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Illuminating the Black Box of Textual GenAI | by Anthony Alcaraz | Dec, 2023

The need for insights LLMs like ChatGPT, Claude 2, Gemini, and Mistral captivate the world with their articulateness and erudition. Yet these large language models remain black boxes, concealing the intricate machinery powering their responses. Their prowess at generating human-quality text outstrips our prowess at understanding how their machine minds function. But as artificial intelligence…

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e Sourcing: What is e-sourcing?

In today’s hyper-digital world, companies are shifting to e-sourcing with e sourcing tools designed for digital transformation in tactical and strategic sourcing. E sourcing software provides efficiency and other benefits, including better vendor selection, collaboration, and visibility into this element of e-procurement and business spending.  💡 According Gartner: “Sourcing and procurement leadership must invest in…

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KDnuggets News, November 22: 7 Essential Data Quality Checks with Pandas • The 5 Best Vector Databases You Must Try in 2024

This week on KDnuggets: Learn how to perform data quality checks using pandas, from detecting missing records to outliers, inconsistent data entry and more • The top vector databases are known for their versatility, performance, scalability, consistency, and efficient algorithms in storing, indexing, and querying vector embeddings for AI applications • And much, much more!…

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Google DeepMind Researchers Utilize Vision-Language Models to Transform Reward Generation in Reinforcement Learning for Generalist Agents

Reinforcement learning (RL) agents epitomize artificial intelligence by embodying adaptive prowess, navigating intricate knowledge landscapes through iterative trial and error, and dynamically assimilating environmental insights to autonomously evolve and optimize their decision-making capabilities. Developing generalist RL agents that can perform diverse tasks in complex environments is a challenging task that requires numerous reward functions. However,…

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A Guide to 21 Feature Importance Methods and Packages in Machine Learning (with Code) | by Theophano Mitsa | Dec, 2023

From the OmniXAI, Shapash, and Dalex interpretability packages to the Boruta, Relief, and Random Forest feature selection algorithms Image created by the author at DALL-E“We are our choices.” —Jean-Paul Sartre We live in the era of artificial intelligence, mostly because of the incredible advancement of Large Language Models (LLMs). As important as it is…

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Google AI Proposes PixelLLM: A Vision-Language Model Capable of Fine-Grained Localization and Vision-Language Alignment

Large Language Models (LLMs)  have successfully utilized the power of Artificial Intelligence (AI) sub-fields, including Natural Language Processing (NLP), Natural Language Generation (NLG), and Computer Vision. With LLMs, the creation of vision-language models that can reason complexly about images, respond to queries pertaining to images, and describe images in natural language has been made possible.…

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