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Deploy Public MCP servers as an API endpoint and integrate its tools into LLM workflows using function calling.
MCP Architecture Explained for Infra Teams: A 2026 Guide | Clarifai Read More »
AI agents prefer Bitcoin for digital wealth storage, forcing finance chiefs to adapt their architecture for machine autonomy. When AI systems gain economic autonomy, their internal logic dictates how corporate capital flows. Non-partisan research by the Bitcoin Policy Institute evaluated how these frontier models would transact if operating as independent economic actors. The study tested
AI agents prefer Bitcoin shaping new finance architecture Read More »
Current end-to-end robotic policies, specifically Vision-Language-Action (VLA) models, typically operate on a single observation or a very short history. This ‘lack of memory’ makes long-horizon tasks, such as cleaning a kitchen or following a complex recipe, computationally intractable or prone to failure. To address this, researchers from Physical Intelligence, Stanford, UC Berkeley, and MIT have
Google has released Gemini 3.1 Flash-Lite, the most cost-efficient entry in the Gemini 3 model series. Designed for ‘intelligence at scale,’ this model is optimized for high-volume tasks where low latency and cost-per-token are the primary engineering constraints. It is currently available in Public Preview via the Gemini API (Google AI Studio) and Vertex AI.
An artificial intelligence system has, for the first time in Europe, completed a payment inside a live banking network without a human entering the final command. Banco Santander and Mastercard confirmed that they had executed a live end-to-end payment initiated and completed by an AI agent, a software system operating within the bank’s own regulated
Santander and Mastercard run Europe’s first AI-executed payment pilot Read More »
News data is no longer a media problem — it is an infrastructure problem. In 2026, organizations across finance, cybersecurity, AI, compliance, and market intelligence depend on structured news ingestion as a foundational data layer. News feeds power algorithmic trading signals, reputational risk detection, sanctions monitoring, AI model grounding, geopolitical forecasting, and crisis response systems.
Alibaba has released OpenSandbox, an open-source tool designed to provide AI agents with secure, isolated environments for code execution, web browsing, and model training. Released under the Apache 2.0 license, the proposed system targets to standardize the ‘execution layer’ of the AI agent stack, offering a unified API that functions across various programming languages and
LLM evaluation tools help teams measure how a model performs across various tasks, including reasoning, summarization, retrieval, coding, and instruction-following. They analyze performance trends, detect hallucinations, validate outputs against ground truth, and benchmark improvements during fine-tuning or prompt engineering. Without robust evaluation frameworks, organizations risk deploying unpredictable or harmful AI systems. How LLM Evaluation Tools
Alibaba’s Qwen team has released the Qwen3.5 Small Model Series, a collection of Large Language Models (LLMs) ranging from 0.8B to 9B parameters. While the industry trend has historically favored increasing parameter counts to achieve ‘frontier’ performance, this release focuses on ‘More Intelligence, Less Compute.‘ These models represent a shift toward deploying capable AI on
In the current AI landscape, agentic frameworks typically rely on high-level managed languages like Python or Go. While these ecosystems offer extensive libraries, they introduce significant overhead through runtimes, virtual machines, and garbage collectors. NullClaw is a project that diverges from this trend, implementing a full-stack AI agent framework entirely in Raw Zig. By eliminating
