most teams in #astrophysics, #earth observation, #oil & gas, and #geothermal are sitting on terabytes of sensor/seismic/satellite data that llms completely choke on.
context windows die, rag hallucinates, and petabytes stay useless.
we built https://t.co/fZI3Tb5bzu to turn that raw physical data into natural language you can actually query and reason with.
to prove it: the first 50 serious teams get $100 in lium tokens just to come try it.
no bs.
if you're dealing with real terabyte-scale science or energy data, dm me
AI will expand engineering jobs, not eliminate them.
Why? Because code was never the product. Outcomes were.
As AI reduces low-value work, strong engineers gain more leverage.
The more value each engineer can create, the more companies can justify investing in additional engineering talent.
AI is everywhere, yet insights rarely persist. Work becomes one-off artifacts: a chat, a sheet, a custom script.
When similar questions return, teams start over and results vary by who asks.
Real ROI comes from AI that learns from prior work and captures the reasoning, definitions, assumptions, and sources so knowledge compounds.