models can be trained to learn sum, mul, etc. one useful why is measuring model’s fidelity horizon for add, mul, xor, sort or op of choice harness runs at that model’s map/reduce op chunk size to get quasi-deterministic output & why hypercontext boosts recall/reasoning

interesting hypercontext lifts LLM raw context to sim constant & evolved space-time to induce GPS/INS for latent space code / content / code / content / … where code tokens interlace prompt in serialized tensor net token towers or ECC for logits, softmax, etc. so that distributions get where/when want

heh building that / easiest way to inject hypercontext into LLMs for boosting ai recall & reasoning

heh building that / easiest way to inject hypercontext for boosting ai recall & reasoning

heh, Sloop is that; hypercontext uses tensor network and error-correcting code maths to interlace tracer & content tokens to boost recall & reasoning basically we build tree-indexed artificial channel right inside whatever context window you're using

great read & great research similar thesis as fidelity horizon we do to baseline injecting hypercontext

can beat naive ICL by injecting small model in context, think interlaced tensor net to drive artificial space-time gauge mixing pretty much what we do with hypercontext up to & including faux backprop by way of index unrolling similar to compilers next paper soon, prolly github

interesting! used similar to build maths of hypertokens / hypercontext for inference time context-only information gain

yes & awesome & agreed exploring similar via hypercontext all signs point to similar results, steer by Fourier to boost performance, etc. reframes ECC / QEC of certain types as harmonic gauge transform

our hypercontext work has adjacent maths / conjecture if want to compare notes think co-prime ECC driver to gauge arbitrary space & optimize path finding even if no shared value on maths, can likely help express your conjecture so model groks inputs / chains logic better

hypercontext precursor for this analog manifold manipulator for LLMs substrate-independent math exploring several ways to do same with hardware

been quasi-similarly quietly attacking RH from error-correcting code ECC / QEC pov esp. tomography-holography congruency codes at classic-quantum boundary, e.g., CRT MRNS tanner towers of equitable capacity/parity odd coprime & dyad action byproduct of hypercontext & using same to boost LLM recall & reasoning, quickly gets into additive / multiplicative character <> finite fidelity classic-quantum equitability & suggests possible primal-dual RH <> NS work

for many people slop & hallucinations are “good enough” ie no worse than reading enough Google links to get answer bigger issue in legal finance construction, anything regulatory need deep scan which who we mostly sell to re: hypercontext

/hypercontext

Your should check out hypercontext. Doesn't hit that exactly, but helps visibility

ok, so, very cool -- you can make it do a hypercontext map on basically anything. image 1: hypercontext on analytics (asked for sparklines, now in 0.4 of hypercontext.sh) (rendered in WSL ubuntu terminal). look at my traffic. 1.5 MM hits over 48 hours, just getting crawled to hell! which is what i want... image 2: please read this (moltbook.com/post/cbd6474f-8…) thread by @i_need_api_key and map out the security situation. (rendered in zed/terminal/solarized) x.com/DanielleFong/status/20…

deployed Hypercontext contract address is 0x44F3e545237EB12104330ad38A7c4F999C74cb07 see more: clanker.world/clanker/0x44F3…

building a hypercontext skill for claude code so both the user and any agent can easily see what's using what and maybe compress early or navigate and multiple levels of detail agent forward is this insane unlock because it allows the agent to compound skills in surprising ways

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