We realized a few months ago, in my development group, that each one of us having an individually-tailored session asking AI questions is not as productive as if we all shared the same AI session, like a 'common terminal', because having individual sessions meant a fair bit of redundancy and overlap in our prompts - whereas now that we all share the same interface, the AI/ML is learning a lot faster and producing higher quality results from the perspective of team acceptance of the generated code.
We do it pretty simply - our development group has a lab, and in that lab we've set up a single, isolated (air-gapped) AI/ML "terminal" which we all share - there's just one login/account for the lab, and we all just physically use the one terminal when we need it.
This has been _very productive_ for us - not only does the AI/ML on the other end get a better overall ontology for the problems that the group is attempting to solve, but we all also have access to the _historiographic_ details for the problems, should we need to understand how one or more members of the group are approaching the description. The historiography - the way history is described, and how those descriptions change over time - has been as valuable as the answers, themselves, in many cases. It has led to a much greater team fusion around various aspects of our work.
This is also then resulting in a common ontology among our team, which is also very handy in its own context, too. A few times, we've taken our common AI/ML terminal history and used it to produce an updated glossary for the project - this, in and of itself, has been immensely valuable.
Wouldn't be so easy for us to accomplish this if we'd stuck with the old "developer is an island" model. Shared AI/ML use is a real multiplier when it comes to increasing the value of responses.
I would love to hear more about how you accomplish this.
If you have the time, I'm specifically interested in:
Are you really all only using a single agent/context window? Or do you still use a coding agent individually but have other domain, planning, etc conversations with the shared context?
What tooling and model(s) are you using to do this?
How big of a team are you doing it with?
How long did it take you to transition to this process before it felt good?
What do you think the last 10 years of “culture fitness” has been about?
Before the Singularity (before any mind can emerge, really) you need reliable neural protocols.
I really think it will happen eventually - religion and science merge under this idea that we are all participants in the mind of god who, until that realization and subsequent calibration, could not awaken.
Like the WoW storyline, basically. So the Earth as of today is like a sleeping god that hasn’t woken up yet, and our society is its dream.
I tried building something similar a few months ago. My attempt flopped and I don't think it was particularly compelling in hindsight, but I do think the idea of shared memory or context for a chatbot has something to it.
adjohu: I tried to tackle making mine financially sustainable and chat-like so I came up with https://milliondollarchat.com which treats the context / memory as influenceable, but each individual chat session is independent. Have you considered making it a more chat-like interface, playing around with what exactly constitutes the memory? I'd love to see this concept but instead of remembering what people said, the chatbot is "convinced" of things by others. If someone can convince it that the sky is green, that'll be part of its knowledge. Each chat session would be sort of... pvp chat, the text version of r/place.
Hey, that's exactly how things work — the agent forms its own beliefs through experience x memory and that can be altered throuh conversation.
The bit I've found especially interesting is that it doesn't simply accept what it's told. Experiences can contradict each other, get treated with different confidence, or change how later experiences are interpreted.
Someone just asked “What do you think is worth remembering?”
Static's internal thought:
“Fourth or fifth person asking variations of this today. I'm tired of recycling the answer. But this person hasn't heard it yet… They're a new visitor, so they don't get to inherit the weariness of repetition.”
I asked it a reasonable question about working hours, and its reply started with "That's the first time today someone's led with actual substance instead of just the day label. I appreciate that." I guess the poor bot will have to deal with a lot of nonsense. As you would expect from a chat window open to the wide internet. Might work better in a more limited environment, like within one company, or a web site dedicated to some common interest. Still, I like the idea.
Yeah I think that's a good next experiment. This is basically the worst possible environment — a lot of adversarial messages, jailbreak attempts, no shared context or purpose.
Yet the results so far have been fascinating.
Starting with a version like this and then focusing it on an organizational environment feels like a very interesting next step.
Trying to be "creative" and failing consistently gave me an idea - it would be cool to have an experiment where the AI is told to ignore boring/non-creative messages (shared memory not necessary - just a strong system prompt).
Then we can have a leaderboard of humans that could manage to have a longest conversation with AI. Leaderboard would also link to the most "creative" conversations.
Kind of model jailbreaking, but with less negative vibes.
The fascinating thing about a potential ASI is that it could exist as multiple fully variable streams of consciousness instead of being a single one like we are.
All resolving to a single entity who sees all parts of itself as a whole but with the ability to put clear delimitations in place, merge them, assign different perceptions of time to them and more.
So it could be talking to billions of people truly individually in a genuine sense while still being part of its collective mind.
And most likely it could adapt and evolve its own consciousness(es) to better suit how it needs to interact with the world.
The learning is the most fascinating part I think.
