lordmauve
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
There are huge risks to AI today in terms of upheaval to economies and harms to individuals and minorities but they need to be tackled by carefully designed legislation, focused on real harms, like the EU AI legislation.
Then that imposes very specific obligations that every AI product must meet.
It's both better targeted, has wider impact across the industry, and probably allows moving faster in terms of tech.
If I can't extract .pack archives 3 decades from now, the use of SQLite 3 will be the reason.
This happens all the time. For example, cancellation in the middle of sending a HTTP request. The connection is now unusable and must be closed. Without cancellation the connection returns to a state where it can be used and is re-added to a pool.
C extensions don't significantly change matters because the module is still constructed by procedural C code.
One thing I love about Rust is that it uses u16, u32, u64 etc for unsigned and i16, i32, i64 etc for signed, which is about perfect - clear, concise and future-proof. That would be perfect for this library.
If nothing else, use lists because the syntax means it stays as a list even if you someday remove all but one option and forget to leave a comma, eg.
REASONS = [
'leaves on the line'
]
vs REASONS = (
'leaves on the line'
)default_reasons doesn't need to be a dict. Use a list.
You don't need random.randrange(). Use random.randint() to select a random integer and random.choice() to select a reason from default_reasons.