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Aim: Immortality LLM is to build an LLM that is able to make human beings immortal. That means understanding physiology and doing lab work for that end. For this the LLM must be super intelligent.

Plan: All of the time when A.I. has surpassed human ability for each category is what the model is comprised of and the model is updated when a new category exceeds human caperbility otherwise it does not get added and goes to a development of the LLM by humans. This is an attempt to widen narrow A.I. to make it more general. It also is nearing S.I as the ability exceeds humans.

Milestone 1 Capacities:

• Chess Master:
• Go Master:
• Texas Hold'em Poker Master:
• Jeopardy Master (not part of milestone 1 as it requires too much data at this stage)
• Add more games

Category 1: Master of Games

Our System

1. Model is asked about chess, generates a python program to train itself in a simulated environment.
2. Appends, alters its training data with the new info (training generates new training data).
3. Hits the re-train button on itself.
4. It has learned. (automate the process, give it resources)

It keeps doing this to improve its ability to for example play chess.

Ability of model:

1. generate the poinent experiment for self-training when prompted.
2. output usable, effective training data
3. it generates python code that runs the simulation, rather than building the simulation from scratch each time, provide it with functions such as init_chess() from a simulated environment. Interfaces with a workbench that sets up testing facilites with single function calls and ensures output data is effective training data.
4. go through its existing training data and improve it with new training data produced.
5. hit its own re-train button when changes reach a threshold.

The workbench can be everything, not just A.I, for instance the problem might be an error in some code or a request to install a particular Linux distro and version and more.