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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

the dumbest model of AI seen till now. They removed other models in the free version. At least give us the choice to choose models like previous. can't understand the queries. answers are not satisfactory or expected.

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! ⬇️

Got a question today: What are AI systems? AI systems learn from training data provided or set by humans. These algorithms adapt to new information, and a knowledge base supports the AI in attempting to solve the queries it receives. If the AI does n

oh vai, i got a call from someone saying that they will give me job to rate 5 ⭐ on Google. let see what happens they will give me 200 thay are saying i am thinking i will take the money and block them😂. follow to know what happens next. 😂

Most AI projects fail after deployment. I’ve explained the core problems step by step. 𝗦𝘁𝗲𝗽 1 – 𝗗𝗮𝘁𝗮 • Collects raw information from multiple sources. • Forms the foundation of every AI system. 𝗘.𝗴: APIs, logs, databases, user inputs. 𝗡

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

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

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