Comment by vb-8448
4 days ago
Complaining about "bad charting" and posting a chart with y-axis that doesn't start at 0 is kinda weird.
4 days ago
Complaining about "bad charting" and posting a chart with y-axis that doesn't start at 0 is kinda weird.
to be fair, you don't need to start the y-axis at zero [0] but for some of the graphs where the lowest value is close to 0 the best practice is to do so
there's a fun Excel artifact where it auto-selects the 'relevant' range with no adjustment for how proportionally close to 0 the values are - a professional researcher publishing to a journal should know better (and should be ridiculed for not incorporating best practices) but for a personal blog by an SWE this really isn't the worst sin
[0] https://digitalblog.ons.gov.uk/2016/06/27/does-the-axis-have...
IMO in this case is mandatory to start from 0 because it alters the visual perception.
Just look at the first chart: the distance between Fable 5.1 and Sol is <5%, but it looks like 25 or 30%.
I disagree. The y-axis is some arbitrary intelligence score that we use as a proxy for performance on whatever our specific task happens to be. So it doesn't matter if a model is a 0, 1, or 20 along this axis, they are all useless for the tasks I want.
And as the complexity of your score increases, the cutoff goes up. We can quibble about where your personal cutoff is, but it aint 0.
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Starting at 0 is really only useful if you’re plotting a ratio measure and not just an interval one (https://en.wikipedia.org/wiki/Level_of_measurement#Interval_... ), which I’m not sure this “intelligence index” is.
Not at all, as long as it's labeled as such. Coming from engineering/science, this is common.
What is bad is starting at 0, showing an indicator of a gap, and suddenly starting at 30 or whatever after the gap.
It gives you a wrong perspective, especially if you are distracted, on model capabilities: Fable 5.1 is not 30% better than Sol, but is the very first impression you get when you look at the first graph.
If I'm not wrong OAI tried a similar trick when GPT5 was announced ... they have been criticized a lot.
> It gives you a wrong perspective, especially if you are distracted, on model capabilities
Only if you aren't schooled in reading graphs. It's a given that you always have to look at the axes when interpreting a graph.
How exactly would you zoom into a section of a graph and just show that section?
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Yeah, this doesn't include older models, some of which were already saturating many common tasks a year ago. I'll often add them to the AA graph for reference.
Yeah this is really funny and annoying. They get better later on in the article, but it is questionable.