Pokee AI released Pokee-Isaac 28B, a 28B text-only foundation model with a 10M-token context window built to run inside the customer boundary. It scores 93.3% on RULER at 10M tokens, where every baseline in its comparison panel returns 0.0 beyond 2M, and leads BFCL v4 at 70.94 while placing second on Terminal-Bench 2.1. Prefill reaches 137,200 tokens/s at full context on a single B200, with decode flat near 335 tokens/s. Weights are not published; deployment is licensed into VPC, on-premises, or on-device, with list pricing at $0.15/$1.00 per million tokens.

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Dive into the advanced visualization capabilities of the Reflex XY Python library. This tutorial guides you through building high-performance, interactive charts—from handling million-point datasets and real-time streaming to creating custom mark plugins and exporting publication-ready visuals.

The post Designing Scalable Interactive Visualizations with Reflex XY: Composition, Million-Point Rendering, Streaming, Custom Marks, and Export appeared first on MarkTechPost.

Mistral AI has released Shieldstral 1.0 3B, an open-weights, policy-adaptive multimodal safety classifier that frames content moderation as a single yes/no question instead of a fixed harm taxonomy. Operators supply the policy as a plain-language query at inference time and get back a calibrated safety score from one forward pass — no retraining required to re-target the model. Built on Ministral-3-3B-Base-2512 with a Pixtral vision encoder and trained on roughly 54.1M samples, it reports 84.9% average F1 on text safety (matching GPT-OSS-Safeguard-20B), 83.8% on multimodal safety, and 91.3% on Mistral's adaptability benchmark — while fitting in 16GB of VRAM under an Apache 2.0 license.

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Tencent Cloud has open-sourced TencentDB Agent Memory v2.0, a team-level memory hub that turns conversations, documents and code into four governed, reusable assets — Chat Memory, Skill, LLM-Wiki and Code-Graph. It is MIT-licensed, self-hosted via Docker, and integrates with Claude Code, OpenClaw, Hermes and CodeBuddy. The differentiator is not retrieval but governance: ACL-based visibility decides which agent gets which asset, and which version is valid.

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In this tutorial, we build an advanced multimodal retrieval-augmented generation pipeline with NVIDIA NeMo Retriever. We begin by configuring a Python 3.12 environment, installing the required packages, and performing offline PDF text extraction without relying on a GPU or external API key. We then extend the workflow with hosted NVIDIA NIM endpoints to detect page […]

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NVIDIA Labs has open-sourced NOOA (NVIDIA Object-Oriented Agents), a model-agnostic Python framework for building AI agents. Agent development today is split across prompt templates, tool schemas, callback code, and workflow graphs. NOOA collapses all of it into one Python class. Methods are the actions the model can take. Fields are agent state. Docstrings are prompts. […]

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Microsoft has open sourced code-testing-generator, a polyglot unit-test agent shipping in the MIT-licensed dotnet/skills repository. It reads a repository before writing anything — detecting the language, test framework, existing conventions, and the real build and test commands — then plans, writes, runs and validates the tests it produces. On Microsoft's internal 152-task benchmark it completed 140 tasks against 120 for stock GitHub Copilot on the same model, with the gain concentrated almost entirely in vague prompts and diff-targeted requests.

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Liquid AI released LFM2.5-2.6B, an agentic model that plans, calls tools, and completes multi-step tasks entirely on-device. The 2.69B parameter model pairs 22 double-gated short convolution blocks with 8 GQA blocks across 30 layers, handles 131,072 tokens of context, and decodes at 220 tokens/s on an M5 Max in under 2.5 GB. Open weights ship in GGUF, MLX, and ONNX.

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Cloudflare has released Kitesurf, a stateless web browser built specifically for AI agents that runs entirely in V8 isolates on Cloudflare Workers, with no Chromium underneath. The browser drops human-facing features like tabs and extensions in favor of what agents need: machine-readable content, scalability, and isolation. Built in 12 weeks using Rust components like Blitz, Stylo, and Boa JS, it already passes 215,000+ Web Platform Tests. Benchmarks show 3.1–3.8× less CPU and 4.7–7.0× less memory than Chromium on screenshots and HTML extraction. Existing Puppeteer, Playwright, and MCP clients work by adding a single browser=kitesurf parameter, free while in beta.

