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Why did some of the earliest artificial intelligence systems focus on board games such as checkers and chess?
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The first conference on artificial intelligence was in
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Generative AI
Microsoft and LinkedIn
| Question | Answer |
|---|---|
| Why did some of the earliest artificial intelligence systems focus on board games such as checkers and chess? | t's easiest to make a computer system seem intelligent when it's working with set rules and patterns. |
| The first conference on artificial intelligence was in | 1959. Computers at that time didn't have the processing power to identify complex patterns. So early artificial intelligence systems needed to focus on board games and other tasks that had simple rules and patterns. |
| When a customer asks a question, then the expert system will ask a follow-up question. It will do this until it makes a recommendation. What's one of the biggest challenges with this system? | There will be too many tax combinations for the experts to cover with one system. |
| Luella seeks medical attention for chest pains. A nurse uses an artificial intelligence program to diagnose the cause. Why is this system likely not really intelligent? | The program only matches her symptoms to steps in a system an expert created. This is an example of weak AI, unlike strong AI in which the system possesses some human traits. |
| How does an artificial neural network learn? | It looks at the data and makes guesses, then it compares those guesses to the correct answer. These guesses are usually expressed as a percentage. So the network might be 60% sure that the image contains a dog. |
| The healthcare and medical insurance industries caution against using machine learning to search for patterns in data, and they do not want machines making decisions about a person's health. Why? | They may be decisions that humans cannot understand. Although humans program machines, they do not understand exactly how machines identify patterns in large datasets, which can lead to errors. |
| What type of impact does artificial intelligence have on robotics? | AI systems can create robots that can more easily learn new tasks. Early robotic systems needed to be explicitly programmed for each task. Newer They can try to mimic someone's behavior or even come up with new actions without being programmed. |
| What impact will the Internet of Things (IoT) have on artificial intelligence? | These devices will be a great new source of “real world” data. |
| A new online camping goods store wants to find connections between products customers buy and other products they might buy. Why would the company use unsupervised learning? | It does not yet have enough customers to make supervised learning meaningful. |
| Supervised learning example | you draw the letter “B” on the board. Then you ask the two-year-old students to find a block with that same letter. the incorrect students compare their block to the letter “B” on the board, recognize the error and then decide to get another block. |
| Supervised learning | relies on labeled data. In this case the two-year-old students would use the letter written on the board as labeled data. Then they would try matching the label. If the student sees that they made a mistake, they adjust and take another guess. |
| Why might you want to use reinforcement learning instead of unsupervised learning? | Reinforcement learning allows the machine to make predictions and create strategies instead of just clustering the data. |
| Reinforcement learning | strategies to better find patterns in the data. Tries to create clusters based on what it already sees in the data. an AI system to buy related items, an unsupervised system would create a cluster of items frequently bought together by other customers. |
| What is one of the greatest challenges with supervised learning binary classification? | You need a lot of pre-classified or labeled data for the training set. That means if you wanted to create a system that looked for dogs in images you needed to have tens of thousands of images known to contain dogs. |
| company wants to get the maximum amount of value from its advertising dollars. by advertising when customers are most interested in purchasing. Your team wants to create a regression analysis based on fuel prices. How might this look on an XY diagram? | Create a trendline with fuel prices along the X axis and electric car sales on the Y axis. |
| regression analysis | plot their data on an XY diagram. Then they will see if there are any trends in the data by creating a line in the center of the largest data point groupings. If the data has a clear trendline then it will be easier to predict relationships. |
| How is K Nearest Neighbor like the old saying, “birds of a feather flock together?” | Classify unknown data against the closest data that you do know. remember the key strength of K Nearest Neighbor. This machine learning algorithm is a quick way to classify data that's similar and might “flock together.” |
| What is ensemble modeling? | This is when you use a mix of different machine learning algorithms or data to improve the outcome. |
| when you use several machine learning algorithms to make better predictions. | Ensemble modeling i |
| two of the most popular techniques of ensemble modeling | bagging and stacking. Bagging uses the same machine learning algorithm with different data sets to improve the prediction power. Stacking can use several different machine learning algorithms “stacked” on top of each other to improve the predictions. |
