APN News

  • Monday, January, 2022| Today's Market | Current Time: 08:35:52
  • Chennai :  Affine, a leading Artificial Intelligence (AI) and Data Engineering consulting and solutions firm was ranked among the top 10 on a leaderboard (/7th position) at the Deep Learning AI data-centric competition by Andrew Ng, who is also co-founder and Chairman of Coursera.  Balu Nair, Jayanth Ajay, Ph.D., and Ashwini Gupta, from Artificial Intelligence Centre of Excellence (AI_CoE), Affine, presented their case to the international leaderboard for the challenge requiring teams to accurately classify handwritten Roman numbers from 1 to 10. 

    The data centric competition, Hackathon is a collaboration between Deep Learning AI and Landing AI and aims to elevate data centric approaches to improve machine learning model performances. Contestants were given datasets to improve and work on by the organisers. The competition was evaluated under two categories- ‘Best Performance Overall’ and ‘Most Innovative’. This competition was powered by CodaLab Worksheets.

    Affine secured 7th position in the Hackathon with 1,480 other entries and was the only Indian company to be a part of the top 10 list.

    “We are very excited about our Top-10 achievement in the Data Centric AI Competition organized by Dr Andrew Ng, DeepLearning.AI and Landing AI teams.

    At Affine, we have always put equal emphasis on the ML architecture as well as building “rich” data pipelines (high quality data + high quality features); resulting in successful ML deployments and lasting benefits for our customers. Our teams continue to innovate and upskill on algorithmic as well as data side of AI, the latter being very important in addressing production data challenges,” said Vineet Kumar, Co-Founder and Chief Solutions Architect, Affine.

    An Indian MNC, founded about ten years ago as an end-to-end analytics service provider, Affine started with descriptive and basic predictive analysis but evolved over the years to COEs with aligned competencies, joint partnerships with academic institutions for R&D with respect to advanced statistical and mathematical models, Deep Learning to capitalize on the need for high end analytics.