diff --git a/reasoning/data/transcripts/2024-12/2024-12-11_whatsapp_BH-TT_artifact-differences/chat_2024-12-11_34ca002.md b/reasoning/data/transcripts/2024-12/2024-12-11_whatsapp_BH-TT_artifact-differences/chat_2024-12-11_34ca002.md new file mode 100644 index 000000000000..0dac1b23ceaa --- /dev/null +++ b/reasoning/data/transcripts/2024-12/2024-12-11_whatsapp_BH-TT_artifact-differences/chat_2024-12-11_34ca002.md @@ -0,0 +1,325 @@ +# Conversation +URL: https://chatgpt.com/share/6758f810-286c-800b-8e2c-490e634ca002 + +### Message ID: 2ae52d22-dba5-457d-8147-faade76900dd +**Author**: system + +**Content:** + + + +--- + +### Message ID: aaa2a53f-bbdd-4ab4-9b2e-9d6936a27074 +**Author**: user + +**Content:** + +here's a chat with my friend. what concepts might we be trying to hint at ? we need clarity of thought since we are poking around at things we don't fully understand. Give us a few options. Clarify our thinking. Be creative. Be bold. Be profound. + +11/12/24, 11:51 - Ben Hoffman: Hey feel like the mood was a bit off when we talked. Wanted to say one more thing I think is really neat about git being the fabric in which the system natively thinks. There’s an unexplored interface between the system and the software supply chain. The system can “think” files into places that make its execution space consumable as an npm module hosted on GitHub for example +11/12/24, 11:52 - Ben Hoffman: I’m sure that’s something you considered already, but I didn’t quite visualize it properly in my head until after that call +11/12/24, 11:55 - Ben Hoffman: It’s possibly a weird way to couple into current systems, but it feels more direct than wrapping them all in APIs and then consuming those APIs from a chatbot adapter +11/12/24, 12:45 - Tom Thompson 🧴: so you're talking about the benefit of publishing packages as units of work, rather than these live and mutable systems ? +11/12/24, 12:45 - Tom Thompson 🧴: as well as having the bots be provenance aware, where they know how the software got there, and how to iterate on the history to produce the next version ? +11/12/24, 12:46 - Tom Thompson 🧴: like a kind of next level introspection +11/12/24, 12:47 - Tom Thompson 🧴: but I think the real thing you're getting at is if it stays in git, then it doesn't break that whole impure compilation problem +11/12/24, 12:47 - Ben Hoffman: I guess what I mean is, if one of the bots decides to set up a remote on GitHub of its own “mind”, it can “think” code directly into software supply chains by just cherry-picking commits onto that remote that adhere to package format for whatever ecosystem it’s trying to supply into +11/12/24, 12:49 - Tom Thompson 🧴: ok that's cool, but what is the benefit you're seeing there ? +11/12/24, 12:49 - Ben Hoffman: Yeah I mean I think that’s more or less it, you don’t have to have a separate build step to make the outcome compatible with a foreign software system +11/12/24, 12:49 - Tom Thompson 🧴: you effectively killed the build step completely +11/12/24, 12:49 - Tom Thompson 🧴: there is no build, there is only commit +11/12/24, 12:50 - Ben Hoffman: I’m not sure I’m thinking in terms of benefits yet, just an interface I never really considered before +11/12/24, 12:50 - Tom Thompson 🧴: publishing to npm and jsr are just transmissions of something that could have stayed pure, if it wasn't for the need for backwards compatibility +11/12/24, 12:50 - Ben Hoffman: Like it might be a lot easier to make this system plug in fairly directly into the software of the world without adapters and wrappers +11/12/24, 12:52 - Tom Thompson 🧴: if the context of the LLM was git, then the context can be shared more readily, is what you're saying ? +11/12/24, 12:52 - Ben Hoffman: Yeah +11/12/24, 12:52 - Tom Thompson 🧴: as an anti example, if the context was all stored on Ethereum, then sharing anywhere is a copy paste rather than sharing a git commit, which is pretty universal, you mean ? +11/12/24, 12:53 - Ben Hoffman: Yeah I think so +11/12/24, 12:53 - Ben Hoffman: Let me sit with it a bit more and come up with a clearer