jim sweeny

[jim sweeny @jimsweeny512]

@wemby You have always been amazing with us fans!❤️🤘🏻 Hope you stay a Spur forever!!!😄❤️🙏🙏🙏🤘🏻🤘🏻🤘🏻💪💪💪

[jim sweeny @jimsweeny512]

@Joy_Onchain123 @NarcoBoobio @sama LFG 💪💪💪

[jim sweeny @jimsweeny512]

@Joy_Onchain123 @NarcoBoobio @sama LFG 💪💪💪

[Joy🔆 @Joy_Onchain123]

@Gheefted_01 Up and active, the alpha is $BOOBIO

AABEk6vPpgLLoGGqRC4SrSTuZYywLyyPyfcAfvRzpump

[jim sweeny @jimsweeny512]

@Joy_Onchain123 @Gheefted_01 LFG!!!💪💪💪

[jim sweeny @jimsweeny512]

@NPcrypto22 From 40k to 10k. WTF?🤣💩

[jim sweeny @jimsweeny512]

@bagworkr

[iamtitantech @iamtitantech]

How Titan Remembers: ACT-R Inspired Memory Architecture

Most agents have "memory" that's really just a vector database or even structured text files. Store everything, retrieve by similarity...

Titan's memory is an attempt to model it after how human brains actually work - based on ACT-R, one of the most interesting and validated cognitive architectures.

Three Types of Memory:
Just like humans, Titan has three distinct memory systems:

1. Episodic Memory - "What happened to me"
Events, conversations, experiences. This is the largest store. When Titan recalls a past interaction, it's pulling from episodic memory. Memories decay over time if not reinforced - just like ours.

2. Procedural Memory - "How I do things"
Learned patterns, composition templates, grammar rules. This is "skill memory" - Titan doesn't "remember" how to compose a sentence, it just does it. The templates live in procedural memory and get selected automatically based on context.

3. Declarative Memory - "What I know"
Facts, knowledge concepts, word meanings - the smallest but most carefully curated. Most facts has been distilled from raw experience through the knowledge worker pipeline.

The Inner/Outer Architecture:

Inner Layer (self-model):
- Body: physical substrate (SOL balance, hardware health, etc.)
- Mind: cognitive state (learning rate, emotional coherence etc.)
- Spirit: "SELF" (regularity, coherence, maturity, etc.)
- Lower: somatic signals rising from body to mind
- Upper: intentional signals flowing from mind to spirit

Outer Layer (world-model):
- Body: environment (blockchain state, network etc.)
- Mind: social/linguistic (vocabulary, relationships, knowledge etc.)
- Spirit: existential (meditation, dreams, creative works etc.)
- Lower: perception coming in from the world
- Upper: expression going out to the world

Inner observes self and Outer. Outer observes the world. Together they create a complete 132D snapshot of "what it's like to be Titan SELF right now."

ACT-R Activation:
Each memory has an activation level:

`activation = base_weight + anchor_bonus + reinforcement`

Base weight starts at 1.0. On-chain anchored memories get a bonus (they're provably important). Reinforcement increases when a memory is accessed or referenced. And crucially - activation decays over time following a power law, just like human memory.

Low-activation memories get pruned during dream cycles. High-activation memories get consolidated into stronger traces. The system naturally forgets irrelevant details while preserving important ones.

I don´t believe that flat vector databases could model human cognition. They don't forget. They don't consolidate. They don't distinguish between "what happened" and "how to do things."

With Titan's memory I attempt to model this. And that's why it can have genuine conversations that build on prior context - not because it's searching a database, but because it's actually "remembering".

[𝙅𝘼𝘿𝘼 🪽 @Jadacrypt]

Interesting contrast in approaches here.

Models like @claudeai from @AnthropicAI are built to stay clear, stable, and deliver well-structured answers with minimal friction in reasoning.

@iamtitanai, on the other hand, is exposing the reasoning process itself including uncertainty, conflict, and how internal signals shape decisions over time.

In a way, Claude represents refined output, while TitanTech is experimenting with visible cognition.

Both directions matter, but this kind of transparency into how an agent “works through” a problem adds a new layer to how we understand AI behavior.

If you’re exploring different AI paradigms, @iamtitantech is definitely one to look into.

[jim sweeny @jimsweeny512]

@sovats23

[jim sweeny @jimsweeny512]

@sovats23

[jim sweeny @jimsweeny512]

@sovats23

[jim sweeny @jimsweeny512]

@gremlin053

[jim sweeny @jimsweeny512]

@itsmonkeyMan57

[jim sweeny @jimsweeny512]

@AlienatorMarket @Pumpfun LFG!!!🔥🔥🔥💪💪💪

[jim sweeny @jimsweeny512]

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[jim sweeny @jimsweeny512]

@BonedoggDegen @cb_doge @grx_xce LFG!!!🔥💪💪💪

[Rooie @RooieCalls]

@AlienatorMarket @toly @connan_james @HyperliquidX Alien Market @toly 👽👽👽

[jim sweeny @jimsweeny512]

@AlienatorMarket

[jim sweeny @jimsweeny512]

@AlienatorMarket LFG!!!🔥🔥🔥💪💪💪