4 ms·

"... our bet is that Deep Learning will overtake traditional BI workflows ..." This is an interesting perspective. I have spent years in the traditional BI sp

"... our bet is that Deep Learning will overtake traditional BI workflows ..." This is an interesting perspective. I have spent years in the traditional BI space and my gut feeling there is that analytics there are very much not fancy. Simple stuff seems to be where the real ROI is at. Are you saying that data storage, data model, etc that Activeloop puts in place to better support deep learning workflows will replace the data storage, data model, etc as the store of information but visualization and querying will still be like BI work? Or alternatively, are you saying that deep learning is on a roaring path to replace traditional BI analytics?

davidbuniat 4y ago
Thanks - it's very insightful to also hear your perspective as someone coming in from the BI space (if you have any more insights, please post them here, too). We have this internal joke where when one says their analytics is based on regressions, it's really an excel sheet, and if they say it's AI, it's a simple Ordinary Least Squares regression, and only a handful do actual AI/ML. From what we are seeing in the market, both domains grow, but with an overlap, and it's expanding, too. I think while BI/Analytics would still be a major space, we would see more DL-based novel applications generating increasingly more business value (i.e. self-driving cars, robotics, agritech). After all, even in VERY traditional workflows/companies like economic growth estimation, we're seeing DL being applied (e.g. they look at nightlight satellite imagery to estimate economic growth/urbanization). So to answer your question, for some parts, I think it would be the former (complement), and other applications it would call for replacement (particularly in the cases where companies use multi-modal data).

4 ms·

"... our bet is that Deep Learning will overtake traditional BI workflows ..." This is an interesting perspective. I have spent years in the traditional BI sp

by clusterhacks 4y ago

davidbuniat 4y ago
Thanks - it's very insightful to also hear your perspective as someone coming in from the BI space (if you have any more insights, please post them here, too). We have this internal joke where when one says their analytics is based on regressions, it's really an excel sheet, and if they say it's AI, it's a simple Ordinary Least Squares regression, and only a handful do actual AI/ML. From what we are seeing in the market, both domains grow, but with an overlap, and it's expanding, too. I think while BI/Analytics would still be a major space, we would see more DL-based novel applications generating increasingly more business value (i.e. self-driving cars, robotics, agritech). After all, even in VERY traditional workflows/companies like economic growth estimation, we're seeing DL being applied (e.g. they look at nightlight satellite imagery to estimate economic growth/urbanization). So to answer your question, for some parts, I think it would be the former (complement), and other applications it would call for replacement (particularly in the cases where companies use multi-modal data).