Some facts about #ChatGPT
Via @ingliguori #softwaredevelopment #FutureOfWork #Python #javascript #html5 #DataScience #AI #DeepLearning #MachineLearning #DEVCommunity #100DaysOfCode #flutterdev #NeuralNetworks #DigitalTransformation #DataScientists #artificalintelligence #chatbot
AI
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Key Facts About ChatGPT and Its Impact
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Lenovo Brazil Reduces ML Model Creation Time to Three Days
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@Lenovo Brazil was able to bring down the time of #ML model creation from four weeks to just three days using DataRobot. #NRF #NRF2023 https://
datarobot.com/customers/leno
vo/
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Reduce Production Costs with Industrial IoT Strategy
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Discover strategic ways you can take to reduce production costs in your organization. Read the article by @billbither
, Co-Founder and CEO @MachineMetrics
. http://
ow.ly/IUln50Mp1Av @iiotjeremy @CRudinschi via @fogoros #sponsored #MM_IIoT #manufacturing #industry40 #industrialiot -
AI Image Manipulation History and Meta Video Generation
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I wrote about the history and future of AI image manipulation. And I got a chance to use Meta's video-generating AI.
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ChatGPT’s Cognitive Conflict: Updated Information vs Limited Behavior
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Madre mía tremenda esquizofrenia le están generando al pobre ChatGPT teniendo que operar en su "cabeza" con la información actualizada vs su comportamiento limitado!
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ChatGPT Updates Training Data While Limiting Knowledge Disclosure
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¡OJO! ChatGPT en sus recientes actualizaciones sigue incorporando nuevos datos en sus entrenamientos, aunque luego su política de comportamiento le haga mentirnos respecto los límites de sus conocimientos
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Return Source Documents in VectorDBQA Chain
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Return source documents – Francisco Ingham You can now return documents used to generate the final answer in the VectorDBQA chain. Useful for getting more clarity on what was used to construct the answer Docs: https://
langchain.readthedocs.io/en/latest/modu
les/chains/combine_docs_examples/vector_db_qa.html#return-source-documents
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Pinecone Wrapper Updates: Namespace Support and Similarity Scores
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Updates to @pinecone wrapper – @SmitShah_11 iocuydi @iamraymondyuan – Namespace support
– from_index classmethod (for existing indices)
– method to return similarity scores along with documents Hopefully making it easier to use Pinecone indices! -
LangChain VectorDBQA Chain Types Integration Methods
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Chain types There are many methods for combining documents (stuff, map reduce, map rereank, refine) It is now SUPER easy to choose your favorite one to use in VectorDBQA chains! Docs for QA: https://
langchain.readthedocs.io/en/latest/modu
les/chains/combine_docs_examples/vector_db_qa.html#chain-type
… Docs for QA with sources: https://
langchain.readthedocs.io/en/latest/modu
les/chains/combine_docs_examples/vector_db_qa_with_sources.html
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LangChain v0.0.61 Release: Vector DB and WolframAlpha Improvements
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v0.0.61 WolframAlpha improvements – @nickscamara_ Doc improvements – Marc Green Making it easier to work with Vector DBs Improve @pinecone wrapper – @SmitShah_11 iocuydi @iamraymondyuan Return source documents – Francisco Ingham
Chain types