Posted by
Pete McBreen
08 Oct 2023 at 19:41
In a nice posting by Gary Marcus - Seven Lies in Four Sentences there are examples of where Generative AI does what it always does via autocompletion and produces text that is unrelated to reality.
A related, earlier posting notes
All they do is match patterns, draw from massive statistical databases of human language. The patterns might be cool, but language these systems utter doesn’t actually mean anything at all.
Overall these generative tools produce the statistically most likely sequence of words based on the prompt that was supplied. The problem with that is that humans as gullible and easy to fool, so it is easy to fall into the trap of thinking that the generative tool is intelligent. Whereas in reality the tool has no idea at all about what it generated, other than that the output was the statistically most likely response.
So generated text is unlikely to be surprising – a.k.a. no new information – it will just be likely information. So yes, it is likely to give a reasonable answer to common prompts (because it was trained with many related examples ), but for novel prompts hallucinations (a.k.a. misinformation) is the likely answer.
Posted by
Pete McBreen
05 Oct 2023 at 04:23
A surprising number of systems I have worked on in the past 15 years have been drastically slower than they need to be because the developers did not understand how to write anything other than a simple single table query. So what was visible in the application was that the application would
- Issue a query to the database for a container.
- In a loop, issue a different query to get the details of each of the contents of the container.
- If you were unlucky, then go through the loop again to get some related details about each of the contents.
This works fine in development with just a few rows in the table, any database can run 1 + 3 + 3 queries in milliseconds. But in production when there are 1000+ items in the container, suddenly the application is trying to do 2,000 queries, and suddenly the milliseconds turns into seconds. All because the developers used the programming language to replace a slightly more complicated SQL statement that could return the desired data in a single database request.
Now whenever I am working on a new codebase, I look for queries that are issued inside loops (or hidden loops inside streams), as practically every time I have to do performance tuning, that is where the excess delays live.