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In this tutorial, we explore adaptive experimentation using Meta’s Ax with the modern Client API. We work through a complete workflow where we tune a RandomForest model on a synthetic classification dataset while balancing predictive accuracy against model footprint. We begin by defining a mixed search space with integer, float, log-scaled, and categorical parameters, then […]

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Prime Intellect has open-sourced Prime Agent, a coding and research harness built on two abstractions: the Recursive Language Model, which turns sub-agent calls into functions inside a persistent IPython kernel, and the Continual Harness, which lets the agent edit its own prompts, skills, memory, and sub-agent specs mid-run. With Opus 5 it reports 95.5% RHAE Best@1 on ARC-AGI-3, above the reported human expert baseline of 95.4%.

The post Prime Intellect Releases Prime Agent: An Open-Source RLM Harness Where Sub-Agents Are Function Calls Inside Persistent IPython Kernel appeared first on MarkTechPost.

Most coverage of Microsoft's SkillOpt centers on its 52/52 result. The more consequential finding is in Section 4.3: the exported best_skill.md keeps working in environments it was never trained on. A Codex-trained SpreadsheetBench skill lifted Claude Code from 22.1 to 81.8, slightly above the 80.4 that harness reached training its own skill. Retention varies sharply by task type — 102% on spreadsheets, 10% on math — which is what makes the result worth reading closely.

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Reflex has released XY, an Apache-2.0 Python charting library that moves rendering work into a native Rust core and a WebGL2 client. It holds roughly 0.08 seconds render time from 10,000 to 100 million points, exports a 10-million-point interactive scatter at 258 KiB, and keeps exact f64 columns in Python so hover, selection, and zoom drilldown still return original rows. The library is early alpha at version 0.0.1.

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Learn how to build an end-to-end security assessment pipeline for AI agent skills using NVIDIA SkillSpector and LangGraph. In this tutorial, we construct a synthetic skill marketplace, scan for malicious prompt injection, credential access, and risky dependencies, and implement custom YARA rules, baseline suppressions, and CI deployment gates.

The post Building an Advanced AI Skill Security Auditing Pipeline with NVIDIA SkillSpector, LangGraph, YARA Rules, SARIF, and CI Policy Gates appeared first on MarkTechPost.

Y Combinator has open-sourced QM, the multiplayer agent harness it uses internally across accounting, legal, events, and engineering. Released July 31, 2026 under an MIT license, QM gives each employee an isolated workspace and each Slack room its own scoped memory, files, keychain view, permissions, crons, web apps, and durable sandbox. Pi, OpenCode, Codex, and Claude Code all drive the same headless core, so deployments avoid vendor lock-in.

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Genspark has open sourced GenOffice under the Apache License 2.0. It is an AI-native office suite for macOS and Windows, covering Docs, Sheets, Slides and PDF as five Electron apps over one shared engine layer. The notable engineering claim is a byte-preserving round trip: only edited paragraphs are regenerated as OOXML and spliced back into the original file, so untouched blocks keep their original bytes and layout survives in Word. Sheets pairs the open-source Univer core with an in-house Rust xlsx sidecar. AI calls route through a signed-in Genspark account and consume credits. The repository labels this an Alpha.

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In this tutorial, we design an end-to-end evaluation workflow for PerceptionBench. This multimodal benchmark measures fine-grained visual perception capabilities across tasks such as OCR, counting, localization, contextual reasoning, comparison, depth understanding, and hallucination detection. We begin by configuring a Colab-compatible environment, installing the required libraries, and loading a balanced subset of the dataset through a […]

The post Evaluating Multimodal Vision Models with Moonshot PerceptionBench Using Robust Data Loading and Automated Judging appeared first on MarkTechPost.

AI agents, MCP servers, and LLM apps break the core AppSec assumption that applications do what their code says. This guide walks through a practical see-fix-protect framework: a five-layer agentic AI attack surface map, a 12-point misconfiguration checklist, an evidence-based triage matrix, runtime guardrails, and system prompt hardening — plus a maturity self-assessment aligned to NIST AI RMF, OWASP AIMA, ISO/IEC 42001, and the EU AI Act.

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