almstimplmntd

Joined 10 years ago

Karma
25
Submissions
16
Member since
Dec 4
2023-now: building @ happenstance.ai 2021-now: PhD student in machine learning + music data science

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2017-2021: ML-engineer (Lighthouse A.I. --> Apple)

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Recent submissions

Comment · 1 month ago
Comment · 1 month ago
a steepness penalty could make sense!

your example (from market & taylor to the top of nob hill) is a nice illustration: (1) straight up taylor is 229 ft of climbing at 25%, (2) via polk and california it's 251 ft at 13%.

as you probably noticed, we only look at the total elevation gain, so taylor "wins"... but I see the argument for preferring an extra 20ft of a more gradual climb.

Comment · 1 month ago
thanks! address search uses the overture address feed, which is patchy (some blocks of 24th st have 5 numbers in it)… i'll make it fall back to the nearest known number on the street
Comment · 1 month ago
Once I was visiting Yamaha’s Yokohama office for work, and I found a pedestrian path from my hotel to the office of ~2.5km that never touched a single roadway…

Google Maps absolutely failed.

Would be fun to rig up something for these cities. Which are you in btw?

Comment · 1 month ago
fair point! it just doesn't know about bike lanes yet, I’ll see about getting the SFMTA bikeway network map from DataSF.
Comment · 1 month ago
good point.. the slider trades distance against total climbing and nothing else. steepness is currently reported but not optimized.

seems like a worthy addition to the objective!

Comment · 1 month ago
ah, I think this is related to SF's "Slow Streets" program and a genuine bug in the parser.

Cabrillo is a Slow Street, and the parser read its "destination-only" tag as closed to pedestrians, so the tool couldn't see the street at all (and started you a block over?). fixed and deployed; your trip should now go Cabrillo → 23rd → Geary.

Comment · 3 years ago
I would like to see human performance on the introduced benchmark, AmbiEnt, and have it added to Table 4.
Comment · 4 years ago
For AMZN software staff (especially in SF Bay Area): was it really 160K capped?

Obviously RSU grants / bonuses are excluded from this, but I still find that surprisingly low (as a salary cap) for FAANG, especially around SF.

Comment · 6 years ago
Played with the gilbert gottfried speaker option, gave me serious Twin Peaks "Red Room" vibes.
Comment · 6 years ago
A bit tangential but related: has anyone else noticed an increased frequency in the desired result of a Google search being the first one on the second page?

Particularly for things involving reviews or booking, I have noticed an uptick in the (subjectively) “right” result being kept off page 1... it seems almost like some post processing logic to favor specific sites/companies. The fact that the “right” result in these instances is almost always the first result makes me think the true Ranking function knows the result’s actual value.

Comment · 7 years ago
Comment · 8 years ago
So is “Quantum“ pure buzzword hype? Or is there a reasonable connection to the product?

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