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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

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?

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.

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.

Is developing a calorie tracking app with AI-based personalized diet plan generation a good idea to start working on?

OpenAI and SoftBank are developing Cristal Intelligence, an AI system for enterprises. SoftBank plans to invest $3B annually, using o1-series models to automate tasks, boosting productivity.

I need everyone's thoughts on this👇👇 Teachers, parents, and even school principals are deeply concerned that the use of generative AI tools like ChatGPT might lead to student laziness and negatively impact their future careers. What's your opinion