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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

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

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

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

Breaking News: My AI just fired me. Apparently, I wasn’t “data-driven” enough, didn’t “scale,” and failed to “synergize with the cloud.” Meanwhile, it’s holding meetings with itself, automating my calendar, and pitching VCs on a startup called “Hum

Can I know the real cost of Running a vertical ai startup ? Let's say I take a base model like " Claude latest model " train it with my data of the niche Market. what's the COST TO RUN IT ?? NOT TO TRAIN or creating the product ( AI ) eg : ai fo

Slice is just few of the fintech startups with a Bank License. So will you ever prefer slice instead of other banks like HDFC?