sudo jajos
Lol lemme tell u, if u were paid 8,881, 255 birr(58,800 dollars) each hour starting from Christ's birth each day without missing u wont reach him bruh ๐๐๐ This is such a disgrace๐๐๐ Ofc u should be aware of the context ๐ณ๐ณ(Elon) @sudojajos
๐คฆโโ๏ธ๐คฆโโ๏ธ๐ถโ๐ซ๏ธ๐ถโ๐ซ๏ธ๐ถโ๐ซ๏ธ๐ซ ๐ซ ๐ซ
The increase rate per-(minute, hour, day, or year)
@sudojajos
The increase rate per-(minute, hour, day, or year)
@sudojajos
๐ฑ1
Forwarded from Bytephilosopher
แแแซแ แฐแแ แต๐
#gotochurch #Sunday
@byte_philosopher
แจแแแฐแ แแแ แญแ แฅแแแค แ แฃแดแ แญแแฐแแแค แแฐ แฅแญแฑแ แแฅแฐแ แ แฅแญแฑ แแแต แแฐแชแซ แฅแแฐแญแแแแข แจแแญแแฐแ แแ แแแ แ แญแ แฅแ แแค แญแ แ แจแแตแฐแแต แแ แจแแจแ แจแ แฅ แแ แแ แฅแแ แจแฅแ แแ แ แญแฐแแแข
แจแฎแแแต แแแแ 14:23-24
#gotochurch #Sunday
@byte_philosopher
โค6โคโ๐ฅ3
This media is not supported in your browser
VIEW IN TELEGRAM
what can I say๐
Was just studying web for exams and I had to send this ๐ ๐
Was just studying web for exams and I had to send this ๐ ๐
๐คฃ5
https://arxiv.org/abs/1711.03705
One of the research papers I will after exams and some work related loads ...
The paper is about online deep learning -> u know the opposite of it which is offline deep learning(if ur familiar with online RL and offline RL it is analogous here).But ofc u dont need to know RL to understand there difference. So, basically the difference between these two is the offline DL is the approach where u have collected and static data then u train ur model then voila u have some learned parameters that are fixed till u have full or partial finetuning here after ... but in online DL u can update ur model on the fly and this is critical for streaming data(I think we can say for example stock price prediction perhaps), non-stationary data ...
I was about to read it because I have something in mind to research about and I will tell u after finals and work loads ... ๐
#papers #random
@sudojajos
One of the research papers I will after exams and some work related loads ...
The paper is about online deep learning -> u know the opposite of it which is offline deep learning(if ur familiar with online RL and offline RL it is analogous here).But ofc u dont need to know RL to understand there difference. So, basically the difference between these two is the offline DL is the approach where u have collected and static data then u train ur model then voila u have some learned parameters that are fixed till u have full or partial finetuning here after ... but in online DL u can update ur model on the fly and this is critical for streaming data(I think we can say for example stock price prediction perhaps), non-stationary data ...
I was about to read it because I have something in mind to research about and I will tell u after finals and work loads ... ๐
#papers #random
@sudojajos
arXiv.org
Online Deep Learning: Learning Deep Neural Networks on the Fly
Deep Neural Networks (DNNs) are typically trained by backpropagation in a batch learning setting, which requires the entire training data to be made available prior to the learning task. This is...
โก1
Forwarded from Biniyam
This is the US straight up telling the world their stance. Even if they build AGI (btw trained on dataset across the globe) theyโre most likely not sharing it with us.
แจแฐแ แแแญ แจแฐแ แแ๐
Thatโs why we need our own models. More African/Ethiopian startups building AI infra. Depending on gatekeepers is always gonna put us in a disadvantage.
@b1n1yamBuilds
แจแฐแ แแแญ แจแฐแ แแ๐
Thatโs why we need our own models. More African/Ethiopian startups building AI infra. Depending on gatekeepers is always gonna put us in a disadvantage.
@b1n1yamBuilds
๐ฅ1
19. แ แแฐ แแ แฅแ แ แ แจแแญ แฐแฐแตแญแค แซแบ แจแณแแแฝ แ แแแแญแ แฅแแดแฃ แ แฅแแแน แฅแแถแฝ แจแแแปแธแแ แฅแแ แแต แจแแซแแ แฑแต แ แแญ แ แแญแซ แ แ แแฐ แแต แตแณแแ แตแแแฃ แแแดแ แจแแซ แจแฃแต แจแแ แแตแฅ แ แแฃแแตแข แแญแแซแฑแ แฅแญแท แฃแแต แฅแแแตแ แซแแฐ แฃแแแฝแ แแแแณแ แฅแญแณ แฅแ แจแแตแฉ แแแแ แ แญแณ แแ แญแค แ แคแฑ แแณ แแญแฃ แ แแฐแ แตแ แตแ แณแแ แฐแแแตแข แ แแฐ แฐแแแตแฃ แแแฃแแแ แ แแแ แ แแค แซ แแแฃ แ แแฐแฐแ แต แตแแซ แแแฃ แฅแญแท แ แธแแจแฝแ แต แฆแณ แแ แแตแฉแ แซแจแฅแฅ แแ แญแค แ แแฃ แ แแฐ แฐแแแตแข
St. Augustine
Our parents have paid a lot for as being here and now ... U might have forgotten and we might have been ignorant of the plain fact but they indeed had ... yeah it might manifest in different forms ... they prayed for us, they provided us their deep and true love, they taught us in different ways ... u name it. Even if it cant be worth of their effort lets be successful as in their eyes it is the greatest of all things on earth to happen
@sudojajos
โค10
https://raytracing.github.io/
A good hands-on teaching book on Computer graphics where u build ur own ray tracer while learning from scratch .... I would have read and done it but I am reading for finals(so u know ๐) ... so if it just helps I am sending it here ... ๐
@sudojajos
A good hands-on teaching book on Computer graphics where u build ur own ray tracer while learning from scratch .... I would have read and done it but I am reading for finals(so u know ๐) ... so if it just helps I am sending it here ... ๐
@sudojajos
๐ฅ2
How much I am planning for this summer ๐๐จ๐จ๐จ,there are lots of things ... what about you?
but yeah we will manage ๐ช, will share what is in my mind ...
