DenisM

lack of appetite, when broadly visible, removes future speculators from the new investment pool, and starts bleeding old speculators. This will create a downward pressure. As the dynamic plays out the second rung of speculators will bleed out too.

Thats how bubbles burst - as each tranche of speculators bails the next tranche gets spooked through the pricing signals.

Reading tea leaves, the market believes that whomever is first to AGI will reap all the benefits, leaving nothing to the runners-up. In this view, even a tiny edge in model quality is decisive.

> until reaching AGI, whatever that word means

Maybe that’s exactly it - AGI is ability to plan well?

Yes, and also a diversity of models. I had argon model catch issues that opus missed.

I like the overall idea of deliberate forgetting. And I found checkpointing into artifacts (code, design, intent) to start with fresh context to work well for that purpose.

Interestingly, the artifacts include not just code but alao retroactive design and retroactive “execution plan”. I feed them to another agent to validate the approach and resume work with fresh context and update mission statement.

Unexpectedly, design doc and an execution plan are now outcomes of coding process, not inputs to it. I’m not sure how to think about this.

We have proof they have no moral qualms or other guardrails, and they have incentive. We also have a decent idea how much it costs to connect to ambient WiFi or cell/5gnetworks. It’s a matter of time, which may or may not be already in the past.

Delegate to ChatGPT.

Like, lower the volume (“turn to tge side”) and say, hey Richard, can you compute 123^45 for me? Or “can you check flights”?

Operating air gapped networks is probably a new area of expertise for most people. It’s not hard to unplug cables, but people need access, updates need to be installed, results need to be extracted.

Also threat actors being on the inside breaking out is a bit new.

Thank you for sharing. Would love to hear more!

AI is the dark energy of engineering - it pushes us further apart, faster. Some of us get pushed towards slop, others towards formal spec validation, and as time goes it will be harder and harder to see each other.

A while back a knowledgeable man was a philosopher, and they could all easily talk to each other and understand. As time went we split up - we have philosophy doctors in various fields who have very little to talk about.

This happened again when the term “engineer” fractured (even before software engineering). Software engineering itself fractured, too.

And it’s happening again now.

This caught my eye:

> Architect Financial Technologies, founded in 2023, offers futures in compute linked to the value of chips in America. The firm has also recently launched a platform where model-makers bid to provide “inference”—the useful output produced by an AI model in response to a prompt—rather than the underlying compute capacity.

I think the idea of selling inference is solid, but I’m not convinced Wall Street is going to be doing that. Superscalers are better positioned.

Inference will likely be priced by evals, specific for each workload.

Can you provide an example f how you did that? Very promising!

How you asked them why?

It could be more productive than being angry. Or not, but worth a try.

I imagine this new awareness could create a lot of new jobs, given how much software out there should be in the same state.

I’m not sure if the job title tho. Software restoration?

Current open weight models are 6 months behind on cyber offensive capabilities. We can use that as a proxy on other hazardous capabilities. Thats how much time we have until the genie is out of the bottle.

The bill may create an incentive for Chinese labs to nerf their open weight models before release. If that works we get another 6 months until unnerfed models leak to public.

Thats what the bill gives us - a few months months to come up with the next bandaid.