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My Brainstem RNS-AI project has made progress for life long learning like a Brain
▲ 11 r/airesearch+9 crossposts

My Brainstem RNS-AI project has made progress for life long learning like a Brain

Here is my current project status, it has become quite extensive in the meantime.

https://github.com/unikum-sol/brainstem/blob/main/Project\_Status\_2026-09-28.md

I look forward to feedback and discussions.

Here is a small excerpt:

„BrainStem is a self-learning language-understanding system designed to acquire sentence-, word-, and relation-level structure from an unsegmented text corpus purely through statistical observation, without word lists, grammars, or filters. The system’s stated design principle is that every unit of knowledge, a sentence-level hypothesis, a word boundary, a relation between two entities, a category, or a question, begins as a low-confidence, fully correctable hypothesis, and only becomes a durable fact, relation, category, or question after surviving a multi-cycle, neuromodulator-gated consolidation process modeled on biological sleep-dependent memory consolidation.”

https://github.com/unikum-sol/brainstem

u/Unikum_01 — 13 days ago
▲ 6 r/airesearch+2 crossposts

Looking for people interested in AI × Infrastructure × Sustainability research

Looking for people interested in AI × Infrastructure × Sustainability research

I've been exploring an area that I find increasingly interesting: the environmental and infrastructure impact of AI, and what we could potentially do about it.

AI isn't just a software problem anymore. Behind every model are GPUs, data centers, electricity, cooling, water, networking, hardware manufacturing, and increasingly complex infrastructure.

I'm interested in exploring questions such as:

  • How do we accurately measure the energy, water and carbon footprint of AI workloads?
  • Can AI inference be made significantly more resource-efficient?
  • Could workloads be scheduled based on energy availability, carbon intensity or water stress?
  • Do we actually need large models for every task?
  • Can smaller models, routing, caching, quantization, batching, etc. meaningfully reduce resource consumption?
  • Can AI itself help optimize energy grids, water systems, agriculture, conservation and other environmental problems?
  • What are the gaps in current research?
  • What interesting research questions haven't been explored enough yet?

At this stage, I'm not trying to sell a specific idea or claim to have the answers.

I'd like to find people who are interested in:

• Reading and analyzing research papers
• Discussing existing findings and identifying gaps
• Challenging assumptions and ideas
• Brainstorming potential research questions
• Designing small experiments or prototypes
• Potentially collaborating on a research paper/project in the future

You don't necessarily need to be an academic researcher. I'm interested in people from AI/ML, backend/infrastructure, distributed systems, data centers, energy, sustainability, environmental science, or related fields.

I'm approaching this as an open exploration: research → discussion → experiments → ideas → potentially a paper/project.

If this sounds interesting to you, feel free to comment or DM me. I'd be happy to start with a small group and see where the discussions lead.

Would love to hear what problems you think are currently being overlooked in AI's environmental/infrastructure impact.

reddit.com
u/Consistent-Cow6205 — 11 days ago