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"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

make ai agents without writing single line of code Microsoft AutoGen: Advancing AI Agent Collaboration Microsoft's AutoGen is an open-source framework designed to simplify the creation of multi-agent systems using large language models (LLMs). It a

Smart City Analytics Platform Idea: Create a platform analyzing government data for urban planning. Features: Data integration, predictive analytics, urban planning tools, real-time monitoring, citizen engagement, performance benchmarking. Revenue Mo

Career Opportunities After AI Training in Pune | Skillfloor AI training in Pune opens up various career opportunities in fields like data analysis, machine learning, and robotics. Graduates can work as AI engineers, data scientists, or AI consultant

How to Jailbreak AI LLMs for ethical practices?

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

OpenAI spent millions if not billions developing and training LLMs. Same is for Google, Microsoft and Meta.. the only difference being they are releasing their LLMs now after the craze of AI is at its peak. But I don't understand how companies like K

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

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! ⬇️

Retrieval-Augmented Generation (RAG) is a GenAI framework that enhances large language models (LLMs) by incorporating information from external knowledge bases, improving accuracy, relevance, and reliability of generated responses. Here's a more det