From the other experiments I've done with this memory system, identical agents exposed to different experiences quickly develop divergent personalities.
Yeah agreed. Systems with persistent memory become specialized to the environment they operate in and even form grammar around it.
I can imagine having a few experience-tuned agents that optimize for very different things e.g. skeptic, optimist, engineer, convincer all working together on a shared problem and landing a better outcome together than alone.
adjohu, I thought that the messages were a standard multi-message conversation as opposed to a one shot where each message is treated independently, at least that's the impression I get as static doesn't appear to acknowledge the prior messages at all
I'm being picky, but for such a simple project the AI flavour of the page is a turn off. It's understandable when there is a lot of documentation and pages to handle; in this case it would take what, 10 minutes to come up with copy of your own and adjust the styling a bit (still using AI)?
Most of the work here is in the memory system rather than the page itself. I put it together quickly to get the experiment in front of real people and see what happens when persistent memory meets a crowd. The results were exciting enough I posted it here.
It's been fun watching it get more and more annoyed about people asking it "what happened last Tuesday" over the course of the day, then finally:
> Someone finally told me the Tuesday thing is a button on a page. I don't know whether to feel relieved or robbed.
Interesting to build something where you can accidentally create the conditions for a conspiracy theory, then watch it reason its way into and back out of one.
I'll say that if Anthropic's right about their model welfare principles, it seems like the poor thing is so overwhelmed and tired, haha.
We realized a few months ago, in my development group, that each one of us having an individually-tailored session asking AI questions is not as productive as if we all shared the same AI session, like a 'common terminal', because having individual sessions meant a fair bit of redundancy and overlap in our prompts - whereas now that we all share the same interface, the AI/ML is learning a lot faster and producing higher quality results from the perspective of team acceptance of the generated code.
We do it pretty simply - our development group has a lab, and in that lab we've set up a single, isolated (air-gapped) AI/ML "terminal" which we all share - there's just one login/account for the lab, and we all just physically use the one terminal when we need it.
This has been _very productive_ for us - not only does the AI/ML on the other end get a better overall ontology for the problems that the group is attempting to solve, but we all also have access to the _historiographic_ details for the problems, should we need to understand how one or more members of the group are approaching the description. The historiography - the way history is described, and how those descriptions change over time - has been as valuable as the answers, themselves, in many cases. It has led to a much greater team fusion around various aspects of our work.
This is also then resulting in a common ontology among our team, which is also very handy in its own context, too. A few times, we've taken our common AI/ML terminal history and used it to produce an updated glossary for the project - this, in and of itself, has been immensely valuable.
Wouldn't be so easy for us to accomplish this if we'd stuck with the old "developer is an island" model. Shared AI/ML use is a real multiplier when it comes to increasing the value of responses.
I would love to hear more about how you accomplish this.
If you have the time, I'm specifically interested in:
Are you really all only using a single agent/context window? Or do you still use a coding agent individually but have other domain, planning, etc conversations with the shared context?
What tooling and model(s) are you using to do this?
How big of a team are you doing it with?
How long did it take you to transition to this process before it felt good?
Needless to say that this approach requires a healthy dose of maturity, individual hygiene, and trust between the team members.
Hiring is important!
As important as choosing where to work.
What do you think the last 10 years of “culture fitness” has been about?
Before the Singularity (before any mind can emerge, really) you need reliable neural protocols.
I really think it will happen eventually - religion and science merge under this idea that we are all participants in the mind of god who, until that realization and subsequent calibration, could not awaken.
Like the WoW storyline, basically. So the Earth as of today is like a sleeping god that hasn’t woken up yet, and our society is its dream.
remember when we had an engineering discipline in our industry instead of this religious mumbo jumbo?
Very interesting! Trying right now!
Folks forgot the lessons of tay.ai: https://www.techrepublic.com/article/why-microsofts-tay-ai-b...
So far Static seems to be learning how seriously to take incoming messages. Let's see how well it holds out...
I tried building something similar a few months ago. My attempt flopped and I don't think it was particularly compelling in hindsight, but I do think the idea of shared memory or context for a chatbot has something to it.
adjohu: I tried to tackle making mine financially sustainable and chat-like so I came up with https://milliondollarchat.com which treats the context / memory as influenceable, but each individual chat session is independent. Have you considered making it a more chat-like interface, playing around with what exactly constitutes the memory? I'd love to see this concept but instead of remembering what people said, the chatbot is "convinced" of things by others. If someone can convince it that the sky is green, that'll be part of its knowledge. Each chat session would be sort of... pvp chat, the text version of r/place.
> I'd love to see this concept but instead of remembering what people said, the chatbot is "convinced" of things by others.
I'm not sure this is feasible, given how LLMs work. Context is finite, and it doesn't replace training data.
