I suspect they've trained it on old stories on which they added this caveat, and now “once upon a time” became tightly coupled to the caveat in the model.
Yes, we wouldn't want to produce output that perpetuates harmful stereotypes about people who live in gingerbread houses; dangerously over-estimates the suitability of hair for safely working at height; or creates unrealistic expectations about the hospitality of people with dwarfism.
I wonder if this sort of behaviour was more nuanced in the initial model, and something like quantisation has degraded the performance?
In fairness, there are lots of things in old tales we may not an LLM to take literally.
For instance, unlike kids, at training time an LLM isn't going to ask “It's not very nice for the parents to abandon their children in the forest, is it?”.
I know conservatives are easily triggered by such caveats, but at the same time, they are literally banning books from library ¯\_(ツ)_/¯
Ya to me this is an immediate disqualification. They're building the political commissars into the tech, and they're actual nonsense political correctness rules. Instead of blocking actual racism etc they block "once upon a time"?
AI models absorb all kind of racist/sexist/hateful speech, so it has to be neutered or it will end up like that Microsoft AI that started spouting nazi lingo after a day or two of training because of trolls.
Apparently AI companies can't be bothered to filter out the harmful training data so you end up with this warning every time you reference something even remotely controversial. It paints a bleak future if AI companies will keep producing these censoring AIs rather than fix the problem with their input.
Firebase uses Google Cloud Logging. Taking a quick look at the blog post here, Google Cloud Logging already seems to support everything it describes.
Is there something in it that makes it a better solution in some way than what Google is already providing? (Note that Supabase Logs appears to rely on Google BigQuery so you'll be running on Google either way.)
> Logflare currently supports a BigQuery backend. We plan to add support for other analytics-optimized databases, like Clickhouse. We will also support pushing data to other web services, making Logflare a good fit for any data pipeline.
>
> This will benefit the Supabase CLI: once Postgres support is available, Logflare will be able to integrate seamlessly, without the BigQuery requirement.
Really great use case to be fair and congratulations on the launch.
Wanted to ask:
1. how well does it handle joins among multiple tables to find an answer
2. what happens if your tables and fields to not make a lot of sense in English?
Thanks!
Developing a similar product and to my surprise switching languages isn't a problem at all. It also uses the correct tables when the user inputs "movies" instead "films" as the table is actually called. Writing this[0] here in German will produce the same result[1]. Now of course GPT version makes a big difference.
