🍔🧠 Containers: Netflix's Predictive CPU Isolation
PLUS: Meta Llama 3 state-of-the-art 🦙, Tinder's API gateway architecture 🛰️, Next-gen Atlas unveiled for commercialization 🤖
Happy Monday! ☀️
Welcome to the first-ever native issue of Hungry Minds on Substack.
If you aren’t subscribed yet, join smart, curious, and hungry folks by subscribing here:
🍔 THIS WEEK’S MENU 🥗
📚 Netflix's predictive CPU isolation for containers. Understand Tinder's API Gateway architecture. Explore advanced retrieval augmented generation.
🗞️ Boston Dynamics commercializes next-gen electric Atlas robot. Meta unveils state-of-the-art Llama 3 models. Adobe develops AI-powered generative video tools.
👨🏻💻 Quick byte: Memory-efficient large model training in PyTorch using gradient checkpointing.
Reading time: 5 minutes
Food for Thought 🧠
A mindset, an example, and an action item to start the week
‘Everything you've ever wanted is on the other side of fear.’
George Addair
Mindset: Embracing fear is the key to unlocking your fullest potential.
Example: SpaceX regularly tackles the fear of failure in aerospace innovation, achieving historic milestones.
Action Item: Identify one fear today and take a small step to confront it directly.
The Rabbit Hole 🐰
Deep dives, trends, and resources curated to stay ahead
Predictive CPU isolation of containers at Netflix
By Benoit Rostykus, Gabriel Hartmann
The Architecture of Tinder's API Gateway
The design of Tinder's API gateway. Plus, a study on the Ballmer peak, how to review code as a junior dev, Mistral's new LLM and more.
How Zapier Automates Billions of Tasks
Written by Neo Kim
System Design: Vertical vs Horizontal Scaling
Written by Ashish Pratap Singh
API Gateway vs. Load Balancer vs. Reverse Proxy
Written by Dr Milan Milanović
LUC #50 [Special Edition]: The Most Popular Issues of the LUC Newsletter
We simply love Level Up Coding!
My 25-Year Engineering Career Retrospective
Written by Nicola Ballotta
💾 SIDE DISHES 💾
ARTICLE (rag to riches)
A Comprehensive Tutorial on Advanced Retrieval Augmented Generation
GITHUB REPO (coding interviews)
A complete study plan to prepare for coding interviews
ESSENTIAL (linux)
Build your own Linux system from the source
ARTICLE (sheets in the backend)
How Row Zero stream sheets content from the server at scale
ESSENTIAL (git)
The guide to git I never had
ARTICLE (SAAS architecture)
Why self-hosting is still a great option
TOOL (ohmygit)
An open-source game to learn about git
PAPER (infinite attention)
The paper from folks at Google on infinite attention
The Weekly Digest 🗞️
Software, AI, and startup news worth your time
🤖 Boston Dynamics Introduces Next-Gen All-Electric Atlas Robot for Commercialization (4 min)
Brief: Boston Dynamics unveils a new, all-electric "Atlas" robot, retiring the iconic hydraulic version, showcasing advanced capabilities in a symbolic video farewell.
💡 Meta Unveils Next-Gen Llama 3 Models with State-of-the-Art Capabilities (5 min)
Brief: Meta introduces the next generation of Llama models, Llama 3, showcasing significant advancements in performance, reasoning, coding, and optimization for real-world scenarios.
⚙️ Adobe Developing AI-Powered Generative Video Tools (4 min)
Brief: Adobe introduces a cutting-edge AI model for video generation, offering features like object addition and generative extend, while emphasizing metadata tools like Content Credentials for media authenticity.
🚀 Elon Musk's x.AI Unveils Multimodal Model Grok-1.5 Vision (3 min)
Brief: Elon Musk's x.AI introduces Grok-1.5 Vision, a cutting-edge multimodal model excelling in real-world understanding and interaction, showcasing progress and potential in AI innovation.
✨ TikTok Introduces TikTok Notes, a Photo-sharing App Similar to Instagram (2 min)
Brief: TikTok unveils TikTok Notes, a new photo-sharing app that mirrors Instagram but with added features like headlines for images above captions and a Pinterest-style homepage layout.
⚖️ Microsoft's $1.5B Investment Shifts Tech Power Balance in UAE (4 min)
Brief: Microsoft's $1.5B investment in UAE's G42 signifies a strategic move amid escalating U.S.-China tech tensions, positioning the country as a key player in the AI race.
The Quick Byte 💾
One coding tip because you’re technical after all
This week’s coding challenge (by John Crickett):
This week’s tip:
When training large neural networks in PyTorch, memory efficiency becomes crucial. Using techniques like gradient checkpointing can significantly reduce memory usage at the cost of additional computation, allowing for the training of larger models or larger batches.
Wen?
Large Model Training: Essential for training models that would otherwise not fit into GPU memory.
Resource-Constrained Environments: Useful when training on hardware with limited memory resources.
Why?
Resource Efficiency: Allows for more efficient use of computational resources by trading off memory usage for compute.
Scalability: Enables scaling up of model complexity and training dataset size without requiring proportional increases in hardware capacity.
Flexibility: Offers a strategic option to manage memory usage during model development and training phases.
The Job Feast 💼
A fresh
cheesejob board if you’re looking for a change
Burp-A-Laugh 🤣
The most important meal of your day
That’s it for today! ☀️
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Thanks for spending part of your Monday morning with Hungry Minds.
See you in a week — Alex.
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Great post and great resources Alexandre! Thanks for the mention 🙂
An awesome post with solid list of resources, thanks for putting it together Alex!
AI is improving rapidly day by day!