Good Morning! Facebook's decision to abandon Git in favor of Mercurial highlights the challenges of managing massive codebases and the importance of scalable version control systems. A JavaScript developer has demonstrated the language's impressive capabilities by simulating 20 million particles with smooth performance, showcasing optimization techniques and the power of modern web technologies. Google is partnering with the Indian government to foster AI innovation, aiming to support 10,000 startups and train thousands of developers in cutting-edge AI tools and technologies.

— Forrest Knight&Meghanadh Vasireddy

Facebook's Decision to Abandon Git

Back in 2012, Facebook faced a big problem with Git. Their code was getting huge - bigger than the Linux kernel! This made Git really slow. They tested what might happen in the future and found that simple Git tasks could take 45 minutes.

Facebook looked for solutions:

• They asked Git experts for help, but weren't happy with the answer to split up their big code repository.

• They checked out other options like Perforce, but found problems with those too.

• Finally, they found Mercurial. It was fast like Git, but easier to change and improve.

This choice led Facebook to make "stacked diffs," a new way of working with code. Former Facebook workers even spread these ideas to other companies. The story shows why it's important for code tools to handle growth well and how working together openly can shape tech choices.

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How Fast is Javascript? Simulating 20,000,000 Particles

A coder has achieved something impressive: simulating 20 million tiny dots in JavaScript at smooth speeds. This shows how powerful JavaScript has become for complex tasks.

Key Technical Points:

• Used web workers to split work across multiple CPU cores

• Employed SharedArrayBuffers for shared memory between threads

• Optimized memory usage and access patterns

The project went through several improvement stages:

1. Started with special arrays (typed arrays) for faster memory use

2. Added a technique called double buffering to work on the next frame while showing the current one

3. Fixed slow memory access issues

4. Created a grid system to count particles, reducing memory needs

For drawing the dots, the project uses WebGL with a custom shader. This lets the graphics card handle the visuals while the main processor does the calculations.

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Google Boosts AI Development in India

Google is teaming up with the Indian government to help 10,000 startups create new AI tools. They announced this plan at a big event in Bengaluru, saying they think India will lead in making new AI technology.

Google's efforts include:

• Teaching 25,000 developers in 43 Indian cities how to use their newest AI tools

• Running a three-month program to help startups grow, teaching them about AI, app-making, and business skills

At the event, three startups showed how they're using Google's AI called Gemini:

1. Miko.AI made a smart robot for kids that gives safe information

2. Karya created a way for people with less money to help make AI data and earn more

3. Cropin built a tool that uses farm and weather information to help grow food better

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🔥 More Notes

• The US Supreme Court Kneecapped US Cyber Strategy

• Musk to Move X, SpaceX to Texas in Deepening Rightward Shift

• Former OpenAI researcher’s new company will teach you how to build an LLM

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