lordmauve
Joined 13 years ago
Joined 13 years ago
I think that buys enough credibility to propose an alternative.
I think there's a case to answer if Anthropic models underperform on a novel benchmark. I'd like to see more novel benchmarks to get a clearer picture.
Or maybe it is, but publish the DeepSWE numbers so we can see for ourselves.
I'm in the UK but my work PC's Internet exit node is in New York due to enforced use of corporate proxies, so the time shown to me is 5 hours out. Javascript would report the correct timezone.
It is not possible to correctly identify physical location from IP addresses. Not just because of proxies and VPNs and the accuracy of the data: you can go near a border and find your mobile phone connects to a cell tower in a neighbouring country, without even visiting! IP Geolocation is accurate enough for statistics and marketing but probably shouldn't be used for anything user-facing.
If someone is right a lot they are likely not making assertions about things that they know nothing about.
If they are making assertions about a domain and those assertions are correct then that domain is one of their competencies.
"Utterly useless" is a bit extreme but it's a reasonable observation to say it doesn't have predictive power.
> I agree, but that's not what the author thinks:
The author of this document is Martin Richards, the creator of BCPL. Of course he thinks you would want to learn it.
If you use wheat flour you will change the flavour and also add a slight graininess as the flour grains don't completely homogenise.
If you have a shiv working it stays working, assuming you have a solution to distribute the required interpreter version.
"What would I get for this share?" can be answered with a float.
"What did I get for selling this share?" should probably be a fixed point value.
This kind of bullshit is how I made a career rewriting people's buggy shell scripts in Python