#Multimodal

Coursera's new course 'AI Data Stream Architecture: From Principles to Practice' teaches the principles of modern accelerator operation

Coursera's new course 'AI Data Stream Architecture: From Principles to Practice' teaches engineers how to work across GPUs, TPUs, Cerebras WSE, Groq LPU, and IBM Spyre accelerators. The course is taught by Kaoutar El Maghraoui, a senior research scientist at IBM Research, covering execution models, compilation, memory systems, debugging, and performance modeling through six courses and hands-on experiments, emphasizing how different architectures affect model performance and the key role of compiler optimization.

Tencent releases Hy-Memory-30B-A3B-GGUF model quantization file

The Hy-Memory-30B-A3B-GGUF model quantization file released by Tencent's Huayan uses a hybrid precision quantization scheme with imatrix calibration and MoE perception, achieving efficient local inference on llama.cpp, where the ~8 GB expert-mixed build file size is reduced to about 24.71 GB, with performance only 1.53% lower than Q6_K.

How vLLM achieves elastic expert parallel near-zero downtime scaling

vLLM achieves a downtime reduction of DeepSeek V4 Pro from 16GB200 to 20GB200 to 0.82 seconds and from 20GB200 back to 16GB200 to 1.96 seconds through asynchronous preparation and NIXL EP technology.

Cloudflare's 27B multimodal decision model Clef has landed on the Ollama cloud platform

Cloudflare's 27B multimodal decision model Clef has landed on the Ollama cloud platform, users can run it locally or use cloud services. Clef transforms state and typed question patterns into decisions, supports text and image input, is compatible with Jev and System One APIs, is fine-tuned based on Qwen3.8-27B, and adopts the Apache 2.0 license. In Cloudflare's decision index evaluation, Clef outperforms Jev and performs leading in most benchmark tests.

Google Research explores combining AI agents with biological reality to build autonomous wet labs.

Google Research releases the VERID framework, enabling AI agents to run in physics-based, safe, and resource-efficient experiments; demonstrates closed-loop intelligent agent scientific discovery on adapter and de novo protein design prototypes; through three rounds of design-test-iterate cycles, AI-driven rational and de novo design will increase confirmed target hit rates to 33.5% and 42.1% on myoglobin and α-thrombin, respectively.

How does the Claude Code team conduct code reviews?

Microsoft AI has released an 80 billion parameter MoE large model MAI-Base-2.

Microsoft AI has completed the pre-training of a new MoE large model MAI-Base-2, with 80 billion active parameters and 2.8 trillion total parameters, surpassing all open-source models in internal evaluations. The model is 4-12 times more efficient in pre-training FLOPs than the strongest open-source base model DeepSeek-V4-Pro-Base and is used to train larger models. Microsoft plans to license the model weights through Foundry using organic data pre-training and full-stack control.

Meta Muse Spark Open launched on the Together AI platform

Meta Muse Spark Open has been launched on the Together AI platform, which is currently the most powerful US open-source heavy model, designed for long-running intelligent coding workflows that require the entire codebase to be stored in context

Three layers, one warehouse: Google ADK-Recipes repository tour

Google has launched the ADK-Recipes repository as a single source of truth for Agent platform content, including core patterns, plugin skills, and services, supporting end-to-end construction of long-term memory agents, one-click installation of retail vertical skills, and deployment to Cloud Run or Gemini Enterprise.

MLX and RDMA implement local and distributed large language model inference on Mac Studio

On a cluster of four Mac Studio machines, Muse Spark Open (816B parameters) generates at a speed of over 36 tokens/second. The Mac Studio M5 Ultra version offers 4.6x faster inference speed (TTFT) and 1.6x faster tokens/second compared to the M3 Ultra, benefiting from the GPU neural accelerator and 1.2 TB/s memory bandwidth.

Step-5-Preview-NVFP4 model release by LeapX Stars

LeapX Stars releases flagship model Step-5-Preview-NVFP4, with 600B total parameters and 27B active parameters, supporting up to 1M context windows, excels in software engineering, professional knowledge work, and financial fields, capable of processing text, images, and video, deployable via OpenAI-compatible API or offline generation.

Whisper-small performs excellently on the Code-Switching Detection task

Whisper-small achieved an average F1 score of 0.798 across 14 language pairs in the CS-FLEURS benchmark test, surpassing CNN's 0.776 and HuBERT's linear baseline's 0.751. The method detects language switching directly from speech by identifying the language-selective hidden state dimension in pre-trained speech encoders, and only requires a small amount of code to convert the dataset to fine-tune decision rules.

Apple Machine Learning Research explores the design space of tri-modal masked diffusion models.

Apple Machine Learning Research has for the first time pre-trained a tri-modal masked diffusion model (MDM) from scratch on text, image-text, and audio-text data, analyzing multi-modal extension patterns.

Gemini 4 Argon: Built specifically to solve complex problems

Gemini 4 Argon ranked first on the Vals Index, surpassing other cutting-edge models in coding, finance, law, cybersecurity, and science with its 175B parameter size; its reasoning depth and accuracy make it a powerful tool for solving complex engineering problems, optimizing business processes, and accelerating scientific breakthroughs.

Google has released the Gemini 4 Argon cutting-edge model.

Google has released Gemini 4 Argon, opening it up to developers, businesses, and researchers, with API pricing at $2 per million input tokens and $10 per million output tokens, offering a 95% discount on cached input tokens.

Amazon Science has introduced Priming technology, allowing AI model architecture changes without the need for micro-adjustments from scratch.

Amazon Science proposes Priming technology, which reduces the pre-training cost of hybrid state space models by over 99% by leveraging pre-trained Transformer weights, enabling developers to explore problems that were previously too costly to investigate.

Multi-Agent Self-Supervision achieves recursive self-improvement

Multi-Agent Self-Supervision (MASS) achieves recursive self-improvement through multi-agent self-supervision, enabling a 27B open-weight model to achieve scores 1.2-1.6 times that of the baseline model for each output token after the second round of synthetic open-ended research tasks.

Mistral AI has launched the public beta version of Mistral Large 4.

Mistral Large 4 is a native multimodal large language model with 100 billion parameters, featuring 52 billion active parameters. It excels in coding, agent workflows, and multimodal understanding, reaching the level of the world's strongest open-source model. It also leads in critical enterprise workloads such as cybersecurity, finance, and law. The model will be open-sourced by the end of this month and is currently available for experience through the public beta API of Mistral Studio.

Graph Center Agent: How to Utilize Graph Structures for Agent Reasoning

Amazon Science has released Graph Center Agent technology, which combines a continuous synchronized graph (digital twin) representing the network with device attributes and connections, with cascade graph algorithms (decomposition, aggregation, tracing) and agent orchestration to achieve minute-level root cause analysis of complex network failures, achieving 95% accuracy in a demonstration at NTT DOCOMO's MWC.