Actually you're saying similar things:

Rent-seeking of old was a ground rent, monies paid for the land without considering the building that was on it.

Residential rents today often have implied warrants because of modern law, so your landlord is essentially selling you a service at a particular location.

> Yes that is correct. I would like a large body of experience and consenus to rely on as opposed to the regular 'trust the experts' argument, which has been shown for decades that is a deeply flawed and easy to manipulate argument.

Yes, it is far inferior to the 'Trust torginus and his ability to understand the large body of experience that other actual subject-matter-experts have somehow not understood' strategy

> I feel somebody better qualified should write

I hate to be rude in a setting like this, but please at least research the things you're sure about/prognosticating on.

> the same way, they are generally capable but until we get the robots and a more reliable interface between model and real world, one needs human feet (and hands) in the lab.

Honestly, the kinds of labs where 'bioweapons' would be made are the least dependent on human intervention.

You need someone to monitor your automated cell incubating system, make sure your pipetting / PCR robots are doing fine and then review the data.

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What do you are you trying to achieve in your example? This is all gobbldey-gook for someone who actually sees real, live cancer patients.

>>It's very easy to learn more about this if it's seriously a question you have.

>No, it's not. It took years of polishing by software engineers, who understand this exact profession to get models where they are now

This reads as defensive. The thing that is easy to learn is 'why are biology ai LLMs dangerous chatgpt claude'. I have never googled this before, so I'll do this with the reader, live. I'm applying a date cutoff of 12/31/24 by the way.

Here, dear reader, are the first five links. I wish I were lying about this:

- https://sciencebusiness.net/news/ai/scientists-grapple-risk-...

- https://www.governance.ai/analysis/managing-risks-from-ai-en...

- https://gssr.georgetown.edu/the-forum/topics/biosec/the-doub...

- https://www.vox.com/future-perfect/23820331/chatgpt-bioterro...

- https://www.reddit.com/r/ClaudeAI/comments/1de8qkv/awareness...

I don't know about you, but that counts as easy to me.

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> I would apply this framework to biology - this time, expert effort, and millions of GPU hours and a giant corpus that is open source clearly has not been involved in biology.

I've been getting good programming and molecular biology results out of these back to GPT3.5.

I don't know what to tell you—if you really wanted to understand the importance, you'd know already.

> Just reading this, the inevitable scaremongering about biological weapons comes up.

It's very easy to learn more about this if it's seriously a question you have.

I don't quite follow why you think that you are so much more thoughtful than Anthropic/OpenAI/Google such that you agree that LLMs can't autonomously create very bad things but—in this area that is not your domain of expertise—you disagree and insist that LLMs cannot create damaging things autonomously in biology.

I will be charitable and reframe your question for you: is outputting a sequence of tokens, let's call them characters, by LLM dangerous? Clearly not, we have to figure out what interpreter is being used, download runtimes etc.

Is outputting a sequence of tokens, let's call them DNA bases, by LLM dangerous? What if we call them RNA bases? Amino acids? What if we're able to send our token output to a machine that automatically synthesizes the relevant molecules?