Manuj Mishra@manuj28

Many ML researchers are unhappy with their development process. Coding from scratch is laborious since the process for developing and testing new models is largely the same each time but no-code and low-code platforms do not provide enough granularity to tweak models, loss functions, and training processes. Most ML researchers experiment in Jupyter notebooks. They are quick, composable, and easy to present.However, even with the help of LLMs: - Copy-pasting code between web-interfaces and notebooks is slow - Errors in generated code are difficult to detect and fix - Writing the appropriate prompt to generate correct boilerplate code is still repetitive Our solution takes existing data and a natural language prompt and uses it to build a model that is compatible with the shape and types of the data. It also uses recursive API calls to fix any errors in the generated code by passing them back to the LLM. In the future, this product could be extended to generate code for the full build, train, test, and measure cycle so that researchers can ask for a set of models to be tested, tweak the generated code as needed, and rapidly evaluate the best model for their needs.

🚀💻 Be the first to build an AI App on Google's models! Hackathon on July 7-10. 🔬🌐 Try new Vertex AI features from Google Cloud Platform. 🤝🌍 Learn from AI leaders and connect with like-minded people. 🛠️📱 Build apps with the world's best AI tools! 💡🌍 Solve real-world problems with Generative AI models

Come to the Cohere Thanksgiving Hackathon and let's build, create, and innovate together! This is a perfect opportunity to use your skills and creativity to support a cause or make a difference. You could build a business idea or a social cause project – it's up to you! 👉 There is not only incredible prizes up for grabs, this is also a perfect opportunity to get into the absolute 🔥🔥🔥 hottest 🔥🔥🔥 trend in technology. <b> <br/><br/>Sign up now and let's make a difference this <u>Thanksgiving!</u></b> Both seasoned AI / Tech pros as well as people with other domain knowledge are welcome, our team matchmaking system will make sure you find a team to work with, or create your own and invite your friends / colleagues.