Physical AI is scaling
Humanoids enter real production in 2025–2027. Makers are choosing their interconnect now — before they build millions of units.
Fermat-Godel
FG-200
the nervous system for physical ai · FG-200 Rev A
The Nervous System
for Physical AI
Light-speed data between a machine's senses and its brain — qualified for the body copper can't survive. FG-200 replaces the harness with a link that is locked, lossless, and weightless.
- Aggregate data rate
- 1.2 Tbps
- Operating range
- −40 °C → +85 °C
- Tuning power
- 0 W
- Harness removed
- 2.2 – 3.1 lbs
The Problem
Physical AI has a nervous-system problem.
Machines that sense, decide, and act have moved past locomotion and into on-platform intelligence. But intelligence is only as good as the substrate carrying its signals. That substrate is copper, and it is the weakest link in the machine.
Already solved
- Edge AI compute — Jetson Thor-class inference on the platform
- Perception — 6–12 camera streams, LIDAR, force-torque at the joints
- Actuation — locomotion largely solved, manipulation advancing fast
Hasn't adapted
- The wiring between senses and brain still uses car-grade copper
- More sensors plus faster chips means more data than copper can carry
- The bottleneck is the nerves — not the brain, not the muscle
Why Copper Fails
A physics limit — not an engineering one.
This is not fixable with better cable. Four independent failure modes converge inside a moving body — and above ~25 Gbps over meter-scale spans inside an actuator cluster, optical is the only medium that closes.
- 01
Flex fatigue
Joints flex 100k–1M cycles per year. Copper conductors crack; harness replacement is a top field-reliability complaint.
- 02
Fretting corrosion
Vibration raises contact resistance ~100× at flexing connectors — and the damage is irreversible.
- 03
EMI coupling
40–60 servo inverters switch 48–400 V at 10–30 kHz, radiating straight through shielded twisted-pair.
- 04
Mass penalty
2.2–3.1 lbs of harness costs 30–60 min of runtime. Distal mass costs the motors 10–20× more.
Why Now
Three curves crossed at once.
None of this was buildable five years ago. Three independent trends arrived together — and the wiring decision is being locked right now.
Light-chips are ready
Co-packaged optics went from lab to data-center product. Shared-wafer runs let small teams get them made cheaply.
Extremities need data
Dexterous hands need 5–10 Gbps at the wrist for fingertip cameras and touch. Copper can't; co-packaged optics can.
The Technology
Light that stays tuned without power.
The athermal trick
Normal light-chips burn tiny heaters to stay tuned as temperature swings. A moving robot can't spare the power or the weight. So the light path straddles silicon and a polymer whose response to heat is the opposite of silicon's. The two cancel — the chip stays locked by itself, with no heaters on the routing layer.
Light-balance ratio
0.54
Tuning power
0 W
Locked across
−40 → +85 °C
FG-200 vs. copper baseline
- Weight
- −2.2 to 3.1 lbs of harness — runtime you get back
- Data rate
- 1.2 Tbps aggregate, against 5–50 Gbps on copper today
- Electrical noise
- Glass fiber ignores EMI; heavy shielding removed
- Cable types
- One fiber replaces 4–6 copper cable types
Architecture
One hub, many spokes.
Head
Cameras + LIDAR
4.0 W
Torso
AI chip + data switch
70 W
Hip
Safety chip + walk
5.0 W
Limb ×4
Motor + touch + camera
1.8 W each
Co-packaged
The optical engine sits beside a standard AI chip on one shared base — no lossy electrical run to a pluggable module.
N+1 redundancy
A spare laser takes over in under 10 µs if one fails — faster than a blink.
Safety by design
Three-layer architecture built to pass the ISO 13482 personal-robot safety standard.
Business Model
We license the layer, not the wire.
ARM for physical-AI interconnect. We don't build robots. We own and license the architecture that connects a machine's senses to its brain — the substrate under every embodied platform, whoever wins.
Transition consulting
Advise on the copper-to-light switch and build the transition hardware that makes adoption immediate.
Architecture licensing
Others build to our design for an upfront fee plus per-unit royalty. Scales without us building factories.
Defense direct
Work straight with defense programs and primes that require US-made, ruggedized parts.
Market
One design, five physical-AI markets.
Revenue per robot = interconnect license + integration fee + digital-twin system + royalties. One patented design; each new market costs less to enter than the last.
TAM
~$30B / yr
by 2035, across all five markets
SAM
~$1.5B / yr
humanoid interconnect — our wedge
SOM
$50–150M / yr
reachable early share
- 01
Humanoid robotics
First market
- 02
Defense / tactical edge
Highest value
- 03
Automotive compute
- 04
Factory automation
- 05
AR / VR headsets
Go-to-Market
Beachhead: defense-grade physical AI.
| Segment | China status | FG-200 positioning |
|---|---|---|
| Consumer ($10–30k) | China dominates | We skip it |
| Defense / tactical edge | Banned (export control) | ITAR-compliant, ruggedized — our main entry |
| Western hand-robots | Does not compete | Gives the data room for fingertip cameras |
Defense is the wedge: highest value per unit, hardest for legacy copper rivals to enter, and fully aligned with US supply-chain policy.
Contact
Every embodied machine needs a path from sensing to action.
Today that path is being set in copper — by default, because no one changed it. FG-200 sets it in light: US-aligned, patent-protected, and something copper physically cannot match.
Blue Mountain Sky Technologies · Patent pending
Request the FG-200 briefUSPTO App. No. 64/065,855