alt Hacker NewsIt's baffling to me that a company like Amazon would choose to use a LLM for a task as simple as ticket classification. Don't they have thousands of engineers and petabytes of data? They even have their Mechanical Turk program if they want a cheap labelling workforce.
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I thought MT was being deprecated if not already?
It’s not that baffling Amazon has something like 70k+ engineers worldwide. Never worked there myself but in large orgs things sometimes get lost in the shuffle.
I don’t think timelines were shared but this reads like a pretty good case of building an MVP and then lowering the cost once it’s proven. One of the whole value props for LLMs from a ML perspective is being able to get something out the door a lot quicker than you would otherwise.
They finally sunset Mechanical Turk.
Ticket classification isn't necessarily so simple, and I can think of various reasons for using ML to classify tickets.
1. Some auto-generated ticket (e.g. a trigger from unusual hardware activity or a log entry) resembles a previous ticket that had meaningful action on it, addressed and solved by a specific team. That ticket could spend a week getting ignored or punted around when the right team can solve it in 5 minutes. ML could detect the similarity and reclassify it by that metric. 2. Human-submitted tickets are annoyingly fallible. For example, an "I can't log into my account" ticket could be auto-classified as "account recovery". Or maybe, e.g. the ticket system attaches a recent activity log from that IP address to be cross-checked by ML, which finds 5xx errors and reclassifies it for the technical team.
These are generic examples, but you can use your imagination and see how a company as huge as Amazon could benefit from this. I think it's for the purpose of minimizing the number of tickets that need to be manually reclassified because the wrong info was given to the wrong person.