Embodied AI: Hardware & Behavior

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Co-design AI with sensors, compute, and actuators.

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XI MIPA 4_36_VALERIE SIFRA

Indonesia

Download the paper version to play

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Froggy Jumps Embodied AI: Hardware & BehaviorOnline version Co-design AI with sensors, compute, and actuators. by XI MIPA 4_36_VALERIE SIFRA 1 What does hardware primarily determine in behaviorist AI? a The exact neural network weights b What stimuli can be sensed and how fast responses occur c Which algorithms are used for learning 2 Which component acts as the 'stimulus receptor' in robotics? a Actuators b Sensors c Processors 3 What is a key reason for co-designing sensors and AI policies? a To ensure efficient learning within hardware limits b To reduce the number of sensors needed c To increase software licensing costs 4 Which is an example of an actuator in robotics? a IMU b DC motor c Camera sensor 5 What is edge computing primarily used for in behaviorist AI? a Cloud-based storage b Low-latency real-time inference c Massive model training 6 What helps mitigate domain randomization in sim-to-real? a Removing sensors b Increasing model size c Calibration and noise injection 7 Which memory type stores recent transitions in RL? a ROM or cache b Replay buffer c ROM 8 What is a common bottleneck when running policies on microcontrollers? a Too many GPUs b Limited RAM and compute c Excessive cloud bandwidth 9 Why are watchdogs and kill-switches important? a To speed up training b Safety in learned behaviors c To bypass sensors 10 Which scenario illustrates a sim-to-real failure mode? a Sensors are ignored during deployment b Policy trains perfectly in all environments c Policy fails due to sensor noise not seen in simulation

Froggy Jumps

Embodied AI: Hardware & BehaviorOnline version

Co-design AI with sensors, compute, and actuators.

by XI MIPA 4_36_VALERIE SIFRA

What does hardware primarily determine in behaviorist AI?

The exact neural network weights

What stimuli can be sensed and how fast responses occur

Which algorithms are used for learning

Which component acts as the 'stimulus receptor' in robotics?

Actuators

Sensors

Processors

What is a key reason for co-designing sensors and AI policies?

To ensure efficient learning within hardware limits

To reduce the number of sensors needed

To increase software licensing costs

Which is an example of an actuator in robotics?

IMU

DC motor

Camera sensor

What is edge computing primarily used for in behaviorist AI?

Cloud-based storage

Low-latency real-time inference

Massive model training

What helps mitigate domain randomization in sim-to-real?

Removing sensors

Increasing model size

Calibration and noise injection

Which memory type stores recent transitions in RL?

ROM or cache

Replay buffer

ROM

What is a common bottleneck when running policies on microcontrollers?

Too many GPUs

Limited RAM and compute

Excessive cloud bandwidth

Why are watchdogs and kill-switches important?

To speed up training

Safety in learned behaviors

To bypass sensors

Which scenario illustrates a sim-to-real failure mode?

Sensors are ignored during deployment

Policy trains perfectly in all environments

Policy fails due to sensor noise not seen in simulation

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Embodied AI: Hardware & Behavior

Froggy Jumps

About this activity

Created by

Download the paper version to play

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Froggy Jumps

Embodied AI: Hardware & BehaviorOnline version

by XI MIPA 4_36_VALERIE SIFRA

What does hardware primarily determine in behaviorist AI?

Which component acts as the 'stimulus receptor' in robotics?

What is a key reason for co-designing sensors and AI policies?

Which is an example of an actuator in robotics?

What is edge computing primarily used for in behaviorist AI?

What helps mitigate domain randomization in sim-to-real?

Which memory type stores recent transitions in RL?

What is a common bottleneck when running policies on microcontrollers?

Why are watchdogs and kill-switches important?

Which scenario illustrates a sim-to-real failure mode?

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