The current state of wide data is that it is not as widely used for Artificial Intelligence as it is for analytics. While analytics needs a treasure trove of historical data, AI merely needs a variety of big data.
And big data needs AI, too. It’s the most efficient and effective way for organisations to optimise their processes and identify their audiences.
But how can we use machine learning practices and AI to tackle critical business challenges?
In this 3 part EM360 Podcast series with Findability Sciences we have previously discussed 'What Big Data Discussions Ignore' In Episode 1. In this second episode, we are joined once again by the Founder and CEO Anand Mahurkar to talk about:
- The relationship between wide data, learning and machine learning
- Critical business challenges when it comes to AI mimicking a more human process
- Why we should be using wide data for AI
We are an award-winning Enterprise AI company, harnessing the power of data, cognitive computing and AI to empower businesses around the world as we solve their most complex and critical business challenges. In simple terms, we drive digital transformation in traditional enterprises by making them data superpowers.
We began our journey in 2018, propelled by an investment from SoftBank KK who also structured a JV with us for the Japanese market. Our proprietary offering, Findability.ai, enables customers accelerate their Data-to-AI Journey and build their own IP & data science capabilities, while gaining real financial RoI.
Our significant IP holdings include multi-modeling, low code prediction algorithms, EDA, NLP & Computer Vision. Our key offerings namely Findability.AI, Findability.DSL, Findability.INSIDE & Findability.LABS help create Strategic, Capability, & Financial Returns on Investments & drive Digital Transformation for our enterprise customers.
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