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The AI Revolution: Super Bowl's Best and Wackiest Commercials

Several companies showcased AI-related ads at Super Bowl LVIII, including Microsoft, which highlighted its AI assistant, Copilot, in a commercial emphasizing its ability to solve various problems and empower individuals. The ad features defiant text overlaid on scenes of people overcoming obstacles, with Copilot generating solutions like creating storyboard images and writing code.

Unlocking the Power of GPT-2: The Rise of Multitask Language Models

The article discusses the evolution of GPT models, specifically focusing on GPT-2's improvements over GPT-1, including its larger size and multitask learning capabilities. Understanding the concepts behind GPT-1 is crucial for recognizing the working principles of more advanced models like ChatGPT or GPT-4.

AI Surveillance: Crime Detection on London Underground

AI surveillance software was used to monitor thousands of people on the London Underground, looking for aggressive behavior, weapons, and unsafe situations. Transport for London tested 11 algorithms, generating over 44,000 alerts, marking the first time AI and live video footage were combined for real-time alerts to staff.

OpenAI's Sam Altman Seeks Trillions to Revolutionize AI Chip Manufacturing

OpenAI CEO Sam Altman is seeking to raise $5 trillion to $7 trillion for AI chip manufacturing to address the scarcity of GPUs for language models like ChatGPT and Microsoft Copilot. Altman is pitching a partnership between OpenAI, investors, chip makers, and power providers to build chip foundries, with OpenAI as a significant customer.

Unleashing the Power of PCA: Simplifying Data Analysis and Machine Learning with C#

The article "Principal Component Analysis (PCA) from Scratch Using the Classical Technique with C#" in Microsoft Visual Studio Magazine explains how PCA can reduce the number of columns in a dataset and its applications in machine learning algorithms. It also discusses the difficulty of computing eigenvalues and eigenvectors and provides a demo using a subset of the Iris dataset.

Enhancing Movie Recommendations: Unraveling Unstructured Data with LLMs and Controlled Vocabularies

Recommender systems generate significant revenue, with Amazon and Netflix relying heavily on product recommendations. This article explores the use of controlled vocabularies and LLMs to improve similarity models in recommender systems, finding that a controlled vocabulary enhances outcomes and building a genre list using an LLM is easy but creating a detailed taxonomy is challenging.