PHYSICS ENGINEERED
Building the Most Advanced Physics Foundation Model

AI EVOLUTION VISUALIZATION

How AI evolves—from understanding language to mastering real-world physics through embodiment.

AI EVOLUTION VISUALIZATION

How AI evolves—from understanding language to mastering real-world physics through embodiment.

AI EVOLUTION VISUALIZATION

How AI evolves—from understanding language to mastering real-world physics through embodiment.

LANGUAGE MODELS

LANGUAGE MODELS

LANGUAGE MODELS

AI begins by understanding and generating human language, transforming simple sentences into tasks for underlying models.

Connected to PHANTOM-MK1

MULTI-MODAL FOUNDATION MODELS

MULTI-MODAL FOUNDATION MODELS

MULTI-MODAL FOUNDATION MODELS

Combining text, images, and other modalities, Al gains a deeper understanding of complex inputs, enabling deeper world knowledge.

PHYSICS-INFORMED AI

PHYSICS-INFORMED AI

PHYSICS-INFORMED AI

By learning from real-world physics, AI begins to master motion and interaction-powering robots that move with purpose.

Instruction: Assist by flicking the button

Instruction: Assist by flicking the button

Instruction: Assist by flicking the button

DVBF IN ACTION

AI MASTERING PHYSICS IN REAL TIME

DVBF IN ACTION

AI MASTERING PHYSICS IN REAL TIME

DVBF IN ACTION

AI MASTERING PHYSICS IN REAL TIME

WATCH VIDEO

HOW DVBFs WORK

A simplified look at the three core steps powering Deep Variational Bayes Filters.

HOW DVBFs WORK

A simplified look at the three core steps powering Deep Variational Bayes Filters.

HOW DVBFs WORK

A simplified look at the three core steps powering Deep Variational Bayes Filters.

ENCODING
Transform high-dimensional input into a low-dimensional point cloud.

ENCODING
Transform high-dimensional input into a low-dimensional point cloud.

ENCODING
Transform high-dimensional input into a low-dimensional point cloud.

BAYESIAN INFERENCE
Continuously update predictions using new sensory input.

BAYESIAN INFERENCE
Continuously update predictions using new sensory input.

BAYESIAN INFERENCE
Continuously update predictions using new sensory input.

DECODING
Turn latent representations into real-world predictions and actions.

DECODING
Turn latent representations into real-world predictions and actions.

DECODING
Turn latent representations into real-world predictions and actions.

DVBFs VS RL/IL

How does DVBFs compare?

DVBFs VS RL/IL

How does DVBFs compare?

DVBFs VS RL/IL

How does DVBFs compare?

MODEL-FREE
Reinforcement learning (RL)

IMITATION LEARNING (IL)

DVBFs + VLM

Data efficiency

Low - requires huge datasets

Medium - needs demonstrations

High - adapts with minimal data

PREdictive power

Reactive

Mimics observed behavior

Anticipates outcomes

adaptability

Slow

None

Fast

ASSUMPTIONS

Needs a human-tuned cost function

Needs human demonstration

Does physics-based prediction for action

MODEL-FREE
Reinforcement learning (RL)

IMITATION LEARNING (IL)

Data efficiency

Medium - needs demonstrations

PREdictive power

Anticipates outcomes

adaptability

None

DVBFs + VLM

adaptability

Fast

Data efficiency

Low - requires huge datasets

PREdictive power

Mimics observed behavior

ASSUMPTIONS

Needs human demonstration

PREdictive power

Reactive

Data efficiency

High - adapts with minimal data

adaptability

Slow

ASSUMPTIONS

Needs a human-tuned cost function

ASSUMPTIONS

Does physics-based prediction for action

MODEL-FREE
Reinforcement learning (RL)

IMITATION LEARNING (IL)

Data efficiency

Medium - needs demonstrations

PREdictive power

Anticipates outcomes

adaptability

None

DVBFs + VLM

adaptability

Fast

Data efficiency

Low - requires huge datasets

PREdictive power

Mimics observed behavior

ASSUMPTIONS

Needs human demonstration

PREdictive power

Reactive

Data efficiency

High - adapts with minimal data

adaptability

Slow

ASSUMPTIONS

Needs a human-tuned cost function

ASSUMPTIONS

Does physics-based prediction for action

KEY benefits

Superior Generalization

Applies learned behavior across varied environments with minimal tuning.

Predictive Power

Anticipates outcomes and acts ahead of time with high accuracy.

Scalability

Effortlessly expands from simple demos to complex real-world tasks.

Efficient Learning

Learns faster using fewer data—ideal for dynamic real-world conditions.

Complex Decision-Making

Processes multiple variables to make layered, intelligent decisions.

Adaptability

Adjusts to changing environments and tasks.

PHYSICS ENGINEEREDBuilding the Most Advanced Physics Foundation Model

PHYSICS ENGINEEREDBuilding the Most Advanced Physics Foundation Model

PHYSICS ENGINEEREDBuilding the Most Advanced Physics Foundation Model

DVBF IN ACTION

AI MASTERING PHYSICS IN REAL TIME

DVBF IN ACTION

AI MASTERING PHYSICS IN REAL TIME

DVBF IN ACTION

AI MASTERING PHYSICS IN REAL TIME

MODEL-FREEReinforcement learning (RL)

IMITATION LEARNING (IL)

DVBFs + VLM

Data efficiency

Low - requires huge datasets

Medium - needs demonstrations

High - adapts with minimal data

PREdictive power

Reactive

Mimics observed behavior

Anticipates outcomes

adaptability

Slow

None

Fast

ASSUMPTIONS

Needs a human-tuned cost function

Needs human demonstration

Does physics-based prediction for action

MODEL-FREEReinforcement learning (RL)

IMITATION LEARNING (IL)

Data efficiency

Medium - needs demonstrations

PREdictive power

Anticipates outcomes

adaptability

None

DVBFs + VLM

adaptability

Fast

Data efficiency

Low - requires huge datasets

PREdictive power

Mimics observed behavior

ASSUMPTIONS

Needs human demonstration

PREdictive power

Reactive

Data efficiency

High - adapts with minimal data

adaptability

Slow

ASSUMPTIONS

Needs a human-tuned cost function

ASSUMPTIONS

Does physics-based prediction for action

MODEL-FREEReinforcement learning (RL)

IMITATION LEARNING (IL)

Data efficiency

Medium - needs demonstrations

PREdictive power

Anticipates outcomes

adaptability

None

DVBFs + VLM

adaptability

Fast

Data efficiency

Low - requires huge datasets

PREdictive power

Mimics observed behavior

ASSUMPTIONS

Needs human demonstration

PREdictive power

Reactive

Data efficiency

High - adapts with minimal data

adaptability

Slow

ASSUMPTIONS

Needs a human-tuned cost function

PHYSICS ENGINEERED
Building the Most Advanced Physics Foundation Model

PHYSICS ENGINEERED
Building the Most Advanced Physics Foundation Model

PHYSICS ENGINEERED
Building the Most Advanced Physics Foundation Model

MODEL-FREE
Reinforcement learning (RL)

MODEL-FREE
Reinforcement learning (RL)

MODEL-FREE
Reinforcement learning (RL)