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Black Forest Labs Releases FLUX 3: A Multimodal Flow Model for Image, Video, Audio and Robot Action Prediction

Black Forest Labs (BFL) has released FLUX 3, a multimodal foundation model that learns from images, videos and audio inside a single architecture. It is also…

Alibaba Previews Qwen3.8-Max, a 2.4 Trillion-Parameter Multimodal Model, Days After Moonshot’s Kimi K3 Open-Weight Launch

On July 19, Alibaba’s Qwen team previewed Qwen3.8-Max-Preview, the next flagship in the Qwen family. The research team describes it as…

Thinking Machines Lab Releases Inkling: A 975B-Parameter Open-Weights Multimodal MoE With 41B Active Parameters And Controllable Thinking Effort

Thinking Machines Lab just released Inkling, their first model trained from scratch, weights are open, fine-tunable on Tinker. The lab pitches it as a base for…

Meta Superintelligence Labs Releases Muse Spark 1.1: A Multimodal Reasoning Model for Agentic Tasks on Meta Model API

Today, Meta Superintelligence Labs released Muse Spark 1.1. Alongside it, Meta opened a public preview of the Meta Model API. That second part is the structural…

RAG-Anything Tutorial: Build a Multimodal Retrieval Pipeline for Text, Tables, Equations, and Images in Colab

print(“\n[5/10] Creating a synthetic multimodal report…”) monthly_data = pd.DataFrame( { “Month”: [“Jan”, “Feb”, “Mar”, “Apr”, “May”, “Jun”], “Query Volume”: [1200, 1700, 2100, 2600, 3300, 4100], “Hybrid…

Google DeepMind Releases Gemma 4 12B: An Encoder-Free Multimodal Model with Native audio that runs on a 16 GB laptop

Google DeepMind just released Gemma 4 12B, a dense multimodal model that strips out traditional encoders entirely. Vision and audio flow straight into the LLM backbone.…

Design a Complete Multimodal RLVR Pipeline with Open-MM-RL, Vision-Language Prompting, Reward Scoring, and GRPO Export

EXTRACT_PATS = [ r”\\boxed\{([^{}]+)\}”, r”final\s+answer\s*[:=]\s*([^\n]+)”, r”answer\s*[:=]\s*([^\n]+)”, ] def extract_final(text): if not text: return “” for p in EXTRACT_PATS: m = re.search(p, text, flags=re.IGNORECASE) if m: return…

Alibaba Qwen Team Introduces Qwen3.5-LiveTranslate-Flash: Real-Time Multimodal Interpretation Across 60 Languages at 2.8-Second Latency

Simultaneous interpretation is one of the harder problems in applied AI. You’re asking a model to translate speech before the speaker has finished a sentence. Every…

Deploying a Multistage Multimodal Recommender System on Amazon Elastic Kubernetes Service

, multimodal recommender system is not trivial especially when it needs to scale, adapt in near real time, and run reliably on cloud. In this post,…

Mira Murati’s Thinking Machines Lab Introduces Interaction Models: A Native Multimodal Architecture for Real-Time Human-AI Collaboration

Most AI systems today work in turns. You type or speak, the model waits, processes your input, and then responds. That’s the entire interaction loop. Thinking…

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