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NVIDIA Released DeepStream 9.1: Bringing Agentic AI to Vision AI With 13 Skills and Multi-View 3D Tracking

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NVIDIA just released DeepStream 9.1. The update targets a persistent problem in video analytics. Tracking one object across many cameras traditionally requires manual camera calibration and complicated calculations. DeepStream 9.1 addresses this with two additions: Multi-View 3D Tracking (MV3DT) and AutoMagicCalib (AMC). Both ship as agentic skills for coding agents. As a result, developers move […]

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Google Cloud’s Always-On Memory Agent Replaces RAG and Embeddings With Continuous LLM Consolidation on Gemini 3.1 Flash-Lite

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Most AI agents forget. They process a request, answer it, then drop the context. Google Cloud’s generative-ai repository now ships a sample that tackles this directly. It is the Always-On Memory Agent, a reference implementation that treats memory as a running process. Always-On Memory Agent Fundamentally, the project is a lightweight background agent that never

Google Cloud’s Always-On Memory Agent Replaces RAG and Embeddings With Continuous LLM Consolidation on Gemini 3.1 Flash-Lite Read More »

Sakana AI’s Error Diffusion Trains Dale-Compliant Dual-Stream Networks, Reaching 96.7% MNIST and 61.7% CIFAR-10 Without Backpropagation

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Backpropagation dominates deep learning, yet it uses a mechanism the brain likely cannot. Specifically, the backward pass needs exact transposes of forward weight matrices. This is the weight transport problem. Sakana AI’s new paper, Diffusing Blame, confronts this constraint directly. The research team trains networks that obey Dale’s principle while avoiding weight transport entirely. What

Sakana AI’s Error Diffusion Trains Dale-Compliant Dual-Stream Networks, Reaching 96.7% MNIST and 61.7% CIFAR-10 Without Backpropagation Read More »

Build an Agentic Event Venue Operator with MongoDB Atlas, Voyage, and LangGraph

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Introduction This tutorial starts where most agent demos stop: giving the agent persistent memory, operational context, and a place to write back what happened. An event operator does not just need an agent that can summarize a weather report or generate a generic plan. The operator needs an agent that can remember what happened at

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Build an Agentic Event Venue Operator with MongoDB Atlas, Voyage, and LangGraph

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Introduction This tutorial starts where most agent demos stop: giving the agent persistent memory, operational context, and a place to write back what happened. An event operator does not just need an agent that can summarize a weather report or generate a generic plan. The operator needs an agent that can remember what happened at

Build an Agentic Event Venue Operator with MongoDB Atlas, Voyage, and LangGraph Read More »

Zyphra Releases ZUNA1.1: An Apache 2.0 EEG Foundation Model With Variable-Length Inputs From 0.5 To 30 Seconds

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This week, Zyphra released ZUNA1.1 under the Apache 2.0 license. The EEG foundation model reconstructs, denoises, and upsamples data across arbitrary channel layouts. It builds on ZUNA1, the Zyphra’s earlier open EEG foundation model. The main change is flexibility, not a jump in raw accuracy. Real EEG recordings are messy. Sessions vary in length, and

Zyphra Releases ZUNA1.1: An Apache 2.0 EEG Foundation Model With Variable-Length Inputs From 0.5 To 30 Seconds Read More »

NVIDIA AI Releases Nemotron 3 Embed: An Open Embedding Collection Whose 8B Checkpoint Ranks #1 on RTEB

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Embedding models decide which passages an agent ever sees. NVIDIA released Nemotron 3 Embed model to work on that layer. It targets production-scale RAG, agentic retrieval, code retrieval, and agent memory. What is Nemotron 3 Embed? The model collection includes three open checkpoints. Nemotron-3-Embed-8B-BF16 is the accuracy-first option. Nemotron-3-Embed-1B-BF16 carries the same design into a

NVIDIA AI Releases Nemotron 3 Embed: An Open Embedding Collection Whose 8B Checkpoint Ranks #1 on RTEB Read More »

Moonshot AI Releases Kimi K3: A 2.8 Trillion Parameter Open MoE Model With Kimi Delta Attention and 1M Context

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Moonshot AI just released Kimi K3. It is a 2.8-trillion-parameter model with native vision and a 1-million-token context window. Moonshot calls it the world’s first open 3T-class model. What is Kimi K3? Kimi K3 is a sparse Mixture-of-Experts (MoE) model built on two architectural updates. Those are Kimi Delta Attention (KDA) and Attention Residuals (AttnRes).

Moonshot AI Releases Kimi K3: A 2.8 Trillion Parameter Open MoE Model With Kimi Delta Attention and 1M Context Read More »

OpenAI Details GPT-Red: An Internal Automated Red-Teaming Model That Beat Human Red-Teamers 84% To 13% On Prompt Injection

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This week, OpenAI published details of GPT-Red, an internal-only automated red-teaming model. Its job is to attack OpenAI’s own models and find prompt injection vulnerabilities. OpenAI gives two reasons. Human red-teaming is time-intensive and does not scale. Commonly used robustness evaluations are already saturated by its latest models. Meanwhile, the attack surface grows. Agents read

OpenAI Details GPT-Red: An Internal Automated Red-Teaming Model That Beat Human Red-Teamers 84% To 13% On Prompt Injection Read More »

SpaceXAI Open-Sources Grok Build: The Rust Agent Harness, TUI, and Tool Layer Behind Its Coding CLI

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SpaceXAI has open-sourced Grok Build, the terminal-based AI coding agent behind its grok CLI. The source landed on GitHub today. The release covers the agent harness, TUI, CLI shell, and developer tooling under the Apache 2.0 license What is Grok Build? A harness is the scaffolding around a model. It assembles context, calls the model,

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