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DeepSeek has reportedly raised $15 billion in one of China's largest funding rounds, just days after the U.S. ordered federal agencies to remove its technology over national security concerns.
The Big Hardening begins
The Big Hardening begins
At the GTC Berlin conference, European financial institutions including Revolut, Starling Bank, Lloyds, and Santander announced that they are building production‑grade AI capabilities based on NVIDIA’s accelerated computing platform and open‑source weight models—such as PRAGMA, the Nemotron series, and the Kumo family—covering core use cases like trading analytics, speech recognition, fraud detection, and data pipeline acceleration, while emphasizing data sovereignty, cost control, and compliant deployment.
NVIDIA has expanded the Cosmos platform by introducing the Cosmos Data Factory blueprint, the Cosmos Framework training optimization tool, and the Cosmos 3 NIM microservice, supporting multimodal data generation, adaptation to open-source world models (such as GR00T and QWEN), and low-latency inference; real-world applications have already been deployed by Porsche, ANYbotics, Ultralytics, ADNOC, and others.
NVIDIA has released the Earth-2 open-source AI model family for Europe, including the region-specific nowcasting model StormScope EU, and is collaborating with organizations such as AXA, Vaisala Xweather, the University of Manchester, and TotalEnergies to conduct real-world validation, covering tasks like storm risk assessment, air quality modeling, solar power generation forecasting, and radar terrain inversion.
NVIDIA, in collaboration with governments and technology partners across multiple European countries, is advancing sovereign, controllable AI applications—leveraging open-source large models such as Nemotron and synthetic persona datasets—in Germany, Poland, the United Kingdom, France, Greece, and other nations. These efforts span areas including medical image analysis, employment services, digital government assistants, classified information processing, and localized language modeling.
AI startup Recursive has unveiled Flint, an open-source coding model that it claims was developed primarily using its in-house AI research system, Eureka Machine. With just 40 billion parameters and only 2.5 billion activations in practice, the model can run offline on a standard laptop—such as an M4 Pro MacBook—at an inference speed of 131 tokens per second, outperforming most models of comparable size on benchmarks like SWE-Bench.
Walmart has officially launched Agent Gateway (an AI agent gateway) along with its accompanying Agent Profiles feature, enabling authorized AI agents—such as ChatGPT, Gemini, Meta Muse, and others—to perform searches and place orders on behalf of users across Walmart and Sam’s Club platforms. User control over agent activities is ensured through mechanisms like independent account configuration, transaction approvals, and spending limits. This move stands in stark contrast to Amazon’s recent ban on AI‑powered shopping agents.
OpenAI’s cutting-edge GPT-6 and 6.1 series models (Astra, Sol, Luna) will be launched on Google Cloud Model Garden in the coming weeks and integrated into Google’s agent-driven programming tool, Antigravity; this move makes Google the first mainstream cloud provider to offer all three major closed-source large models—Gemini, Claude, and GPT.
Claude Mods is Anthropic’s programmable plugin system for Claude Code, representing an early form of the “Attention Interface”—it shifts the traditional machine-oriented agent harness toward a customizable interaction layer centered on human attention. Users can write Mods in TypeScript/JS or have Claude generate them automatically using natural language, thereby determining when to be interrupted, what content to see, and what decisions to make.
Claude Mods is a programmable plugin system for developers launched by Anthropic, marking a shift of the ‘agent harness’ from a machine-side interface to a human-side interface—namely, the ‘Attention Interface’. It enables users to customize Claude Code’s behavior, rendering, and interaction logic via TypeScript/JavaScript, thereby facilitating co-design workflows between humans and AI. This mechanism has already been applied to built-in features (such as You Should Know) and supports users in building plugins themselves or having them generated with Claude’s assistance.
Mistral and NVIDIA announced a deepened collaboration, integrating Mistral’s Large 4 model, physics-based modeling pipelines, and NVIDIA’s accelerated computing stack (CUDA-X, Warp, Omniverse) to co-develop AI-native engineering workflows for industries such as aerospace, automotive, and semiconductors. The two parties will jointly release open-source datasets and public evaluation benchmarks, covering the assessment of agent capabilities in physics-informed AI and CAE/EDA use cases.
NVIDIA announced that its cloud partners across Europe, the Nordics, Africa, and Central Asia are scaling up regional AI computing infrastructure based on the NVIDIA DSX platform, focusing on sovereign computing (local deployment), open model support (such as Mistral Large 4 and the Nemotron series), and AI agent security boundaries (via the OpenShell reference architecture), covering use cases including training, inference, physics‑based AI, and retail agents.
An open source “bomb” drops from China
An open source “bomb” drops from China
NVIDIA has launched Kumo Relational, a pre-trained relational foundation model that can perform predictive tasks—such as churn prediction, fraud detection, and demand forecasting—directly on enterprise‑grade relational databases, without the need for task fine-tuning, feature engineering, or table flattening. In 41 benchmark tests spanning 15 databases, it outperformed supervised models like XGBoost across the board, and on the SAP SALT enterprise benchmark, its MRR metric surpassed AutoGluon by 8%. The model supports databases with up to 500 billion rows and enables zero‑code predictive queries via Predictive Query Language (PQL).
Learn how OpenAI built ChatGPT’s LLM-powered ad stack to understand conversational intent, keep ads separate from answers, and deliver relevant ads at scale.
In October 2026, Google announced that it would extend Gemini’s Personal Intelligence feature to in-vehicle scenarios, initially rolling it out to Android Auto users and expanding to vehicles equipped with the Google Built-in system over the following months. This feature is optional and relies on user authorization to access local data such as Gmail and Calendar to enhance response relevance.
My latest vibe coded game experiment is a Command & Conquer style RTS (Real Time Strategy) game called Battle Drones (play it here). Unlike my previous experiments, this one is actually fun to play. I'm somewhat embarrassed to admit that I got there by telling Claude to "Make it a LOT more fun". It also supports multiplayer between nearby devices using audio to synchronize game state! Here's what I've built so far, and some of the things I learned along the way. Battle Drones How I built this v1: the initial prototype v2: full sprites v3: varied terrain v4: the fun update v5: Battle Drones goes 3D v8: Archipelago v10: Goliath, and agent battles Agent battles v11: Random Maps v12: Multiplayer via sound Some thoughts Update: Online multiplayer support Battle Drones My initial goal was to bui
