7

SaaS Competitive Advantage Through Elegant LLM Feedback Mechanisms

 9 months ago
source link: https://tomtunguz.com/easy-feedback-ml-bard/
Go to the source link to view the article. You can view the picture content, updated content and better typesetting reading experience. If the link is broken, please click the button below to view the snapshot at that time.
neoserver,ios ssh client

1 minute read / Oct 3, 2023 / product /AI /

SaaS Competitive Advantage Through Elegant LLM Feedback Mechanisms

Eliciting product feedback elegantly is a competitive advantage for LLM-software.

image

Over the weekend, I queried Google’s Bard, & noticed the elegant feedback loop the product team has incorporated into their product.

I asked Bard to compare the 3rd-row leg room of the leading 7-passenger SUVs.

image

At the bottom of the post is a little G button, which double-checks the response using Google searches.

image
I decided to click it. This is what I would be doing in any case ; spot-checking some of the results.

LLM systems aren’t deterministic. 1 can be larger than 4 for an LLM. If an LLM produces a few spurious results, the user won’t trust it.

image
Bard highlights confirmed data in green & potentially erroneous data in red. I confirmed the green is correct. The red sometimes was correct and other times wasn’t.

In addition to saving me time, I can use a less-than-trusted system, benefit from the accurate portion of the response - which should keep me coming back - all while improving the system for the next time.

It’s symbiotic.

I wonder if it won’t become the dominant feedback mechanism for LLM-enabled apps, replacing the now ubiquitous but deeply amorphous thumbs up/down.


Read More:

Centaurs & Cyborgs : The Jagged Frontier of AI


About Joyk


Aggregate valuable and interesting links.
Joyk means Joy of geeK