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Welcome to this new edition!

In Today’s Menu:

• AI-related Quote

• AI-ducation: What’s Dimensionality Reduction?

• AI decrypted: Deep Learning

• Top 3 News of the Week

• AI story: Stuart Russell

• Extra News

• Image of The Day

The AI-related Quote

The AI-ducation

What’s Dimensionality Reduction?

Dimensionality reduction is like tidying up a messy room. Imagine you have a huge dataset with hundreds of features or variables. It’s overwhelming and hard to work with. Dimensionality reduction simplifies this by shrinking the data down to just the most important pieces.

There are two main ways to do this: feature selection and feature extraction. Feature selection keeps only the most relevant features, while feature extraction combines features to create new, more meaningful ones. Techniques like Principal Component Analysis (PCA) or t-SNE are popular methods for feature extraction, helping to reveal hidden patterns by projecting data into fewer dimensions.

By reducing the number of variables, AI models can process data faster, learn better, and avoid "overfitting" – where the model learns too much from the noise rather than the actual patterns. It’s like focusing on the essentials, making sure the AI sees the forest and not just the trees.

The AI Decrypted

Deep Learning

Deep learning is a subset of machine learning that mimics the way our brains work. Instead of giving the AI step-by-step instructions, we build a neural network that can learn by itself from data. Think of it as teaching a child how to recognize objects by showing them thousands of examples. Eventually, the child learns to identify objects on their own.

Neural networks have layers of neurons that process information. In deep learning, we add many layers—hence, the “deep” part. The deeper the network, the more complex patterns it can learn. These networks excel at tasks like image recognition, language translation, and even playing complex games like Go.

What makes deep learning special is its ability to automatically discover patterns in large datasets, with minimal human intervention. Thanks to advances in computing power and data availability, deep learning is behind many of today’s AI breakthroughs.

The 3 News of the Week

#1 - OpenAI Launches 'Canvas' for ChatGPT Users

OpenAI has introduced a new workspace interface called Canvas for ChatGPT Plus and Teams users, designed to enhance productivity by allowing users to work on writing and coding projects alongside ChatGPT. Canvas integrates real-time AI assistance and shortcuts for editing and coding, positioning it as a powerful tool for those who need to combine AI with project management. Expansion to Enterprise and Edu users is expected next week.

#2 - Apple Intelligence Features Rolling Out in October

Apple is starting the release of its highly anticipated AI-powered features, dubbed Apple Intelligence, beginning with iOS 18.1 on October 28, 2024. However, the rollout will be staggered, with updates continuing through March 2025. Key features include AI-driven writing tools, photo enhancements, and a revamped Siri with personalized responses. Notably, only iPhone 16 models and iPhone 15 Pro/Pro Max will support these features, leaving older devices with basic updates.

#3 - Google Adds Ads to AI-Generated Search Summaries

Google is now integrating ads into its AI Overviews, the AI-generated summaries seen in search results for U.S. mobile users. These ads will be clearly labeled as "Sponsored" and accompany links to relevant web pages. This move, part of Google’s strategy to retain users and compete with AI-driven search alternatives, will also introduce AI-organized search result pages, providing aggregated content from sources like YouTube and forums.

The AI Story

Stuart Russell

Stuart Russell is one of the most influential figures in the AI field, known for his work on AI ethics and safety. As a professor at UC Berkeley and co-author of the widely-used textbook Artificial Intelligence: A Modern Approach, Russell has shaped how AI is taught around the world.

But his biggest contribution is his work on AI alignment—ensuring that as AI systems grow more powerful, they act in ways that align with human values. He’s been a vocal advocate for creating AI systems that are not only intelligent but also beneficial and safe for society.

His recent book, Human Compatible, raises important questions about the future of AI, urging researchers and policymakers to focus on designing AI that respects human goals and safety above all. Russell's work reminds us that building intelligent machines is just the beginning—ensuring they work for us is the real challenge.

The Extra News

• The racist AI deepfake that fooled and divided a community

• Imagining faces in tree trunks and your morning eggs? AI can see them, too

• Microsoft and Rezolve AI partner to drive global retail innovation with AI-powered commerce solutions

• Accenture and NVIDIA Lead Enterprises into Era of AI

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Image of The Day

Prompt: 
BABA YAGA BALACLAVA This vibrant 4-color intaglio engraving by Albrecht Dürer features deliberate and precise lines on dark paper, creating textures through hatching, cross-hatching, contour lines, and stippling. The fine line patterns envelop every surface, Bauhaus, Japanese minimalism, her gaze is so intense and so evil through her pale blue eyes, and angry expression, as she screams some curse in your direction, the reflected flickering orange light of the candle making her look even older and angrier, spooky, horror-core

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