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Machine Learning AI Limitations | TAU 💎
Question: In the papers I’ve read about Tau, it’s said, approximately, that machines can’t understand human speech. I have been working with some large language models that do a very good job of understanding what I write. Models such as GPT-3 and GPT-J to name just a couple, are great at this. Granted that it takes some practice, what is called prompt engineering, to get the words down, so that these models can produce what is required. Why then, the need for yet another language: TML? Couldn’t we just produce a well-tested set of prompts for people to use?
Answer: For one thing, there are things that we know that no GPT or any other machine algorithm can do which is, for example, finding contradictions. It's mathematically impossible to detect contradictions using machine learning methods. A set of prompts for people to use, how are you going to have a discussion imagine Twitter which would only let you choose from very certain sentences to what to say, how can it be taken seriously, how can you have normal communication or discussion using predefined sets of sentences. Yes so we want to do something that actually works, that's naturally usable. We don't want something that is just academically or partially working. We want to bring real usefulness.
#Tauchain #Agoras #Tau #TML #LanguageModels #GPT3 #GPTJ #PromptEngineering #NaturalLanguageUnderstanding #MachineLearning #HumanSpeech #ComputationalLimits #ContradictionDetection #Communication #Discussion #Twitter #LanguageFlexibility #RealUsefulness #Academics #LanguageProcessing #ConversationalAI #AIAssistants #SemanticUnderstanding #InformationRetrieval #ContextualUnderstanding #LanguageUnderstanding #MachineLimits #IntelligentSystems #LanguageComprehension #NLP #AIResearch #SemanticReasoning
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