Data Science by ODS.ai 🦜
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First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @malev
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​​AI Generated Pokemon Sprites with GPT-2

Author trained #GPT2 model to generate #pokemon sprites, encoding them as the lines of characters (including color). Surprisingly, results were decent, so this leaves us wonder if #GPT3 results would be better.

YouTube: https://www.youtube.com/watch?v=Z9K3cwSL6uM
GitHub: https://github.com/MatthewRayfield/pokemon-gpt-2
Article: https://matthewrayfield.com/articles/ai-generated-pokemon-sprites-with-gpt-2/
Example: https://matthewrayfield.com/projects/ai-pokemon/

#NLU #NLP #generation #neuralart
The Illustrated Retrieval Transformer
by @jayalammar

The latest batch of language models can be much smaller yet achieve GPT-3 like performance by being able to query a database or search the web for information. A key indication is that building larger and larger models is not the only way to improve performance.


http://jalammar.github.io/illustrated-retrieval-transformer/

#nlp #gpt3 #retro #deepmind
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🦜 Hi!

We are the first Telegram Data Science channel.


Channel was started as a collection of notable papers, news and releases shared for the members of Open Data Science (ODS) community. Through the years of just keeping the thing going we grew to an independent online Media supporting principles of Free and Open access to the information related to Data Science.


Ultimate Posts

* Where to start learning more about Data Science. https://github.com/open-data-science/ultimate_posts/tree/master/where_to_start
* @opendatascience channel audience research. https://github.com/open-data-science/ods_channel_stats_eda


Open Data Science

ODS.ai is an international community of people anyhow related to Data Science.

Website: https://ods.ai



Hashtags

Through the years we accumulated a big collection of materials, most of them accompanied by hashtags.

#deeplearning #DL β€” post about deep neural networks (> 1 layer)
#cv β€” posts related to Computer Vision. Pictures and videos
#nlp #nlu β€” Natural Language Processing and Natural Language Understanding. Texts and sequences
#audiolearning #speechrecognition β€” related to audio information processing
#ar β€” augmeneted reality related content
#rl β€” Reinforcement Learning (agents, bots and neural networks capable of playing games)
#gan #generation #generatinveart #neuralart β€” about neural artt and image generation
#transformer #vqgan #vae #bert #clip #StyleGAN2 #Unet #resnet #keras #Pytorch #GPT3 #GPT2 β€” related to special architectures or frameworks
#coding #CS β€” content related to software engineering sphere
#OpenAI #microsoft #Github #DeepMind #Yandex #Google #Facebook #huggingface β€” hashtags related to certain companies
#productionml #sota #recommendation #embeddings #selfdriving #dataset #opensource #analytics #statistics #attention #machine #translation #visualization


Chats

- Data Science Chat https://yangx.top/datascience_chat
- ODS Slack through invite form at website

ODS resources

* Main website: https://ods.ai
* ODS Community Telegram Channel (in Russian): @ods_ru
* ML trainings Telegram Channel: @mltrainings
* ODS Community Twitter: https://twitter.com/ods_ai

Feedback and Contacts

You are welcome to reach administration through telegram bot: @opendatasciencebot
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πŸ”₯Out of One, Many: Using Language Models to Simulate Human Samples

TLDR: GPT-3 has unexpected application β€” modelling of socialogical studies. Average responses of a certain groups can be to some algorithmical accuracy predicted by in silico modelling.

What this means: sociologists won’t have to conduct costly live researches and will be able to run experiments in simulations. Marketers and politicians are getting their hands on cheap solution for modelling their slogans and value propositions. This enables people to check more hypothesis faster and to manipulate society with more efficiency.

ArXiV: https://arxiv.org/abs/2209.06899

#gpt3 #psychohistory #nlu #sociology
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There is a claim that #ChatGPT is capable of writing a code based on a text input

Why does it matter: it potentially can lower the barrier for programmers and allow more tools for efficient software development to emerge.

Source: tweet

#GPT3 #NLU #NLP #codegeneration
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