2.0M
ALShould I drop the method #foryou
@alex2learn
#Brain Computer Interface Breakthroughs 2026
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RIYou’re looking at a real neural network. Not the machine learning kind. The biological kind.
Everyone’s building bigger models. I’m building a brain.
I built a neuromorphic AI platform with 1 million spiking neurons, 11 brain regions, and 1.2 billion connections. It doesn’t memorize training data. It learns continuously from real experience, the same way a biological brain does.
The reason I started building this is pretty simple. Every time an AI model gets smarter, it costs more energy, more hardware, more money. A single query to a large language model uses more power than running this entire brain for an hour. That math doesn’t work long term, and I don’t think brute force compute is how intelligence actually works in nature.
So I went the other direction. This system runs on a single CPU, uses less than 5 watts, and never stops learning. No retraining. No massive datasets. No data center. It forms its own concepts, builds associations between things it sees and hears, develops reflexes, and adapts to situations it’s never encountered before. All on its own.
The architecture is modeled after real neuroscience. There’s a sensory cortex for vision, audio, and touch. An association cortex that binds those signals together. A predictive layer that anticipates what comes next and pays more attention when it’s wrong. Motor cortex for movement and speech. A brainstem that manages energy and survival. Every connection strengthens or weakens based on experience. Nothing is hardcoded.
One thing I built in from the start is a safety kernel. Every motor command the brain generates passes through a safety supervisor before it can reach the real world. It checks joint limits, force thresholds, and collision boundaries. If something looks dangerous, the system triggers a reflex withdrawal before the action ever executes. The brain can learn freely, but it can’t act without clearance. That’s not a feature I added later. It’s part of the architecture.
The brain is live right now and will disclose demos to serious individuals. I am looking for researchers that would like to join me in neuromorphic hardware/computing for this next shuttle.
Patent pending
@rio_roue
7.8K
DEBrain computer interface | credit/source: https://www.sixthtone.com/news/1018307 #dystopian #bci #neuralink #brainchip
@deegthinks
2.0M
HAScientists developed a brain–computer interface so small that it could be placed between hair follicles.
@hashem.alghaili
10.0K
SODid you know AI was inspired directly by brain neurons?
.
The idea behind modern AI started with a simple realization:
the brain might run on logic, not mystery.
In 1943, two thinkers asked a radical question:
What if human thought could be modeled mathematically?
One was Warren McCulloch,
who believed the brain functioned like a computing system.
The other was Walter Pitts,
a self-taught prodigy who translated that idea into equations.
Together, they studied neurons —
billions of cells in the brain —
and reduced their behavior to a simple principle:
They either fire or they don’t.
On or off.
1 or 0.
From this, they proposed something powerful:
If individual neurons follow basic logical rules,
then networks of neurons could perform complex computation.
Their 1943 paper,
A Logical Calculus of the Ideas Immanent in Nervous Activity,
demonstrated that simple units, when connected,
could simulate reasoning itself.
At the time, the idea went largely unnoticed.
But later, others expanded on it —
transforming the concept into what we now call
artificial neural networks.
And that became the foundation of modern
Artificial Intelligence.
What makes this insight powerful is not just the history.
It’s the principle:
Complex intelligence doesn’t always require complex building blocks.
It can emerge from simple rules,
repeated at scale.
Your brain works this way.
And now, so do the systems we build.
From biological neurons
to digital networks —
the same logic applies:
Small patterns, repeated enough,
become intelligence.
⸻
🎥 Visuals: Higgsfield.ai
🎙 Voice: ElevenLabs
🌿 More reflections on inner transformation and conscious growth at SoulUnity.art
@soulinsights_
32.7K
SAI built an AI second brain and made it open source 🧠
Here's what it does:
→ Drop any paper, article or video transcript into a folder
→ Claude reads it and builds a structured wiki automatically
→ Extracts concepts, people, ideas — all cross-linked
→ Ask questions, get cited answers from your own knowledge base
→ Everything syncs to GitHub and Obsidian automatically
I've already ingested 21 foundational AI papers:
Transformers → BERT → GPT-3 → LoRA → RAG →
FlashAttention → Constitutional AI + more
The best part?
You don't need to pay for Claude.
Works with Groq, Gemini and Ollama — all free.
Comment "Brain" for link.
#AI #SecondBrain #Obsidian #PKM #BuildInPublic
#MachineLearning #OpenSource #LLM #ClaudeAI #DeepLearning
@saisridhar.tarra
1.9M
KAMassive breakthrough…Scientists are using living brain cells to build computers that are ALIVE!
This is a brand new industry of technology called biocomputing.
These are real human neurons that can actually think and learn for themselves.
When scientists combine them with silicon chips they bring the computer to life.
Now if you’re like me, you’re probably wondering one thing…
Why are scientists doing this?
It feels a bit much to be growing human brains just to put them inside of computers.
Well listen to this…it turns out, human brain cells have extremely rare abilities to process things without being trained.
Normal computers need to be taught how to solve certain problems.
It’s why AI models take so much energy and training data to build.
But as soon as you add brain cells to a computer chip, they don’t really need as much training.
They kinda start figuring out what to do on their own, just like a human would.
Now because of this, these biocomputers are super efficient.
A regular supercomputer might use 40M watts of power to solve a complex task.
The human brain can do it in just 20.
That’s 2M times more efficient.
And this means these biocomputers could become the secret weapon to solving humanity’s hardest computational challenges.
But…there is just one massive problem…
Brain cells tend to die when their temperature deviates from 98.6 degrees.
And computers generate a ton of heat.
So we have this wild situation where living computers might be the solve for everything, but it’s almost impossible to keep the brain part alive.
Today, companies like Cortical Labs are selling these biocomputers for $35,000.
But over time, scientists are gonna figure out how to get them stable & more accessible.
It’s wild to say but I think soon we’re gonna have living computers that literally think like humans.
Follow @kallaway for more videos on tech & AI
#ai #artificialintelligence #tech #technology #computing #computer #future #coding #newtech
@kallaway
358.1K
ALcomment “brain” I’ll send you the PDF guide #explore #claude
@alex2learn
984.3K
RAHow to build a second brain with Claude and Obsidian #ai #tech
@raycfu
117.3K
SIInfinite memory with Claude using multiple brains. Comment BRAIN for the free guide in my community #claude #claudecode #ai #tech
@simon.saysai
61.4K
HANew brain-computer interface allows man with ALS to ‘speak’ again.
@hashem.alghaili
2.2M
CNSynchron has developed a Brain-Computer Interface that uses pre-existing technologies such as the stent and catheter to allow insertion into the brain without the need for open brain surgery. Tap the 🔗 in our bio to see more. #tech #synchron #bci
@cnet
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