Generative AI. GAN. GPT. #BigData #NLProc #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/Generative-AI
MACHINE LEARNING
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Generative AI Technologies: GANs, GPT, and Machine Learning Tools
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Prediction capability exceeds the intelligence of predicted processes
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Prediction is not bounded by the intelligence of the process that produces the thing to predict. Eg, somewhere on the Internet are tuples in that order.
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Essential AWS Books for Data Science and Cloud Computing
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The Top Amazon #WebServices #Books You Need to Read! #BigData #Analytics #DataScience #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode https://
geni.us/AWS-Need -
Multimodal World Models: The Future of Grounded AI Systems
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How to attain Multimodal World Models is a great open question in AI. The solutions will likely lead to more grounded models that interact better with people and make better physics predictions. Hopefully, they will enable scientific generalisation, but this too I feel is an open
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State Space Models Survey: Analysis and Applications
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10/ A Survey on State Space Models – a survey paper on state space models (SSMs) with experimental comparison and analysis; it reviews current SSMs, improvements compared to alternatives, challenges, and their applications.
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Emerging AI Agent Architectures: Reasoning, Planning, and Tool Calling
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8/ Emerging AI Agent Architectures – a summary of emerging AI agent architectures; it focuses the discussion on capabilities like reasoning, planning, and tool calling which are all needed to build complex AI-powered agentic workflows and systems.
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State-Space Models Express Power Limited to TC0 Complexity
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6/ The Illusion of State in State-Space Models – investigates the expressive power of state space models (SSMs) and reveals that it is limited similar to transformers in that SSMs cannot express computation outside the complexity class 𝖳𝖢^0…
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Chinchilla Scaling: Replication Attempt Challenges Hoffmann et al.
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3/ Chinchilla Scaling: A replication attempt – attempts to replicate the third estimation procedure of the compute-optimal scaling law proposed in Hoffmann et al. (2022) (i.e., Chinchilla scaling); finds that “the reported estimates are inconsistent with their first two
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Top ML Papers Week: Llama 3, Mixtral, RAG Advances
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The Top ML Papers of the Week (April 15 – April 21): – Llama 3
– Mixtral 8x22B
– A Survey on RAG
– How Faithful are RAG Models?
– Emerging AI Agent Architectures
– Chinchilla Scaling: A replication attempt
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Llama 3 token vocabulary expansion optimization benefits
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I don't think I've talked about going beyond tokenization? Still seems like a sensible approach to me – Llama 3 upped their token vocabulary from 32,000 to 128,000 which gave them some optimization benefits