We've launched a $50k competition called "LLM Science Exam" that's great for data scientists wanting to test out using LLMs: https://t.co/tsm8eaCMK9
To get started, we recommend checking out some EXCELLENT resources community members have published. More in thread 🧵...
One of the best parts of the @fastdotai community are the wonderful study groups run by the community.
If you'd like to join one, thanks to @benjamin_warner we now have a list of upcoming meetups on our Discord.
Here's an invite to join our server: https://t.co/gf0HTe3nUe
I've written up my study group lectures on implementing Transformers in PyTorch into a blog series:
Creating Transformers from Scratch:
- Part 1: The Attention Mechanism https://t.co/ZCMiCMzQIp
- Part 2: The Rest of the Transformer https://t.co/kWq9gWkvtp
Back in April, I set out to write an explainer on how large language models work. First I had to learn how they worked, and that was harder than I expected. This article is the culmination of 2+ months of in-depth research. I hope people find it useful. https://t.co/mDVbfcv1kI
I was interviewed on ABC (Australia's national broadcaster) about the new agreement between big AI companies and the US government.
Overall, I'm pretty nervous about the cozy relationship that's developing here, and it's impact of safety and innovation.
https://t.co/5DrP2WnyYu
I've spent the last few months interviewing >60 experts in law, economics, AI, alignment, etc, on the impacts of AI, and safety interventions.
Today I'm publishing my first article, showing regulation designed to increase AI safety may backfire badly!
https://t.co/NsZZ5H2BVH
Why should you care about Langchain?
I found this to be the best answer to, “why everyone should spend a weekend experimenting with @langchain”
@OfficialLoganK has written one of the crispiest posts touching all aspects or “rough edges” of working with LLMs and the solution that langchain offers to these problems.
It’s a 5 minute read, perfect and a must to enjoy over chai:
https://t.co/FTgSHI2xvh
Hello everyone! 👋
I'm thrilled to share with you the journey I've embarked on in the world of AI and Machine Learning. Over the past few years, I've had the privilege of diving deep into various topics, exploring new technologies, and sharing my insights through numerous blog posts and reports.
I've compiled a list of all my writings so far, each one a stepping stone in my learning journey. I hope these resources can be of help to you as they have been to me.
https://t.co/EcEHPGo8us
I'm incredibly proud of the work I've done and the knowledge I've gained. But more than that, I'm excited about the opportunity to share it with all of you. I believe in the power of community and the collective wisdom we can build by sharing our experiences and insights.
I'd love to hear your thoughts on these topics. Have you found any of these resources helpful? Do you have any favourite articles or insights you'd like to share? Let's start a conversation!
🚨Exciting news! Next week, we’ll be launching a brand-new Audio Course! 🤗
Sign up today (https://t.co/2cLmirTddm) and join us for a LIVE course launch event featuring amazing guests like @DynamicWebPaige, Seokhwan Kim, and @functiontelechy! ⚡️
https://t.co/jy7Y2FIQgf
"instead of alarming the public with ambiguous projections about the future of AI, we should focus less on what we should worry about, and more on what we should do" https://t.co/ZZAVzAb1WX excellent thoughts by @sethlazar@jeremyphoward@random_walker#ResponsibleAI#EthicalAI
ML which is put to solve problems is about two main skillsets:
1. How to trade off latency, throughput, and cost against each other?
2. How to measure what is good?
The rest is just do https://t.co/j6xhFIkFeK — yes, even after OpenAI's GPT4 that is the best there is
The best advice for ML! 👨🎓
@radekosmulski has written one of my favorite books on the topic of learning effectively. Last week, I had shared my mistakes from my first attempts at @fastdotai.
This collects all the best ideas to try:
✅ Embracing Top Down Learning
✅ Maximising your learning rate
✅ 1 cup of theory, 1 cup of practice
✅ Becoming a great ML developer
Here’s a video telling you all about the book:
https://t.co/LJM8FhL7cY
However, I would suggest picking it up directly: https://t.co/VKhAX2tViL
AI Twitter is flooded with low-quality stuff recently. No, GPT is not “dethroned”. And thin wrapper apps are not “insane”. At all.
I feel obligated to surface some quality posts I bookmarked. Every one of them should've been promoted 10x, but ¯\_(ツ)_/¯
In no particular order:
Next week, @wasimlorgat @fly_upside_down and myself will be doing a tutorial on #nbdev and @quarto_pub at @JupyterCon
Here is the outline of the tutorial https://t.co/fcORFCqi6Y
We will be covering our favorite tricks
If are around come check it out!
“A cookbook of Self-Supervised Learning” @ylecun et al👩🍳👨🍳
SSL is the tasty sauce behind a lot of the success in Language models, Computer Vision and beyond.
It permits working with limited data by allowing you to include unlabelled data in your workflow. Hence becoming “the dark matter of intelligence” since it’s infinitely scalable.
This is a 45 page bible on the current SSL techniques, covering all key concepts.
I’ve finished my first pass and I highly recommend this as a must read to anyone working on cutting edge applications.
Pick it this weekend, you won’t be disappointed!
https://t.co/YD3HKExbaw