Please do

Wait what..? please elaborate or provide any references for further reading!

Sure!

The first is an attempt to provide a semantics for activity diagrams as constraints on a state machine and thereby allow folks to specify correctness properties for the state machine using a visual language. Existing work on semantics for activity diagrams already exists but doesn’t come with tooling in the way that temporal logic does (https://arxiv.org/pdf/1409.2366)

The second is an attempt to fix a long standing problem with state machine specification languages. While many support composition operators (parallel and/or nesting) none of them come with strong theorems about when temporal properties proven about constituent elements will remain valid in the composite.

Interesting, how does the automatic system diagram generation work?

With a bit of tuning, you can get models like Claude to output Mermaid-style diagrams. I built this as a feature into the tasks, so that you can hit a toggle which adds a prompt asking the agent to create a Mermaid diagram during or after the task execution. I pull this diagram back into the GUI and display it with the task information. So user flow is like:

-User creates task as usual but toggles the "mermaid diagram" option on

-Agent takes additional step during execution to create diagram

-User sees that diagram on the task details panel for that task

If you specify in your overall task prompt what kind of diagram you want or what you want it to show, it will take your specifications into account. It's just a prompt control + automatically pulling that diagram back into the task tracking.

Looks cool. A missing layer perhaps

Too early to give any sort of trust

hierarchical specs? Sounds hard to understand where they overlap. Or, they are independent?

"But MCP is still useful, because it is uniform"

Yes, I was also thinking.. y MCP den

But even my simple class project reveals this. You actually do want a simple tool wrapper layer (abstraction) over every API. It doesn't even need to be an API. It can be a calculator that doesn't reach out anywhere.

as the article puts it: "MCP makes tools uniform"

lol "agents are better at writing code that calls MCP, then using mcp itself"

In hindsight, it's pretty funny and obvious

Yes, that's precisely the problem, you want continuous learning but you also want continuous pruning.

I'm not sure if you want models perpetually updating weights. You might run into undesirable scenarios.

If done right, one step closer to actual AGI.

That is the end goal after all, but all the potential VCs seem to forget that almost every conceivable outcome of real AGI involves the current economic system falling to pieces.

Which is sorta weird. It is like if VCs in Old Regime france started funding the revolution.

I think VCs end up in one of four categories

1. They're too stupid to understand what they're truly funding.

2. They understand but believe they can control it for their benefit, basically want to "rule the world" like any cartoon villain.

3. They understand but are optimists and believe AGI will be a benevolent construct that will bring us to post scarcity society. There are a lot of rich / entrepreneurs that still believe they are working to make the world a better place.. (one SaaS at a time but alas, they believe it)

4. They don't believe that AGI is close or even possible

If it makes the models smarter, someone will do it.

From any individual, up to entire countries, not participating doesn't do anything except ensure you don't have a card to play when it happens.

There is a very strong element of the principles of nature and life (as in survival, not nightclubs or hobbies) happening here that can't be shamed away.

The resource feedback for AI progress effort is immense (and it doesn't matter how much is earned today vs. forward looking investment). Very few things ever have that level of relentless force behind them. And even beyond the business need, keeping up is rapidly becoming a security issue for everyone.

If Moore's Law had fully kicked over twice more we'd all have 64GB GPUs, enthusiasts would have 2x64GB, and data center build outs wouldn't be needed.

Eventually GPU memory is going to creep up and local models will powerful enough.

I agree. I also think we have only hit the surface of model efficiencies.

Apple's M3 Ultra with RAM up to 512GB shared directly across CPU/GPU/NPUs is a great example of an architecture already optimized for local models. I expect Apple will start offering larger RAM sizes for other form factors too.

And prices for RAM will drop eventually, because of the extreme demand for RAM with higher densities.

It reminds me of the huge infra investments in Sun and Cisco during the first .com boom, and then 5-10 years later those fancy Sun boxes were out performed by Grandma's Windows XP box.

Yes the planet got destroyed. But for a beautiful moment in time we created a lot of value for shareholders.

And for your comparison, they did fund the American revolution which on its turn was one of the sparks for the French revolution (or was that exactly the point you were making?)

The funding of the American revolution is a fun topic but most people don't know about it so I don't bother dropping references to it. :D

I wonder which side tried to forget that first (;->

1. Progress is unstoppable. Refusing to fund it won't make it disappear.

2. Most VCs are normal people that just want a bigger slice of pie, not necessarily a bigger share of the pie. See the fixed pie fallacy.

Our brains, which are organic neural networks, are constantly updating themselves. We call this phenomenon "neuroplasticity."

If we want AI models that are always learning, we'll need the equivalent of neuroplasticity for artificial neural networks.

Not saying it will be easy or straightforward. There's still a lot we don't know!

I wasn't explicit about this in my initial comment, but I don't think you can equate more forward passes to neuroplasticity. Because, for one, simply, we (humans) also /prune/. And... Similar to RL which just overwrites the policy, pushing new weights is in a similar camp. You don't have the previous state anymore. But we as humans with our neuroplasticity do know the previous states even after we've "updated our weights".

How would you keep controls - safety restrictions - Ip restrictions etc with that, though? the companies selling models right now probably want to keep those fairly tight.

This is why I’m not sure most users actually want AGI. They want special purpose experts that are good at certain things with strictly controlled parameters.

I agree, the fundamental problem is we wouldn't be able to understand it ("AGI"). Therefore it's useless. Either useless or you let it go unleashed and it's useful. Either way you still don't understand it/can't predict it/it's dangerous/untrustworthy. But a constrained useful thing is great, but it fundamentally has to be constrained otherwise it doesn't make sense

The way I see it, we build technology to be what we are not and do what we can’t do or things we can do but better or faster.

An unpredictable fallible machine is useless to us because we have 7+ billion carbon based ones already.

Tay the chatbot says hi from 2017.

How about we just put them to bed once in a while?

Please elaborate on this one

I think they mean that the model should have sleep period where they update themselves with what they learnt that day.

it is interesting

Please elaborate