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hi guys..!! I have one fabulous idea of healthy fast food like salad, fruits, fruit juice one stop solution for healthy snacks.

"Synthetic Data" is used in AI and LLM training !! • cheap • easy to produce • perfectly labelled data ~ derived from the real world data to replicate the properties and characteristics of the rela world data. It's used in training an LLM (LLMs

Planning to open a small Cloud kitchen Cafe Pan India with some very unique italian, chinese dishes it's a very healthy concept for dieticians , for proper weight loss management, doctors, especially for gym lovers because our food is prepared with

IDEA : AI Training Data generator A Developer Platform which is much specify for AI-ML field to achieve various tasks like Analysis, Generation and Segmentation of real time data across data like text, image, audio, video that requires heavy and hig

Facing a lot of problems while opening any link from medial

Will AI hit a wall? 🤔 Future advanced models need complex data—but is there enough available? Or are we running out of high-quality training data? What’s the solution? More synthetic data? Better datasets? Discuss! ⬇️

X-Revenge - A video editing service where you can make NSFW videos of your ex, using just her face. I know it works, I have created a lot of material. I’m currently training my own local AI to process the entire pipeline automatically given the input

Random Thought : I was wondering, why ChatGPT weren't build on the Increment Learning modle.. Because I might destroy it's algo.... Let me expain.. In the world of machine learning, training models can be approached in two main ways, Batch Lea

As of 2023, the average data consumption per user per month in India was at 24.1 gigabytes. 4G data traffic contributes to 99 percent of the overall data traffic while 5G was launched in India in October 2022.

Food for thought. Instead of building AI models/agents/RAGs, why not build for AI. There is a dearth of auxiliary products and services for AI development such as benchmarking, training environments, data cleaning, synthetic data generation etc. But