#Brain Computer Interface Breakthroughs

You’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

Should I drop the method #foryou

New brain-computer interface allows man with ALS to ‘speak’ again.

Comment “Brain” and I’ll send you the guide #explore #claude

Obsessed with AI memory, building a brain that never forgets about your business. Every conversation, every decision — connected and searchable. Comment “BRAIN” and I’ll send you the full breakdown.

I 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

Scientists developed a brain–computer interface so small that it could be placed between hair follicles.

Synchron 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

Massive 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

comment “brain” I’ll send you the PDF guide #explore #claude

Comment “BRAIN” and I’ll DM you the full guide 🧠 Your AI is resetting every single session. Every breakthrough. Every decision. Every pattern you spent hours debugging. Gone. Not because Claude isn’t smart enough — because you never gave it a memory system. Here’s what changes when you do: 👾 CLAUDE.md — The first thing Claude reads every session. Not a config file. A teaching document. Your architecture, your conventions, your hard nos. It shows up to every session already knowing who you are. 💾 Auto-memory directory — Claude starts writing down what it learns. Patterns it noticed. Things you corrected. Solutions that worked. Organised into topic files. Persistent across every session from now on. 🧠 Obsidian + MCP — Your vault becomes a live knowledge graph it can search at runtime. Two MCP servers: smart-connections for semantic search, qmd for structured queries. The key? Name notes as claims, not categories. Not `memory-systems.md` — `memory graphs beat giant memory files.md`. The titles alone tell Claude if something’s relevant before it reads a word. ”brain-ingest pipeline” — One command. Paste a YouTube link, a voice memo, a meeting recording. It downloads, transcribes locally, extracts the key claims and frameworks, and drops a structured note straight into your Obsidian inbox. That’s the insight from a talk you watched 6 weeks ago — available to Claude today. Each layer compounds on the last. Skip one and the others degrade. Comment “BRAIN” — full guide with MCP config, vault structure, and setup checklist 👇

🇨🇳🧠⚙️China's brain tech breakthroughs are challenging Elon Musk's Neuralink as the nation rapidly advances in brain-computer interface (BCI) technology to help paralyzed people speak, move, and walk. CNN has gained special access to the Chinese Institute for Brain Research, which developed the semi-invasive Beinao-1 chip that recently enabled a speech-impaired ALS patient to communicate through a screen. Backed heavily by state support and national initiatives, China is fostering a booming ecosystem of research, clinical trials, and commercial BCI applications. Here's our report on the current state of the high-stakes neurotech race between China and the United States. @stephenbekker @whatwoodbryansay