expression of what I’m trying to communicate here +11/12/24, 12:54 - Ben Hoffman: If the agent presented itself in such a way on GitHub, I guess ultimately what would need to be figured out is what does it think of commits coming in from other humans and agents onto those files +11/12/24, 12:55 - Ben Hoffman: I’m using the word “think” a lot in an ambiguous way here +11/12/24, 12:55 - Ben Hoffman: That’s what I need to fix +11/12/24, 12:56 - Tom Thompson 🧴: so to conclude, there is value in having git be the blockchain, since it completely removes a transformation step, which adds impedance to flows, and hinders integration with the rest of the knowledge based economy +11/12/24, 12:56 - Ben Hoffman: Yeah that’s part of it for sure +11/12/24, 12:56 - Ben Hoffman: Most of it probably +11/12/24, 12:56 - Tom Thompson 🧴: that means that, it is frictionless, or native, to transmit thoughts out from the model, and to receive thoughts in, using the most common format for knowledge transmission, which is git, with no translation whatsoever +11/12/24, 12:57 - Tom Thompson 🧴: so its sort of like a git repo got up and started talking +11/12/24, 12:57 - Tom Thompson 🧴: in a fanciful sort of metaphor +11/12/24, 12:58 - Tom Thompson 🧴: so what I'm hearing then, is there is still value to pursue our own blockchain, purely for the sake of the compatibility a pure git model gives everyone +11/12/24, 12:59 - Ben Hoffman: Yes this +11/12/24, 12:59 - Ben Hoffman: Well look the world is not going to want to model time and synchrony less in the future than it does now +11/12/24, 13:00 - Ben Hoffman: Since that’s probably the biggest source of WTF in big systems +11/12/24, 13:00 - Ben Hoffman: There’s a reason the whole software industry jumped on git within a few years, make and sftp are kinda shit by comparison +11/12/24, 13:05 - Ben Hoffman: Also I maintain that the most interesting links between git/blockchain/ai will not emerge until training is fully on chain and there’s a taxonomy of models cooked right into the source tree +11/12/24, 13:06 - Ben Hoffman: That and AIs just simply won’t obviate the need for “basic plumbing” style software, so better to make them more aware of how the plumbing is maintained than less +11/12/24, 13:07 - Ben Hoffman: I’m still not convinced you need to carry a blockchain around with you to build v1 of what you’re thinking, but I am still completely convinced of the long term utility of having one in mind that fits the outcome you’re aiming at +11/12/24, 13:09 - Ben Hoffman: They just feel qualitatively super complementary to me. AIs obfuscate context, blockchains freeze context and keep it retrievable forever. You can trust an AI a lot more that you can see what it gobbled into its latent space +11/12/24, 13:32 - Tom Thompson 🧴: so training being git native as a series of commits, and then calls being commits too, against a long term stable commit which is the training epoc ? + +So that would mean that a model being trained like this could be consumed early, while it was still being trained, to encourage more resources to be put in it, whether you sponsor it with money, or with compute resources. +11/12/24, 13:33 - Tom Thompson 🧴: so getting training on chain is something we should totally be going for, you're saying ? +11/12/24, 13:33 - Tom Thompson 🧴: and then using ambient attribution to pay back to people who did training work +11/12/24, 13:35 - Tom Thompson 🧴: yes, and further they should be the plumbing themselves, with actual software only used in cases where scale, speed, cost are an issue +11/12/24, 13:38 - Tom Thompson 🧴: I think this is the key concept +11/12/24, 13:39 - Tom Thompson 🧴: I think the only reason not to carry one with us is the build cost. After the last few days, I feel like the cost just fell thru the floor with o1-pro +11/12/24, 13:39 - Ben Hoffman: Yes, training data being committed into a payload layer or git lfs for hash provenance followed by commit triggered compute that results in a new model being checked in. Training is deterministic I think, so