3 ms·

We built an Artificial Brain that forms memories, generate original thoughts

6 points by 10111two 1y ago

10111two 1y ago
At JN Research, we are exploring a third path between mainstream traditional AI and descriptive neuroscience. Instead of scaling or optimizing trained function approximators, we build Adaptrons; artificial neurons that behave like biological neurons (subthreshold + graded + Action Potential) and autonomously adapt internally and with other Adaptrons in a system. On this substrate, our small artificial brain Primite 1.02 (500 Adaptrons) now shows: • Original thoughts (novel outputs not seen as stimuli). • Memory formation and consolidation (short/intermediate/long-term). • Anticipation: outputs that appear before the corresponding stimulus is presented. We ran 8 independent experiments with different genetic parameters and share detailed counts, timing, and example outputs. This is not ML training; it’s a principles-first cognitive substrate where higher functions emerge from the interaction rules. Furthermore, we also show that higher cognitive functions do not need bigger models or scale to emerge, we can see their early signs if the fundamental framework allows for it. If you are curious (or skeptical), we have included the full technical report and a data repo with outputs for verification, plus our prior 1.02 report on original thought and memory. Github Repository: https://github.com/10111two/primite-1.02 https://github.com/10111two/primite-1.02
10111two 1y ago
Few Anticipatory Questions • “Isn’t this just ML/randomness?” - No training or gradient descent is used. Only neuron-like rules (graded, subthreshold, action potentials). Outputs are logged and timestamped; anyone can verify them. • “How do you define ‘original thought’?” - An output is “original” if it was never presented as a stimulus during that system’s lifetime, yet emerges autonomously. • “What about controls?” - We ran multiple experiments with different genetic parameters; each yielded different system behaviors. One run was deliberately configured as a pure input/output machine, confirming that adaptability is essential for higher functions. • “Independent replication?” – We are open to live demos (reviewers choose inputs) and will provide full raw outputs. Under NDA, reviewers can also set genetic parameters and observe the system’s lifetime behavior. • “Why 500 Adaptrons?” – Our approach is milestone-driven: we demonstrate emergence at small scales first (memory, anticipation), then scale gradually (20k, multimodal, 1M).
reify 1y ago
I always find it fascinating how the use of words (spin) can take something, like a pretty little box of electrical impulses, manipulated with a few lines of code, into something amazing called a brain. Given enough time I could make this little box into the next god, with my extremely intellectual choice of words, even though there is no evidence that the little box can even think, feel or experience life as we know it. Thinking, in the human sense, now there is a real thing.
- 10111two 1y ago
  The skepticism from your end is very understandable. But human brain is made of approximately 86 billion of those pretty little boxes (neurons) of electrical impulses, all governed by same fundamental principles. whether, you have 100 pretty boxes, trillion boxes, the rules remain the same. The real magic is to understand those rules and simulate them using lines of code. Thinking, feeling or experiencing are higher cognitive functions resulting from the interactions of those pretty little boxes. And obviously to get to these cognitive functions, you need more boxes. That's totally fair. But even at small scale, if those rules are correct, you will start seeing early signs which will mature into cognitive functions you are referencing. Think of a development of newborn into an adult. So if you get the rules right, it is completely justified calling it an artificial brain. A toy car is essentially also a car, both governed by same laws of motion. The logic and definition of the use of words(spin) is formally defined in the report. I hope this clarifies some of the skepticism.

6 points by 10111two 1y ago

At JN Research, we are exploring a third path between mainstream traditional AI and descriptive neuroscience. Instead of scaling or optimizing trained function approximators, we build Adaptrons; artificial neurons that behave like biological neurons (subthreshold + graded + Action Potential) and autonomously adapt internally and with other Adaptrons in a system. On this substrate, our small artificial brain Primite 1.02 (500 Adaptrons) now shows: • Original thoughts (novel outputs not seen as stimuli). • Memory formation and consolidation (short/intermediate/long-term). • Anticipation: outputs that appear before the corresponding stimulus is presented. We ran 8 independent experiments with different genetic parameters and share detailed counts, timing, and example outputs. This is not ML training; it’s a principles-first cognitive substrate where higher functions emerge from the interaction rules. Furthermore, we also show that higher cognitive functions do not need bigger models or scale to emerge, we can see their early signs if the fundamental framework allows for it. If you are curious (or skeptical), we have included the full technical report and a data repo with outputs for verification, plus our prior 1.02 report on original thought and memory. Github Repository: https://github.com/10111two/primite-1.02 https://github.com/10111two/primite-1.02

10111two 1y ago

Few Anticipatory Questions • “Isn’t this just ML/randomness?” - No training or gradient descent is used. Only neuron-like rules (graded, subthreshold, action potentials). Outputs are logged and timestamped; anyone can verify them. • “How do you define ‘original thought’?” - An output is “original” if it was never presented as a stimulus during that system’s lifetime, yet emerges autonomously. • “What about controls?” - We ran multiple experiments with different genetic parameters; each yielded different system behaviors. One run was deliberately configured as a pure input/output machine, confirming that adaptability is essential for higher functions. • “Independent replication?” – We are open to live demos (reviewers choose inputs) and will provide full raw outputs. Under NDA, reviewers can also set genetic parameters and observe the system’s lifetime behavior. • “Why 500 Adaptrons?” – Our approach is milestone-driven: we demonstrate emergence at small scales first (memory, anticipation), then scale gradually (20k, multimodal, 1M).

reify 1y ago

I always find it fascinating how the use of words (spin) can take something, like a pretty little box of electrical impulses, manipulated with a few lines of code, into something amazing called a brain. Given enough time I could make this little box into the next god, with my extremely intellectual choice of words, even though there is no evidence that the little box can even think, feel or experience life as we know it. Thinking, in the human sense, now there is a real thing.

10111two 1y ago
The skepticism from your end is very understandable. But human brain is made of approximately 86 billion of those pretty little boxes (neurons) of electrical impulses, all governed by same fundamental principles. whether, you have 100 pretty boxes, trillion boxes, the rules remain the same. The real magic is to understand those rules and simulate them using lines of code. Thinking, feeling or experiencing are higher cognitive functions resulting from the interactions of those pretty little boxes. And obviously to get to these cognitive functions, you need more boxes. That's totally fair. But even at small scale, if those rules are correct, you will start seeing early signs which will mature into cognitive functions you are referencing. Think of a development of newborn into an adult. So if you get the rules right, it is completely justified calling it an artificial brain. A toy car is essentially also a car, both governed by same laws of motion. The logic and definition of the use of words(spin) is formally defined in the report. I hope this clarifies some of the skepticism.