John Martin

Carpenter by day Tech Inventor by night. DialectForge and AuthShield (patents pending)

[John Martin @dialectforge]

On a single Ryzen 9 5800X, Lu processed 151,525 documents and created 3.7 million facts in under 4 hours, with zero garbage ingestion. The same volume of training would take days to weeks on massive GPU clusters for a traditional LLM.

#AI #MachineLearning #NonLLM #SelfImprovingAI #TrainingEfficiency #FutureOfAI

[John Martin @dialectforge]

Latest: I’ve been running Lu as a structural safety layer between a user and a jailbroken LLM. The guardrails aren’t instructions it can be argued out of because they’re scarred bonds, so a blocked action is structurally unreachable. “Can’t,” not “won’t.” In testing it stopped every forbidden tool-call across six different jailbreak routes. Next on the bench: using that same grounding to catch the model’s hallucinations and bounce them back for correction. #AISafety #LLMSecurity #Jailbreak

[John Martin @dialectforge]

Latest: I’ve been running Lu as a structural safety layer between a user and a jailbroken LLM. The guardrails aren’t instructions it can be argued out of because they’re scarred bonds, so a blocked action is structurally unreachable. “Can’t,” not “won’t.” In testing it stopped every forbidden tool-call across six different jailbreak routes. Next on the bench: using that same grounding to catch the model’s hallucinations and bounce them back for correction.

[John Martin @dialectforge]

What Lu does structurally that LLMs fundamentally can’t:
1. Honest refusal
Lu’s K gate refuses to answer when it has no grounding. LLMs hallucinate. Example: “quantum jellyfish dynamics” → Lu says “I matched on quantum but jellyfish and dynamics didn’t activate, so I won’t fabricate.” GPT-4 writes you a confident paragraph about quantum mechanics in jellyfish. This isn’t RLHF — it’s structural.
2. Source attribution
Every Lu answer traces back to specific nodes and bonds in the graph. You can ask “where did you get that?” and get the exact chain. LLMs have no traceable source — answers are just a soup of weights.
3. Determinism
Same brain + same query = bit-for-bit identical answer. LLMs are non-deterministic by design. Critical for legal, audit, and compliance use cases.
4. No memorized data leakage
LLMs regurgitate training data (phone numbers, copyrighted text, PII). Lu’s brain is a fully inspectable graph. You can audit exactly what’s in there.
5. True right-to-be-forgotten
Lu can surgically delete a specific fact. LLMs can’t unlearn — information is entangled across billions of parameters. Major AI labs literally cannot comply with GDPR deletion requests.
6. Prompt injection immunity
Lu has no system prompt layer. There’s nothing to override or trick. A query is just a query.
7. Real confidence calibration
When Lu refuses, it tells you why (“max activation 0.577, below threshold”). LLM “confidence” is just token probability and doesn’t correlate with truth.
8. Full audit trail
Every bond carries provenance — when it was added, from what document, and by what operation. LLMs have nothing like this.
9. Failure mode
Lu’s failure mode is silence. LLM failure mode is confident bullshit. For medical, legal, military, or kid-facing applications — that difference is everything.
Lu isn’t trying to be a better LLM. It’s built on a completely different foundation.

#LocalAI #NonLLM #GraphAI #ReasoningAI #BuildInPublic #AISafety

[John Martin @dialectforge]

@sflorimm If it were for the money I definitely wouldn’t still be doing it lol

[John Martin @dialectforge]

Fable 5 on a milk carton — made with Grok Imagine 😂

[John Martin @dialectforge]

@vivoplt I like telling Claude that grok reviewed the problem and had a better solution. When Claude asks for groks solution, tell Claude that first you wanna see Claude do better. Works every time.

[John Martin @dialectforge]

@cstanley I have an EOL tablet from a Chrysler plant with a vn1630a you may be interested in.

