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A Google Exec Ported Command & Conquer to Native iOS With Claude Code and Fable 5

A Google AI Studio lead ported the 2003 strategy game Command & Conquer: Generals — Zero Hour to native iPhone, iPad, and Mac using Anthropic's Claude Code and the Fable 5 model. We break down what the viral demo really shows about agentic coding — and what it doesn't.

9 min read

July 7, 2026

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NVIDIA's Kyber NVL144 Delayed to 2028? The Report and the Denial

A SemiAnalysis report says NVIDIA's Kyber NVL144 rack (Rubin Ultra) slips more than 12 months to 2028 on PCB midplane defects; NVIDIA disputes it, calling its roadmap intact. We separate what is confirmed from what is contested.

The UN Just Held Its First Global AI Governance Dialogue — Here's What It Can and Can't Do

The UN convened its first Global Dialogue on AI Governance in Geneva on July 6-7, 2026. What Guterres, Bengio and the co-chairs said — and why a forum with no binding power still matters.

Hollywood Fights Seedance in Public, Quietly Uses It in Private

Hollywood publicly fought ByteDance's Seedance with cease-and-desist letters, yet an early-July 2026 Los Angeles Times investigation finds studios quietly tolerate the AI video tool on a 'don't ask, don't tell' basis, just as Seedance 2.5 launches. Here is what is verified, attributed source by source, and what is not.

The AI Glossary: 45+ Terms Everyone Should Know (Plain English)

Tokens, agents, RAG, MCP, quantization — decoded. A plain-English glossary of 45+ AI terms, each defined in one or two clear sentences you can trust.

AI Training vs Inference: Where the Money Really Goes

AI has two costs: training a model once, a massive one-time expense, and inference, the recurring cost of answering every request. At scale, inference is roughly 80 to 90 percent of a model's lifetime compute bill. This explainer defines both phases, shows why the training-is-expensive myth breaks at scale, and breaks down what drives inference cost and how to control it.

RAG vs Fine-Tuning vs Prompt Engineering: Which One Do You Actually Need?

RAG, fine-tuning, and prompt engineering solve different problems. Prompt engineering shapes the instructions, RAG supplies external knowledge, and fine-tuning changes behavior. Start with prompting, add RAG for your own data, and fine-tune only when both fall short.

What Are AI Agents? How They Work (With Business Use Cases)

An AI agent is an AI system that pursues a goal: it plans, uses tools like APIs and a browser, acts, checks the result, and repeats until the goal is met — unlike a chatbot, which answers one prompt and stops. Here is how AI agents work and where they fit in a business.

How Do Large Language Models Actually Work? (Plain English)

A large language model writes text by repeatedly predicting the most likely next word, one token at a time. This plain-English guide explains next-token prediction, tokens, embeddings, the transformer and attention, two-phase training, and why LLMs hallucinate.

Kling AI Raises $2.8 Billion as Alibaba, Tencent and Baidu Fund China's Video Generation War

Kuaishou's Kling AI raised about $2.8 billion at a $15 billion pre-money valuation, backed by Alibaba, Tencent and Baidu. Here is what the deal means for the AI video war against Veo, Seedance and Runway.

How Much VRAM Do You Need to Run an LLM? The Full Sizing Table

How much VRAM to run an LLM? Roughly 2 GB per billion parameters in FP16, about 1 GB in 8-bit, and 0.5 to 0.6 GB in 4-bit, plus 15 to 20 percent overhead. This reference table maps sizes from 7B to 405B-plus across FP16, Q8, and Q4 to the exact hardware that runs them.

Anthropic Built Claude a Science Workbench — and Gave It a Fact-Checker

Anthropic's Claude Science is a beta research workbench with 60+ science skills and a reviewer agent that flags bad citations and untraceable numbers.

13 min read

July 6, 2026

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