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Which approach is more profitable and scalable? 1. Complimentary AI tools for existing big softwares 2. Developing fully new software with AI integration

Approximately how many users are there in this app actively

Hello everyone! I'm genuinely interested in working at a startup and eager to learn how one is built—everything from responsibilities to the dev tools and AI techniques commonly used. I'm open to contributing and actively working in a startup environ

How do you stop yourself stop getting overwhelmed with the new upcoming and latest AI tools , toolkits , Agents and Models ?

Here are some AI tools which are useful for the startups: 1. TensorFlow and PyTorch: Open-source frameworks for building machine learning models. 2. IBM Watson: Offers AI tools and services like natural language understanding and computer vision.

India should focus on fine-tuning existing AI models and building applications rather than investing heavily in foundational models or AI chips, says Groq CEO Jonathan Ross. Is this the right strategy for India to lead in AI innovation? Thoughts?

How many hours are you genuinely working?

BREAKTHROUGH INSIGHT: Most people train AI models. Smart people fine-tune AI models. But the real secret? Learning to dance with AI's existing knowledge. Stop forcing. Start flowing.

I have to make some promotional music videos using AI models or my own friend dancing by AI. Tried many tools, partial success. Can an AI expert guide me on it? just for info, I am not coder, or developer, just keen to learn things. #AI

Researchers are developing AI models to predict the onset of diseases like Alzheimer’s and Parkinson’s. These models analyze patterns in medical data to identify early signs, potentially leading to earlier and more effective treatments.