genai

Which of the following are correct about Generative AI (3 correct): A type of foundation model that is designed to understand and generate human language. An application of ML that focuses on creating new content. Building machines that can perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. A type of artificial intelligence that can create new content and ideas, including text, images, music, and even code. Its applications can be multimodal, enabling them to process and generate different types of data like text, images, and code simultaneously.

What are the four primary ways to use generative AI?. Create: new content. Summarize: condense large amount of information into concise summaries. Discover: find information at the right time. Automate: task that previously require human intervention. Learn: from data to perform specific tasks.

What are examples of using generative AI to create new content: Writing articles, emails, and social media posts. Creating images, videos, and audio. Transform complex data into easily understandable visuals like graphs using Gemini in BigQuery. Generate unit tests and other test cases for code, reducing the manual effort required for testing while still ensuring the code works as expected. Search for a file or ask questions about its contents using Gemini in Google Drive.

What are examples of using generative AI to condense large amounts of information into concise summaries: Summarize a lengthy financial report without having to read the entire document using NotebookLM Enterprise. Project managers can automatically generate meeting notes that highlight key decisions and action items using Gemini in Google Meet. Use anomaly detection to identify fraudulent transactions and prevent financial losses. Convert content to accessible formats in real time by using Google Cloud's APIs, like Text-to-Speech, Speech-to-Text, Translation, and more. Transform complex data into easily understandable visuals like graphs using Gemini in BigQuery.

What are examples of using generative AI to discover what customers and employees need at the right time: Analyze purchase history and website traffic to predict future demand and optimize inventory using forecasting models on Vertex AI. Identify viewing patterns of streaming viewers to recommend personalized content to subscribers, increasing engagement and reducing churn using Vertex AI Search. Automate customer feedback analysis and ticket creation. Sales teams can use summaries to quickly recap client calls and identify next steps. Generate multiple design concepts for brainstorming marketing materials such as website pages using Imagen.

What are examples of using generative AI to automate tasks that previously required human intervention: Analyze code and automatically generate clear and concise documentation, saving developers time and ensuring consistency using Codey. Convert content to accessible formats in real time by using Google Cloud's APIs, like Text-to-Speech, Speech-to-Text, Translation, and more. Draft emails to clients using Gemini in Gmail. Summarize a lengthy financial report without having to read the entire document using NotebookLM Enterprise. Unlock enterprise expertise for employees with agents that bring together Gemini’s advanced reasoning, Google-quality search, and enterprise data, regardless of where it’s hosted using Google Agentspace.

Using generative AI to create new content, such as: Generate text responses to customer service inquiries using Conversational AI. Draft emails to clients using Gemini in Gmail. Create a custom image for a presentation using Gemini in Google Slides. Generate multiple design concepts for brainstorming marketing materials such as website pages using Imagen. Create video tutorials to guide customers through troubleshooting steps using Google Vids. Generate unit tests and other test cases for code, reducing the manual effort required for testing while still ensuring the code works as expected. Generate code as a starting point for larger software development projects using Gemini Code Assist. Writing articles, emails, and social media posts. Creating images, videos, and audio. Generating code in various programming languages.

Condense large amounts of information into concise summaries, such as: Summarize a lengthy financial report without having to read the entire document using NotebookLM Enterprise. Summarize customer reviews to understand product feedback and sentiment using Gemini in Looker. Project managers can automatically generate meeting notes that highlight key decisions and action items using Gemini in Google Meet. Sales teams can use summaries to quickly recap client calls and identify next steps. Transform complex data into easily understandable visuals like graphs using Gemini in BigQuery. Extracting key takeaways from meetings or presentations. Summarizing long documents or articles. Creating concise reports from complex data.

Gen AI helps your customers and employees find what they need at the right time, such as: Uncovering hidden patterns and insights in data. Analyze purchase history and website traffic to predict future demand and optimize inventory using forecasting models on Vertex AI. Identify viewing patterns of streaming viewers to recommend personalized content to subscribers, increasing engagement and reducing churn using Vertex AI Search. Analyze vast datasets of molecular structures to identify potential drug candidates with higher success rates by fine-tuning models on Vertex AI. Search for a file or ask questions about its contents using Gemini in Google Drive. Unlock enterprise expertise for employees with agents that bring together Gemini’s advanced reasoning, Google-quality search, and enterprise data, regardless of where it’s hosted using Google Agentspace. Use anomaly detection to identify fraudulent transactions and prevent financial losses. Monitoring real-time events. Searching for resources or documents.

Automate tasks that previously required human intervention, such as: Automated format conversation. Convert content to accessible formats in real time by using Google Cloud's APIs, like Text-to-Speech, Speech-to-Text, Translation, and more. Automated documentation. Analyze code and automatically generate clear and concise documentation, saving developers time and ensuring consistency using Codey. Automate contract review and information extraction with Document AI. Automated notifications and alarms. Automate customer feedback analysis and ticket creation.

Models can process various input types individually or combine multiple kinds of data simultaneously. Can process and integrate information from diverse formats like plain text, images, videos, audio, and PDFs. This capability–known as: Gen AI. Large language models (LLMs). multimodal gen AI. Machine learning (ML). Foundation models.

What examples of different multimodal use cases: A marketing team uses gen AI to create a series of social media posts (text) with accompanying images that align with their brand guidelines, including captions, hashtags, and optimal posting times. A legal team uses gen AI to summarize a lengthy legal contract (PDF) and answer specific questions about its clauses and implications, identifying potential risks and suggesting alternative language. A market research firm uses gen AI to analyze customer sentiment in video testimonials, the spoken words (text), and survey data collected alongside the video. This helps identify key themes, pain points, and overall customer satisfaction. A manufacturing team enhances worker safety with gen AI. The AI analyzes real-time camera feeds and sensor data to identify potential hazards, such as spills or equipment malfunctions, and immediately alerts workers to the danger. A law firm uses a GPT-based tool to summarize 50-page NDAs into 5 key bullet points for lawyers to review quickly. A doctor uploads a chest X-ray and enters “persistent cough and fatigue.” The AI analyzes the image + text and responds: “Likely pneumonia, mild stage. Suggest chest CT scan for confirmation.”.

Expands the capabilities of AI by allowing it to process and integrate different data types, like images, audio, and video, alongside text and numbers, which leads to a more complete and nuanced understanding of business processes, which is essential for solving complex problems. Multimodal gen AI. gen AI. AI. Deep Learning. Machine Learning (ML).

Only uses text (input: text documents, output: text summaries). No images, no audio, no video involved. Uses a single-modality model like GPT-4 (text-only variant). Choose the correct answers: Unimodal AI. Multimodal gen AI. Single Modality AI. Text-only AI.