-Mistral 3 Family: Mistral AI launched Mistral 3, featuring open-source multimodal models like Mistral Large 3 (41B active parameters) and the Ministral series (3B, 8B, 14B sizes), optimized for edge devices such as laptops, drones, and robots. These models support image understanding, multilingual capabilities, and run efficiently on NVIDIA GPUs without license fees, challenging closed-source leaders with distributed intelligence.
-DeepSeek Models: Chinese AI lab DeepSeek released DeepSeek-V3.1, DeepSeek-V3.2-Speciale (reasoning engine rivaling proprietary models in math and logic), and DeepSeek-Math-V2, with costs as low as $5.57M for training. These open-source models surpass GPT-5 and Gemini 3.0 Pro on benchmarks like AIME (96% accuracy) and are fully MIT-licensed.
-OMo 3: The Allen Institute for AI released OLMo 3, a radically transparent open-source model with full training code, final weights, and 2 trillion training tokens, competing against closed models from OpenAI and Google. It's free via Open Router APIs until December 22, 2025.
-LongCat Image: A new 6B-parameter open-source image generation model achieving SOTA photorealistic quality on a single consumer GPU, with bilingual (Chinese/English) text rendering for poster-grade typography. The full training pipeline and tools were also released.
-Other Notable Releases: GLM-4.6 (200K context, strong coding); Kimi-K2-Thinking (1T params, 71% on SWE-Bench as an agentic model); Qwen3 (119 languages, 1M token context, 235B MoE params); Runway Gen 4.5 (top in cinematic video generation benchmarks); DeepCogito v2 (enhanced reasoning, open-source).
New Papers
From arXiv submissions on December 5, 2025, key papers focus on innovative models and frameworks:
-SIMA 2: A Generalist Embodied Agent for Virtual Worlds – Advances scalable multi-task learning for embodied AI in simulated environments, pushing robotics and agent capabilities.
-STELLA: Guiding Large Language Models for Time Series Forecasting with Semantic Abstractions – Enhances LLM accuracy in forecasting via semantic abstractions, bridging AI and data science.
-BioMedGPT-Mol: Multi-task Learning for Molecular Understanding and Generation – A biomedical AI model for drug discovery and molecular tasks, integrating multi-task learning.
-BiTAgent: A Task-Aware Modular Framework for Bidirectional Coupling between
Multimodal Large Language Models and World Models – Enables adaptive interactions in complex tasks, improving multimodal AI.
-GTM: Simulating the World of Tools for AI Agents – A simulation environment for training agents with virtual tools, advancing agent-based AI realism.
-Chameleon: Adaptive Adversarial Agents for Scaling-Based Visual Prompt Injection in Multimodal AI Systems – Tests and bolsters AI security against visual attacks.
-Toward Continuous Neurocognitive Monitoring: Integrating Speech AI with Relational Graph Transformers for Rare Neurological Diseases – Combines speech AI for detecting rare diseases, a healthcare breakthrough.
-Economies of Open Intelligence: Tracing Power & Participation in the Model Ecosystem – Analyzes shifts in open AI economy via Hugging Face data (2020–2025), noting rise in non-US developers and multimodal trends.
-twAIn Robotics: TWAIN Working Group launched this open-source initiative for AI robotics post-Converge Conference 2025, focusing on adversarial AI and smart systems.
-NVIDIA Tools and Models: New open-source suite for speech AI, plus NVIDIA's Alpamayo-R1 vision language model for autonomous vehicles.
-AI Programming Languages/Frameworks: Bend + HVM2 (Python-like for GPUs); Mojo (Python superset for accelerators); QICK (quantum control); Pareas (GPU compiler for parsing).
-UMA Physical AI Robotics: New platform for physical AI, emphasizing end-to-end audio generation in videos.
-AI Devtools: Conductor (agent orchestration); Graphite (code review); others from December spotlight.
Other Key Announcements and Updates
-US HHS AI Strategy: Unveiled a plan with five pillars for governance, risk management, and AI adoption in healthcare.
-DOE AMP2 Platform: Launched an AI-driven biotechnology tool at PNNL for faster scientific breakthroughs.
-AWS re:Invent 2025: Focused on Nova models, Trainium3 silicon, AI Factories; Amazon Bedrock AgentCore and Reinforcement Fine Tuning (66% accuracy boost for agents).
-Industry Insights: Geoffrey Hinton warns of AI-driven unemployment; debates on AI bubble bursting for innovation; NTT DATA named leader in AI app development.
Jason Wade
Founder & Lead at
NinjaAI
I’ve spent two decades engineering growth at the intersection of technology, marketing, and artificial intelligence, turning complex systems into measurable revenue instead of busywork metrics. My foundation was forged in early SEO, where I scaled Modena, Inc. into a national ecommerce operation before “search” was a department and not yet a discipline. Today, that same technical rigor powers a new category: AI Visibility, the practice of placing brands inside the answer layer where decisions are now made.
At NinjaAI, I design prompt architectures and visibility systems that convert large language models into operating infrastructure for real businesses. My work blends sales psychology, machine reasoning, and search intelligence into a single acquisition system that replaces ad dependency with owned inbound. The outcome is not better marketing. It’s leverage, velocity, and authority that compounds.
If you want traffic, hire an agency.
If you want ownership, build with me.
