Hey friends! Welcome to ./engineered_mind.sh – in this newsletter we explore & discuss strategies, systems & tools that help us become better, smarter and more effective scientists, gadgeteers and thinkers.
❤️ Weekly Favourite Things
🎬 My Favourite Video
🏫 Courses – One Free Month of Skillshare to explore your creativity with classes in illustration, photography, design, productivity and more!
📚 Structural Optimization: 7 Design Tips for for Lighter Designs
Lightweighting means more than just reducing mass. Through smart design techniques, you can maximize product functionality and minimize costs. In this blog post, Alkaios Bournias Varotsis gives his seven design tips for efficient structural design.
🚀 The Next Generation of Smart Meters Using Self-Learning Models
The global market for smart meters, including water, gas, heat, and electricity, is expected to reach $20 billion in 2022. However, many factors are contributing to the increasing difficulty of building reliable smart meter systems. These include an outdated smart meter infrastructure, fast urbanisation, and rising costs for testing and developing these devices, among others.
Smart meter systems must fulfill complex regulations, operate in harsh climate conditions while also reducing non-revenue water losses, as well as fulfilling a carbon-neutral and sustainable future under mounting time-to-market pressure while increasing product performance.
🧠 AI Beats 8x World Champions at Bridge
AI researcher Véronique Ventos, NukkAI’s other co-founder, calls NooK a “new generation AI” because it explains its decisions as it goes along. “In bridge, you can’t play if you don’t explain,” she says.
The game relies on communication between partners.
Explainability is a hot topic in AI. “Most of what the general public have heard in recent years about machine learning is based on black box systems such as AlphaGo, which is unable to explain to human beings how decisions are being made,” said Muggleton.
💻 Engineering Tool of the Week – JupyterLab
JupyterLab is the latest web-based interactive development environment for notebooks, code, and data. Its flexible interface allows users to configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning. A modular design invites extensions to expand and enrich functionality.
📚 Book of the Week
An Introduction to Statistical Learning: with Applications in R
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications.
Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented.
🙃 Meme of the Week
🎬 Animation of the Week
✍️ Closing Remarks
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See you next week and in the meantime, make sure to keep engineering your mind! 🧠