The whole idea of putting something in your body that AI came up with is unnerving, but this microfluid jet stream method of injection is kind of blowing my mind.
The whole idea of putting something in your body that AI came up with is unnerving, but this microfluid jet stream method of injection is kind of blowing my mind.
I assure you that they did not use LLM transformers to develop the vaccine. Pharmaceuticals have been using neural networks for years now to accelerate the process of drug discovery and it does amazing things, but it’s not because they’re taking text from medical journals and guessing what the most likely next token should be.
For most people AI == LLM.
I saw someone compare the word AI to the word vehicle. A truck, train, bicycle, submarine, and spaceship are all vehicles, but are very different things. AI can be LLMs, analytic AI, or just a bunch of if functions chained together.
Most people are idiots.
Most people knew absolutely nothing about AI before ChatGPT.
The annoy thing is that many of those same people now act like experts about it. Much like OP and some of the commenters understanding of vaccine development. They seem to think that a liquid was dispensed from a giant, gas powered “AI” and was put into a syringe without further investigation.
Most people still don’t know anything about AI, whether it be llm based or otherwise; they just think it’s magical, knows everything, and they should use it for absolutely anything without any discernment.
I’ve done a bit of work on this front a few years ago. We had a number of simulators that can tell you the likelihood that something binds to a specific protein, and you’re basically just searching through all possible compounds to find things that bind to a target while minimizing their interactions with other proteins that would be known to cause problems in the human body. When we find promising candidates, we send them off to a lab to synthesize and test in vitro.
This kind of search problem isn’t exactly easy to automate mainly because naive solutions are very expensive. It’s never been a problem of outputting nonsense. The automations use the same evaluation metrics as human researchers.
the low likelihood of LLM being involved in any active pharmaceutical R&D efforts is enough for me to wager