My day job is in the data space, so naturally I am exposed to AI quite a bit. I'm not a coder, however, so I don't use it a ton. I have been exploring ways to incorporate it on a day to day basis since everyone says it can increase your productivity significantly, but nothing seems to be totally applicable to me.
I don't receive THAT many emails that I need AI to comb through and summarize things for me/draft responses, and I'm not in sales so I don't need research tools or automated workflows to follow up with clients. Those seem to be the biggest two use cases right now. Of course I play around with it, ask it things, do research with it, but that's about it.
Anyone using AI in really cool ways that they'd like to share?
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Whenever we get a new poster, I use it to analyze their posting and figure out what their old handle was.
@bradstevens uses the heck out of it to look smarter on the message boards.
😎
Emerging technologies can sometimes asked to do more than they're currently capable...
@bradstevens uses the heck out of it to look smarter on the message boards.
😎
Emerging technologies can sometimes asked to do more than they're currently capable...
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Here's a real world example. We have a client that moved to a new eCommerce platform. The way search worked on the old platform was kludgy and over the course of a dozen years, they manipulated their data in an unorthodox way in an ogoing effort to get the correct search results. Now they're live on a new system that actually has a good search, but their data isn't clean or really organized in a reasonable way, so their search results are trash. One of the simpler examples is products don't show up in a keyword search and/or products show up that are not related to the search term. To clean up the data and index everything properly will take the better part of the next 12 months.
We're using Google Vertex to bridge the gap. We feed everything in their product catalog into the model and it begins learning so it will populate the search with items that belong in the results and suppress the things that don't. Meanwhile, they're focusing on the top 10% of their products, Then they'll move onto the next group of products to get the top 20% clean.
It's not a long term solution, but for the time being it's helped them regain revenue they were losing to poor search results and the results are improving every day.
Hope is not optimism, which expects things to turn out well, but something rooted in the conviction that there is good worth working for. - Seamus Heaney, Irish poet and likely Hoosier basketball fan.
POTFB
It's not a long term solution, but for the time being it's helped them regain revenue they were losing to poor search results and the results are improving every day.
I remember when Google emerged and set the world on fire that one of the other players -- may have been Bill Gates -- said "Search is Everything."
It's not a long term solution, but for the time being it's helped them regain revenue they were losing to poor search results and the results are improving every day.
I remember when Google emerged and set the world on fire that one of the other players -- may have been Bill Gates -- said "Search is Everything."
It certainly is everything with what we do.
Hope is not optimism, which expects things to turn out well, but something rooted in the conviction that there is good worth working for. - Seamus Heaney, Irish poet and likely Hoosier basketball fan.
POTFB
Here's a real world example. We have a client that moved to a new eCommerce platform. The way search worked on the old platform was kludgy and over the course of a dozen years, they manipulated their data in an unorthodox way in an ogoing effort to get the correct search results. Now they're live on a new system that actually has a good search, but their data isn't clean or really organized in a reasonable way, so their search results are trash. One of the simpler examples is products don't show up in a keyword search and/or products show up that are not related to the search term. To clean up the data and index everything properly will take the better part of the next 12 months.
We're using Google Vertex to bridge the gap. We feed everything in their product catalog into the model and it begins learning so it will populate the search with items that belong in the results and suppress the things that don't. Meanwhile, they're focusing on the top 10% of their products, Then they'll move onto the next group of products to get the top 20% clean.
It's not a long term solution, but for the time being it's helped them regain revenue they were losing to poor search results and the results are improving every day.
Very interesting!! That's a super cool example - thank you for sharing
Check out my latest at Hoosier Huddle here
@evanalvarez8 You're welcome
Hope is not optimism, which expects things to turn out well, but something rooted in the conviction that there is good worth working for. - Seamus Heaney, Irish poet and likely Hoosier basketball fan.
POTFB