english to regex
generating regex by just describing it and providing an example (apparently powered by gpt-3)
web page: https://losslesshq.com
#regext #gpt3
generating regex by just describing it and providing an example (apparently powered by gpt-3)
web page: https://losslesshq.com
#regext #gpt3
ββPhilosopher AI β website to generate text with #GPT3
Tool to generate text on different topics. Sensible topics such as sex, religion or even nationality are blocked.
Great way to spread the awareness on #ai and to show nontechnical friends that #Skynet is not a problem to be concerned with yet.
Website: https://philosopherai.com/philosopher/humanity-on-mars-73ac00
#nlu #nlp
Tool to generate text on different topics. Sensible topics such as sex, religion or even nationality are blocked.
Great way to spread the awareness on #ai and to show nontechnical friends that #Skynet is not a problem to be concerned with yet.
Website: https://philosopherai.com/philosopher/humanity-on-mars-73ac00
#nlu #nlp
ββπ₯New breakthrough on text2image generation by #OpenAI
DALLΒ·E: Creating Images from Text
This architecture is capable of understanding style descriptions as well as complex relationship between objects in context.
That opens whole new perspective for digital agencies, potentially threatening stock photo sites and new opportunies for regulations and lawers to work on.
Interesting times!
Website: https://openai.com/blog/dall-e/
#GAN #GPT3 #openai #dalle #DL
DALLΒ·E: Creating Images from Text
This architecture is capable of understanding style descriptions as well as complex relationship between objects in context.
That opens whole new perspective for digital agencies, potentially threatening stock photo sites and new opportunies for regulations and lawers to work on.
Interesting times!
Website: https://openai.com/blog/dall-e/
#GAN #GPT3 #openai #dalle #DL
ββSummarizing Books with Human Feedback
#OpenAI fine-tuned #GPT3 to summarize books well enough to be human-readable. Main approach: recursively split text into parts and then meta-summarize summaries.
This is really important because once there will be a great summarization #SOTA we won't need editors to write posts for you. And researchers ultimatively will have some asisstance interpreting models' results.
BlogPost: https://openai.com/blog/summarizing-books/
ArXiV: https://arxiv.org/abs/2109.10862
#summarization #NLU #NLP
#OpenAI fine-tuned #GPT3 to summarize books well enough to be human-readable. Main approach: recursively split text into parts and then meta-summarize summaries.
This is really important because once there will be a great summarization #SOTA we won't need editors to write posts for you. And researchers ultimatively will have some asisstance interpreting models' results.
BlogPost: https://openai.com/blog/summarizing-books/
ArXiV: https://arxiv.org/abs/2109.10862
#summarization #NLU #NLP
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ββAI 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
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
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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π¦ 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
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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
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#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
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Chats
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* 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
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://xn--r1a.website/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
GitHub
ultimate_posts/where_to_start at master Β· open-data-science/ultimate_posts
Ultimate posts for opendatascience telegram channel - open-data-science/ultimate_posts
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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 wonβt 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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Data Science by ODS.ai π¦
Speaking about real #usecases of #gpt3, there is a wonderful application for improving business communication through the adoption of #nlp / #nlu tools
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