Maligned - November 26, 2025

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. Apple Intelligence: GenAI Goes Mainstream & Private 🍎

Apple’s deep integration of generative AI across its device ecosystem isn’t just a feature update; it’s a massive shift in how AI is delivered to the masses. With on-device processing and Private Cloud Compute, they’re tackling the privacy concerns head-on, setting a new standard for secure, personalized AI experiences directly where users live. This move validates the consumer demand for powerful, context-aware AI assistants that respect user data.

Source: Apple (Initial announcement: WWDC 2024) Link: https://www.apple.com/apple-intelligence/

2. Multi-Agent LLMs Break Multimodal Barriers 🧠

Forget training colossal, monolithic VLMs. New research introduces “Be My Eyes,” a multi-agent framework that lets powerful text-only LLMs perceive new modalities like vision by collaborating with smaller, specialized VLMs. This modular approach significantly cuts development costs and preserves the LLM’s core reasoning, proving you don’t need one giant model to master multimodal challenges. It’s a pragmatic, scalable path for future multimodal AI.

Source: arXiv Link: https://arxiv.org/abs/2511.19417v1

3. Agentic LLMs Turbocharge Enzyme Design 🧬

Genie-CAT is an agentic LLM system that’s turning protein design on its head. By combining an LLM with RAG, structural parsing, electrostatic calculations, and ML predictions, it autonomously generates testable hypotheses for enzyme design, like identifying residue modifications for redox tuning. This isn’t just “protein language models”; it’s LLMs evolving into active partners for mechanistic scientific discovery in biotech.

Source: arXiv Link: https://arxiv.org/abs/2511.19423v1

4. Cloud4D Reconstructs 4D Cloud States from Ground Up ☁️

For climate and weather modeling, accurate, high-resolution cloud data is gold. Cloud4D is a learning-based framework that reconstructs physically consistent 4D cloud states (3D liquid water content + horizontal wind vectors) purely from ground-based cameras. This delivers an order-of-magnitude improvement in space-time resolution over satellite data, promising significantly better prediction of extreme weather events and crucial climate insights.

Source: arXiv Link: https://arxiv.org/abs/2511.19431v1

5. Generative Models Get Faster (Without the Data Hassle) ⚡

Diffusion models are great, but slow. And distilling them for speed often means relying on static datasets, leading to “Teacher-Data Mismatch” BS. New research shows you can distill flow maps for 1-step sampling without external data, purely from the prior distribution. This technique boosts efficiency and robustness, achieving state-of-the-art FID scores on ImageNet in just one sampling step, pushing generative AI towards true real-time performance.

Source: arXiv Link: https://arxiv.org/abs/2511.19428v1

That’s it for today. Stay aligned. 🎯

Maligned - AI news without the BS