530 karma · joined March 14, 2014
perfect tutorial is just one search away from understanding everything but understanding nothing because breadth without depth is just surface tension holding together illusion of knowledge that breaks moment you try to apply it but application requires confidence and confidence comes from experience and experience comes from doing and doing requires starting which brings us back to fundamental problem of infinite choice paralysis paralyzed by possibilities spending hours researching best way to do simple task that would take minutes if just picked any way and did it but what if there's better way what if missing crucial optimization what if code isn't clean enough for imaginary code review by developers who don't exist because project doesn't exist because still researching best practices for project type I haven't defined but definition requires decision and decision tree has infinite branches each leading to different tutorial series on youtube where someone explains their way is best way until next video autoplays explaining why that way is actually worst way and real best way is completely different approach requiring different tools and different mindset and different everything except result which is same hello world application with extra steps but those extra steps are what separate amateurs from professionals according to blog post written by someone selling course about becoming professional which I almost buy before remembering
It says - Numbers of the form a^2 + n*b^2 are closed under multiplication.
Weird = True generates the puffy/bloated JD Vance that's circulating around
Weird = False generates regular JD Vance
In Advance Mode you can guide generation with your own prompts. Works best with simple word combinations like Goth Pony, Vladimir Putin, Fairy muffin splat etc
Made using an ancient workflow - SDXL + IP Adapter etc
Star => Twinkle => Twinkle Khanna => Married to Akshay Kumar => Canadian Citizen => Maple Syrup ( Leaf ? )
Intersecting Lines https://replicate.com/p/s24aeawxasrgj0cgkzabtj53rc
Overlapping Circles https://replicate.com/p/0w026pgbgxrgg0cgkzcv11k384
Touching Circles https://replicate.com/p/105se4p2mnrgm0cgkzcvm83tdc
Circled Text https://replicate.com/p/3kdrb26nwdrgj0cgkzerez14wc
Nested Squares https://replicate.com/p/1ycah63hr1rgg0cgkzf99srpxm
Here's an interesting tidbit from his wikipedia page - He is not related to the Russian mathematician Grigori Perelman, who was born in 1966 to a different Yakov Perelman. However, Grigori Perelman told The New Yorker that his father gave him Physics for Entertainment, and it inspired his interest in mathematics
Tested with one of the comments from this thread.
requests.post(
"https://x2vud9xfq0.execute-api.ap-south-1.amazonaws.com/api/text/classify",
json={
"text": """
And, to be frank, I can't see why I'd send my confidential information to you when I can send it to Google. (Ahem!)
But the problem with theirs and yours is the OOTB categories are for a global topic set, something like Yahoo directory, rather than for a given discipline. And what's generally needed is a set of disciplines, or several topic trees. (Think Amazon.com instead of Yahoo.)
I've found the general lists, like LCM[^1] (what you really want is LCSH[^2] subject headings, not LCM), too broad for my business or personal content, while something like ACM[^3] is more what's needed for, say, computing related content.
For a firmwide knowledge base at a {field}-tech firm, you have a mix of the firm's focus field, and computing, and a broad scope fallback like you're starting with. Even libraries have their own topic hierarchy! [^4]. Plenty fields have controlled vocabularies[^6], and if you can't find one for a field, you can usually generate one by finding someone who is already classifying that field, and looking at their TOC. All of which is to say, to be generally useful, you have to let people BYOT (bring your own topics) for this.
For instance, we built our topic list based on combining a reference taxonomy for our field, a reference taxonomy for computing, a reference taxonomy for business books, and the Google NLP tool mentioned above.
There are occasional tools that try to match arbitrary documents to arbitrary hierarchies such as clerk [^5] but they are challenging for various reasons.
You have a note to contact you for different topics, but raising this here since so far (6 hours) you had no feedback, and I'm a big fan of what you're doing and the niche is underserved.
A couple other thoughts:
""",
'key': 'HACKERNEWS'
}
).json()
{
'genres': {'Technology': 24, 'Finance': 16, 'Education': 11},
'tags': {'/Business & Industrial/Small Business/MLM & Business Opportunities': 5.094265117745211,
'/Internet & Telecom/Web Services': 5.51434499612552,
'/Finance/Investing': 5.72584536853734,
'/Business & Industrial/Business Operations': 5.888633926463297,
'/Jobs & Education/Education/Standardized & Admissions Tests': 6.0132143106028435,
'/Business & Industrial/Business Services': 6.100261915913882,
'/Jobs & Education/Jobs': 6.126547614437338,
'/Science/Earth Sciences/Atmospheric Science': 6.1553064528175545,
'/Finance': 6.249046550441405,
'/Business & Industrial': 6.333431648078183},
'id': '65f891a111ec14ddd4b56bda'
}
Your result {
"result": [
[
"/Arts & Entertainment/Books & Literature/Reference",
0.138976
],
[
"/Jobs & Education/Job Listings",
0.138976
],
[
"/Computers & Technology/Networking/Distributed & Cloud Computing",
0.069488
],
[
"/Jobs & Education/Online Learning",
0.069488
],
[
"/Arts & Entertainment/Music & Audio/Music Reference",
0.046325
]
]
}Links to a couple of my creations/generations
Made with Processing - https://twitter.com/Pfatagaga/status/1697919529945555280
Made with Diffusers - https://twitter.com/Pfatagaga/status/1696091383361327493
https://twitter.com/Pfatagaga/status/1696092107545759791/pho...
Here's something interesting I did few days ago.
- Generated images using mixture of different styles of prompts with SDXL Base Model ( using Diffusers )
- Trained a LoRA with them
- Generated again with this LoRA + Prompts used to generate the training set.
Ended up with results with enhanced effects - glitchier, weirder, high def.
Results => https://imgur.com/gallery/vUobKPK
I’m gonna train another LoRA with these generations and repeat the process obviously!
This is a pretty neat way to bypass the 77 token limit in Diffusers and develop tons of more styles now that I think about it.
You can play around with the LoRA at https://replicate.com/galleri5/nammeh ( GitHub account needed )
Will publish it to CivitAI soon.
Programming in particular was a gamechanger for me and helped me see and appreciate the beauty in practical problem solving using simulations etc.
I kinda took that to the extreme when I was young. Used to loathe anything practical - experiments, programming, applied math etc cuz you know they weren't "pure" and engaging enough. I would also have a hardtime processing/registering something if I'm not able to derive it analytically from first principles. It felt like cheating if I have to use a formula without fully understanding how it was derived haha.