| when customers are buying electronics it's much more likely to be a fraudulent transaction. Then customers started to complain that they couldn't use their credit cards to purchase any electronics. What is the challenge with your model? | You underfit the model to the data, the simple rule made too many inaccurate predictions. |
| When creating a model | be careful not to underfit or overfit the data |
| underfitting the data. | identify patterns that work with a small set of data but that doesn't fit when you start to look at larger dataset |
| overfitting the data. | you can add more variables. This can create a lot of complexity and you might miss data outliers (data that is close but doesn't quite fit the model). |
| How does the bias-variance trade-off affect machine learning? | If the machine makes a change to one, it must consider how the other is affected. For example, correcting high bias could lead to higher variance, which would make the data less reliable. |
| Kira is building a neural network to identify customer returns using binary classifications of defective or unsatisfied. In which layer of this neural network will Kira have a probability score? | the output layer |
| You initialize the artificial neural network with random weights assigned to all its connections.The system does a terrible job identifying whether those people are included in the video. What would the artificial neural network now do to try and improve? | It will adjust the weights of the connections to see if it does a better job making a prediction. |
| A supervised learning artificial neural network is self-tuning | That means it makes a prediction and then checks that prediction against the labeled data. The network tunes itself by adjusting the weights of the connections and the bias on the neurons. Then it sees if these adjustments improve the outcome. |
| With an artificial neural network what is the point of having a cost function? | It helps the network determine the cost of the error so they can make larger or smaller adjustments to its guesses. |
| Artificial neural networks need a measurement of “wrongness.” | to know how much to adjust its weights and biases., done through a calculation of the gradient descent which will increase or decrease the cost function. |
| How can you best describe the cost function as it applies to neural networks? | a number the system uses to measure its answer against the correct answer |
| What will be the most significant impact of generative AI on the future of jobs? | We will focus on what makes us unique as a species: our consciousness and our vision. |
| The invention of generative AI can be likened to what other monumental discovery? | Photography, because it is a true creative revolution. |
| What is an AI model? | a model is a set of algorithms that have been trained on a specific dataset |
| Do you need to have a technical AI background in order to start a generative AI venture? | No,you can either make partnerships with generative AI research institutions, or you can use open-source models in your next business endeavor. or you can make use of a generative AI services that are free or are accessible with a modest fee. |
| What is the primary function of generative AI? | to generate new content such as text, picture, and video |
| What is the most notable functionality of Natural Language models like Chat GPT? | its large scale capability to generative human-like text |
| What are Midjourney, DALL-E, and Stable Diffusion, and which industries are their early adopters? | They are primary text-to-image generation services and models. Art, filmmaking, fashion, and marketing are the first industries to widely adopt their use. |
| Do Natural Language models like Chat GPT understand the text they write? | No they do not. They synthetically mimic human language. "Understanding" is a function that is unique to consciousness-based biological organisms. |
| How can VAEs can be used in anomaly detection? | VAEs can be trained on a dataset of normal data, and later on be used to identify instances that deviate from the normal data. |
| How does a GAN network improve its ability to generate better content? | The generator and discriminator parts of the network work together in a competition to improve the generator's ability to create realistic data. |
| It is correct to say "AI is replacing humans"? | FALSE, The objective of generative AI is to be a (creative) assistant to humans in their production workflow. |
| What will be the main benefit of generative AI in the next years? | automate repetitive tasks and liberate humanity from dull, difficult, or robotic jobs |
| Why is the presence of a board of ethical use of AI advised for every AI company? | It is our moral responsibility as early adopters of AI to provide guidance and education around AI and inform our employees and colleagues on how to overcome their fears, challenges, and biases towards this new tool. |
| What are the top moral and executive skill sets required when working with generative AI? | Transparency, fairness, empathy and responsibility. Approach the production and all operations with caution, always ask "who is benefiting" from our generative AI solution. |
| What should we be doing if we have doubts, anxieties, or fear over AI and our future? | Seek to inform ourselves better to overcome these fears. The nature of a singular fear is often related to complex web of several different fears in our subconscious, we shall inquire to transcend these fear |
| What shall be in the center of all (generative) AI research and development? | Human creativity and human decision-making |
| What is the goal of the continuous crawling process of a search engine? | to keep the search engine's index up-to-date |
