I don't see how any of this is different from ten years ago when it was called "big data"
-
-
Big data really only let us avoid the need for sampling. It allowed us to process all of our data, instead of just small amounts.
1 reply 0 retweets 0 likes -
Replying to @sbyrnes @bobpoekert and
This is about training models that can do things humans can’t do. You don’t even need big data for that.
1 reply 0 retweets 0 likes -
the no. 1 "big data" applications were recommender systems and predictive analytics...
2 replies 0 retweets 0 likes -
No, that’s not true. The most common big data projects were simply business analytics. They did simple math using map reduce.
1 reply 0 retweets 0 likes -
so the difference is "big data" is buying a hadoop cluster and "AI" is finally learning how to use it?
1 reply 1 retweet 1 like -
No, big data was processing previously impossible data loads using distributed systems.
1 reply 0 retweets 0 likes -
Replying to @sbyrnes @bobpoekert and
The current AI wave is about replacing people with better ML implementations. They are unrelated, but in parallel.
2 replies 0 retweets 0 likes -
point is the current period is about productizing existing techniques rather than discovering new ones
1 reply 0 retweets 1 like -
Replying to @alicemazzy @sbyrnes and
you would not know that this is the case if you were only going on the hype
1 reply 0 retweets 0 likes
difference between message communicated by the hype and the reality that will collapse expectations
-
-
The value either grows fast enough that it catches up to the hype (mobile) or falls short (VR). Even if it falls short, likely here to stay.
0 replies 0 retweets 1 likeThanks. Twitter will use this to make your timeline better. UndoUndo
-
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.