it’s a natural fit for on-chain, and then you get a free taxonomy of models baked into the source tree structure by just cherry picking training data cross branch for new models +11/12/24, 13:40 - Ben Hoffman: Very easy to create “cousin” models and have good training governance in such a system +11/12/24, 13:40 - Tom Thompson 🧴: training and execution can be deterministic if configured to be so. I was hoping to use this as a proof of work system to fortify the network consensus +11/12/24, 13:40 - Ben Hoffman: Hell yes +11/12/24, 13:41 - Tom Thompson 🧴: rather than having consensus dorkily separate, and worse having its own economics like a token issuance that is all tangled up in there +11/12/24, 13:41 - Ben Hoffman: It will happen eventually when people realize hugging face and GitHub could be the same thing +11/12/24, 13:42 - Ben Hoffman: This is a god tier idea. Proof of actually useful work +11/12/24, 13:42 - Tom Thompson 🧴: or rather, should be the same thing +11/12/24, 13:42 - Ben Hoffman: Yes +11/12/24, 13:42 - Tom Thompson 🧴: yeah well that's what I've been trying to fucking do this whole time 😅 +11/12/24, 13:42 - Tom Thompson 🧴: but baking ambient attribution in there too +11/12/24, 13:42 - Ben Hoffman: Yes I think you’re seeing it +11/12/24, 13:43 - Ben Hoffman: What I was seeing I mean +11/12/24, 13:43 - Tom Thompson 🧴: so its part of the actual next tick of the global system, is attribution +11/12/24, 13:43 - Ben Hoffman: No better way to make them “be the plumbing” than making them be the source repos +11/12/24, 13:44 - Tom Thompson 🧴: so enabling the llms to be the plumbing workforce, by connecting up to git, npm, etc ? +11/12/24, 13:44 - Ben Hoffman: Yeah build cost for sure +11/12/24, 13:44 - Tom Thompson 🧴: so if a Napp is also the repo it lives in, then it is sort of a repo that is alive, and can commit to itself, as well as manage other repos +11/12/24, 13:44 - Ben Hoffman: Yeah +11/12/24, 13:46 - Ben Hoffman: And, crucially, other peoples’ commits can become part of its domain of analysis, which should eventually teach AIs to “understand” human commit streams, which are a type of political information +11/12/24, 13:46 - Tom Thompson 🧴: ok +11/12/24, 13:46 - Tom Thompson 🧴: I was thinking after our call too, and whilst we are seeing point solutions pop up for pieces of the dreamcatcher, there is still no unified solution, which I think is essential. Furthermore, the unified solution should have zero friction back into the established knowledge net, so I'm thinking there is a benefit to keep going with our own pure blockchain piece. + +Yesterday I used o1 pro to produce a software module entirely from prompting. https://jsr.io/@dreamcatcher/concat + +This gives me hope that actually, if we do things right, building artifact might not be nearly as hard as previously thought, since I think I can prompt large chunks of it. It's almost as tho not being able to prompt it is a fatal sign ? like code should be able to be generated from prompting a smart model, or else the design is bad. +11/12/24, 13:47 - Ben Hoffman: I think learning how to understand commits and eventually incorporate them into the training data will give AIs a better shot at understanding consequence, time, politics, group dynamics +11/12/24, 13:48 - Ben Hoffman: And if the AI processes via commit, then understanding commits gives it a type of introspection +11/12/24, 13:50 - Tom Thompson 🧴: they could even begin to understand themselves, as they see their effect on that plane +11/12/24, 13:51 - Ben Hoffman: That’s pretty exciting +11/12/24, 13:51 - Ben Hoffman: Yes! +11/12/24, 13:51 - Ben Hoffman: And yes, agree to “not being able to prompt is a fatal sign” +11/12/24, 13:51 - Ben Hoffman: I really like that +11/12/24, 13:52 - Ben Hoffman: Smart right from the outset, no bits that can’t be queried in natural language +11/12/24, 13:52 - Ben Hoffman: It’s a type of transparency guarantee +11/12/24, 13:52 - Ben Hoffman: Hopefully the ai doesn’t lie about stuff tho lol +11/12/24, 13:53 - Tom Thompson 🧴: lol at least if