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This week in tech and crypto, Bitcoin hits a new all-time high as ETFs and altcoins surge, while DeFi sees a breakthrough with Kamino integrating tokenized stocks as collateral. Major institutional moves include Ant Group's USDC integration and new U.S. crypto custody guidelines. In AI, Moonshot’s trillion-parameter Kimi K2 challenges proprietary models, the EU releases an AI Code of Practice, and xAI debuts Grok-4 with minimal censorship. Meanwhile, Docker and Google Cloud roll out powerful tools for AI and app development, and new insights emerge on cloud capacity planning and automation-driven workflows
Let's dive 🚀 into the topics:
🌐 Web3
Dose of weekly crypto news, global market shifts, and institutional updates.
This move marks a significant milestone for decentralized finance (DeFi), making Kamino the first major borrow/lend protocol to onboard tokenized equities as collateral.
World Network, co-founded by OpenAI’s Sam Altman, and the intellectual property (IP) blockchain Story have announced a strategic partnership aimed at empowering creators to prove authorship and monetize their work securely onchain.
Ant Group’s planned integration of USDC, pending regulatory approval, marks a significant step in the institutionalization of stablecoins and the evolution of global digital finance infrastructure.
This joint statement by U.S. financial regulators represents a pivotal step in integrating digital assets into the mainstream financial system. It provides banks with the clarity and structure needed to safely and efficiently manage cryptocurrency custody, while maintaining strong oversight and consumer protections.
📘 AI/ML
In this tutorial, you will learn how to use n8n’s new model selector node to set up intelligent AI model routing that automatically selects the best model for each task at hand.
This represents a major breakthrough in open-source AI, challenging the dominance of proprietary models like GPT-4 by delivering superior performance, broader capabilities, and free accessibility.
The EU published an AI Code of Practice to help companies comply with AI Act obligations on safety, transparency and copyrigh
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An AI veteran who's interviewed 100+ leaders reveals the exact framework that took him from 4-hour workflows to 90-second automation
The Windsurf deal was set to be one of OpenAI’s most significant acquisitions to date — now, it marks yet another headache in what has been a rocky summer for the AI giant. The fallout stemming from Microsoft complications also adds fresh strain to an already frigid relationship between the former AI power couple.
xAI announced Grok-4, which is now available for Perplexity Pro and Max subscribers, as announced by @perplexity_ai and @AravSrinivas. The model is described as the "LEAST censored frontier model" and shows strong long-context performance. However, it has faced criticism for its tendency to search Elon Musk's tweets for answers on controversial topics.
🔧 DevOps
Docker’s latest announcements mark a significant leap for developers building AI-powered and agentic applications. With enhanced Compose support, seamless cloud offloading, and deep integrations with cloud and AI partners, Docker is making it easier than ever to build, run, and scale intelligent software from development to production.
This new offering aims to accelerate the iterative experimentation process that typically consumes the majority of a data scientist’s time, including data preparation, model experimentation, and evaluation.
This article breaks down how to solve classic Python pattern problems, focusing on star patternsusing nested loops. It provides clear logic, code, and step-by-step explanations for beginners and those looking to strengthen their coding fundamentals.
In this course, you will learn what Vibe Coding means, how it fits into modern software engineering, and then dive straight into building production-ready workflows using n8n, AI coding agents, and custom backend logic.
💡 Did you know?
In this article, you’ll learn what modern capacity planning looks like in the cloud. You’ll learn how it’s different from older methods, why autoscaling isn’t always enough, and which metrics matter most.
