These are a must for any mid-size seller. Their goal is to pretty self-explanatory; reprice your ASIN, live, to hit maximum sales. If your competitor is selling the same mug for $10.00, the repricer sees that and immediately reprices your mug for $9.99.
Its one of those "Well, if I don't use one, others will" situations.
Thanks to whoever posted this 11yo gem. I've never read it. Its humbling and encouraging to see someone willing to post his fumblings even in his 50's. I feel like he'd been lambasted or mocked had he posted this today on substack or twitter.
As a younger man I was more of the "Just say what you mean, get straight to the point" kind of guy. I think what changed for me is that I learned that people are often much more interesting than their opinions. Going to someone wanting one-word answers to everything (outside of a work context) can become very impersonal and extractive. Its reductionist. It's assuming you're the only one with deep thoughts, conflicted feelings on certain topics, and interesting opinions.
I'd also add that they're hoping Jevon's Paradox also leads to a whole new segment of users who would have never reached for a classifier in the first place, given the barrier to entry.
Yes this is what I'm interested in. I think they might be right. I'm already finding myself thinking "well maybe a classifier would be useful here now that it's so easy to do...".
This probably just means that I could have been reaching for that tool more often already. But in practice I wasn't, and this has opened my eyes to the potential opportunities there.
And if you do get complaints or feedback on the classification, have a dev log into the user's account, tweak the Jev prompt a little until the issue goes away, and push it to production
> "[I don't understand what it's actually doing under the hood, or why we should be excited.] Jev feels more and more like a glorified if/else block"
You should be excited because there's so many low-hanging classification problems (e.g. "Is this email spam?", "Is this yelp review happy or sad or neutral?") that a "cheap" LLM is overkill for. It really should be this cheap, and now Jev is the first to do it well and do it at scale.
If I was explaining it to my mom, I'd say "Classifying 1000 yelp reviews used to cost $50. Now it costs 5¢, at similar accuracy"
This is one of those masterpieces that I'm surprised hasn't been scooped up by Netflix and turned into a movie.
Its not that I don't like it as a game, but it's just so chock full of character.
The premise alone is so compelling; in the Land of the Dead, even dead men chase money. Even with the literal afterlife a train ticket away, you have conmen and good guys living (or dying?) like there's no end of the line.
Love it. One of those rare pieces of art that continues to live in my head rent-free.
On the other hand, I still think Disney should make a Monkey Island TV show or movie. They could use Sea of Thieves-style water effects in the Volume for useful shenanigans.
> The world ships more than a billion capable phones, tablets, and laptops a year, most with a chip built for exactly this work, paid for and idle most of the day. Run the model there and the economics flip: no per-call cost, no round-trip, and nothing leaves the device.
This. I run small models (>50MB) for bio-imaging/biotech applications, it feels like every README implies that you need a discrete GPU to get started. While some do, many, especially the most useful ones, do not. Sure it matters if you're also going to do fine-tuning, but I believe your typical user just wants to detect some nuclei and get some cell-body ratios.
The laptop on your desk won't be running Meta's SAM, but it has more than enough compute to crunch 100's of your H&E slides overnight.
Cellpose[0] and Stardist[1] are the two you'll see most heavily run and talked about on the forums[2]. They're classic CNN's, but it just feels like they (and any modern models) are swept up in "Go out and buy a 4090.But these guys will give you plenty of mileage before you have to reach for the bigger ones.
I used it for testing my voice agent. It was basically what I expected. Good fast model but "generic" or "vanilla" is how i would describe its personality emulation capability as. Gemma models still outperform it in that department. As far as technicals, one thing i found annoying is cash use was not that good, it missed more then i liked, i contacted support and they were fast and responsive and said they were working on that issue, maybe they solved it with 2.5? Anyways, im prolly gonna try 2.5 again see if anything different, but cant deny the speed, thats the biggest thing this company has going for this offering as if you are in the business of classical cascaded voice agent systems, latency is number one priority and this thing is fast....
latency, instruction adherence, reliable tool cools, conversationality are all in tension.
it's great when you can get a 170ms ttft. but if you have 700 ms endpointing on the stt side and 300ms ttfb on the voice side, then you haven't really made something super snappy.
Love this take. In the bio-imaging space, Napari is a great example of this. Wonderfully solid base, but extremely extensible since its just python all the way down.
There's something wonderful about having my coworker walk up with an issue, and being able to bang out a Napari plugin that solves their exact problem before lunch.
My order of 'tool escalation' usually goes:
- Can I solve their problem from napari's inline terminal?
- Can I solve it with a one-off script?
- Can I solve it with a one-off script that creates a one-off plugin interface?
- Should I add the plugin to our company-wide repo since this problem seems to occur a lot?
Google "FBA repricer" and you'll find companies like https://goaura.com/ and https://sellersnap.io/.
These are a must for any mid-size seller. Their goal is to pretty self-explanatory; reprice your ASIN, live, to hit maximum sales. If your competitor is selling the same mug for $10.00, the repricer sees that and immediately reprices your mug for $9.99.
Its one of those "Well, if I don't use one, others will" situations.
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