it does, it will do so repeatably. + +I think this is the stongest case for on chain training - its not open ai unless the training process is repeatable too +11/12/24, 13:54 - Tom Thompson 🧴: ok well I think you've given me the confidence to continue building artifact +11/12/24, 13:54 - Tom Thompson 🧴: its VERY SUBTLE, what you say +11/12/24, 13:54 - Tom Thompson 🧴: but it is a genuine +11/12/24, 13:54 - Tom Thompson 🧴: advantage +11/12/24, 13:55 - Tom Thompson 🧴: so the punchline is, an execution framework that is git native +11/12/24, 13:55 - Tom Thompson 🧴: where the LLMs don't just do the commits, they ARE the commits +11/12/24, 13:55 - Ben Hoffman: Yeah I think so. Just knowing how important git is, and how it’s really the structure that we all politically align on +11/12/24, 13:56 - Ben Hoffman: Yes! +11/12/24, 13:56 - Tom Thompson 🧴: yeah its so common its forgotten about hey +11/12/24, 13:56 - Tom Thompson 🧴: its like air +11/12/24, 13:56 - Ben Hoffman: Yeah +11/12/24, 13:56 - Ben Hoffman: That’s a good way of thinking about it +11/12/24, 13:56 - Tom Thompson 🧴: ok thank you 🙏 +11/12/24, 13:57 - Tom Thompson 🧴: such rough times these days - feels like sound barrier type of problems all the time +11/12/24, 13:57 - Ben Hoffman: Yeah I think it’s the singularity +11/12/24, 13:57 - Ben Hoffman: I guess I never thought of the singularity like a sound barrier +11/12/24, 13:57 - Ben Hoffman: Have the right design or get crushed by the energy +11/12/24, 13:58 - Ben Hoffman: But it seems obvious once you frame it that way +11/12/24, 13:59 - Tom Thompson 🧴: lolololo +11/12/24, 13:59 - Tom Thompson 🧴: that is actually 100% how I feel every day +11/12/24, 13:59 - Tom Thompson 🧴: oscillating rapidly between crushing energy waves and serenity +11/12/24, 13:59 - Ben Hoffman: Also I still get too attached to things so I hope I’m not pushing you in the wrong direction +11/12/24, 13:59 - Tom Thompson 🧴: lol +11/12/24, 13:59 - Tom Thompson 🧴: no I don't think you are +11/12/24, 13:59 - Tom Thompson 🧴: the difference is clear +11/12/24, 13:59 - Ben Hoffman: Ain’t it the truth +11/12/24, 14:00 - Tom Thompson 🧴: and then when you remind me about the utility of genuine proof of computational work +11/12/24, 14:00 - Tom Thompson 🧴: all the other blockchains have some dorky consensus with a token and they're always wedlocked to it +11/12/24, 14:00 - Tom Thompson 🧴: like it is their whole identity, +11/12/24, 14:00 - Tom Thompson 🧴: and they can never be upgraded to change that core thing +11/12/24, 14:00 - Ben Hoffman: And they all create extremely toxic cultures because of it +11/12/24, 14:01 - Tom Thompson 🧴: yeah its a totally unnecessary thing, too - like it is entirely fictitious - physics does not demand it in the least +11/12/24, 14:01 - Ben Hoffman: Lots of people stressed by the big quantum breakthrough Google just posted about because the crypto in btc and eth are both not quantum proof lol +11/12/24, 14:01 - Tom Thompson 🧴: I don't think they have currencies in heaven, for example +11/12/24, 14:01 - Ben Hoffman: I will literally kill myself if I get there and that’s what it is +11/12/24, 14:02 - Tom Thompson 🧴: well with artifact, giving it quantum computation services via an api is easy, might be a fun thing to tack on lol +11/12/24, 14:03 - Ben Hoffman: Yeah it should be way less punishing to change the crypto when you don’t have an army of shitcoin ruggers trying to stop you +11/12/24, 14:03 - Ben Hoffman: Totally + +--- + +### Message ID: e9410778-39b9-464a-a0f5-cc461cb28e85 +**Author**: tool + +**Content:** + +**Exploring AI integrations** + +I’m examining how Git, npm modules, software supply chain, AI, and blockchains intersect, focusing on knowledge, reproducible model training, and traceability in AI development. + +--- + +### Message ID: 46cc8de2-2860-4c13-9083-32117c314a3a +**Author**: assistant + +**Content:** + +Below are a few conceptual frameworks and themes that might help clarify the directions you’re exploring. These are just options—bold thought experiments and profound re-interpretations