nx_nofloat_scale_research_fetch.nx
buildroot/runtime/nx_nofloat_scale_research_fetch.nx
about
nx_nofloat_scale_research_fetch.nx -- SOVEREIGN researcher: GROUND the "how do we AFFORDABLY + EFFICIENTLY
land a real working no-float transformer LM (CAP-AI-FRONTIER)" roadmap in REAL fetched facts (Rule 4:
roadmaps need VERIFIED facts, never assumptions). The no-float MECHANISM ladder is complete (train→generate→
sample→generalize→prose→in-context-copy→induction); what remains is SCALE/DATA/COMPUTE -- so this fetches the
literature on the CHEAPEST high-leverage moves: compute-optimal scaling, tiny-but-capable models, integer/
ternary LLMs (our exact no-float axis), and efficiency techniques.
Mirrors nx_ng_research_fetch: sovereign TLS-1.3 (nx_https_fetch_follow) + Mozilla CA store, idempotent
skip-if-have, saves each source to knowledge/fetched/nfs_*.raw so the corpus COMPOUNDS + can be grepped to
CITE (>=2-source / no-hearsay). 100% sovereign (own TLS, nx_cc->nxasm, no curl/wget/gcc). expect_exit: 0
dependencies 4 imports · 0 importers
imports: nx_syscalls.nxnx_x509_trust_store.nxnx_trust_store_load_from_certdata.nxnx_https_fetch_follow.nx
imported by: nobody (leaf or entry point)
call flow from main pre-order; caps 40 nodes / depth 6 declared; ↻ = already shown
structs
| none |
consts
| 15 | const K_MAGIC_4194304: i64 = 4194304 |
| 16 | const K_MAGIC_8388608: i64 = 8388608 |
functions
| 18 | func df_puts(s: *u8) -> i64 { var n: i64 = 0; while s[n] != (0 as u8) { n = n + 1 } sys_write(1, s, n); return 0 } |
| 19 | func df_putn(v: i64) -> i64 |
| 29 | func have_file(path: *u8) -> i64 { let fd: i64 = sys_openat_rd(path); if fd < 0 { return 0 } sys_close(fd); return 1 } |
| 30 | func fetch_save(url: *u8, opath: *u8, store: *TrustStore, out: *u8, cap: i64) -> i64 |
| 46 | func main() -> i64 |