An advice from wise LLMS :)
1. Curiosity Needs Direction
2. The Artifact Is Not the Goal
3. The Urge Never Leaves
4. Depth Compounds
5. Don't Optimize for Applause
6. Foundations Before Innovation
7. Let Difficulty Teach
8. A North Star
#advices
@sudojajos
Notes to My Future Self
1. Curiosity Needs Direction
Curiosity is a gift.
But unmanaged curiosity can become a trap.
Don't let your curiosity trick you into starting five foundations at once.
You don't build depth by touching everything.
You build depth by staying with something long enough for it to become difficult, confusing, and eventually clear.
The goal isn't to learn everything.
The goal is to learn something deeply.
2. The Artifact Is Not the Goal
When I ask:
"How long will it take?"
Sometimes what I'm really asking is:
"Can I have the artifact soon?"
The understanding-brain asks:
"What should I do next?"
The artifact-brain asks:
"How quickly can I finish?"
The understanding lasts.
The artifact is only evidence that the understanding happened.
The artifact is the receipt.
The learning is the purchase.
3. The Urge Never Leaves
The urge to rush.
The urge to show progress.
The urge to impress.
It doesn't disappear.
Senior engineers feel it.
Researchers feel it.
Founders feel it.
The difference is not that experienced people are free from the urge.
The difference is that they learn to recognize it and not let it drive the car.
4. Depth Compounds
Six months spent understanding a foundation is rarely just six months.
Deep understanding compounds.
Knowledge stacks.
Depth in one area often becomes leverage in another.
5. Don't Optimize for Applause
Many people optimize for things they can show.
Few optimize for becoming the kind of person who can build those things repeatedly.
One creates temporary results.
The other creates capability.
Choose capability.
6. Foundations Before Innovation
Before asking:
"How can I improve this?"
First ask:
"Why does it work this way?"
Most good ideas come from understanding existing solutions deeply enough to see their tradeoffs.
Innovation built on ignorance is guessing.
Innovation built on understanding is engineering.
7. Let Difficulty Teach
The temptation is to remove friction.
But often the friction is the lesson.
The bug.
The confusion.
The failed experiment.
The week spent stuck.
Those moments are not interruptions to learning.
They are learning.
8. A North Star
Desire to become the person who deeply understands things, not just the person who shows things.
When roadmaps fail,
when timelines slip,
when progress feels invisible,
this matters more than any deadline.
Becoming the person is the real project.
Everything else is a byproduct.
#advices
@sudojajos
๐3๐2
Me: "I want to learn X."
Brain: "Okay, but first let's understand the foundations."
Foundations: "To understand me, you need these foundations."
Those foundations: "To understand us, you need even deeper foundations."
Me, 5 years later:
"The good news is I now understand the origins of the universe."
๐
#memes
@sudojajos
๐6๐ฏ2
Lemme introduce u to my Sister Nahili :) She is grade 5 ... and u know I want her to be great in her future spiritually and also in her worldly life ...
Two years ago I thought her how to code just plain html, css(and she was having fun writing some page which includes collage of images of our family แตแแ แ แตแ แ แแแแ) and after that I thought her scratch(u know this right) and am very glad she is interested on it and even she built a trivial game but u know it was interesting if I find it will send u ... แฅแ now I was not even following up on her but she is using it and participating in แแ แซ แแตแตแญ in her school that is fire แจแแญ
I buy her books to read and she even read more than 5 books, each more than 5 times(because I forgot to buy her new ones) and she can tell me what is next to the sequence of words I say ... Just she is fire ๐ฅ
แฉแฌ แฅแซแแ we needed like someone just to spark our curiosity and just guide as a bit and we could have done a lot ...
#guidance #siblings
@sudojajos
Two years ago I thought her how to code just plain html, css(and she was having fun writing some page which includes collage of images of our family แตแแ แ แตแ แ แแแแ) and after that I thought her scratch(u know this right) and am very glad she is interested on it and even she built a trivial game but u know it was interesting if I find it will send u ... แฅแ now I was not even following up on her but she is using it and participating in แแ แซ แแตแตแญ in her school that is fire แจแแญ
I buy her books to read and she even read more than 5 books, each more than 5 times(because I forgot to buy her new ones) and she can tell me what is next to the sequence of words I say ... Just she is fire ๐ฅ
แฉแฌ แฅแซแแ we needed like someone just to spark our curiosity and just guide as a bit and we could have done a lot ...
#guidance #siblings
@sudojajos
๐ฅ25๐ฏ3
sudo jajos pinned ยซLemme introduce u to my Sister Nahili :) She is grade 5 ... and u know I want her to be great in her future spiritually and also in her worldly life ... Two years ago I thought her how to code just plain html, css(and she was having fun writing some pageโฆยป
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
This is such a disgrace๐๐๐
Ofc u should be aware of the context ๐ณ๐ณ(Elon)
@sudojajos
๐ญ5
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
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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
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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