an era of increasingly […]

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This paper proposes an information-theoretic framework for analyzing the theoretical limits of pool-based active learning (AL), in which a subset of instances is selectively labeled. The proposed framework reformulates pool-based AL as a noisy lossy compression problem by mapping pool observations to noisy symbol observations, data selection to compression, and learning to decoding. This correspondence enables a unified information-theoretic analysis of data selection and learning in pool-based AL. Applying finite blocklength analysis of noisy lossy compression, we derive […]

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In my previous analysis of Power Stranding, I explored the multi-billion-dollar art of ensuring that massive power infrastructure doesn’t sit idle. But for a data center financial analyst, solving the power equation isn’t just about building better substations. It’s about what sits inside the racks. Looking at a modern data center’s balance sheet in early 2026, the “Hardware” line item is undergoing a silent coup. For decades, the industry operated as a one-stop shop: cloud providers bought their […]

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Every few years, the same question resurfaces: “What skills will be in demand in the future?” The recurring question of future in-demand skills has gained new urgency in 2026 due to rapid labour market transformation. The real issue isn’t a lack of information, but that most people are preparing for the wrong future by learning skills in isolation. They treat competencies as siloed resume points (e.g., a single programming language or tool), believing this offers security. However, the modern labour […]

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OpenAI has acquired Torch, a healthcare startup that aims to consolidate fragmented medical records into a single AI-accessible system. CNBC reports that all Torch employees are joining OpenAI, though the company has chosen not to disclose financial terms. At face value, the deal looks like a simple expansion of OpenAI’s health portfolio. However, that explanation sidesteps the real story. Centralizing health data inside a private AI ecosystem is not a step toward progress. It signals a future where […]

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