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✨ Thank You, 2025 — What a Year for RELIANOID! ✨

As the year comes to a close, we want to take a moment to look back and saythank youto everyone who has been part of RELIANOID’s journey in 2025. This year has been all aboutgrowth, innovation, and community: 🚀Product & Technology - Continued evolution ofRELIANOID Enterprise Edition, delivering high..

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AI-driven cyberthreats are reshaping industrial security faster than many manufacturers expect.

As we approach 2026, attackers are already leveraging AI to automate reconnaissance, social engineering and intrusion workflows—often at machine speed. For manufacturing environments, where IT and OT increasingly converge, this creates a new risk landscape. In our latest article, we explore: - Why A..

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Your Guide to Cloning in JIRA: How to Clone Issues in Different Ways

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DeepSeekMath-V2 is a state-of-the-art mathematical reasoning model built on the DeepSeek-V3.2-Exp-Base architecture with 685 billion parameters. Unlike conventional math-focused language models that optimize only for correct final answers, DeepSeekMath-V2 introduces a self-verification framework where the model generates, inspects, and validates its own mathematical proofs.

This approach enables rigorous, step-by-step reasoning suitable for theorem proving, scientific research, and domains requiring high-integrity logic. The model is trained through a generation-verification loop involving a dedicated LLM-based verifier and reinforcement learning optimized for proof correctness rather than answer matching.

DeepSeekMath-V2 achieves gold-level scores on IMO 2025 and CMO 2024, along with a groundbreaking 118/120 on the Putnam 2024 contest. Released under the Apache 2.0 license and hosted on Hugging Face, it is fully open source for research and commercial use.