this post was submitted on 07 Sep 2025
385 points (94.5% liked)

World News

49660 readers
2687 users here now

A community for discussing events around the World

Rules:

Similarly, if you see posts along these lines, do not engage. Report them, block them, and live a happier life than they do. We see too many slapfights that boil down to "Mom! He's bugging me!" and "I'm not touching you!" Going forward, slapfights will result in removed comments and temp bans to cool off.

We ask that the users report any comment or post that violate the rules, to use critical thinking when reading, posting or commenting. Users that post off-topic spam, advocate violence, have multiple comments or posts removed, weaponize reports or violate the code of conduct will be banned.

All posts and comments will be reviewed on a case-by-case basis. This means that some content that violates the rules may be allowed, while other content that does not violate the rules may be removed. The moderators retain the right to remove any content and ban users.


Lemmy World Partners

News !news@lemmy.world

Politics !politics@lemmy.world

World Politics !globalpolitics@lemmy.world


Recommendations

For Firefox users, there is media bias / propaganda / fact check plugin.

https://addons.mozilla.org/en-US/firefox/addon/media-bias-fact-check/

founded 2 years ago
MODERATORS
 

If an LLM can't be trusted with a fast food order, I can't imagine what it is reliable enough for. I really was expecting this was the easy use case for the things.

It sounds like most orders still worked, so I guess we'll see if other chains come to the same conclusion.

you are viewing a single comment's thread
view the rest of the comments
[–] yetAnotherUser@discuss.tchncs.de 1 points 2 days ago (1 children)

There are machine learning algorithms for anomaly detection though. They actually work decently well because exploits like this do in fact differ significantly from regular orders. Because they assume all anomalies are attempted exploits, their false negative rate is rather low while their false positive rate can be a bit higher.

Taco Bell has the capability to create a decently large training set from all recorded orders (which must all be valid and non-malicious) so they shouldn't have too many issues developing this model.

If an anomaly is detected, make a human verify it is indeed an irregular order.

[–] hark@lemmy.world 1 points 1 day ago (1 children)

This is handwaving, which, to be fair, describes a lot of AI "solutions". An anomaly could be as basic as a customer not wanting onions on their burger because the vast majority don't make that modification.

Now what do you do in that situation? Force orders to never have modifications? That customization is such an important feature to the point that burger king adopted it as a slogan with "have it your way".

[–] yetAnotherUser@discuss.tchncs.de 1 points 23 hours ago* (last edited 23 hours ago) (1 children)

The idea of anomaly detection is to project some input onto a (high dimensional), numeric output. From the training data alone, you can then see where the projections are clustered and develop a high dimensional "boundary" where everything within is known and good and everything outside is unknown and possibly bad. Since orders come in relatively slow, a human would be able to check for false positives and overwrite the computer decision.

By the way, an ideal training set is preprocessed and has duplicates removed and new orders added by recombining parts of individual orders.

For example, if we have 3 orders:

  • (Hamburger, Fries)
  • (Hamburger, Fries)
  • (Cheeseburger, Sandwich)

We could then create the following set:

  • (Hamburger)
  • (Cheeseburger)
  • (Fries)
  • (Sandwich)
  • (Hamburger, Fries)
  • (Hamburger, Cheeseburger)
  • (Hamburger, Sandwich)

And so on, and so forth. A naive variant is just taking the power set of all valid orders.

[–] hark@lemmy.world 1 points 16 hours ago (1 children)

This is more complicated than just having the available menu items, the available modifications, and the limits on quantities to compare against. This is already available through the app/online ordering.

[–] yetAnotherUser@discuss.tchncs.de 1 points 10 hours ago

That doesn't prevent someone ordering "everything" at max quantity, which is almost certainly a "malicious" order.