🚨 BREAKING: Microsoft just dropped an 18-episode series called "Generative AI for Beginners".
Ideal for beginners, developers, and AI enthusiasts looking to build a solid foundation.
Here’s a breakdown (Save this👇):🧵
The most socially accepted form of self-sabotage:
Overthinking.
It’s why you can’t make decisions, finish anything, or sleep without scrolling.
The 6 hard truths from Naval Ravikant that shattered my obsession with "Mental effort":
Google just dropped a 100% free learning path on Generative AI with 9 Courses 👇
Intro to Gen AI
Intro to LLMs
Intro to Responsible AI
Intro to Image Generation
Encoder-Decoder
Attention Mechanism
Transformers and BERT
Image Captioning
Gen AI Studio
cloudskillsboost.google/paths/118
Trending repository of the day 📈
localGPT
Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
Main language: Python
Last 24h: 1584 ⭐
Total: 3949 ⭐️
github.com/PromtEngineer/…
Something interesting caught my attention over the weekend.
** Scikit-LLM - github.com/iryna-kondr/sc…**
This integrates powerful LLMs like ChatGPT into scikit-learn for enhanced text analysis tasks, and queries OpenAI API and transforms the response into a regular list of labels.
Oops haven't tweeted too much recently; I'm mostly watching with interest the open source LLM ecosystem experiencing early signs of a cambrian explosion. Roughly speaking the story as of now:
1. Pretraining LLM base models remains very expensive. Think: supercomputer + months.…
#ECCV2022 We propose Relighting4D, which enables free-pose and free-viewpoint relighting from only monocular videos under unknown illuminations.
Code and models: github.com/FrozenBurning/…
#ECCV2022 We propose Relighting4D, which enables free-pose and free-viewpoint relighting from only monocular videos under unknown illuminations.
Code and models: github.com/FrozenBurning/…
The digital transformation in the healthcare sector, respecting the due privacy for sensitive data, must not be considered a different path from that of any other industry.
Microblog & social design by @antgrasso via @LindaGrass0#DigitalTransformation#healthcare#HealthTech
ML bugs are so much trickier than bugs in traditional software because rather than getting an error, you get degraded performance (and it's not obvious a priori what ideal performance is).
So ML debugging works by continual sanity checking, e.g. comparing to various baselines.
Saw this today. Lifecycle of a leaf. Kinda synonymous with humans too. And to think I'm already in the dark green section was food for thought.
It's funny how the early bright green leaves look more beautiful, and the dark green ones look wiser. 😂
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