🍔🧠 GitHub Gems: Top Projects to Learn by Building

🍔  THIS WEEK’S MENU  🥗

• 📚 How Shazam's magic fingerprints music, how Uber computes ETAs at scale, and learn to code with real-world projects.

• 🗞️ Tesla bots can now crack eggs safely, Amazon to beam internet between satellites, and the funding of the French Mistral AI startup.

• 👨🏻‍💻 Quick byte: Use Python decorators to cache expensive functions.

Read time: 5 minutes

Food for Thought
A mindset, an example, and an action item to start the week

Mindset: This quote inspires perseverance - with dedication, we can achieve goals that once seemed impossible.

Example: Airbnb disrupted the hotel industry by allowing people to rent out their homes, achieving exponential growth despite initial doubts.

Action item: Identify one goal that seems daunting and break it into smaller, actionable steps you can start on today.

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The Rabbit Hole
Deep dives, trends, and resources curated to stay ahead

💾  SIDE DISHES  💾

ARTICLE (large language what?) → Explaining ChatGPT in clear and simple terms under 20 minutes

TOOL (free AI value) → Use AI to practice and ace your next system design interview

ARTICLE  (rm -rf) → Deleting 50k lines of code from a production app serving > 100K requests per day

GITHUB REPO (how to use the new Apple stuff) → Examples on using MLX, the new open source framework from Apple

ARTICLE (git) → GQL: How to query git and extract data from it

ARTICLE (html, really?) → 10 weird HTML hacks that shaped the internet

The Weekly Digest
Software, AI, and startup news worth your time

💡 Tesla's Latest Humanoid Robot Optimus Gen 2 Can Handle Eggs Without Cracking Them (2 min)

Brief: Tesla unveils Optimus Gen 2, a non-production prototype humanoid robot that showcases impressive improvements such as better balance, weight reduction, increased walk speed, and most notably, the ability to manipulate eggs without breaking them.

Takeaway: Although skepticism is warranted following recent AI demonstration controversies, Tesla's Optimus Gen 2 represents the company's progress in humanoid robotics, positioning them at the forefront of innovation in this field. This development showcases Tesla's commitment to pushing boundaries and revolutionizing automation technologies.

✨ Amazon's Project Kuiper Successfully Tests Advanced Optical Inter-Satellite Links (2 min)

Brief: Amazon's Project Kuiper has validated its advanced optical inter-satellite links (OISL) technology, enabling faster data transfer in space through a mesh network that can connect multiple spacecraft simultaneously.

Takeaway: With the success of its OISL technology, Amazon aims to revolutionize satellite internet service, offering higher throughput and reduced latency, positioning itself as a dominant player in the emerging market of low Earth orbit satellite networks.

📰 French Startup Mistral AI Closes $415M Funding Round (2 min)

Brief: Mistral AI, a French startup co-founded by Google's DeepMind and Meta alums, has closed its Series A funding round, raising €385 million ($415 million) and valuing the company at around $2 billion. The company is focused on foundational models and has released its first model, Mistral 7B, as a free download for developers to run on their devices and servers.

Takeaway: Mistral AI's successful funding round and focus on foundational models highlight the growing interest and investment in AI technology. The company's open technology angle and lobbying efforts for exemptions in AI regulation underscore the importance of balancing innovation and regulation in the AI industry.

🤖 OpenAI's Superalignment Program Aims to Control Future Superintelligent AI Systems (2 min)

Brief: OpenAI's superalignment program seeks to tackle the challenge of controlling future superintelligent AI systems through a test involving a weak AI model supervising a strong one, showcasing the potential to align AI behavior with human goals.

Takeaway: OpenAI's research and experimentation with aligning AI behavior demonstrate their commitment to addressing the future challenges associated with superintelligent AI systems, highlighting the importance of ethical considerations and control in shaping the development of AI technology.

🔍 Google Launches Gemini: A Large Multimodal Model for Text, Images, and Audio (2 min)

Brief: Google introduces Gemini, a powerful Large Multimodal Model (LMM) that combines text, images, and audio capabilities, enabling a wide range of applications and tasks.

Takeaway: Gemini's launch signifies Google's commitment to advancing multimodal AI models, facilitating enhanced text understanding, image processing, and audio analysis, and offering new possibilities for innovative applications and research in various fields.

🔎 AI System FunSearch Helps Mathematicians Generate New Solutions (2 min)

Brief: FunSearch, an AI system based on large language models, is enabling mathematicians to generate new solutions to complex mathematical problems. The system uses specially trained language models to create computer programs that yield potential solutions, making it more effective than previous methods. This has implications for various fields in mathematics and computer science.

Takeaway: The development of FunSearch highlights the potential of AI in assisting mathematicians and researchers in finding novel solutions to complex problems. By harnessing the power of large language models, FunSearch can improve upon existing solutions and contribute to advancements in mathematics and computer science.

The Quick Byte
One coding tip because you’re technical after all

Decorators in Python provide a powerful way to modify the behavior of functions or classes. A particularly useful application is implementing caching, which can significantly improve performance in certain scenarios by storing the results of expensive function calls and reusing them when the same inputs occur again.

Wen?

• Expensive Computation: Best for functions with time-consuming operations, like complex calculations or data processing tasks, where the results are reusable.

• Repeated Calls with Same Arguments: Ideal when the function is called multiple times with the same arguments, as it avoids redundant computations.

• Limited Variation in Input: Effective in scenarios where the function inputs don't vary widely, as caching a large number of different inputs can consume substantial memory.

Why?

• Performance Optimization: Caches results of expensive function calls, reducing the overall execution time when functions are called repeatedly with the same arguments.

• Memory Efficiency: The lru_cache decorator allows you to specify a maxsize parameter to limit memory usage, using a least-recently-used policy to discard old entries.

• Ease of Implementation: Simple to apply to existing functions without altering their core logic, making it a non-invasive performance enhancement.

Burp-A-Laugh
The most important meal of your day