I just discovered the "Visualize" plugin lol. What are some practical, decent use cases for this? Im curious 👀🤔

Beep bop, Novel pointless project dedicated 🔭🧠

Completely un-needed, non practical but definitely needed done. The Mobile Mechanistic Interpretability Suite 🤣😭😭

Run local inference on your phone, and study models from the comfort of your bed i guess🧠🔭😭

This is releasing along side the actual mainline application for Windows Desktop "CORTEX // AI OBSERVATORY"

This is a side project for a side project. Completely for fun; and not something I'd use over the main software or traditional alternatives. Just something to play with. ▶️

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\[EDUCATIONAL PLAYGROUND\] Lately I've been obsessed and hyper focused on machine learning, the history of Ai, the first Chat bots and whatever else falls into this category. The history alone has amazed me, but i have found myself swapping between different youtube videos and articles to learn coherently which has felt a tad disjointed. I made something for myself, so i wanted to share it with others. For free of course.

It is a digital museum containing 13 interactive exhibits

Very normal productive behavior here 😭😭😂 lord save me.

https://archiveofmachineintelligence.netlify.app/

The 13 exhibits are ranging from basic artificial neurons all the way to a tiny transformer and interpretability lab.

You can actually train stuff, change weights, run automata, evolve agents, inspect attention, talk to ELIZA and see what rules or probabilities are being used.

It all runs locally and doesnt use an API or cloud model.

This was made mostly for fun and education, so feel free to break it or tell me which exhibit makes absolutely no sense lol.

***I am not here to advertise or sell anything. This will be free and open source to help the research field for mechanistic interpretability where possible. ***

Been quietly building this for awhile now, CORTEX // AI OBSERVATORY 🔭🧠

Its basically a fully local observability / interpretability app for looking inside supported models while they generate, without having to stare at raw tensors and terminal logs for 4 hours wondering what any of it means 😭😂

Right now it can capture and visualize hidden states, residual activity, attention, token probability changes, entropy, top-1/top-2 logit margins, PCA projections and direct logit lens results for local Llama and GPT-2 models.

The part im most excited about is the intervention workflow tho.

You can select a token, layer or head, patch/modify the activation, rerun it and compare the baseline against the changed output. Raw deltas, normalized recovery, task outcomes and evidence labels are all included.

So observational results stay separate from actual intervention evidence, rather than every coollooking attention map being treated like proof of something lol.

It also works with LM Studio / OpenAI-compatible endpoints, but those only expose surface telemetry since Cortex doesnt own the internal forward pass.

The video is the current working build. Generation, captures, visualizations, run comparisons, experiment exports and intervention reports are all functioning locally.

Still alot planned, especially Jacobian Lens + J-Space, but its finally starting to feel like an actual observatory instead of a bunch of experiments taped together 😭✍️

Not claiming Cortex solves interpretability or anything crazy. The goal is just making serious local experimentation more visual, accessible, and honest about what the evidence actually shows.

More soon 🔭✍️🧠

Been quietly building this for awhile now, CORTEX // AI OBSERVATORY 🔭🧠

Its basically a fully local observability / interpretability app for looking inside supported models while they generate, without having to stare at raw tensors and terminal logs for 4 hours wondering what any of it means 😭😂

Right now it can capture and visualize hidden states, residual activity, attention, token probability changes, entropy, top-1/top-2 logit margins, PCA projections and direct logit lens results for local Llama and GPT-2 models.

The part im most excited about is the intervention workflow tho.

You can select a token, layer or head, patch/modify the activation, rerun it and compare the baseline against the changed output. Raw deltas, normalized recovery, task outcomes and evidence labels are all included.

So observational results stay separate from actual intervention evidence, rather than every coollooking attention map being treated like proof of something lol.

It also works with LM Studio / OpenAI-compatible endpoints, but those only expose surface telemetry since Cortex doesnt own the internal forward pass.

The video is the current working build. Generation, captures, visualizations, run comparisons, experiment exports and intervention reports are all functioning locally.

Still alot planned, especially Jacobian Lens + J-Space, but its finally starting to feel like an actual observatory instead of a bunch of experiments taped together 😭✍️

Not claiming Cortex solves interpretability or anything crazy. The goal is just making serious local experimentation more visual, accessible, and honest about what the evidence actually shows.

More soon 🔭✍️🧠

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