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Another point is that while we technologists love to marvel at data science and machine learning, it still begs the question of what value does it bring to the
by tixocloud 6y ago
Another point is that while we technologists love to marvel at data science and machine learning, it still begs the question of what value does it bring to the business. Does the added responsibility of creating all the infrastructure and processes worth it to justify a 5% increase in conversion rates? As you say, even the dirty work has a cost and whether that cost is worth paying to find out that there's nothing you can do to improve the business. That's why all the massive multi-year central data warehouse cleansing type projects keep failing without yielding much value. There's just a lack of focus on delivering incremental value with these data projects.
- atupis 6y agoI think currently it creates new possibilities to do business. Computer vision is that point that nowadays it is more engineering than data science so adding something like somewhat good object detection is not that hard. NLP is probably same point where cv was 5 years ago so we start seeing very good NLP models.
- tixocloud 6y agoDefinitely. Even as an engineer working on CV 10 years ago, the hard part wasn’t object detection but rather network bandwidth to stream incredible amounts of data and processing it in real-time. Spoke to an experienced engineer who used to lead NLP at MSFT and same comment. NLP models are already fantastic and it isn’t very hard to build a smart chatbot. The implementations these days are just very poor because they are not well thought out from a user perspective.