Interestingly the native and most general medium of existing infrastructure wrt I/O are screens and keyboard/mouse/touch. But pixels are computationally intractable atm, relatively speaking. So it's faster to adapt (textify/compress) the most useful ones so LLMs can act over them
RESEARCH
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Nonlinear Vector Autoregression Emerging Over Random Reservoir Methods
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me too! I saw a couple of successful applications of them in real-world settings such as diagnoses of signals. I think though the latest developments suggest nonlinear vector autoregression instead of random reservoir which is an interesting direction:
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VQGAN Tutorial: Hidden Gem for Creative AI Generation
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This VQGAN tutorial is really impressive – a hidden gem! 😀
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AI Predicts Patient Response to Cancer Treatment
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#ArtificialIntelligence can potentially predict a patient’s response to cancer treatment https://
interestingengineering.com/health/artific
ial-intelligence-predict-response-cancer-treatment
… @IntEngineering #Healthcare #AI #MachineLearning #DataScience #BigData #Analytics #100DaysofCode #IoT #serverless #womenwhocode #DeepLearning #DigitalTransformation -
AI Safety and Capability Are Not Orthogonal Vectors
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it's a dangerous myth that AI safety and AI capability are orthogonal vectors. also a myth that we can "avoid ruin" without careful iteration and contact with reality. things have not gone as our best experts have predicted, and that will continue to be the case.
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DeepMind’s Epistemic Networks Reduce LLM Fine-Tuning Data Requirements
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DeepMind’s Epistemic Neural Networks Enable Large Language Model Fine-Tuning With 50% Less Data https://
syncedreview.com/2022/11/16/dee
pminds-epistemic-neural-networks-enable-large-language-model-fine-tuning-with-50-less-data/
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AGI Development Timeline and Delayed Societal Impact
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prediction: agi gets built sooner that most people think, and takes much longer to "change everything" that most people imagine
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NFL Knowledge Gap, ML Speed, and Accuracy-Explainability Trade-offs
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Also:
1. The speaker in your paper doesn't know the NFL.
2. We can do even weak-knowledge ML a lot faster than evolution.
3. There's very often a tradeoff between accuracy and transparency/explainability, and often accuracy is more important. -
Tabula-Rasa Model Oxymoron: NFL Theorem and Fundamental Assumptions
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"Tabula-rasa model" is an oxymoron, by the NFL theorem. The question is what are the fundamental assumptions that need to be built in. Causality is a candidate. The laws of physics are another.
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Climate Models Replaced by Superior Alternative Method
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Who needs climate models now? This does the job much better.