Basically, it was sort of going through a decision before I decided to come to this conference because I come mostly from the technical world of AI. But then by seeing the type of people who are coming here and the type of panels, I found it very interesting because essentially I thought it will give me the opportunity to really hear out from the real people, the real people who are doing the asset management and other things. How do they see the AI can help and also to know their real problems, their approach towards alternate data, all those various stuff. So, it is pretty much learning experience for me too. When IBM we surely have a great strategy for artificial intelligence and actually I am probably, you know, I am really entitled to say everything, but I can talk about a couple of very good products what we have towards AI. Like IBM has just released AI OpenSkill a month before which essentially a platform using which one can integrate multiple AI products which is coming from IBM like products like Watson as well as products which are outside of IBM, but all those things can be integrated pretty much in the AI OpenSkill for an Intuent solution. And apart from that we also have Watson Studio which right now available in the cloud, it is available on-prem, it is even we are also coming out with the personal version of the Watson Studio which is also a great tool to create an Intuent AI solution especially the machine learning part of it. I basically work as a data scientist thought leader for IBM Cloud Lab, the analytics part of the IBM Cloud Lab and my role is essentially to help our customers adopt AI as I mean everybody knows right now it is still pretty much on the fan, you know, in fancy of the things. So my role is to really, you know, understand their requirements where they can apply AI, what are the IBM tools can be used for them even open source tools so there where I come into the picture. Before coming to this conference probably I didn't even realize this much but after going through this conference for almost one and a half day I think it is a lot starting from the how one can really cure it alternate data which are typically pretty much, you know, in the raw form then starting from there how to do the feature engineering to really map it to the right level of relevance whether it is quant or whether it is more fundamental products, those type of stuff. You see I also picked up this great terminology just, you know, from this conference. So I see that it would be a lot useful to use AI to come out with the right type of products, especially for the products which are essentially a little bit short term because in that case the AI can provide them great insight by consuming all the data, crunching them in an automated way, much more intelligent way in a much lesser time frame. There where I see there should be a great value.