OpenAI Stack Hack

Join us to find out how developers can interact with Redis, a real-time data platform with its blazing-fast vector database

Redis Talk

Paweł Czech and Mathias Asberg, co-founders of New Native will talk about lablab.ai's mission and vision. https://www.twitch.tv/lablabai

Start

We will shortly introduce you to the OpenAI Whisper, GPT3, Codex & DALL-E 2 Hackathon, Challenge, lablab.ai platform, Discord server.

Introduction to the Challenge

Short intro from lablab.ai's partner - Redis, the leading provider of enterprise-class solutions for vector search, data storage, and ML feature workloads

Redis Introduction

Startup lessons especially when it comes to actually applied NLP AI

Useful tips from lablab.ai developer Fabian

ChatGPT for developers/ how are for what to use

Whisper Tutorial for developers

Go-to-market strategy, basics of pricing, funding and valuation for AI startups

GPT-3 Live Coding Session

Under the hood: Building a QA app using Redis

Time's up! Submit your solution before the deadline

Delta Force

DVlachopoulos

statecLata

Mulleter

Ioannis Alimpertis

Sotiris

xtrelis

Plant diseases can have a devastating impact on crop yields, leading to significant economic losses for farmers and threatening global food security. To address this challenge, an Android application has been developed using a combination of machine learning and API technology to accurately identify and diagnose plant diseases.

The application uses a machine learning model trained on a large dataset of plant images, allowing it to recognize and differentiate between various diseases affecting crops. Users simply upload a photo of the affected plant, and the app provides a diagnosis along with recommendations for treatment.

The app also integrates with an API to securely store user data and provide personalized recommendations for managing plant health. This data can include information such as the user's location, soil type, and environmental conditions, which can all have an impact on plant health. The app can use this data to provide recommendations for specific treatments or crop varieties that are better suited to the local environment.

By providing a fast and accurate diagnosis of plant diseases, this application can help farmers and gardeners take proactive measures to protect their crops and improve yields. The app can also promote sustainable agriculture practices by reducing the use of pesticides and other harmful chemicals. Overall, this tool has the potential to play a significant role in addressing the global challenge of plant disease and promoting sustainable food production.

An Android app using API and ML to identify plant diseases.

"Delta Force team on OpenAI Stack Hack Hackathon"

Team Idea

Submission