| When a user enters a query, what does the reasoning engine strive to provide? | a relevant, informative text response using human-like speech. Because reasoning engines process and understand human language, they are able to provide a relevant, well-reasoned, informative response using human-like speech. |
| When might a search engine be a superior tool to a reasoning engine? | when you’d like to read further about a subject across a collection of different sources—but not necessarily when you want to ask deeper questions |
| Which is not a main function of a search engine? | transforming. The main functions of a search engine are crawling, indexing, and ranking. |
| What is the most important benefit that the synergy between modern search engines and reasoning engines provides, as far as confidence in the results? | verifying and validating search results |
| How can a user best combine a search engine and a reasoning engine to find information about an unknown topic? | Use the search engine to find basic information, and then use the reasoning engine for a deeper dive. |
| How does a reasoning engine's ability to understand and interpret language provide the greatest advantage over a search engine? | It can have an actual conversation with the user. |
| How are reasoning engines an improvement over search engines when it comes to entering what you are looking for? | They can understand your intent and not just the words you used. |
| How do human supervisors assist in training a reasoning engine? | In early training phases, human supervisors oversee the process, guiding the model towards accurate responses and contributing to its knowledge development. |
| True or False: Reasoning engines are an all-knowing source of truth and should be trusted implicitly. | FALSE |
| When a user enters a query, what does the reasoning engine strive to provide? | a relevant, informative text response using human-like speech Because reasoning engines process and understand human language, they are able to provide a relevant, well-reasoned, informative response using human-like speech. |
| When might a search engine be a superior tool to a reasoning engine? | when you’d like to read further about a subject across a collection of different sources—but not necessarily when you want to ask deeper questions |
| If your reasoning engine response is problematic (i.e., inaccurate, discriminatory, limited in view, etc.) what should you do? | Continue iterating. Keep regenerating and refining the prompt to get a more accurate, better result. |
| In prompt engineering, what is one-shot or few-shot learning? | It refers to how much instruction you provide in order to guide the answer. This may involve including examples of what a "correct" answer may look like. |
| In most instances, how should you craft your prompts? | Use clear language with proper grammar. |
| Why is the iteration process necessary when you use a reasoning engine? | You want to keep honing your prompt to get more and better results. |
| Riva considers herself a prompt engineer. What does this mean? | She can create a prompt with samples of her question and the answers that she would like to see. |
| What is the following creative type of prompt known as: “Imagine you’re the manager of a small botique video editing company. What are 10 innovative marketing ideas that could attract new business?" | Role play |
| True or False: Reasoning engines are an all-knowing source of truth and should be trusted implicitly | FALSE |
| Three of these actions will help if you're having trouble using conversational-style Bing chat. Which actions will help | Try using the Edge browser, Make sure you have enabled the page context setting for page-related contextual chat, Make sure you are in the chat window rather than the search box. |
| Bing chat has composed a collection letter for you, but you aren't entirely happy with the results. Which is the best choice of action you should take? | Use the letter as a starting point and edit it until it fits your needs. |
| You want to get clarification on a question you posed in Bing chat. Which action will not help? | Start a new topic on the same question. |
| Which three sources of data can Bing chat summarize for you? | the contents of the current website you are on, a Microsoft Word document you have open in the browser , text you have pasted into the Bing chat sidebar |
| Which item should include a disclosure that it was created using Bing chat? | a housing contract between a landlord and tenant |
| What type of misused AI can give false advice, which is extremely dangerous in a situation such as providing medical advice? | inaccurate chatbots |
| ABC Corp's management uses AI to provide advice on selecting options for its marketing strategy. How can robust transparency help the company? | It can assist in understanding the input-analysis-output process. |
| Layla learns that her company's AI-driven chatbot has been giving inaccurate and sometimes rude responses to customers' questions. How should Layla deal with this issue? | Limit the chatbot to customer service questions and no other purpose. |
| Ahmad is creating a technology team for a new project. When should the team get together to discuss ethical considerations? | before starting the project |
| Why is it a good practice for the C-suite to develop, and perhaps even mandate, an AI training and education program for all employees? | It democratizes decision-making around AI tools. |
| In which situation are ethical considerations the responsibility of a board of directors? | when it involves compliance with a regulatory agency |
| How can a company best build customer trust, which can translate to a loyal customer base? | Share a transparent privacy policy. |
| Why, more than any other reason, should a company perform a privacy audit? | so it can develop a company-wide privacy policy |
Created by:
avanimami