LeonardoTolstoy

I, at this point, use Qwen2.5-VL-3B-Instruct for most of the small OCR I want to do. It is much much better than my experience with Tesseract in general. The nice thing about it is that if you give it, say, a movie poster you can ask for the "title of the movie" and it will, to the best of its ability, do just that, no need for regex or filtering after. For smallish images after loading the 3B model runs in <1 second. 7B takes longer but is obviously more accurate.

I might be a bit behind, all of this is from early this year for the most part, but for something like "I have 3000 movie posters and I want to get the titles with like 90% accuracy" it is good (much better than Tesseract), and it'll do that in like an hour.

EDIT: I guess one thing is Tesseract will kind of give gibberish back when it fails. The main issue with the LLMs are that instead they take a stab at it (like for a movie poster it'll give part of a quote, or a actor name) back. Makes knowing when it fails a little harder. As long as you have some way to verify when it is likely failing they are very good though.

What models did you use for the stages? I see Qwen2.5-VL-7B-Instruct mentioned as an advanced option, so I assume maybe Qwen2.5-VL-3B-Instruct by default (which is what I also use for a lot of stuff, it is incredibly good at "clean" OCR, but as you maybe indicate not the best at "describing a scene").

EDITED: I didn't realize Whisper was a local model. I never tried transcription before, so I had always figured it was a pay model by OpenAI. I'll have to check it out (although the runtime listed here is a bit daunting).

For that project I'll say I don't see much degradation in embedding quality at much much worse quality than 720p (all the way down to 240p), which speeds things up considerably. Although I don't really do face or object detection, just scene embeddings. To me any process whereby it would take longer to process the video than watch it is probably a no go in general. Obviously a challenge for local-first analysis.

I feel like if you followed the NBA scandal involving Chauncey Billups the wire fraud charge for insider prediction market trading was inevitable.

Damon Jones didn't work for the NBA and basically just told some people the status of an injury to LeBron because he hangs out with him (in exchange for money). His crime I guess is gambling illegally? But wire fraud (I think they even say "creating a fraudulent market") was thrown in there.

Seemed inevitable they were going to start charging prediction market insiders the same way.

It is a spectrum. My advisor was very hands off. He didn't, ultimately, even really understand my PhD. He knew the problem, but he had no path in mind to solve it, that was up to me. I'm now working (as a software engineer) with a person who is very hands on with his students (and even postdocs) to the point of giving them specific tasks to do and then discussing the result every week. He defines the problems and structure of the solution, the students at least partially are an extension of himself, they are doing stuff he merely doesn't have time to do himself.

And there is everything in between.

Most of my podcasts are movie related. If I had to purge them all and start with just 5 though I would go with.

Blank Check The Flophouse 99% Invisible Cautionary Tales The Rewatchables

I maintain The Flophouse is the funniest podcast around.

I read close to 40 books this year which I assume is up from the previous year, and way more than I used to read prior to starting to do the Rochester Library reading challenge (which I've done for the past two years). I won't get into a lot of it, but after reading Middlemarch three years ago, Napoleon: A Life two years ago, and The Power Broker last year I decided to read two "big" books.

In the first half of the year War and Peace, which obviously was excellent, although I liked Middlemarch more.

In the second half of the year David Copperfield which was very excellent. Just beautifully written. I still think I probably like Middlemarch more... but it might now require a re-read to know for sure.

This year is going to be Tom's Crossing to start as I just got that for Christmas.

This is it. I had the same thing happen to me a year ago and there was a month between the original access to our system and the attack. And similarly they waited until a perceived lull in what might be org diligence (just prior to thanksgiving) to attack.

Almost this exact thing happened to me about a year ago. Very old account login, SES access with request to raise the email limit. We were only quickly tipped off because they had to open a ticket to get the limit raised.

If you haven't check newly made Roles as well. We quashed the compromised users pretty quickly (including my own, the origin we figured out), but got a little lucky because I just started cruising the Roles and killing anything less than a month old or with admin access.

To play devil's advocate a bit. In our case we are pretty sure my key actually did get compromised although we aren't precisely sure how (probably a combination of me being dumb and my org being dumb and some guy putting two and two together). But we did trace the initial users being created to nearly a month prior to the actual SES request. It is entirely possible whomever did your thing had you compromised for a bit, and then once AWS went down they decided that was the perfect time to attack, when you might not notice just-another-AWS-thing happening.

Does that count the time it takes to get a masters? I feel like I recall my coworkers in England doing a 1-2 year masters, and then the 3-4 year PhD after.

Maybe a nonsequitur but in grad school I was in a study group which naturally split into two. In one group (mine) we'd read a problem and immediately charge in, sometimes have to backtrack, and meander around until the answer revealed itself. In the other they would plan everything out, and figure out what they needed to do, and from that the answer would reveal itself and they would write it all down.

The interesting part is neither group really finished the problem sets faster than the other. Individual problems my group could, if we knew or guessed the right path immediately, be faster. But over the span of a 10 question p-set it would mostly come out in the wash and both groups would finish in roughly the same amount of time.

I often think back on that when reflecting on how I still work that way years later.

Library. I order DVDs to my local library all the time. Maybe your library system is terrible, but if it isn't you certainly can do this. There are hundreds a big wide release films with, effectively, are only available on DVD from a library (legally).

Bonus when I go I can still get that browsing the aisle experience like in an old video store (but in this case I am lucky, my local library has a large DVD / Blu-ray collection to browse)

Tolstoy after my old dog. But also because I think a good language name should be able to be iterated on. E.g. C can become D or E or F. Java can be Mocha or Cappuccino. Etc.

With my new language Tolstoy you'd be able to have a little family of languages all named after classic authors. Tolstoy, Dickens, Melville etc. Plus my dog Tolstoy was the best dog ever so bonus for everyone as well.

You have to go pretty deep though for the record. At least, using one of your examples, for Altman if you look at his top 25 films on Letterboxd, 20 of them are available to rent or stream online. And for me at least the other five I can get at the library. There are none that are totally unavailable of those 25.

How's your local library system?

My local library and the nearby highschool both have solar panels over the parking lot. They certainly exist. I suppose the ROI they've had would be interesting (although this is in Massachusetts so not exactly the solar capital of the world as far as potential is concerned).

I do like them though. Gives both shade and (some) rain cover.