BTE 210 Final (Latest 2026) Real Questions
and Answers 100% Correct (verified)
• Gartner hype cycle -✓✓Separate hype from the real drivers of a technology's
commercial promise
Helps getting educated on an emerging technology within the context of the industry
and individual appetite for risk
• five phases of Gartner hype cycle -✓✓innovation trigger, peak of inflated expectations,
trough of disillusionment, slope of enlightenment, plateau of productivity
• innovation trigger -✓✓A potential technology breakthrough kicks things off. Early proof-
of-concept stories and media iinterest trigger significant publicity. Often no usable
products exist, and commercial viability is unproven.
• peak of inflated expectations -✓✓Early publicity produces a number of success stories
— often accompanied by scores of failures. Some companies take action; many do not.
• trough of disillusionment -✓✓Interest wanes as experiments and implementations fail
to deliver. Producers of the technology shake out or fail. Investments continue only if the
surviving providers improve their products to the satisfaction of early adopters.
• slope of enlightenment -✓✓More instances of how the technology can benefit the
enterprise start to crystallize and become more widely understood. Second- and third-
generation products appear from technology providers. More enterprises fund pilots;
conservative companies remain cautious.
• plateau of productivity -✓✓Mainstream adoption starts to take off. Criteria for
assessing provider viability are more clearly defined. The technology's broad market
applicability and relevance are clearly paying off
• NFT (non-fungible token) -✓✓A non-fungible token (NFT) is a unit of data stored on a
blockchain that represents a unique item
Real-world physical items or digital assets
Unlike bitcoin or another cryptocurrency, not mutually interchangeable, i.e., not fungible
• why is NFT unique -✓✓One bitcoin is indistinguishable from any other bitcoin and can
be readily exchanged, but NFT is unique; it is a one-of- a-kind piece of code, stored and
protected on the blockchain
An NFT can represent anything that exists as or can be represented by a digital - e.g.,
ownership of a digital asset that resides in a digital wallet
NFTS are cryptocurrnecy where each piece accompanies artwork or a video clip
, Therefore, in effect, you are purchasing an original work of art that is simply a digital
artwork rather than a physical drawing
• NFTS provide -✓✓Permanency
Blockchain recorded provenance
A way to authenticate ownership - each owner of a NFT has a one-of-a-kind token for
his or her copy of that piece of digital asset
• discriminative AI algoritms -✓✓try to classify input data; that is, given the features of
an instance of data, they predict a label or category to which that data belongs. They
simply map features to labels.
• example of discriminative AI -✓✓For example, given all the words in an email (the data
instance), a discriminative algorithm could predict the probability that an email is spam
given the words it contains. It does so by gathering words from the email (input),
analyzing it, and assigning a label - "spam" or "not spam"
• generative algoritms -✓✓One way to think about Generative Algorithms is that they do
the opposite. Instead of
predicting a label given certain features, they attempt to predict features given a certain
label.
For example, the question a generative algorithm tries to answer is: "Assuming this
email is spam, how likely are these features?"
• distinguish discriminative vs generative -✓✓Discriminative models learn the boundary
between classes
Generative models model the distribution of individual classes
• application of generative AI -✓✓Portrait of Edmond Belamy, AI reference 15,000 other
portraits
Generative AI - AI systems can now compose text, audio, and images to a sufficiently
high standard that humans have a hard time telling the difference between synthetic
and non-synthetic outputs for some constrained applications of the technology.
• Generative AI - LLM ChatGPT -✓✓Chat-based interface to GPT(Generative Pre-
Trained Transformer) developed by OpenAI as an automated text generator
• Generative - uses AI to predict - and generate - the next word, one word at a time,
based on what has come
• Pre-trained - based on much of the internet, Wikipedia, mullion of function books and
fact-based references, laws, etc.