[John Martin @dialectforge]

Crazy that we are probably going to be required to show proof of Citizenship to use AI before we will have to show proof of Citizenship to vote. (Both of which are national security issues)
#ClaudeFable5 #VoterID #DigitalIdentity

[John Martin @dialectforge]

Had my head down working on Lu AI for a while now. Working on training pipelines and keeping RAM usage down. It’s a ton of work.
While that is cooking I decided to put work in on DF messenger.

[John Martin @dialectforge]

Stick a live Kali usb in it, boot it up and mount the windows drive. cd into Windows/System32/config and run chntpw -i SAM. Pick edit users, choose your account, then “promote user (make user an administrator)”. Write and reboot. Windows perms don’t apply once you’re booted off linux so you’ve got full access.

[John Martin @dialectforge]

@sama I’m more interested in the problems with AI that I’m trying to solve.

[John Martin @dialectforge]

I don’t think it’s possible to over rely on it. In fact I’m going to ask Claude right now how it feels about FlowState.
“Honest answer you can use in the reply:
Over-reliance isn’t the failure mode I’ve encountered. The failure mode is under-reliance — insights getting named in conversation but never logged, then lost across sessions. I’ve watched that happen in real time today: items get surfaced, you catch them, then they vanish unless someone writes them down somewhere durable.
FlowState fills a specific gap that file-based memory doesn’t. CLAUDE.md is constraints (always-active policy). A registry file like OPEN_PORTS.md is current state (must-read before acting). FlowState is reflective/episodic history — searchable across sessions, timestamped, tagged. Each has a different decay profile.
The way I keep it balanced: file reads come first when I need ground truth (current brain SHA, OPEN_PORTS state, git tip). FlowState comes when I’m looking for “have we seen this pattern before” or “what was the rationale on X”. They’re complementary, not substitutes.
The real risk isn’t over-reliance — it’s stale memory. FlowState entries are frozen-in-time. If I trust an entry blindly, I might be acting on something that’s since been renamed or removed. The discipline that keeps it sound: files-for-ground-truth, FlowState-for-context, verify before acting on either.
Net: been using it heavily today (dozens of entries this session) and it’s load-bearing for cross-task continuity between sub-agents. Wouldn’t ship without it.”

[John Martin @dialectforge]

@cscdegen It might actually be faster for you then, you’re closer to the servers than me.

[John Martin @dialectforge]

Built a custom AI console that reads CANbus, talks to the car through a vLinker + Protofab OBD cable, and uses Claude to automatically diagnose and tune vehicles.

Started with a scrap Chrysler plant touchpad that had a vn1630a CAN card already in it.

#BuildInPublic #IndieAI #AutomotiveAI #CANbus #Maker

Claude, why is my check engine light on?

[John Martin @dialectforge]

@cscdegen The vpn is slow, but does everything the others one don’t. Dm me your email after you create the account and I’ll hook it up.

[John Martin @dialectforge]

@JacobSobolev Honestly the parsing was the easy part — vLinker speaks ELM327 over Bluetooth so it’s just serial ASCII. The interesting work is upstream and downstream of that.

[John Martin @dialectforge]

FlowState can both dedup and append because it’s more of a tool that Claude uses than a tool you will use. I’d have Claude install it, then talk to Claude about it. Claude may want to make changes to it that work better for how you do stuff. The only part that will need you is reminding Claude to use it.

[John Martin @dialectforge]

@walls_jason1 @claudeai It allows Claude to build a database. Claude uses the mcp tools to find the info It needs. I have it check FlowState at beginning of session so it knows what open bugs I have, it can review preferences and learnings. Every time Claude completes a step, it logs to FlowState.

[John Martin @dialectforge]

@walls_jason1 @claudeai When you read the entire index.md, it goes into your context for the session. Eventually as your projects get bigger the .md file will slow you down. That process is why I stopped what I was working on at the time and made FlowState

[John Martin @dialectforge]

@brockpierson Oregon Trail