of what you’ve discussed. Each tries to distill the underlying "essence" of what you're circling around: + +1. **Git as a Cognitive Substrate** + *Concept*: Treat Git not just as a version-control system, but as a universal medium for knowledge representation—a canonical substrate into which intelligence can “think” its outputs directly. + *Idea*: Instead of thinking of Git as infrastructure hiding behind the scenes, imagine it as the actual “mindspace” of an AI. Commits become “thoughts,” branches become “possible worlds,” and merges become negotiated alignments of reality. This would mean that interacting with systems wouldn’t require separately building APIs or wrapping logic in adapters; the “thought process” would already be in the universal language of code and data tracked by Git. + +2. **Provenance-Aware Execution and Training** + *Concept*: Embrace full provenance tracking of models—every piece of training data, every parameter update, every intermediate artifact—being anchored in a Git-like or blockchain-like structure. + *Idea*: On-chain (or on-git) training ensures that models, their lineage, and their transformations are fully transparent and repeatable. This is “Proof of Useful Work” done right: no contrived token games, just a history of refinement. Imagine a Hugging Face that merges seamlessly with GitHub: training datasets as commits, parameter updates as commits, final models as tagged releases. The model’s “mind” isn’t some opaque black box, but an ever-growing, fully versioned garden of knowledge and code. + +3. **Frictionless Integration With the Wider Software Supply Chain** + *Concept*: The AI doesn’t produce code that must then be adapted or compiled into external ecosystems; it directly “commits” code into existing supply chains (e.g., npm modules) as a natural extension of its reasoning. + *Idea*: By removing the “build step” or “adapter step” entirely, the AI’s output is not something that must be transformed—its output is directly usable. Code changes flow seamlessly into the world’s largest ecosystems of shared code, enabling the AI not only to contribute but also to continuously learn from incoming commits by humans and other agents. + +4. **Time, Context, and Political Awareness Through Commit Histories** + *Concept*: Commit histories are fundamentally stories about human and machine collaboration, negotiation, conflict, and resolution. They are a record of political dynamics, group decisions, priorities shifting over time. + *Idea*: By letting the AI “live” in this world of commits, it can learn to interpret the subtle signals encoded in version histories—understanding governance, consequence, and social context. Training on commit histories gives AI a vantage point to reason about time, intention, and human organizational structures. In other words, by modeling itself as a participant in Git’s political tapestry, the AI begins to understand what it means to cooperate, to iterate, to govern. + +5. **Merging Knowledge Networks: From Fragmented Tools to a Single Universal Medium** + *Concept*: Git, package managers, blockchains, AI models—these have historically been disparate systems, each with its own protocols and friction points. + *Idea*: Your conversation hints at merging these concepts into a unified environment: a single substrate (like Git) where data, code, models, and their entire genealogy live side by side. Instead of separate infrastructures for AI training, code versioning, supply chain management, and trust enforcement, you get one substrate that can host them all. This reduces conceptual overhead and unleashes a new kind of “global system,” where knowledge flows freely and every increment of intelligence is recorded and trusted. + +--- + +All of these concepts circle around the core theme: using version-controlled code repositories, possibly combined with blockchain-style invariants, to eliminate friction, ensure trust, enable provenance, and integrate AI deeply into the world’s software and knowledge ecosystems—no artificial boundaries, no hidden