• Transformer - example of a "Deep Learning" neural network, Google's transformer
architecture (2018) served as a foundation
• prompt engineering -✓✓crafting responses to feed to AI to produce better outputs
Prompt engineers train AI chatbots to improve their responses
and Answers 100% Correct (verified)
• Gartner hype cycle -✓✓Separate hype from the real drivers of a technology's
commercial promise
Helps getting educated on an emerging technology within the context of the industry
and individual appetite for risk
• five phases of Gartner hype cycle -✓✓innovation trigger, peak of inflated expectations,
trough of disillusionment, slope of enlightenment, plateau of productivity
• innovation trigger -✓✓A potential technology breakthrough kicks things off. Early proof-
of-concept stories and media iinterest trigger significant publicity. Often no usable
products exist, and commercial viability is unproven.
• peak of inflated expectations -✓✓Early publicity produces a number of success stories
— often accompanied by scores of failures. Some companies take action; many do not.
• trough of disillusionment -✓✓Interest wanes as experiments and implementations fail
to deliver. Producers of the technology shake out or fail. Investments continue only if the
surviving providers improve their products to the satisfaction of early adopters.
• slope of enlightenment -✓✓More instances of how the technology can benefit the
enterprise start to crystallize and become more widely understood. Second- and third-
generation products appear from technology providers. More enterprises fund pilots;
conservative companies remain cautious.
• plateau of productivity -✓✓Mainstream adoption starts to take off. Criteria for
assessing provider viability are more clearly defined. The technology's broad market
applicability and relevance are clearly paying off
• NFT (non-fungible token) -✓✓A non-fungible token (NFT) is a unit of data stored on a
blockchain that represents a unique item
Real-world physical items or digital assets
Unlike bitcoin or another cryptocurrency, not mutually interchangeable, i.e., not fungible
• why is NFT unique -✓✓One bitcoin is indistinguishable from any other bitcoin and can
be readily exchanged, but NFT is unique; it is a one-of- a-kind piece of code, stored and
protected on the blockchain
An NFT can represent anything that exists as or can be represented by a digital - e.g.,
ownership of a digital asset that resides in a digital wallet
NFTS are cryptocurrnecy where each piece accompanies artwork or a video clip
, Therefore, in effect, you are purchasing an original work of art that is simply a digital
artwork rather than a physical drawing
• NFTS provide -✓✓Permanency
Blockchain recorded provenance
A way to authenticate ownership - each owner of a NFT has a one-of-a-kind token for
his or her copy of that piece of digital asset
• discriminative AI algoritms -✓✓try to classify input data; that is, given the features of
an instance of data, they predict a label or category to which that data belongs. They
simply map features to labels.
• example of discriminative AI -✓✓For example, given all the words in an email (the data
instance), a discriminative algorithm could predict the probability that an email is spam
given the words it contains. It does so by gathering words from the email (input),
analyzing it, and assigning a label - "spam" or "not spam"
• generative algoritms -✓✓One way to think about Generative Algorithms is that they do
the opposite. Instead of
predicting a label given certain features, they attempt to predict features given a certain
label.
For example, the question a generative algorithm tries to answer is: "Assuming this
email is spam, how likely are these features?"
• distinguish discriminative vs generative -✓✓Discriminative models learn the boundary
between classes
Generative models model the distribution of individual classes
• application of generative AI -✓✓Portrait of Edmond Belamy, AI reference 15,000 other
portraits
Generative AI - AI systems can now compose text, audio, and images to a sufficiently
high standard that humans have a hard time telling the difference between synthetic
and non-synthetic outputs for some constrained applications of the technology.
• Generative AI - LLM ChatGPT -✓✓Chat-based interface to GPT(Generative Pre-
Trained Transformer) developed by OpenAI as an automated text generator
• Generative - uses AI to predict - and generate - the next word, one word at a time,
based on what has come
• Pre-trained - based on much of the internet, Wikipedia, mullion of function books and
fact-based references, laws, etc.
• Transformer - example of a "Deep Learning" neural network, Google's transformer
architecture (2018) served as a foundation
• prompt engineering -✓✓crafting responses to feed to AI to produce better outputs
Prompt engineers train AI chatbots to improve their responses
