Did you know that 43% of cyberattacks target small businesses, yet only 14% are prepared to defend themselves? For start-ups, the stakes are even higher. A single breach could lead to significant financial losses, tarnish your reputation and derail your growth trajectory. So, all things considered, cybersecurity is no longer a luxury or an afterthought,
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Normalization layers have become fundamental components of modern neural networks, significantly improving optimization by stabilizing gradient flow, reducing sensitivity to weight initialization, and smoothing the loss landscape. Since the introduction of batch normalization in 2015, various normalization techniques have been developed for different architectures, with layer normalization (LN) becoming particularly dominant in Transformer models. Their
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LLMs are widely used for conversational AI, content generation, and enterprise automation. However, balancing performance with computational efficiency is a key challenge in this field. Many state-of-the-art models require extensive hardware resources, making them impractical for smaller enterprises. The demand for cost-effective AI solutions has led researchers to develop models that deliver high performance with
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As the complexity and size of transformer-based models grow, so does the need to optimize their inference speed, especially in chat applications where the users expect immediate replies. Key-value (KV) caching is a clever trick to do that: At inference time, key and value matrices are calculated for each generated token. KV caching stores these
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The US extradites LockBit ransomware developer, Rostislav Panev, from Israel. Learn how his arrest impacts the fight against cybercrime and understand LockBit’s devastating impact. The United States has achieved a significant victory in its ongoing battle against cybercrime with the extradition of Rostislav Panev, a 51-year-old dual Russian and Israeli national, who is accused of
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At a large-scale model training (in huge models), anomalies are not rare events but problematic patterns that drive failure. Detecting anomalies early in the process saves days of work and training. ML model training observability is not just about tracking metrics. It requires proactive monitoring to catch issues early and ensure model success, given the
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The Hague, the Netherlands, March 13th, 2025, CyberNewsWire Founded in 2024, Modat – the European-crafted, research-driven, AI-powered cybersecurity company, has announced the launch of its premier product, Modat Magnify. Designed by and for cybersecurity professionals, the team behind the product aims to speed up the lives of these individuals easier by giving them access to
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KnowBe4, the world-renowned cybersecurity platform that comprehensively addresses human risk management, today announced that it has been awarded first place in this year’s teissAwards Cybersecurity Company of the Year category for enterprise organisations. The teissAwards celebrate excellence in cyber and information security, recognising the outstanding contributions of vendors and technologies over the past year. Winning first place
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How AI is Shaping the Future of Stock Market Predictions Introduction: The stock market is a dynamic and unpredictable environment, and for years, predicting its movements has been both an art and a science. But what if technology could enhance our ability to predict these fluctuations more accurately and efficiently? Enter artificial intelligence (AI). AI
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In our paper, Understanding LLMs Requires More Than Statistical Generalization, we argue that current machine learning theory cannot explain the interesting emergent properties of Large Language Models, such as reasoning or in-context learning. From prior work (e.g., Liu et al., 2023) and our experiments, we’ve seen that these phenomena cannot be explained by reaching globally
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