Recent submissions

Comment · 3 years ago
same! I was excited to see something so esoteric from my grad school days come up
Comment · 3 years ago
Check out SSCD from Meta https://github.com/facebookresearch/sscd-copy-detection

(full disclosure: I am an employee who has worked with this team before internally, but I was not associated with this paper)

Comment · 4 years ago
Number of times I've had a true positive alert from Apple's new device tracking notifications: 0 Number of times I've had false positives due to intermittent connectivity issues with my airpods or from my partner using mine: over a dozen. I'm this close to disabling all of these features
Comment · 5 years ago
Ha! A friend sent me this comment when he recognized this project. Unless there happens to be another firm who did the exact same thing we did, I was a part of this project (see this blog post https://www.svds.com/introduction-to-trainspotting/).

You misunderstood the point of the presentation. The company was a consulting firm that specialized in data science and engineering. Our clients wanted to kick the tires and see what our technical chops were before hiring us but they didn't want to let us use their proprietary and confidential data for our own tech demos.

We didn't want to just use the same open source datasets everyone else did, so we got to thinking about novel datasets we could create that might have applications for industries we sold our services to. From this, the Trainspotting project was born.

Many of us commuted via the Caltrain, which was right next to our office, and we were frequently frustrated with the unreliability (this was in ~2016 or so when car and pedestrian strikes were happening seemingly every week), so we made an app that tried to provide more accurate scheduling.

We used the official API for station:train arrival times, but we found that it was unreliable, so we wanted some ground truth data on whether a train was passing. Since our office was right next to the Castro MTV station, I had the idea to use a microphone (attached to a raspberry pi) to just listen for when the train went by. In addition to ground-truth data for validating arrival times, this gave us a chance to show off some IoT applications. It actually worked pretty well, but it had false positives (e.g. the garbage truck would set it off). So we added a camera.

We pointed it at the tracks and started streaming data off of it. At first we used very simple techniques, processing the raw stream on-device with classic computer vision algos (e.g. Haar cascades) in openCV. We discovered that the VTA, which had a track parallel to the Caltrain and was "behind" the Caltrain in our camera's shot, could cause false positives. Gradually we used more and more complex techniques like deep learning, but the raspberry pi couldn't handle it (IIRC it could only process a single frame in like 6 seconds). So we used a two-stage validation whereby the simpler, faster detectors that could run on the raw stream in real time detected a positive and then we'd send a single frame to run deep learning.

TL,DR: The whole point was to be a tech demo, not to gauge the speed. The trains were either stopping or pulling out of the station, so speed would have been useless.

Comment · 6 years ago
Instagram doesn't do facial recognition though, so this seems pretty baseless.
Comment · 6 years ago
I'm surprised and skeptical about some of this. In particular:

  We also measured networks across more than 90,000 Microsoft employees in the United States. Frankly, we expected to see them shrink significantly, given the rapid shifts in environment, daytime rhythms, and personal responsibilities. Instead, we discovered that most employees maintained their existing connections. Even more encouraging, most people’s network size increased. We had assumed that in a time of crisis, employees might strengthen networks within their own work groups in an insular way. In fact, we saw network growth not only within existing work groups but also across different groups, indicating that to adapt and thrive teams sought to build bridges.
This does not square with my lived experience. Close connections at work have stayed relatively strong, perhaps even strengthening as we shore them up with recurring 1:1s and social team meetings. Peripheral connections have gone down the toilet. Team and role homophily run rampant.

I wonder what evidence they actually used to back up this statement. I suspect the effect is actually in the opposite (and more intuitive) direction, and that their finding is actually a result of the McNamara fallacy.

Comment · 6 years ago
Comment · 6 years ago
Comment · 6 years ago
BJ's models are breathtakingly simple and universally applicable. Highly recommended reading
Comment · 6 years ago
This whole thing seems overblown. The conditions required to induce NDMA accumulation are so far outside the normal bounds as to be farcical. Every drug I’ve ever seen advises you to keep it in a controlled temperature environment.
Comment · 7 years ago
Incredible. I wish people would take themselves less seriously like this. I would never have read that paper and learned a bit about that space if it hadn't been such an engaging read.
Comment · 7 years ago
They top out at 15 mph in SF. I wish they went faster. I am a cyclist and usually maintain close to 20 mph (not counting lights). It's kind of maddening not to be able to go 20 or 25 on them.
Comment · 7 years ago
At a sufficiently large scale, even rare events happen constantly.
Comment · 7 years ago
Can confirm
Comment · 7 years ago
No. Did you read the OP's article? I'll excerpt a relevant section for you:

Although the current focus on isolation is often described in the media as “the loneliness epidemic,” Robin Hewings, Director of Campaigns, Policy and Research for the U.K.’s Campaign to End Loneliness, warns that for a subjective, self-reported experience like loneliness, “it’s not very easy to make comparisons across time, and it’s not obvious that it’s getting worse.”

While he acknowledges that aging populations mean that there are likely to be a greater number of elderly people around who are suffering from isolation than in previous decades, he also points out that when you look at the percentages of those affected, the trends are harder to discern. “There was some work done in the late 1940s, which would seem to suggest a not dissimilar level to today. This is right at the speculative end,”

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