GTP-4 integration will make NPCs in video games a whole lot more interesting
LLMS
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Expert Choice: Novel Mixture-of-Experts Routing Algorithm
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Introducing a novel mixture-of-experts routing algorithm, called Expert Choice, that can achieve optimal load balancing between experts while allowing heterogeneous token-to-expert mapping. Learn how it’s done at https://
goo.gle/3OdpO9t -
LangChain 0.0.14 Release with GitHub Actions and Vector DB Improvements
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🦜🔗LangChain version 0.0.14
— LangChain (@LangChain) 16 novembre 2022
🧹Improve GitHub Actions (@PredragGruevski)
🎉Improve env var handling (@deliprao)
🥗Improve coloring of logginghttps://t.co/LuIrkDkbzM
Also, here's an example of using the new vector DB question/answering chainhttps://t.co/hPFqkC1l2cLangChain version 0.0.14 Improve GitHub Actions (
@PredragGruevski
)
Improve env var handling (
@deliprao
)
Improve coloring of logging https://
github.com/hwchase17/lang
chain
… Also, here's an example of using the new vector DB question/answering chain -
Hugging Face Releases 1.3T Parameter Mixture-of-Experts Model
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We’ve heard mixture-of-experts (MoE) were in the air (GPT4??) so we’ve just added the first one in the transformers library for you to play with 🙂 With for nothing less than a 1.3 trillion parameters checkpoint model on the hub! The largest model on the hub at the moment
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Self-examination in AI science models for error detection
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what would be cool with science models like Galactica would be to add self examination of the inputs like the coming Codex model, where the model can inspect it’s theorem proofs or essays and spot errors
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Galactica: Open-Source Large Language Model for Science
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Paper: https://
galactica.org/static/paper.p
df
…
Github: https://
github.com/paperswithcode
/galai
…
Demo: https://
galactica.org -
Galactica: 120B Scientific Language Model for Research
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"Galactica" is a large scientific language model with 120B parameters, that can be used for a lot of tasks including
⦿ Predicting citations
⦿ Generating literature review
⦿ Generating molecules ⦿ Generating Jupiter notebooks etc., -
Galactica LLM Performance with XGBoost Model Implementation
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Amazed by the performance of Galactica by @paperswithcode
— SRK (@sudalairajkumar) 16 novembre 2022
Tried with prompt "jupyter notebook on how to use xgboost model" @tunguz might like it 🙂 #LLM #NLP #AI pic.twitter.com/7ohrREfiltAmazed by the performance of Galactica by @paperswithcode Tried with prompt "jupyter notebook on how to use xgboost model" @tunguz might like it 🙂 #LLM #NLP #AI
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Large Language Models Are Not Zero-Shot Communicators
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Large language models are not zero-shot communicators Ruis et al.: https://
arxiv.org/abs/2210.14986 #Artificialintelligence #DeepLearning #MachineLearning -
Data Quality and Curriculum Learning for LLM Training
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"Obviously anything that looks useless (like SHA hashes or other noise) is not worth training on and is just wasting training capacity and time"
"You may want to start with simpler topics and work up to more complex later, just like in human school"