// liv.jpg — drop Olivia’s portrait here
Olivia — the original L.I.V.
I was grinding on MIKE, trying to push it past the one wall compression can’t
argue with: entropy. Squeezing an already-compressed file is a fool’s errand — the math simply
says no. MIKE had already beaten 7-Zip and RAR where the data has structure, so I’d made my peace and left it there.
Then my friend Victor called. “In security footage we store enormous amounts of data — it
costs us a fortune. Can’t MIKE help?” And I said no — flatly. Security footage is
lossy, and MIKE is lossless; different worlds. End of call.
But the thought wouldn’t leave. Wait a minute… what if I don’t replace JPEG, MPEG and MP3
— what if I push them further than they’re supposed to go, and teach something to bring the lost
detail back? It lingered for days.
And while it lingered, my youngest daughter Olivia — Liv — planted her hands on her hips
and asked the only question that mattered:
“Dad — you built a whole program for Mike. Where’s my program?”
— Olivia (Liv), who was not going to be out-done by her brother
I know female jealousy when I see it coming. And just like that — Victor’s problem, the lingering idea,
and a daughter who wanted her name in lights — Lossy Implicit Vector was born. A human name first, an
acronym made to earn its letters second, exactly like MIKE:
Lossy — unlike MIKE, LIV lets go. Pictures, sound and video, where the eye and ear forgive far more than a checksum ever would.
Implicit — the intelligence isn’t in the file. It’s an implicit model living in the decoder, reconstructing detail instead of storing it.
Vector — a compact learned representation does the remembering, so a few thousand parameters stand in for a great deal of discarded data.
LIV puts a micro-AI engine right inside the codec, trained to understand how the picture changes. It lets
JPEG, MPEG and MP3 throw away more than they safely should — and then re-establishes parity,
bringing the detail back as if you’d encoded at high quality all along. Where MIKE is the mathematician who
stores the exact rule, LIV is the artist who remembers what the picture is supposed to look like —
and paints it back.
It’s built for Victor’s problem: security footage. Decompress a whole archive back to a big file
for viewing, or scrub it frame by frame on a computer — the frame-decode speed just tracks how much
computing power you throw at it. And because it’s still evolving — we think there’s more to
push — the µAI mode is still just a mode. That’s the beta.
Let’s see how it grows.
LIV is born.
With thanks and dedication to:
— my daughter Olivia (Liv), who wanted her own program — and was absolutely right to;
— my friend Victor, whose one honest question turned a “no” into a whole engine;
— and her brother
Miguel (
Mike), for going first.
// Spoiler: I have another daughter — Madalena. So don’t be surprised if a MAD — or a Maddie — shows up on this site before long. IDK. We’ll see.