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There are plenty of demo videos on Twitter:

https://x.com/colin_d_m


that doesn't help people who aren't on twitter.




Does it not? I could view the videos in incognito


The motion tracking system used by ARKit/ARCore is called SLAM, combination of sensors + camera data if available.


Sure, but my point was that just because something uses the same inputs and gets a similar output doesn't mean the processing is the same. This is just localization. Which is still impressive. But I'm not understanding there being any mapping going on.


Great question. Partly on device compatibility, but mostly that we can achieve an amazing, reliable experience right now without those anchors. If we weren't getting the accuracy we needed from our current methods, we would have to look at alternatives like UWB and consider the trade-offs.


We've had the solution live in stores for years without any issue. Our algorithms can clean up and filter out unreliable data, based on all of the other data we have, from other APs, from previous data etc..

If they re-fit the WiFi, which they might spend a month doing once every 5-10 years, it would need a re-survey, which could take 1-2 hours. But thankfully no new infrastructure.


Thank you! I tried to keep it interesting but not get lost in rabbit holes.

We have around 300 hours of ground-truth data now, in 1-second intervals, which we use for algorithm training and refinement. The same as performing a survey, our team marks their location on the map, then walks to the next location, and through post-processing we can correct any errors and interpolate the locations in between. You can see this process in the diagram with the large black dots, where the user marked their location.


Thanks for the feedback. I wanted to keep it balanced to be accessible but also insightful.

To answer your point: we have the digital map, can use that to understand obstacles etc in the space. In some of those larger stores you see in the visual, we typically survey the entire store within 2-3 hours, it's low-effort work, not a blocker.


All of the videos shown on the speed-run of our technology is on 4 year-old Android devices, such as Samsung S21, Pixel 6 etc.. We always test and gather statistics on older devices to fairly represent what's available, rather than latest-and-greatest.


So, devices that were top of the line a few years ago. But what about budget devices? in the 100-200 range new? I remember my old xiaomi started literally running in circles as the phone heated up 10-15 minutes after starting navigation: If i stood still the position would move in a circle of a few meters of radius.

Incidentally, the devices you metion are what i also use to develop, because those line of products actually behave as they should, per documentation. But most bugs and crashes always come from budget and no name devices because both the hardware and firmware is crap


Thanks. Very interested in robotics so that'd be an ideal home, given the SLAM + sensors tech stack.


Yes - one of the limitations with mobile is engaging the camera/quality of the SLAM. With a robot, they're already using SLAM with strong tracking, and controlling the hardware stack means no device limitations (uncalibrated sensors, limited WiFi pings etc.)


Aside from saving time, I'm bad at writing. Especially emails. I often open ChatGPT, paste in the whole email chain, write out the bullets of the points I want to make and ask it to draft a response which frames it well.


I'd prefer to get the bullet points. There's no need to waste time reading autogenerated filler.


> write out the bullets of the points I want to make

Just send those bullet points. Everyone will thank you


My boss does that I am sure

One of their dreadful behaviors, among many

My advice is to stop doing this for the sake of your colleagues


Hopefully you're specifying that your email is written with ChatGPT so other parties can paste it back into ChatGPT and get bullet points back instead of wasting their time reading the slop.


Why not just send the bullet points? Kinder to your audience than sending them AI slop.


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