Lance @PyroVonNice
Joined June 2014-
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Someone qualified [has written ] a paper [outlining]: "Large Language Models and AI: Intelligence Conflation in the paradigm of Abstracted Intelligence" [This is] a paper I [am] definitely [reading soon].
Someone qualified [has written ] a paper [outlining]: "Large Language Models and AI: Intelligence Conflation in the paradigm of Abstracted Intelligence" [This is] a paper I [am] definitely [reading soon].
Someone qualified [has written ] a paper [outlining]: "Large Language Models and AI: Intelligence Conflation in the paradigm of Abstracted Intelligence" [This is] a paper I [am] definitely [reading soon].
Someone qualified [has written ] a paper [outlining]: "Large Language Models and AI: Intelligence Conflation in the paradigm of Abstracted Intelligence" [This is] a paper I [am] definitely [reading soon].
If anyone starts saying LLMs have consciousness to you, just ask them if the LLM communicates with them or if it processes valid inputs to predict contextual outputs If it does communicate, ask them when it does so; what motivates it to do so - they may have discovered something
If anyone starts saying LLMs have consciousness to you, just ask them if the LLM communicates with them or if it processes valid inputs to predict contextual outputs If it does communicate, ask them when it does so; what motivates it to do so - they may have discovered something
Maybe the AI is just fine but we are using it wrong; (perfectly 'serviceable' with the appropriate implementation) Maybe there is plenty enough data already but we are just not getting the quality right; (polluting 'effectual' data for our models with irrelevant data at scale)
Maybe the AI is just fine but we are using it wrong; (perfectly 'serviceable' with the appropriate implementation) Maybe there is plenty enough data already but we are just not getting the quality right; (polluting 'effectual' data for our models with irrelevant data at scale)
The question is not whether LLMs are, or will become, AGI - cannot be the case if you only look at how they work. The question is whether they can and will be used for AGI - and the prospect of this possibility is not a precluded one.
The question is not whether LLMs are, or will become, AGI - cannot be the case if you only look at how they work. The question is whether they can and will be used for AGI - and the prospect of this possibility is not a precluded one.
Hopefully we won't start calling the models "Digitized Ethereal Weather Spirits" like is happening in the Language prediction space. Saying AI is not 'Silicon Alive' still seems to (strangely) offend some. Sober article describing AI as useful tech in quoted post below.
Hopefully we won't start calling the models "Digitized Ethereal Weather Spirits" like is happening in the Language prediction space. Saying AI is not 'Silicon Alive' still seems to (strangely) offend some. Sober article describing AI as useful tech in quoted post below.
LMs may not be best placed to be used for lower level NLP (Natural Language Processing) tasks, because of how they currently work and what they actually do. Like using a butter knife as a screwdriver: you could try it... but it's not the correct or best tool for the job.
LMs may not be best placed to be used for lower level NLP (Natural Language Processing) tasks, because of how they currently work and what they actually do. Like using a butter knife as a screwdriver: you could try it... but it's not the correct or best tool for the job.
The real question is: for what predictions or generative task is your model being optimized? When you realise that AI models preserve nothing more than interrelated/dependent parameterized ontologies from token correlations this suggests that relevant data (quality) beats scale.
The real question is: for what predictions or generative task is your model being optimized? When you realise that AI models preserve nothing more than interrelated/dependent parameterized ontologies from token correlations this suggests that relevant data (quality) beats scale.
Funny how, once understood, the nub of any interesting idea can usually be explained in three parts or even three words, sometimes. Like: Ideas are like aircraft - the bigger they are, the more runway you gonna need for them to land. Prerequisites burden brilliance.
Funny how, once understood, the nub of any interesting idea can usually be explained in three parts or even three words, sometimes. Like: Ideas are like aircraft - the bigger they are, the more runway you gonna need for them to land. Prerequisites burden brilliance.
Helps confirm, AI Ethics is actually about AI Model Performance - as better quality data-sourcing avoids harmful and unhelpful biases. Also confirms, AI Safety actually helps AI Performance - as irrelevant connections may cause deviations in behaviour, hampering reliability
Helps confirm, AI Ethics is actually about AI Model Performance - as better quality data-sourcing avoids harmful and unhelpful biases. Also confirms, AI Safety actually helps AI Performance - as irrelevant connections may cause deviations in behaviour, hampering reliability
There is no such thing as Confabulations, or hallucination; only unwarranted prompting
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