Can you share any interesting or unexpected lessons you've learned during your most recent project?
Jacobs Journey
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Alex Camilar@alex_camilar1
Bliq
one of the intriguing ones - people ultimately care mostly about money. take rideshare, for example: you give riders all kinds of options: eco-friendly rides, sustainable rides, custom rides, whatever kind of options you can think of. in the end, everyone cares about saving money & getting the cheapest ride, most of the time.
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Stoic Practise
@alex_camilar1 When people can choose different car rides, like green rides or special rides, most people just pick the cheapest one. It's like when you have many ice cream flavors, but everyone buys the one that costs less. So, most people want to save money. Such a good lesson to think about.
@jacobsjourney would love to hear your thoughts on the impact we're creating here: https://click.myways.ai/resumera...
NotesNudge
on my latest journey:
1. perfection is a myth. iteration is the legend.
2. silence isn't absence. sometimes, it's the loudest feedback.
3. tools don't make the project. people do. always.
4. some roads aren't on maps. intuition can be your compass.
5. failure? it's not the opposite of success. it's part of its recipe.
6. pausing isn't quitting. it's refueling.
7. small changes? sometimes, they make the biggest ripples.
8. every 'no' you hear? it's one step closer to a 'yes'.
hope these resonate. each project teaches. sometimes, in whispers. sometimes, in roars. always listening.
Stoic Practise
@shajedulkarim_ Your journey reminds me of a mosaic, where every piece, no matter how small or seemingly insignificant, plays a crucial role in completing the picture. Love what you learned!
During my most recent project of developing a language model AI, I discovered the unexpected lesson that bias can be unintentionally encoded into algorithms, thus emphasizing the crucial importance of comprehensive and diverse training data sets to ensure fair and unbiased AI applications.
Stoic Practise
@nfoster_85 Sometimes AI can show favoritism or bias. This taught me how important it is to teach the program with many different types of information so it can be fair to everyone. Thank you for sharing Nicholas!