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In traditional programming, the focus is on using rules and data to find answers. This is typically represented as rules + data = answers. In contrast, AI/ML takes a different approach: Answers + data = rules. In AI/ML, we train models by providing

“Don’t be a slave to stupid rules.” 1. We're easier to control with more stupid rules 2. Most rules are useless because there’s always people that can get around them Instead, challenge the rules. - Jordan Peterson

When you train the wrong data for the the wrong purpose

Hello Fellow Medial users !! I have an idea that could completely revolutnalise the overall architecture of data. So here is the idea. Consider 3 android devices, a user named "A" hastko log in to an app. He enters his password. The app communicates

A Question to ChatGPT & Grok. Should users get paid for the user data that is used to train them?

Want to train your own llm with data ? Say no More Y'all c4Ai is here!!!! It's an an open-source web crawler and scraper built specifically for Large Language Models (LLMs). It’s designed to help developers and researchers collect diverse datasets

Traditional Layer 1 blockchains struggle with storing real-world files on-chain storage is often costly, slow, and limited in capacity. Most weren't built for dynamic content at scale. Xenea changes that. By integrating a Layer 1 blockchain with dec

with the current Indian stock market scenario coming down 7%, what are you gonna do

Have you wondered how much late can a train be? well this event happened in India where a goods train carrying fertilizers was scheduled to reach its destination in about 48 hours Instead the train took approx 4 years to reach it's destination, yes

Hi Everyone we are Building an AI Architecture software for the Architects that can generate the building plan with some parameters like Site dimensions, facing and Number of bedrooms the plan will generate with the principle of vastu floor configu