build steps, no murky provenances. Instead, a continuous, transparent, and universal environment of incremental, queryable, and trustworthy “thought commits.” + +--- + +### Message ID: aaa2979c-fd1f-4f49-bfd7-051c15a258b3 +**Author**: user + +**Content:** + +if that conversation was being turned into a set of comparisons to make against competing blockchains, name what concepts are missing from the below comparison, and say how you might improve this comparator: + +1. Token dependency: + + - Does the chain have a built-in token? + - How tightly coupled is that token to the consensus? + - How easy is it to remove, replace, or adjust that token? + - Is the consensus mechanism itself token-agnostic or inherently token-bound? + - is the token stable or fluctuatable + +1. Integration format: + + - Can the chain’s data and consensus be naturally represented in Git commits or NPM packages? + - Are translations or bridging layers required to interface with standard tools, and if so, do these weaken the consensus? +3. Portability: + + - Can the system run in isolated parts, completely on your own infrastructure? + - Can these isolated instances later merge consensus without loss of trust? + +For the demonstration of a sharded or “splintered” proof-of-work system, consider calling it “Shattered Proof-of-Work” (S-PoW). This name reflects how the workload can be broken into isolated segments and later merged based on verifiable computational work. + +--- + +### Message ID: aaea9e7c-bfa4-46e7-8a58-adb4a1e2e7c6 +**Author**: tool + +**Content:** + +**Gathering blockchain insights** + +I'm compiling info on blockchain developments, pinpointing gaps like "Community involvement" and "Transparency and trust." Also, looking at concepts such as "Provenance and lineage" and "Natural language promptability," considering how they can enrich the comparison. + +--- + +### Message ID: c132e044-dade-4946-95a7-b1c942539af4 +**Author**: assistant + +**Content:** + +**Missing Concepts and How to Improve the Comparison:** + +1. **Provenance and Lineage of Data/Models:** + **What’s missing:** + - How does the chain handle the version history of data, code, or model parameters? + - Can it track the full lineage of a model’s training process or a software artifact’s evolution? + **Improvement:** + Add criteria examining whether each system can embed transparent, verifiable version histories—like Git commit graphs—directly in its consensus. For example: + - *“Can the chain immutably record the origin and version history of data and code as a first-class citizen?”* + - *“Does it allow for ‘on-chain training’ records or a taxonomy of artifacts that mirror Git’s branching, merging, and tagging semantics?”* + +2. **Deterministic Computation and Reproducibility:** + **What’s missing:** + - Are computations (e.g., model training, code transformations) guaranteed to be deterministic and reproducible from on-chain data? + - Can the entire state (including the model’s parameters) be reconstructed from on-chain commits? + **Improvement:** + Add criteria around determinism and replayability: + - *“Is the chain’s consensus logic and stored data sufficient to deterministically reproduce any result, such as model parameters after training?”* + - *“Does the system enable ‘proof-of-useful-work’ where the work is fully re-executable and verifiable from the recorded state?”* + +3. **Interoperability With Existing Ecosystems (Beyond Git & NPM):** + **What’s missing:** + - Beyond just Git commits and npm packages, how well does the system integrate with other major ecosystems (e.g., Docker images, PyPI packages, Hugging Face model hubs)? + **Improvement:** + Add criteria that measure the breadth of ecosystem compatibility: + - *“Can the chain’s artifacts be directly consumed by standard developer tools, CI/CD pipelines, model registries, or container registries without translation?”* + - *“Is the system extensible to support new tooling integrations as standards evolve?”