Ambient Scientific

Architecture · A-Cube

Meet A-Cube. AI-native, from the metal up.

Not an AI chip with a legacy brain, a new architecture built around what AI actually does. Energy-aware at every layer, scaling from coin-cell AI to Edge AI boxes

The PROBLEM

AI isn't just a math problem, but also a memory problem.

The multiply was never the expensive part. Moving the data was.

A-Cube

We put the compute inside the memory. The commute disappears. Compute where the data lives.

95%

of a neural net is matrix math. ~75% of the effort is moving it around.

Where compute happens

Inside Memory

Data Movement

Minimal

Efforts spent on moving data

Low

Efficiency

High

Legacy

Compute and memory sit apart. The chip spends its life shuttling numbers, not crunching them. ~75% of operations are just memory traffic.

Compute

Memory

Where compute happens

Outside Memory

Data Movement

High

Efforts spent on moving data

High

Efficiency

Low

One architecture that thinks senses, & speaks you language

Three breakthroughs as one: a physics-based brain, a responsive nervous system, and familiar language. Server-class AI with low power.

The Brain That think

CubicCore™

Server-class math. Microwatt power.

It runs the math on physics itself. Ohm's law multiplies, Kirchhoff's law sums - right inside the memory, almost for free. Digital keeps every result exact.

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In-memory analog compute - no data commute

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~1/100th the energy per operation vs. digital

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Scales by replication - tile in more cores, rom a smart ring to autonomous robots

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Fully programmable · 4–32-bit precision, tuned at runtime

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Built in standard CMOS - no exotic process

Inside Sensemesh

Always aware, InstantlyAwake

Always-on inference at microwatts. Full power the moment it’s needed. Then straight back to idle, no reset, no wake-up.

ReflexSurge Mode

on-demand. high performance

SUBCONSCIOUS MODE

Always on. Ultra low power

Subconscious AI

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Legacy chips switch off. A-Cube sleeps like you: the brain stays aware. A-Cube runs AI at microwatts while the host controller is powered down. Always processing, never draining.

Always processing, never draining.

ReflexSurge mode

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When something matters, the brain wakes instantly. The moment SenseMesh flags a real event, runtime DVFS ramps the chip from subconscious idle to full performance

live, no reset — settles back down.

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Once the task is completed, the chip settles back into subconscious mode.

A unified architecture for seamless adoption and scalability.

One architecture, one software stack, from a wrist to an autonomous drone.

GPX10 PRO

EDGE SENSOR

GPX40

CONNECTED VISION

GPX80

PERCEPTION & CONTROL

GPX Ultra

AUTONOMOUS AI

The efficiency gap isn’t a few percent. It’s a different category.

Every other approach trades something away. A-Cube doesn’t.

Rank

The Trade - off

1

A cube

Analog digital in memory

None

Power efficiency

~30 TOPS/W

Compute density

~5 TOPS/mm2

2

Flash

Compute in memory

Model Lock In

Power efficiency

~5 TOPS/W

Compute density

~1 TOPS/mm2

3

GPU

Paralle SMO

Too hot & power hungry

Power efficiency

1 TOPS/W

Compute density

~0.5 TOPS/mm2

4

MCU

Von-Neumann

Not built for AI

Power efficiency

0.1 TOPS/W

Compute density

~0.1 TOPS/mm2

A-Cube is live

Proven in silicon, shipping today.

A-Cube powers the GPX10 Pro's full neural networks on-device, at microwatt power.

512 GOPS

PEAK PERFORMANCE

High AI throughput enough to run full neural networks on-device, not rule-based shortcuts.

~80 uW

ALWAYS-ON POWER

Always-on AI inside a coin-cell power budget for months of battery, not hours.

A new architecture for AI, energy-aware at every layer, scaling from coin cell to cloud.

Put A-Cube to Work

Whether you’re scoping a product or pressure-testing the architecture, there’s a direct path forward.

Get anEvaluation Kit.

Explore how Ambient AI can unlock new capabilities in your wearable product. Strategic planning session with our applications team.

Buy an Evaluation kit.

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