2 ms·
Here is a little GIF demo: https://twitter.com/timo_schick/status/1624058382142345216 https://twitter.com/timo_schick/status/1624058382142345216 The possibilit
by modeless 4y ago
Here is a little GIF demo: https://twitter.com/timo_schick/status/1624058382142345216 https://twitter.com/timo_schick/status/1624058382142345216
The possibilities of this line of research are endless. When language models can call APIs and/or use UIs, they can become the unified natural language interface to any software, any website, any app. See also https://www.adept.ai/act https://www.adept.ai/act.
Siri and Alexa and Google Assistant are dead ends. Language models trained to use tools will finally be able to start delivering on the promise of a software assistant that works. And eventually, they will be a key part of robots that accept natural language commands to perform everyday tasks in the real world, like this: https://sites.research.google/palm-saycan https://sites.research.google/palm-saycan
- amelius 4y agoCan they also perform fact-checking?
- option 4y agoOne idea is if the probability of QA API call is high but API returns nothing or conflicting results, then model may learn to say it isn’t sure about the result.
- nestorD 4y agoThe fact checking with prompt chaining[0] repository has something along those lines (their readme has an example). It is not perfect and it is costly in number of calls to a language model but it does help a lot. [0]: https://github.com/jagilley/fact-checker https://github.com/jagilley/fact-checker