Businesses of all shapes and sizes are recognising the power of AI. Small businesses and enterprises can leverage these technologies to help improve efficiency, and large companies are automating whole departments of their business. Some companies however do not have the resources to employ whole data science teams to implement and manage AI systems.
With only one week to go until the AI Assistant Summit in San Francisco, we caught up with Shekhar Yadav, Founder of Objects.AI to hear how his startup is striving to make it easy for companies to implement and scale machine learning.
Shekhar explained that Objects.AI is early stage startup who will be at the summit looking to network with partners and potential clients. ‘Also we will be looking for new developments in the field and to learn from other experts to gauge how machine learning will shape up in 2018 and beyond.’ Their first offering is focused on the retail sector, and it helps retailers get predictive analytics on their users and increase shopping cart conversion.
Objects.AI is machine learning as a service platform. Our AI based engine maps enterprise business goals into machine learning algorithms that can process billions of rows of data and are smart to adapt to new information, data and business changes. We can enable:
1. > 70% in cost savings
2. Reduce time to market from months to few weeks.
3. Power of latest Machine Learning models without the cost of infrastructure.
My interest in ML started after I took a elective course in my undergrad studies. After that, my major thesis in engineering was in ML, specifically on the application of NLP in database query interfaces. This was few years back and ML has evolved quite a bit over time. I have worked over time in different applications of ML -from email marketing to drug discovery. One of the common theme that I saw all through was it is still incredibly difficult to get started in ML. We hope to solve that problem with Objects.AI.
Machine Learning is like an additional worker that shows up to work everyday. It does not matter what your business does or how big it is - you can always benefit from adding more workers. The beauty about an ML worker is that it learns over time, has infinitely more processing power and does not have work fatigue. If we accepted the coexistence model almost all businesses can improve their efficiency, reduce workload and improve general profitability.
This has two implications on the evolution of ML itself:
1. By accepting that ML is not only limited to big enterprises we have to invest in simplifying it or change how we design it. The current ML can almost be compared to Mainframe back in the days, it is incredibly powerful but not generally accessible.
2. ML gives competitive advantage to the business that has it. So if Amazon can deploy ML to better predict product demand and therefore implement a tighter supply chain, we are putting the small retailers at a disadvantage. Therefore to keep healthy competition and marketplace we will have to make sure ML is adopted and deployed across the breadth of size and scale.
As a technology platform in such a evolving space, everything is changing very fast. We are a small company with limited resources, so keeping focus but still being relevant is constant challenge. Also there is so much noise in the market. Everyone is talking about ML, and it has now become such a cliche to even say the word ML. We are seeing some dust settling down and hopefully this will be good for the serious players like us.
I think 2018 is going to be a year of investment in simplification of the ML infrastructure at big cloud vendors and the technology will finally start trickling down to smaller size businesses. We are excited to be one leading on this charter.
Join Objects.AI at the AI Assistant Summit this January 25-26 where they will be showcasing their product in the expo area. Lean how to reimagine your business with AI and machine learning.