@sudojajos
but yeah we will manage ๐ช, will share what is in my mind ...
@sudojajos
๐ฅ2๐1
Totals
๐ Shared Expenses is now available in Totals Split expenses with friends, end-to-end encrypted. What's new in v1.5 Shared Expenses โข Create private groups for splitting expenses โข Track who paid, who shared, and who owes who โข Settle balances, send nudgesโฆ
Of course we should use this ๐๐๐
๐2
Forwarded from Dagmawi Babi
ScholarXIV
Introducing Papers API
This media is not supported in your browser
VIEW IN TELEGRAM
Introducing Papers API
โข scholarxiv.com/developers
We hosted 3,032,697+ (3M+) papers so you don't have to explore research at the rate of one query per 3 seconds (arXiv's API limits) โ instead you can explore research at 3,600 queries per hour.
That's one query every single second, everyday! With that kind of rate you can imagine what kind of research agents and products you can build!
Filter by title, author, category, abstract, or date. Get clean, structured metadata containing titles, authors, abstracts, categories, PDF links and more without parsing XML or rate-limiting yourself.
Alongside the Papers API we're also launching our developers platform. This's where you can manage your API keys, track usage, try the playground and explore the documentation.
There's a lot more we're building and we can't wait to see what you're going to build with this.
#Launch #PapersAPI #DevelopersPlatform
@ScholarXIV
โข scholarxiv.com/developers
We hosted 3,032,697+ (3M+) papers so you don't have to explore research at the rate of one query per 3 seconds (arXiv's API limits) โ instead you can explore research at 3,600 queries per hour.
That's one query every single second, everyday! With that kind of rate you can imagine what kind of research agents and products you can build!
Filter by title, author, category, abstract, or date. Get clean, structured metadata containing titles, authors, abstracts, categories, PDF links and more without parsing XML or rate-limiting yourself.
Alongside the Papers API we're also launching our developers platform. This's where you can manage your API keys, track usage, try the playground and explore the documentation.
There's a lot more we're building and we can't wait to see what you're going to build with this.
#Launch #PapersAPI #DevelopersPlatform
@ScholarXIV
This media is not supported in your browser
VIEW IN TELEGRAM
A math learning tool that teaches u every topic by generating manim-slides or manim videos and every video having the insane story telling Grand Sanderson's videos have would be like an insane product a lot of us would buy ... but the problem is current LLMs generate shitty manim codes ... I mean shitty as compared to 3b1b's videos ...
The above was about line clipping algorithm in computer graphics and I dont think it was explanatory enough ... I dont buy the storytelling it followed and also overlapping texts blah blah but just to give u a sense how insane it would be to have that kind of platform ... Who knows this could grow to something ...
#manim #animations
@sudojajos
The above was about line clipping algorithm in computer graphics and I dont think it was explanatory enough ... I dont buy the storytelling it followed and also overlapping texts blah blah but just to give u a sense how insane it would be to have that kind of platform ... Who knows this could grow to something ...
#manim #animations
@sudojajos
๐ฅ1
sudo jajos
A math learning tool that teaches u every topic by generating manim-slides or manim videos and every video having the insane story telling Grand Sanderson's videos have would be like an insane product a lot of us would buy ... but the problem is current LLMsโฆ
https://www.youtube.com/shorts/nXIHYB0Gp70?feature=share
dont u see how insane it would be to have a platform that made videos like this for every topic u aspire to deeply understand ... ๐ฅน๐ฅน๐ฅน
dont u see how insane it would be to have a platform that made videos like this for every topic u aspire to deeply understand ... ๐ฅน๐ฅน๐ฅน
YouTube
Fourier series
A link to the full video is at the bottom of the screen.Or, for re...
แฅแแแ แฅแแญแกแจแ แซแตแกแแแกแญแ แฝแกแแตแคแแคแตแแกแฅแแตแญแแฅแ แญแทแแกแฐแตแกแญแ แแแข
แแ 118 แฅ 24
แแแซแ แแ ๐ฅฐ๐ฅฐ๐ฅฐ
@sudojajos
โคโ๐ฅ5
sudo jajos
https://telegra.ph/Train-Serve-Skew-06-18 #5min #post #ai @sudojajos
You would stumble upon same kind of problems often ... like for example I had. When working on video generation models, I had been tasked to increase the number of frames, i.e., the generated time length, but the model we were using was trained to only accept 81 frames at once - so feeding it 120 frames or beyond would collapse the generation pipeline (a customary challenge of distribution differences) ... and there are a lot instances ... Ur training data distro should be the same with the one the model gets when served (online)
@sudojajos
@sudojajos
๐1
Forwarded from Ezra's Ramblings
This week Ethiopia is getting so much representation ๐
[Hacker attempting to steal 69BTC, with piss poor opsec, is from Ethiopia]
[Hacker attempting to steal 69BTC, with piss poor opsec, is from Ethiopia]
OALABS Research
Captured Logs Reveal Hackers Using Claude and Codex to Breach Companies
Full agent sessions captured on a compromised host turned honeypot offer an unprecedented look at how attackers are using AI in real-world intrusions.