Project Management

Please login or join to subscribe to this thread

Does GenAI Data Diversity attribute will always be positive?

linkedin twitter facebook   Artificial Intelligence  
Will the data which has much diversity (as this is positive trait)  not under threat of getting ambiguous results out of GenAI model?
e.g.
source 1: Harry like red color.
source 2: Harry likes blue more than yellow.
source 3: Harry sometimes also likes black more than red, blue and yellow.

GenAI-Q. which color Harry likes all the time and always?

will this system not face ambiguity while preparing for the results?
Sort By:
avatar
Abolfazl Yousefi Darestani Manager, Quality and Continuous Improvement| Hörmann-TNR Industrial Doors Newmarket, Ontario, Canada
It depends on the AI that you use. Generally, more details to the system mean better results.
...
1 reply by Mirdul Sachan
May 23, 2024 2:25 AM
Mirdul Sachan
...
Thanks for your response, ya i got your point it depends on the AI model capacity it may be confusing for some inferior AI models but top of line AI models will take all the ambiguity just as pure data and try to infer better outcomes.
avatar
Keith Novak Tukwila, Wa, United States
The situation you describe can be easily handled by fuzzy logic. An appropriate response would be that the question "all the time and always" is a logical error known as a false dilemma but rather the conditions when he likes one color best do not have absolute boundaries. .
...
1 reply by Mirdul Sachan
May 23, 2024 2:43 AM
Mirdul Sachan
...
Thanks for your response, I agree to your point that question itself having fallacy, but my adjoining doubt is whether or not the AI model should fall back to next possible recommendations? e.g. "although there is no such color but there is a high possibility that Harry will go for Red almost always"
Actually I am trying to understand this from the point of view of what AI should rather than what AI could.
Actually I wanted to know if there is any guideline in the AI systems which may bar AI models to extrapolate the user query and try to response in more subjective way if direct answers not possible? Thanks for your time.
May 21, 2024 10:20 AM
Replying to Abolfazl Yousefi Darestani
...
It depends on the AI that you use. Generally, more details to the system mean better results.
Thanks for your response, ya i got your point it depends on the AI model capacity it may be confusing for some inferior AI models but top of line AI models will take all the ambiguity just as pure data and try to infer better outcomes.
May 21, 2024 11:17 AM
Replying to Keith Novak
...
The situation you describe can be easily handled by fuzzy logic. An appropriate response would be that the question "all the time and always" is a logical error known as a false dilemma but rather the conditions when he likes one color best do not have absolute boundaries. .
Thanks for your response, I agree to your point that question itself having fallacy, but my adjoining doubt is whether or not the AI model should fall back to next possible recommendations? e.g. "although there is no such color but there is a high possibility that Harry will go for Red almost always"
Actually I am trying to understand this from the point of view of what AI should rather than what AI could.
Actually I wanted to know if there is any guideline in the AI systems which may bar AI models to extrapolate the user query and try to response in more subjective way if direct answers not possible? Thanks for your time.
avatar
Sergio Luis Conte Helping to create solutions for everyone| Worldwide based Organizations Buenos Aires, Argentina
The answer is simple: take a look to the way ChatGPT works. ChatGPT is "predictive text with steroids". Just that. So, the answer will depends on the format of your question (prompt).

Please login or join to reply

Content ID:
ADVERTISEMENTS

When an elephant is in trouble even a frog will kick him.

ADVERTISEMENT

Sponsors