Here is a nice review about Code Interpreter by @emollick
. Well written and lots of experiments there! https://
oneusefulthing.org/p/what-ai-can-
do-with-a-toolbox-getting
…
AI
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Code Interpreter Review by Ethan Mollick: Experiments and Analysis
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Code Interpreter by OpenAI: A Game-Changing AI Assistant
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Code Interpreter by OpenAI is truly a game changer. It's an analyst/assistant on your fingertip, who have general knowledge about the world(such as mathematics, stats, economics, etc…), who can answer your questions with beautiful visualizations, who can code, etc… Like many
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Three Force Multipliers for Digital Transformation Success
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3 force multipliers for #DigitalTransformation https://
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EU’s 2028 ChatGPT equivalent plan outdated says economist
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Le ministre de l’économie
@BrunoLeMaire
propose que l'Union européenne lance l’équivalent de #ChatGPT en 2028 Le ministre ne se rend pas compte que ChatGPT sera une antiquité en 2028 Cet objectif n’a aucun sens ! -

Generative AI and Human Rights: What You Need to Know
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What you need to know about generative AI and human rights
#AI #AIio #BigData #ML #NLU #Futureofwork @CRudinschi @AntonioSelas @alexjc @RobotLaunch @karpathy @andyjankowski @bobgourley @CadeMetz http://
ow.ly/SCvy30sw8oK -
Roberta-Large and Decoder-Style LLMs Comparison
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I would consider Roberta-Large (see above) an LLM. But you are also welcome to swap that with decoder-style LLMs. I have a BLOOM (GPT-3 equivalent) example here:
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10 Innovative Ways to Monetize Using AI and ChatGPT
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10 innovative ways to monetize using #AI
#ChatGPT http://
hubs.la/Q01WKR370
V/ @DataScienceDojo CC @Khulood_Almani @RagusoSergio @Analytics_699 @GlenGilmore @MargaretSiegien @avrohomg @cleartechtoday @sallyeaves4 @piccard_paula @ingliguori @efipm @HopeFrank @HaroldSinnott -
Positional Embeddings and Learned Query-Key Weights in Transformers
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That's true, but you still have positional embeddings, and Q and K weights that are learned
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Enterprise Cloud Migration Strategy for Legacy Workloads
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Any enterprise-scale cloud adoption plan includes workloads that don't deserve significant investments in the creation of new business logic. Cloud migration – Cloud Adoption Framework https://
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Fine-tuning RoBERTa for Sentiment Classification to 95% Accuracy
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Then, you can boost that performance (on the same movie review sentiment classification dataset) to ~95% finetuning model = AutoModelForSequenceClassification.from_pretrained( "siebert/sentiment-roberta-large-english", num_labels=2)