Emerging trends Flashcards
The field of 1._________ and 2._________ is always 3._____ and 4._____.
1.information technology (IT)
2.Information Systems (IS)
3.growing
4.changing
1.______ is making 2._____ in many 3._____, and the 4.____ for these 5.______ is growing quickly.
1.Artificial Intelligence (AI)
2.big changes
3.industries
4.market
5.technologies
1.___ allows 2.______ and 3.____ to think and act on their own, meaning they can recognize patterns and respond in real-time.
1.AI
2.machines
3.software
AI allows machines and software to think and act on their own, meaning they can 1._________ and 2._____
1.recognize patterns
2.respond in real-time
AI allows machines and software to 1.____ and 2._____, meaning they can recognize patterns and respond in real-time.
1.think
2.act on their own
AI tools also help businesses 1._____ and 2.___ customer 3.___. This provides useful insights for leaders. For instance, companies use AI for customer service chatbots that can answer questions and for reports that analyze customer feelings about products.
1.collect
2.analyze
3.data
1.________ brings us closer to the 2._______we see in movies. A good example is 3.______, which was released in 4.______. This technology uses 5._______ processing to create text based on your question. When it came out, it generated a lot of interest as business leaders considered how it could be used in their work and thought about the ethical questions raised by a technology that can produce 6.________
1.Generative Al
2.futuristic technology
3.ChatGPT
4.November2022
5.natural language
6.human-like responses.
The term 1._______ was first used by American computer scientist 2._____ in 3.____. He described it as a computer’s ability to learn on its own without being specifically programmed for each task.
1.”machine learning”
2.Arthur Samuel
3.1959
Machine learning works by 1.___________ to find 2.______. It uses 3._________—to identify patterns and improve over time.Instead of following a fixed set of rules, machine learning algorithms learn directly from the data.
1.analyzing large amounts of data
2.useful information
3.algorithms—step-by-step procedures
In 1.________, machines are trained using 2.________. This means that the input data has already been 3.____ with the 4.______. The machine learns from this 5.______ so it can make predictions later. After training, the machine uses a separate test dataset to predict outcomes based on what it learned.
1.supervised machine learning
2.labeled datasets
3.matched
4.correct output
5.information
1.________ is different because it 2._______. Instead,the machine is trained with an 3._____ and must figure out patterns and groupings on its own. The goal is to organize the data based on 4._____________ without any 5.________.
1.Unsupervised machine learning
2.does not use labeled data
3.unlabeled dataset
4.similarities and differences
5.guidance
1._________ combines both supervised and unsupervised learning. It uses a mix of 2.________ to train the algorithms. This approach helps overcome some 3._____ of using only one type of dataset, making it more 4.______.
1.Semi-supervised learning
2.labeled and unlabeled datasets
3.limitations
4.effective
1.________ works through a 2._____. The AI learns by trying different actions and seeing what happens, similar to a 3.______ method. It receives rewards for good actions and penalties for mistakes. The goal is to 4.______ by learning to make 5.______ over time.
1.Reinforcement learning
2.feedback system
3.trial-and-error
4.maximize rewards
5.better decisions
1._______ is a part of 2.________ that allows computers to learn from 3.______ and 4._______. This means they can find patterns and make predictions with little help from people.
1.Machine learning (ML)
2.artificial intelligence (AI)
3.data
4.past experiences
Machine learning (ML) is a part of artificial intelligence (AI) that allows computers to learn from data and past experiences. This means they can find 1.____ and make 2._____ with little help from 3._____.
1.patterns
2.predictions
3.people
It’s important to note that 1._______ is not the same as 2._______, even though the terms are often mixed up. 3.________ is a specific area within AI. It’s also different from 4._______, which is about using data to predict future outcomes. While 5._______ can be used for 6._______, it has many other 7.________ as well.
1.machine learning
2.artificial intelligence
3.Machine learning
4.predictive analytics
5.machine learning
6.predictions
7.applications
He described it as a 1._______ to learn on its own without being 2.________ for each 3._______.
- computer’s ability
2.specifically programmed
3.task
To create a 1._______, these 2.______ are trained on a set of data called a 3.________. Once the model is 4.______, it can make 5._______ when 6._______ is provided.
1.machine learning model
2.algorithms
3.training dataset
4. trained
5.predictions
6. new data
Further, the 1.______ is checked for
2.______. Based on its accuracy, the
3.______ is either 4.______ or
5._______with an 6.________ until the desired 7.________.
1.prediction
2.accuracy
3.ML algorithm
4. deployed
5.trained repeatedly
6.augmented training dataset
7.accuracy is achieved
1.________ refers to 2.________ of
3.________ that 4.______ may
have trouble processing 5._______.
1.Big data
2.very large amounts
3.information
4.traditional methods
5.efficiently
1.________ is the process of examining
these 2._____ and 3.______ to find useful insights, patterns, trends, and connections.
1.Big data analytics
2.large
3.complex datasets
Big data analytics is the process of examining these large and complex datasets to find 1._____, 2._____, 3.______, and 4.______.
- useful insights
2.patterns
3.trends
4.connections
Big data refers to very large amounts of
information that traditional methods may
have trouble processing efficiently. Big
data analytics is the process of examining
these large and complex datasets to find
useful insights, patterns, trends, and connections. This analysis uses1._____
like 2.______, 3._______,
and 4._______.
- techniques
2.statistical analysis - machine learning
4.predictive modeling
Big data looks at both the numbers 1.________ and the details 2._______in various types of 3.______, including 4._______ and 5.________.
1.(quantitative data)
2.(qualitative data)
3. information
4.unstructured
5.semi-structured data
In addition to the common factors known as the 1.______ “—2._____ (the amount of data), 3.______(the speed at which it is created), and 4.______ (the different types of data)—big data analytics also considers 5._____ (making sure the data is accurate and reliable) and 6._____ (the usefulness
of the data).
1.”Three V’ s
2. volume
3.velocity
4. variety
5.veracity
6.value