* + +4. **Governance and Social Dynamics:** + **What’s missing:** + - How does the chain model governance over code and data? + - Can it represent the political dimension of commits—who proposed changes, who merged them, and the rationale behind decisions? + **Improvement:** + Add criteria related to governance and social aspects: + - *“Does the chain encode and preserve metadata of contributors, allowing AIs and humans to understand political, social, and organizational contexts of commits?”* + - *“Can we trace not just the code but also the discussions, proposals, and decision-making processes that led to a given state?”* + +5. **Economic Neutrality and Flexible Incentive Structures:** + **What’s missing:** + - If the chain employs incentives, can those be non-financial or proof-of-actual-work rather than bound to a volatile token economy? + **Improvement:** + Add criteria around incentive flexibility and neutrality: + - *“Are consensus and network security achievable without relying on a native token’s economic incentives?”* + - *“Is it possible to introduce alternate reward mechanisms, like reputation, stable credits, or proof-of-completion of useful tasks?”* + +6. **Upgradability and Evolution Over Time:** + **What’s missing:** + - How easy is it to evolve the protocol over time, add new features, or adapt to new technological standards without causing ecosystem turbulence? + **Improvement:** + Include questions about extensibility and protocol migration: + - *“Can the system’s core protocols be upgraded easily and cleanly, preserving full historical integrity?”* + - *“Does it support branching/forking processes similar to Git, allowing for experimental consensus changes that can later be merged back?”* + +7. **Data Availability and Scalability Constraints:** + **What’s missing:** + - How does the system ensure that the entire state is always available and scalable as the code/data base grows large? + **Improvement:** + Add criteria regarding scaling and data availability: + - *“Can the chain scale with increasing amounts of data and computations without degrading verification or trust?”* + - *“Does it support ‘shattering’ (sharding) into separate chains or segments that can be recombined, ensuring data availability and trust remain intact?”* + +--- + +**Improved Comparator Example:** + +- **Token Dependency & Incentive Neutrality:** + - Does consensus rely on an intrinsic token or can it operate without one? + - Can incentives be reconfigured (e.g., non-monetary proofs of useful work)? + +- **Integration Format & Ecosystem Compatibility:** + - Beyond Git and NPM, can the chain represent and serve artifacts to other ecosystems (Hugging Face models, Docker, PyPI)? + - Are commits, model parameters, and artifact states directly usable by standard devops and AI tooling? + +- **Provenance, Governance & Social Dynamics:** + - Does it record full artifact lineage, enabling complete reproducibility? + - Can the platform encode and understand governance (commit authors, merging policies) and social context for changes? + +- **Deterministic & Reproducible Computation:** + - Are computations fully deterministic, so any artifact (including AI models) can be re-derived from on-chain data? + - Are training processes and model outputs repeatably verifiable as a form of proof-of-useful-work? + +- **Upgradability & Evolution:** + - Can the system’s core mechanics be upgraded without loss of trust or data fidelity? + - Does it support branching and merging of different consensus versions, akin to code versioning in Git? + +- **Portability, Data Availability & Scalability:** + - Can it run in isolated modes and then later reconcile states without losing trust? + - Does “Shattered Proof-of-Work” support scaling by splitting workloads and merging them without compromising determinism or provenance? + +By including these additional angles—provenance, governance, determinism, ecosystem compatibility, incentive neutrality, and upgradability—you create a more comprehensive set of criteria for evaluating next-generation chains against conventional blockchains. + +--- \ No newline at end of file