How Will #AI And #5G Power the Next Wave Of Innovation? https://
entrepreneur.com/en-in/technolo
gy/how-will-ai-and-5g-power-the-next-wave-of-innovation/439056
… @EntrepreneurIND #MachineLearning #DataScience #BigData #Analytics #DeepLearning #100DaysofCode #IoT #serverless #DEVCommunity #womenwhocode #ArtificialIntelligence #DigitalTransformation #Robots
MACHINE LEARNING
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AI and 5G: Powering the Next Wave of Innovation
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Contrastive Language-Audio Pretraining with Feature Fusion
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Large-scale Contrastive Language-Audio Pretraining with Feature Fusion and Keyword-to-Caption Augmentation Wu et al.: https://
arxiv.org/abs/2211.06687 #Artificialintelligence #DeepLearning #MachineLearning -
Data Executive Priorities: Relationships, Results, and Reach
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Why this data executive prioritizes ‘relationships, results, and reach’ http://
mitsloan.mit.edu/ideas-made-to-
matter/why-data-executive-prioritizes-relationships-results-and-reach
… #AI #MachineLearning #DeepLearning #DataScience #BigData #Analytics #100DaysofCode #IoT #serverless #DEVCommunity #womenwhocode #ArtificialIntelligence #Robots #DigitalTransformation -
Fine-tuning Whisper in Google Colab Now Available
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I’m sorry about that. We’ll try our level best to arrange for that this time.
Besides you should be able to fine-tune Whisper in Colabs quite comfortably now 🙂 -
ML Research on Function Fitting and Inductive Logic Programming
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There's a lot of ML research on what functions need fitting. In particular, the field of inductive logic programming – learning logical theories – should be relevant. Also, to Konrad's point, I think many people working on causal learning see connections with "mainstream" ML.
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Causal Theories as Inductive Biases: Benefits and Questions
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Of course, but the question is: how have causal theories to date benefited from being viewed as inductive biases?
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Building Better ASR Models Community Event Discord
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Brilliant idea. The event would be focused on building better ASR models but you can join our discord server and we have a thriving community of people experimenting and testing things out. They’ll be more than happy to help out.
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Understanding Problem-Solving: Key to AI Mastery
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when you figure out you can figure out anything, you figure out everything
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Learning Algorithms and Inductive Biases in Action Variables
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Essentially every learning algorithm / inductive bias is applicable to this. E.g., think of learning a Bayes net where some of the variables are your actions. (How well it works is another question, and here causal theories are presumably very useful, but not exhaustive.)
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Evaluation Metrics for Language Modeling Explained
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Evaluation Metrics for Language Modeling https://
thegradient.pub/understanding-
evaluation-metrics-for-language-models/
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