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  • πŸ”πŸ§  GitHub: Essential Software Design Patterns

πŸ”πŸ§  GitHub: Essential Software Design Patterns

PLUS: Cloudflare logging πŸ“, junior engineer influence πŸ‘©β€πŸ’», frontend tools to know in 2024πŸ› οΈ

Happy Monday! β˜€οΈ

Welcome to the 144 new hungry minds who have joined us since last Monday!
If you aren’t subscribed yet, join smart, curious, and hungry folks by subscribing here.

This week, I am giving a special shoutout to Eugene Shulga and his website: Crushing Tech Education.
It offers amazing content on system design and interview preparation at different price ranges.
Eugene also has a YouTube channel packed with free content on system design, go check it out!

πŸ”Β  THIS WEEK’S MENU Β πŸ₯—

  • πŸ“š Explore awesome design patterns on GitHub. Tips for junior engineers to gain influence. Strategies for cost-effective uptime in startups.

  • πŸ—žοΈ Facebook's Meta in the AI race. OpenAI and ASU partner for ChatGPT. Microsoft's Copilot Pro at $20/month.

  • πŸ‘¨πŸ»β€πŸ’» Quick byte: PyTorch's Autograd for dynamic neural networks.

Reading time: 5 minutes

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

β€˜Believe you can and you're halfway there.’

Theodore Roosevelt

Mindset: This quote emphasizes the power of positive thinking - if you believe in yourself, you're already on the path to success.

Example: Southwest Airlines embraces this "can-do attitude" and empowers employees to take initiative and think outside the box.

Action item: Set a small, achievable goal today that moves you toward a bigger dream - accomplishing it will build your confidence.

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

πŸ’ΎΒ  SIDE DISHES Β πŸ’Ύ

FREE COURSEΒ (interview prep) β†’ Leetcode coding patterns and roadmap for your interviews

ARTICLE (react to it) β†’ ReactJS design patterns explained with visuals

DEEP DIVEΒ (just log it) β†’ How Cloudflare handles its logging strategy

ESSENTIALΒ (frontend tools) β†’ The top front-end tools to know for 2024

ARTICLEΒ (CSS in 2024) β†’ 5 useful CSS snippets packed with value

ARTICLE (re-dundant) β†’ Redundant stories about redundancy

ARTICLEΒ (test test test) β†’ Thoughts on testing in software development by Brandon Smith

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

Brief: As part of its efforts to harness the power of generative AI, Facebook's Meta reorganizes its AI research group, FAIR, to collaborate with the team building generative AI products across Meta's apps, aiming to directly reach its billions of users.

Takeaway: Meta's strategic restructuring signifies its commitment to staying competitive in the fast-paced AI landscape, as it seeks to leverage generative AI to unlock new frontiers of technology and better serve its vast user base.

Brief: OpenAI announces partnership with Arizona State University, providing full access to ChatGPT Enterprise for coursework, tutoring, and research, as well as plans to build a personalized AI tutor and AI avatars for study help.

Takeaway: OpenAI's partnership with ASU highlights the growing importance of AI in education, enabling personalized learning experiences and expanding the use of AI in diverse subjects, ultimately preparing students for a tech-driven future.

Brief: Microsoft introduces Copilot Pro, a paid version of Copilot, with advanced features such as cross-device AI experiences, access to Copilot in various Microsoft applications, faster performance with GPT-4 Turbo, enhanced AI image creation, and the ability to customize Copilot for specific topics.

Takeaway: This release showcases Microsoft's commitment to offering users a comprehensive AI-driven experience across their devices, improving productivity and personalization. It also highlights the growing market demand for advanced AI solutions and the need for companies to continuously innovate and stay competitive.

Brief: MIT researchers have used deep learning to identify a class of compounds that can effectively kill drug-resistant bacteria, including methicillin-resistant Staphylococcus aureus (MRSA), laying the groundwork for the development of new antibiotics.

Takeaway: This breakthrough in using AI to uncover antimicrobial compounds showcases the potential of technology in tackling the ongoing threat of antibiotic resistance, offering hope for the future of healthcare and public health.

Brief: Market research firm IDC reports that Apple has achieved its highest-ever market share for smartphones in 2023, capturing 20.1% of the market and surpassing its competitors, including Samsung, Xiaomi, and Oppo.

Takeaway: Apple's dominant market share in 2023 is indicative of its continuous success in the highly competitive smartphone market, with its high-end flagship models such as the iPhone 14 Pro Max driving sales and solidifying its position as the top player. This achievement highlights Apple's ability to maintain a strong user base and deliver products that resonate with consumers.

Brief: Google has laid off over a thousand employees across various departments since January 10th, with CEO Sundar Pichai warning of more cuts ahead.

Takeaway: This move by Google reflects the company's determination to streamline its operations and prioritize its key objectives, but raises concerns about the impact on employees and the overall job market.

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

PyTorch's Autograd system automatically calculates gradients, which is crucial for training neural networks. This feature allows for dynamic computation graphs, meaning the network can change behavior on each forward pass, very useful for models that change over time like Recurrent Neural Networks (RNNs).

Wen?

  • Training Neural Networks: Essential for calculating the gradients needed during the backpropagation.

  • Implementing Custom Layers: Useful when creating layers or functions with trainable parameters.

  • Dynamic Neural Networks: Ideal for RNNs and models that require varying structures during training.

Why?

  • Simplifies Gradient Calculations: Automatically handles the differentiation, removing the need for manual gradient computation.

  • Dynamic Computation Graphs: Supports models that change over time, unlike static graph frameworks.

  • Improved Readability and Flexibility: Makes the code more intuitive and adaptable to complex neural network architectures.

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

That’s it for today! β˜€οΈ

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Thanks for spending part of your Monday morning with Hungry Minds.
See you in a week β€” Alex.

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