KidComputer

Move fast and break things is why we have progressed from chopping off people's limbs and giving them cocaine to now.

This is just false. Healthcare does not move fast.

As a hiring manager, I personally wouldn't hire any of them.

Shredders have legitimate uses, this is more like a ghost gun. It's pretty much only used for breaking the law.

Probably because the entire population of Montana makes up just one neighborhood of NYC

https://extrapolations.com/selective-tyk2-inhibition-a-story...

What additional benefit do you bring over just running ControlNet myself?

I think you misunderstood my initial comment, the point I was trying to make is that it's the amplification of the abilities of bad actors that should be of concern, not AI going rogue and deciding to exterminate the human race.

If one were to actually try to do such a thing you wouldn't need a LLM. For a very crude pipeline, you would need a good sequence to structure method such as Alphafold 2 (or maybe you can use a homology model), some thermodynamically rigorous protein-protein binding affinity prediction method (this is the hardest part) and an RL process like a policy gradient with an action space over possible single point sequence mutations in the for-example spike protein of SARS to maximize binding affinity (or potentially minimize immunogenicity, but that's far harder).

But I digress, the technology isn't there yet, neither for an LLM to write that sort of code or the in-silico methods of modeling aspects of the viral genome. But we should consider one day it may be and that it could result in the amplification of the abilities of a single bad actor or enable altogether what was not possible before due to a lack of technology.

Doesn't matter if AI can cure it, a suitable number of the right initial infected and a high enough R naught would kills 100s of millions before it could even be treated. Never mind what a disaster the logistics of manufacturing and distributing the cure at scale would be with enough people dead from the onset.

Perhaps the more likely scenario anyway is easy nukes, quite a few nations would be interested. Imagine if the knowledge of their construction became public. https://nickbostrom.com/papers/vulnerable.pdf

I agree with you though, the promise of AI is alluring, we could do great things with it. But the damage that bad actors could do is extremely serious and lacks a solution. Legal constraints will do nothing thanks to game theoretic reasons others have outlined.

This was merely an example to suggest the danger is not in AI becoming self-aware but amplifying human abilities 1000 fold and how they use those abilities. GPT is not necessary for any part of this. In-silico methods just need to catch up in terms of accuracy and efficiency and then you can wrap the whole thing an RL process.

Maybe you can ask GPT for some good starting points.

I'm willing to wager there are zero subject matter experts today who could do such a thing. The biggest reason is that the computational methods that would let you design such a thing in-silico are not there yet. In the last year or two they have improved beyond what most people believed was possible but still they need further improvement.

Hey GPT-5, write the code implementing a bioinformatics workflow to design a novel viral RNA sequence to maximize the extermination of human life. The virus genome should be optimized for R-naught and mortality. Perform a literature search to determine the most effective human cellular targets to run the pipeline on. Use off the shelf publicly available state-of-the-art sequence to structure models and protein free-energy perturbation methods for the prediction of binding affinity. Use cheaper computational methods where relevant to decrease the computational cost of running the pipeline.

And so on.

https://github.com/whitead/paper-qa

Seems quite similar to https://github.com/whitead/paper-qa with a few more document types added

It's when they get their money that matters, it may takes months. Can't pay employees, cloud bills, vendors, etc until then. The most they get out on Monday is $250k, how long it takes the government to make good on the receivership certificate is unknown. Startups will likely have to take an additional line of credit from somewhere fast.

You shove the whole corpus in a vector db using embeddings, query the nearest neighbors to an input and inject those into a prompt to pass to GPT.

https://langchain.readthedocs.io/en/latest/modules/chains/co...

Standard Tesla build quality, nothing to see here.

https://nickbostrom.com/papers/vulnerable.pdf

It’s difficult, but doable and nowhere near as hard as the synthetic chemistry need to produce small molecule therapeutics to fight novel pathogens. The hardest part in my opinion would be getting accurate predictions of protein-protein binding free energies.

create novel drugs rapidly or even prevantatively. On your final point I’m skeptical. Drugs are difficult to design because you need to account for off-target effects among other things. That’s not a concern when designing a harmful agent. Furthermore I presume one could intelligently harden the pathogen so any potential treatment might be as harmful as the pathogen itself. But that’s a strong assumption and I know of no way to formally verify it.

This is the real AI threat. Soon it will be all too easy to engineer novel viral proteins hardened against all known drugs with lethal consequences. You’ll just have to have faith that there’s no deranged grad student out there with genocidal intentions.

Even many big companies like Uber are operating at a loss, contrary to the public perception that these companies are a rip-off that exploit everyone to the max.

To state the obvious, operating at a loss is not contrary to exploiting your workers.

no

Yup just took a look and they changed the text

Yes, they imply they will.

Notion may, however, use your Content or Customer Data to improve and train Notion’s own models.

https://www.notion.so/Notion-AI-Program-Terms-c0066e30039041...

Notion may, however, use your Content or Customer Data to improve and train Notion’s own models.

Nope, I'm out.

Yet VR has none of those limitations and it still hasn't taken off like personal computers. Weird, it's almost like VR is just an interface and anything you can view in it you can just view on a regular screen, which most people prefer.

Also the comparison to early computers a little weird. VR isn't a platform that can scale out to to handle billions of e-commerce transactions or solve computational biology problems. Apples to oranges.

They’re screwed if they don’t make something viable before most people get pushed back into the office.

Is that a serious argument? PCs offered tremendous utility over phones and letters. What utility does VR provide over a regular PC? Oh that’s right, virtually none.

Nice, it can also work on non-linguistic semantic tasks. How long till we have to report into government thought screening centers that check our responses to propaganda?

Only if it was frag warhead, it could have been a continuous-rod warhead.

That doesn't work because of the contradiction of NERFs needing multiple images of the same geometry and stable diffusion not producing images with stable underlying geometry because it's purely image-based.