S355 AI Quiz Practice

VR is good for marketing because it creates a:

Supervised, Unsupervised, Reinforcement, and RNN learning are all Machine Learning.

Edge computing is the question of where we process the data generated by sensors

Reinforcement learning: the AI gets a ______ if it's correct and a ____ if it's incorrect. Then the AI corrects itself.

Transformer is a neural network that stores and remembers the context from previous encounters:

Reinforcement learning is used when the only way to learn from an environment is to interact with it.

IoT is just sensors.

The cost of digital reality is low, so orgs should create detailed plans to determine whether it should be implemented

Unsupervised learning is used when we need to find patterns within the data.

Immersive:

Artificial Intelligence: the ability of a machine to perform _____ functions we associate with the human mind

Which is an example of supervised learning?

Generative Adversarial (GANS) is a neural network that combines Generators and Discriminators to:

RNN is a neural network that is good for assigning the likelihood of an outcome like:

We are NOT talking about ___ because current technology has not reached that level yet

Deep Learning requires less interference from humans and less data for training.

Which is an example of reinforcement learning?

Healthcare has a lower ROI on AI because health problems are more complex to develop technology for than manufacturing.

Processing data in the cloud is the hardest and most difficult to manage.

In edge computing there is a balancing act between fast processing time and complex data processing.

Siri is an example of an intelligent interface.

CPU consists of only a few powerful cores, which makes it good for parallel processing.

Supervised learning is used when the relationship is theorized but calculation is needed to determine the strength

CNN is a neural network that is good for dealing with unstructured data like:

Businesses that do IoT projects (ex. Amazon & Google) are gaining big ROIs

Which is not true about quantum computing?

To improve Big Data, we continue to expand storage capabilities for __________ ____.

With IoT we can be everywhere, and with AI + IoT we can _________ everywhere

Organizations must have an effective system for collecting and storing data, otherwise they run the risk of

AR and MR work well in controlled environments with few variables so that accurate info can be given at the right time.

The further that the IoT sensor is from the processing location, the faster the processing time.

Big Data means that all data has value.

Machine-learning is human-directed.

Intelligent interfaces are in high demand because we want other ways to interact with machines than typing and tapping

Affective computing focuses on understanding emotional language so it can be:

MR:

Any industry that could benefit from remote data collection is an opportunity for IoT improvements.

GPU is capable of parallel processing

Which is an example of unsupervised learning?

Select which is NOT an example of AI technology that solve business problems:

AR:

Computing power has grown dramatically: even doubling every two years.

GPU consists of thousands of less-powerful cores that work simultaneously to process complex outcomes.

The closer the processing is done to the device that collects info, the lower the latency (delay).

Computing close to the edge increases risk of theft and vandalism.

The race between AI companies centers around access to ______ & ______ data

Between two similar AI systems, the one with access to more valuable data is the better AI.

Big Data is data that is generated and stored on a small scale.