NeilBrü

Fundamentally, the brain still receives “bite-size-chocolate” dopamine hits from Lemmy by receiving positive affirmations from upvotes, cortisol from downvotes, and lends to dark behavior patterns like any forum. Adrenaline dumps when engaged in “online arguments”.

The nature of both anonymous or personally identifiable online forums’ neurochemical stimulation of our over-sized and over-active (but evolutionarily necessary for our ancestors’ survival) amygdala fosters social media addiction.

People like Lemmy for many reasons. Some of them are good. However, let’s not pretend that it’s “all of the good with none of the bad.” It’s healthy to be skeptical of Lemmy instances too. Screen time is the enemy.

realize you’re addicted to social media like a drug

Lemmy included.

Yes, I agree wholeheartedly with your clarification.

My career path, as I stated in a different comment in regards to neural networks, is focused on generative DNNs for CAD applications and parametric 3D modeling. Before that, I began as a researcher in cancerous tissue classification and object detection in medical diagnostic imaging.

Thus, large language models are well out of my area of expertise in terms of the architecture of their models.

However, fundamentally it boils down to the fact that the specific large language model used was designed to predict text and not necessarily solve problems/play games to “win”/“survive”.

(I admit that I’m just parroting what you stated and maybe rehashing what I stated even before that, but I like repeating and refining in simple terms to practice explaining to laymen and, dare I say, clients. It helps me feel as if I don’t come off too pompously when talking about this subject to others; forgive my tedium.)

Absolutely interested. Thank you for your time to share that.

My career path in neural networks began as a researcher for cancerous tissue object detection in medical diagnostic imaging. Now it is switched to generative models for CAD (architecture, product design, game assets, etc.). I don’t really mess about with fine-tuning LLMs.

However, I do self-host my own LLMs as code assistants. Thus, I’m only tangentially involved with the current LLM craze.

But it does interest me, nonetheless!

I’m impressed, if that’s true! In general, an LLM’s training cost vs. an LSTM, RNN, or some other more appropriate DNN algorithm suitable for the ruleset is laughably high.

An LLM is a poor computational/predictive paradigm for playing chess.

Mullvad DNS has been great also.

So, a network enabled call light?