Google is conducting an exciting hackathon on AI model runtime optimisation titled ‘Fast or Slow?’ Checkout the exciting prizes and details below!
Google LLC is an American multinational technology company focusing on artificial intelligence, online advertising, search engine technology, cloud computing, computer software, quantum computing, e-commerce, and consumer electronics. It is one of the world’s most valuable brands due to its market dominance, data collection, and technological advantages in the field of artificial intelligence. Google is also the largest search engine, mapping and navigation application, email provider, office suite, video sharing platform, photo and cloud storage provider, mobile operating system, web browser, ML framework, and AI virtual assistant provider in the world as measured by market share
The Fast or Slow? Predict AI Model Runtime hackathon by google is a competition for data scientists and machine learning engineers to build models that can predict the runtime of AI models. The goal of the hackathon is to train a machine learning model based on the runtime data provided to you in the training dataset and further predict the runtime of graphs and configurations in the test dataset. The hackathon is based on compiler’s configurations that change the way the compiler compiles and optimizes the models, and hence make the models run faster or slower.
A bit of technical background on an AI compiler will help you get started! An AI model can be represented as a graph, where a node is a tensor operation (e.g. matrix multiplication, convolution, etc), and an edge represents a tensor. A compilation configuration controls how the compiler transforms the graph for a specific optimization pass.
The hackathon is open to the Students, technologist, freelancers and professional developer community. To be eligible to enter the Competition, you must be:
As a condition to being awarded a Prize, a Prize winner must provide a detailed write-up on their solution in the competition forums within 14 days of the conclusion of the competition.
Interested candidates can apply online via this link.
