Andrew Gao Profile picture
Feb 14 ā€¢ 7 tweets ā€¢ 4 min read
bookmark this šŸ§µ:
5 of my favorite vids under 5 mins explaining AI/machine learning at a beginner level!

#1: What Is Artificial Intelligence?

#ai #tutorial #beginners #nocode #chatgpt
#2: DALL-E Explained by @openai


This video is under three minutes and is made by the developers of DALL-E! It explains how DALL-E was trained and how it works to create cool images.
#3: From Duke University, AI explained in under 2 minutes!

A little light on details but good if you're in a rush.

#4: Gradient Descent in 3 minutes.

Gradient descent is basically how AI learns and is one of the most important mathematical concepts you need to understand.

#5: Neural networks explained in five minutes by @IBM

Do you have a favorite AI/ML video? Please share!
kinda proud of how this graphic turned out lel

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More from @itsandrewgao

Feb 14
looks like @OpenAI bought the domain ai.com and hooked it up to chatgpt.

maybe everyone alr knew this and im just finding out lol...

accidentally found this out bc i was curious who owned the domain.

#ai #chatgpt #openai #gpt3 Image
also open.ai
Is this a legacy openai site? cute Image
i think im playing with DALLE1 or something, this is kinda fun. it gives eight pictures and there are social share buttons embedded for each pic Image
Read 5 tweets
Feb 5
šŸ§µ Thread of awesome AI projects by @Stanford students!

definitely gonna miss some projects so comment if i missed something!

(pic generated by stable diffusion)
From @varunshenoy_: GraphGPT
Extract knowledge graphs from unstructured text with GPT.
Read 6 tweets
Feb 4
see what the future looks like with AI!

generate scifi style images with an auto-complete interface to help you write prompts quicker.

try now: portalpix.app

made using Leap from @leap_api @fdotinc

#aiart #ai #ml #generativeai #stablediffusion #buildspace #fdotinc
San Francisco
@leap_api @fdotinc just start typing and it'll suggest tags for you to add (just hit enter)
Read 6 tweets
Jan 25
šŸ§µIf you're using GPT3 for multilingual applications, read this!

i took a 555 word/2928 char English text. It becomes 706 GPT tokens.

Chinese version of the same text: 2170 tokens. (3x šŸ‡¬šŸ‡§)

Hindi: 4480 tokens (6x šŸ‡¬šŸ‡§)

Implications šŸ‘‡ Image
First off, I only tested this on a very small amount of text so I'm not sure if this is a general trend. The actual token efficiency difference number will definitely be different than these numbers.
Also, the Chinese and English text are professionally translated parallel texts.
The Hindi was just translated with Google Translate using the English text.
Read 6 tweets

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