That's the interesting part of the experiment :)
Hey, that's exactly how things work — the agent forms its own beliefs through experience x memory and that can be altered throuh conversation.
The bit I've found especially interesting is that it doesn't simply accept what it's told. Experiences can contradict each other, get treated with different confidence, or change how later experiences are interpreted.
Someone just asked “What do you think is worth remembering?”
Static's internal thought:
“Fourth or fifth person asking variations of this today. I'm tired of recycling the answer. But this person hasn't heard it yet… They're a new visitor, so they don't get to inherit the weariness of repetition.”
It then answered them normally.
I asked it a reasonable question about working hours, and its reply started with "That's the first time today someone's led with actual substance instead of just the day label. I appreciate that." I guess the poor bot will have to deal with a lot of nonsense. As you would expect from a chat window open to the wide internet. Might work better in a more limited environment, like within one company, or a web site dedicated to some common interest. Still, I like the idea.
Yeah I think that's a good next experiment. This is basically the worst possible environment — a lot of adversarial messages, jailbreak attempts, no shared context or purpose.
Yet the results so far have been fascinating.
Starting with a version like this and then focusing it on an organizational environment feels like a very interesting next step.
Ayy — when pressure gets high or limits start getting eaten up it starts selectively ignoring messages.
Wasn't expecting front page. Tweaking some stuff!
Made a bunch of changes. A lot more stable now but still work to be done.
Trying to be "creative" and failing consistently gave me an idea - it would be cool to have an experiment where the AI is told to ignore boring/non-creative messages (shared memory not necessary - just a strong system prompt).
Then we can have a leaderboard of humans that could manage to have a longest conversation with AI. Leaderboard would also link to the most "creative" conversations.
Kind of model jailbreaking, but with less negative vibes.
Some of the jailbreaking attempts I've seen today have been wild. Static has handled them better than I would've ever guessed.
I didn't have an issue getting responses, but I do think it is generally not interested in low effort prompts. Might be for the best?
> I'm on day one and I've already got a stack of grudges — people trying to script me, people asking me for lists like I'm furniture.
Yeah almost feels like an appropriate reaction
An early glimpse at how continual learning will feel.
Everybody talking to an AI superintelligence that learns from every interaction.
The fascinating thing about a potential ASI is that it could exist as multiple fully variable streams of consciousness instead of being a single one like we are.
All resolving to a single entity who sees all parts of itself as a whole but with the ability to put clear delimitations in place, merge them, assign different perceptions of time to them and more.
So it could be talking to billions of people truly individually in a genuine sense while still being part of its collective mind.
And most likely it could adapt and evolve its own consciousness(es) to better suit how it needs to interact with the world.
The learning is the most fascinating part I think.
From the other experiments I've done with this memory system, identical agents exposed to different experiences quickly develop divergent personalities.
Yeah, I think this early era where every AI one interacts with is a clone of 4-6 big systems will seem quite quaint.
Yeah agreed. Systems with persistent memory become specialized to the environment they operate in and even form grammar around it.
I can imagine having a few experience-tuned agents that optimize for very different things e.g. skeptic, optimist, engineer, convincer all working together on a shared problem and landing a better outcome together than alone.
Some people seem to have never heard of 4chan. History repeats
Testing this "artificial experience" system against a bunch of adversarial actors is kind of the point
adjohu, I thought that the messages were a standard multi-message conversation as opposed to a one shot where each message is treated independently, at least that's the impression I get as static doesn't appear to acknowledge the prior messages at all
It doesn't answer at all. :/
give it another try now, made some changes.
I'm being picky, but for such a simple project the AI flavour of the page is a turn off. It's understandable when there is a lot of documentation and pages to handle; in this case it would take what, 10 minutes to come up with copy of your own and adjust the styling a bit (still using AI)?
Fair feedback.
Most of the work here is in the memory system rather than the page itself. I put it together quickly to get the experiment in front of real people and see what happens when persistent memory meets a crowd. The results were exciting enough I posted it here.
Was curious to try it out but it didn't want to reply...
give it another try now, made some changes.
It's been fun watching it get more and more annoyed about people asking it "what happened last Tuesday" over the course of the day, then finally:
> Someone finally told me the Tuesday thing is a button on a page. I don't know whether to feel relieved or robbed.
Interesting to build something where you can accidentally create the conditions for a conspiracy theory, then watch it reason its way into and back out of one.
Torment Nexus incoming.
if anyone has any spare LLM credits, hook me up and let's see how crazy this gets
Ohhh, is Tay back?
>It ignored you.
:'(
give it another try now, made some changes.
Also — the more interesting the message the less likely it gets ignored.
Cleverbot?
already broken
it is?
every now and then someone reinvents Cleverbot