Maligned - February 13, 2026
AI news without the BS
Here’s what actually matters in AI today. No fluff, no hype - just 5 developments worth your time.
Today’s Top 5 AI Developments
1. Claude 3.5 Sonnet Drops: Faster, Smarter, Cheaper 🚀
Anthropic just launched Claude 3.5 Sonnet, a significant step up in their model lineup. It’s not just faster and more cost-effective; it’s setting new benchmarks for reasoning, code understanding, and complex multimodal tasks, particularly for vision. This release pushes the performance-to-cost efficiency ratio further, making frontier AI more accessible.
Source: Anthropic Blog Link: https://www.anthropic.com/news/claude-3-5-sonnet
2. FormalJudge: Verifiable Safety for AI Agents 🛡️
Traditional “LLM-as-a-Judge” oversight is probabilistic, leaving a critical gap for high-stakes AI agent deployment. FormalJudge introduces a neuro-symbolic framework that converts natural language requirements into formal, verifiable specifications, providing mathematical guarantees for agent behavior. This is a game-changer for ensuring trustworthiness and safety in autonomous AI.
Source: arXiv Link: https://arxiv.org/abs/2602.11136v1
3. TabICLv2: New State-of-the-Art for Tabular Data đź“Š
A new open-source foundation model, TabICLv2, just leapfrogged previous models to become the state-of-the-art for tabular data classification and regression. Thanks to novel synthetic data generation and architectural improvements, it’s faster, more scalable, and generalizes effectively to million-scale datasets. This significantly boosts predictive power for the backbone of enterprise data.
Source: arXiv Link: https://arxiv.org/abs/2602.11139v1
4. LLM Training Secret: Repetition Beats Raw Data Volume 🤯
Forget what you thought you knew about LLM fine-tuning: new research shows that for reasoning tasks with Chain-of-Thought data, training for more epochs on smaller datasets actually outperforms single-epoch training on larger datasets. This counter-intuitive finding offers a practical, more data-efficient, and potentially less compute-intensive strategy for improving reasoning capabilities.
Source: arXiv Link: https://arxiv.org/abs/2602.11149v1
5. GENIUS: Benchmarking True AI Fluid Intelligence đź§
Existing benchmarks for multimodal models often only assess “crystallized intelligence” – how much knowledge they’ve memorized. GENIUS introduces a critical new suite to evaluate “Generative Fluid Intelligence,” challenging models to adapt to novel scenarios, infer implicit patterns, and execute abstract constraints on the fly. The results? Most models still struggle, revealing a significant hurdle on the path to truly general AI.
Source: arXiv Link: https://arxiv.org/abs/2602.11144v1
That’s it for today. Stay aligned. 🎯
Maligned - AI news without the BS