LLM vs NLP | Kevin Johnson

Kevin Johnson (Head of AI at dscout) breaks down the difference between LLM, NLP, and other terms related to AI.

[mauricecinque]

Good and concise presentation. The problem mentionned by Kevin about the « i don’t know » answer of LLM is quite limiting as of today. I asked a simple question (related to a specific object whose name was invented in a novel) to two different LLM’s and both answered wrong answers rather than saying « i don’t know ». After reiterating my same question, LLM answered but still with different wrong answers. I ended up providing the wikipedia link (a quite short page) where correct answer could be found. LLM answered « i am not allowed to read pages ». A basic human intelligence would accept the proposal to read a source at least a widely recognized source to learn something… So the word « Intelligence » appears just usurped when applied to LLM and deep learning in general that « freeze » knowledge in a constantly revolving world. Infering on an intrinsically limited thus biased corpus, will inevitably reach limits thus provide at some point wrong or no answer.

[SudipBishwakarma]

Such a great presentation - concise and clear.

[kishorekumar]

Super impressed with the explanation. Now I know what NLP and LLM are and their significance. Damn, This shit is buzzing, no cap

[pamelaanang]

does that mean perplexity is dependent on the prompt given to the model?

[mlhuman]

"NLP predicts the next word"
Very revealing - the speaker doesn't have a lot of NLP experience for sure.

[jellezuidema]

We all need to simplify when giving talks to an audience of non-experts, but redefining "NLP" to mean "the technology from 10 years ago", without recognising that the *field* NLP has co-produced LLMs is a bit too silly.

[mpat]

Large language models and natural language processing

[kartikpodugu]

There is something called as emergent property of LLM. Though it is not trained for reasoning, math, images containing text; many LLMs are able to do those tasks. In fact there are many benchmarks w.r.t reasoning which LLMs are giving good scores though not great yet. Saying that it is just based on probability and no reasoning, is no more valid I think. Of course, chat bots like Bard and ChatGPT do more than just inference using LLM. Shed your thoughts on this please.

[aimlesspainter]

same same but different










but still same

[connormcmk]

Humans: can predict the next token accurately.
Kevin: See, now that's intelligent
LLMs: can predict the next token accurately.
Kevin: Haha, nice "intelligence"

[user_a]

Its doing more than rolling dice - emergent intelligence. But nice try.