jrowen

I think it will look more like Claude just helping every expert along the way do their job better. Analyzing and synthesizing data to make better experimental suggestions and design new equipment (or totally new experiments based on unconceived-of apparatuses?). Managing the flow of information and building bespoke knowledge bases and tools. The more it is integrated into all the systems and researchers involved the faster it can put things together.

Although, on second thought, maybe there even is a near future where it takes our models and understanding and just galaxybrains a better model. Has anyone tried feeding it some collection of datasets and saying "can you make a more detailed model of a cell?"

Society? Why are you less crazy about Musk properties than any of the rest of the S&P? Does that suggest that a system that allows such concentrations of wealth and control in so few individuals might be flawed?

IMO, let the unicorns leave. Europe figured it out. Get the vast majority of the benefits of their contributions without being sucked dry and subjected to their whims in whatever other domains they fancy.

My question was a sincere ask to define, in this scenario, what is prohibiting that other magic?

In fact, a lot of stuff is already slop, largely because of the design and engineering expertise required. I don't think one-shotting "design me a house in the style of Frank Lloyd Wright with these specifications" is that far off.

If it's not C3PO it's a Boston Dynamics dog with a couple appendages, better software, and automated manufacturing.

Imagine I give you a perfect roadmap to build that robot...

Responding to your edit, none of those things strike me as any more challenging than the control software.

You don't even need Autodesk. You can have Claude whip up a web app and build a higher level understanding of the building and then translate it to whatever output or format you desire.

The mythical man-month is an interesting point. I think there are limitations or hurdles to human collaboration, in that sense, that may not exist for them. Wildly different experience levels, knowledge levels, emotional states, and goals. Games of telephone and other misunderstandings. One big reason you can't easily increase velocity by adding team members is that the existing team has to stop to train them.

An agent is already a perfect stand-in for another agent with a bit of context. That's why I'm comparing them to neurons. They're highly fungible. Think orchestration, compartmentalization, and hierarchy more than GPU-style parallelization.

Regarding your experiments with networks of agents, a lot of "primordial soup" bounced around for a long time before more complex structures formed. I'm reminded of Shawshank Redemption - "all it takes is pressure and time."

The implication i'm pushing back on is that parallelization lets them assemble something greater than the sum of its parts.

What about all of the examples I described where that happens in nature? Even though humans are hard to orchestrate, we do still have things like CERN and space rockets. Personally I would take my stance as the null hypothesis that needs to be proven wrong.

HF was a failure - an insight into the quirks of the model after they compacted their context 25 times.

That's a human framing, nature doesn't know the difference. Look at all the explorations and quirks and dead ends of evolution. It's a mess, but it moves forward. This mess is moving at unfathomable speeds in comparison.

> the trick of scaling really isn't all that mind-bending beyond increasing an integer somewhere to gamble with more money.

What's the big difference between a cell and an animal? A molecule and a protein? A nucleotide and DNA? A human and a society (or a corporation)? Taking a functional unit and putting a lot of them together with some semblance of coordination represents a step change in complexity and capability. I think people are caught up on the model and this monolithic concept of intelligence but even for us it's just layers of swarms of simple things working together.

Why is it tough to understand what's going on in our brains? Because there's 100 billion neurons and 500 trillion synapses. We get neurons pretty well. And yet we don't know how to identify "a memory".

> I'm sure there are 5000 people experiencing something unique and categorically different with dealing with problems, but unique does not mean they're the place for a glimpse into the future or holders of exclusive insights.

It's not really about those people. It's about all of humanity having created something from first principles that is really starting to outstrip our understanding. They just happen to be in a position right now where they do have a unique vantage point. Don't worry, you're right, they're not that special, it's not about that. But they are very clearly getting results. It can't be said that it just adds more dirt.

Even if there's just one or two unquestionable results at this time, how many will there be in 5 years? 10 years? You don't think we're at the ENIAC stage of superintelligence right now? Is it a fluke or is the government gonna slow it down? These kinds of results have been demonstrated to be within reach, there's blood in the water now, even moreso than the AI boom we've already been seeing.