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jack morris (@jxmnop) on X
observations from my first two weeks as a Meta research intern
- research jobs are the same everywhere: no one ever asks me what I’m doing or how I’m spending my time; there’s an implicit expectation to be interested and work hard
- biking to work in the…
- research jobs are the same everywhere: no one ever asks me what I’m doing or how I’m spending my time; there’s an implicit expectation to be interested and work hard
- biking to work in the…
What's it's like to work at Meta(FAIR) as a Research Intern.
observations from my first two weeks as a Meta research intern
- research jobs are the same everywhere: no one ever asks me what I’m doing or how I’m spending my time; there’s an implicit expectation to be interested and work hard
- biking to work in the sunshine has noticeably improved my quality of life
- you can schedule a meeting with anyone and they will actually talk to you; this is an amazing and I suspect under-utilized perk of the job
- had my first good research idea in a while and it wasn’t exactly in line with the goal of my internship; i was excited about it and folks were really supportive in letting me change course
- even though meta is a big company and has lots of process like any other, they put a lot of effort into removing barriers (unnecessary meetings, forms to fill out, etc.) and just letting you do research
- no meeting wednesdays is a good rule
- no H100s at FAIR (at least not that I can get) and A100s are few and far between
- SF office is beautiful and has great views of the Bay (see pic)
- it’s funny to come from academic setting where i would bring my own lunch to Facebook where i overheard some coworkers complaining about the dryness of the (free) duck served at lunch
- Meta is a great place to work; i like it here
jack morris tweet
observations from my first two weeks as a Meta research intern
- research jobs are the same everywhere: no one ever asks me what I’m doing or how I’m spending my time; there’s an implicit expectation to be interested and work hard
- biking to work in the sunshine has noticeably improved my quality of life
- you can schedule a meeting with anyone and they will actually talk to you; this is an amazing and I suspect under-utilized perk of the job
- had my first good research idea in a while and it wasn’t exactly in line with the goal of my internship; i was excited about it and folks were really supportive in letting me change course
- even though meta is a big company and has lots of process like any other, they put a lot of effort into removing barriers (unnecessary meetings, forms to fill out, etc.) and just letting you do research
- no meeting wednesdays is a good rule
- no H100s at FAIR (at least not that I can get) and A100s are few and far between
- SF office is beautiful and has great views of the Bay (see pic)
- it’s funny to come from academic setting where i would bring my own lunch to Facebook where i overheard some coworkers complaining about the dryness of the (free) duck served at lunch
- Meta is a great place to work; i like it here
jack morris tweet
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Are you interested in pursuing a Masters or PhD in an AI-related field but unsure where to start? Apply to Black In AI’s Emerging Leaders In AI Grad Prep Program.
Link to apply
Link to apply
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My good friend Nebiyu a senior software engineer 🔥who is currently Asus🔥 have created a channel and I just found out today. Join his channel to learn and also explore Taiwan🇹🇼 with him😁 https://t.me/netale1
Telegram
netale
ኩሩ 🇪🇹 ሰውዬ (人 rén) currently living in 🇹🇼. I share about my boring life 😂. Sometimes I also share about Mandarin.
Some people were asking me for beginner resources in ML and here is one.
It is a comprehensive repository containing 35 notebooks on Python, data manipulation, data analysis, data visualization, data cleaning, classical machine learning, Computer Vision and Natural Language Processing(NLP).
GitHub Link
It is a comprehensive repository containing 35 notebooks on Python, data manipulation, data analysis, data visualization, data cleaning, classical machine learning, Computer Vision and Natural Language Processing(NLP).
GitHub Link
GitHub
GitHub - Nyandwi/machine_learning_complete: A comprehensive machine learning repository containing 30+ notebooks on different concepts…
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques. - Nyandwi/machine_learning_complete
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Leetcode for machine learning🔥.
We now have leetcode for ML, even though the industry isn't ready for it.
I tried to solve Implementing Basic Autograd Operations it's pretty neat, you can also see the solutions for it too. Also, the questions are not a lot now, they are cool.
https://www.deep-ml.com/
We now have leetcode for ML, even though the industry isn't ready for it.
I tried to solve Implementing Basic Autograd Operations it's pretty neat, you can also see the solutions for it too. Also, the questions are not a lot now, they are cool.
https://www.deep-ml.com/
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You know Llama right, so let me introduce you to LLaMAX specifically trained for translation and it includes Amharic and Afan Oromo from Ethiopian languages.
It says they used millions of Amharic sentences and thousands of Afan Oromo sentences, I'll test the models and see how they do later.
Paper
Model on HF
It says they used millions of Amharic sentences and thousands of Afan Oromo sentences, I'll test the models and see how they do later.
Paper
Model on HF
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Some saying 🎶 እንደነትና አልኖርም...እንደነ እገሌ... and literally living it😂😂😂
Context: I hear this song play everywhere and got bored
Context: I hear this song play everywhere and got bored
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Puzzle Time🚀
I've made a very simple puzzle where it takes you on a small journey to train a neural network for image classification. You can be an absolute beginner or a pro in ML, but don't worry I got you. Make sure to read all the comments and fill the puzzles section to run the cells successfully.
Click the link to the Colab Notebook and start your journey to train your first neural network.🔥
The code can run on the free Google Colab and doesn't even need GPUs.
Start the Puzzle Here🧩
I bet it won't take you more than 5 minutes.
Good Luck🍀
I've made a very simple puzzle where it takes you on a small journey to train a neural network for image classification. You can be an absolute beginner or a pro in ML, but don't worry I got you. Make sure to read all the comments and fill the puzzles section to run the cells successfully.
Click the link to the Colab Notebook and start your journey to train your first neural network.🔥
The code can run on the free Google Colab and doesn't even need GPUs.
Start the Puzzle Here🧩
I bet it won't take you more than 5 minutes.
Good Luck🍀
Google
Neural_Networks.ipynb
Colab notebook
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Forwarded from KiNFiSH Farms
Fr I used AI to just do some of my dirty and repetitive stuff ...I'm just least person to utilize AI😂
COLM
This is the first conference that started this year in 2024 that's mainly for LLMs and language models. Today they released the accepted papers and I can tell you most of the authors maybe 80% have some east Asian names. I don't really know what to infer from this tbh.
https://colmweb.org/AcceptedPapers.html
This is the first conference that started this year in 2024 that's mainly for LLMs and language models. Today they released the accepted papers and I can tell you most of the authors maybe 80% have some east Asian names. I don't really know what to infer from this tbh.
https://colmweb.org/AcceptedPapers.html
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