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TinyFish Launches Full Web Infrastructure Platform for AI Agents — Search, Fetch, Browser, and Agent Under One API Key

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AI agents struggle with tasks that require interacting with the live web — fetching a competitor’s pricing page, extracting structured data from a JavaScript-heavy dashboard, or automating a multi-step workflow on a real site. The tooling has been fragmented, requiring teams to stitch together separate providers for search, browser automation, and content retrieval. TinyFish, a […]

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NVIDIA and the University of Maryland Researchers Released Audio Flamingo Next (AF-Next): A Super Powerful and Open Large Audio-Language Model

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Understanding audio has always been the multimodal frontier that lags behind vision. While image-language models have rapidly scaled toward real-world deployment, building open models that robustly reason over speech, environmental sounds, and music — especially at length — has remained quite hard. NVIDIA and the University of Maryland researchers are now taking a direct swing

NVIDIA and the University of Maryland Researchers Released Audio Flamingo Next (AF-Next): A Super Powerful and Open Large Audio-Language Model Read More »

MiniMax Releases MMX-CLI: A Command-Line Interface That Gives AI Agents Native Access to Image, Video, Speech, Music, Vision, and Search

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MiniMax, the AI research company behind the MiniMax omni-modal model stack, has released MMX-CLI — Node.js-based command-line interface that exposes the MiniMax AI platform’s full suite of generative capabilities, both to human developers working in a terminal and to AI agents running in tools like Cursor, Claude Code, and OpenCode. What Problem Is MMX-CLI Solving?

MiniMax Releases MMX-CLI: A Command-Line Interface That Gives AI Agents Native Access to Image, Video, Speech, Music, Vision, and Search Read More »

Meta AI and KAUST Researchers Propose Neural Computers That Fold Computation, Memory, and I/O Into One Learned Model

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Researchers from Meta AI and the King Abdullah University of Science and Technology (KAUST) have introduced Neural Computers (NCs) — a proposed machine form in which a neural network itself acts as the running computer, rather than as a layer sitting on top of one. The research team presents both a theoretical framework and two

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MiniMax Just Open Sourced MiniMax M2.7: A Self-Evolving Agent Model that Scores 56.22% on SWE-Pro and 57.0% on Terminal Bench 2

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MiniMax has officially open-sourced MiniMax M2.7, making the model weights publicly available on Hugging Face. Originally announced on March 18, 2026, MiniMax M2.7 is the MiniMax’s most capable open-source model to date — and its first model to actively participate in its own development cycle, a meaningful shift in how large language models are built

MiniMax Just Open Sourced MiniMax M2.7: A Self-Evolving Agent Model that Scores 56.22% on SWE-Pro and 57.0% on Terminal Bench 2 Read More »

Liquid AI Releases LFM2.5-VL-450M: a 450M-Parameter Vision-Language Model with Bounding Box Prediction, Multilingual Support, and Sub-250ms Edge Inference

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Liquid AI just released LFM2.5-VL-450M, an updated version of its earlier LFM2-VL-450M vision-language model. The new release introduces bounding box prediction, improved instruction following, expanded multilingual understanding, and function calling support — all within a 450M-parameter footprint designed to run directly on edge hardware ranging from embedded AI modules like NVIDIA Jetson Orin, to mini-PC

Liquid AI Releases LFM2.5-VL-450M: a 450M-Parameter Vision-Language Model with Bounding Box Prediction, Multilingual Support, and Sub-250ms Edge Inference Read More »

Researchers from MIT, NVIDIA, and Zhejiang University Propose TriAttention: A KV Cache Compression Method That Matches Full Attention at 2.5× Higher Throughput

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Long-chain reasoning is one of the most compute-intensive tasks in modern large language models. When a model like DeepSeek-R1 or Qwen3 works through a complex math problem, it can generate tens of thousands of tokens before arriving at an answer. Every one of those tokens must be stored in what is called the KV cache

Researchers from MIT, NVIDIA, and Zhejiang University Propose TriAttention: A KV Cache Compression Method That Matches Full Attention at 2.5× Higher Throughput Read More »

How to Build a Secure Local-First Agent Runtime with OpenClaw Gateway, Skills, and Controlled Tool Execution

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In this tutorial, we build and operate a fully local, schema-valid OpenClaw runtime. We configure the OpenClaw gateway with strict loopback binding, set up authenticated model access through environment variables, and define a secure execution environment using the built-in exec tool. We then create a structured custom skill that the OpenClaw agent can discover and

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How Knowledge Distillation Compresses Ensemble Intelligence into a Single Deployable AI Model

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Complex prediction problems often lead to ensembles because combining multiple models improves accuracy by reducing variance and capturing diverse patterns. However, these ensembles are impractical in production due to latency constraints and operational complexity. Instead of discarding them, Knowledge Distillation offers a smarter approach: keep the ensemble as a teacher and train a smaller student

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Alibaba’s Tongyi Lab Releases VimRAG: a Multimodal RAG Framework that Uses a Memory Graph to Navigate Massive Visual Contexts

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Retrieval-Augmented Generation (RAG) has become a standard technique for grounding large language models in external knowledge — but the moment you move beyond plain text and start mixing in images and videos, the whole approach starts to buckle. Visual data is token-heavy, semantically sparse relative to a specific query, and grows unwieldy fast during multi-step

Alibaba’s Tongyi Lab Releases VimRAG: a Multimodal RAG Framework that Uses a Memory Graph to Navigate Massive Visual Contexts Read More »