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INNOTECH
MIDTERMS - REVIEWER
| Term | Definition |
|---|---|
| Technological Innovation | process of creating new technologies |
| Neural Networks | inspired by the human brain, made of “neurons” |
| Intelligence | the ability to learn, adapt, and solve problems. |
| Quality of life | the improvement in living standards due to technological advancements that make everyday tasks easier, enhance healthcare, and increase access to information and education, particularly in fields like medicine and communication. |
| K-means clustering | learning algorithm groups similar data points into clusters without using labels, and is common in market segmentation. |
| Reinforcement Learning | type of machine learning allows agents to learn by receiving rewards or penalties from their actions. |
| Global Competitive | term describes the advantage that nations gain in the global market when they foster innovation, allowing them to lead in key industries, attract investment, and influence international standards and practices. |
| Process innovation | type of innovation that focuses on improving the methods and processes used to create and deliver products or services, often leading to increased efficiency and reduced costs. |
| Machine Learning | subset of AI focused on algorithms that allow machines to learn from data. |
| Internet of Things (IoT) | term describes the network of interconnected devices and objects that can collect, exchange, and act on data through the internet, often without human |
| Bayesian Algorithm | learning algorithm uses probability and statistics to make predictions based on past knowledge. |
| Cyberthreats/Cyberattacks | terms refers to the risks associated with unauthorized access, data breaches, and other malicious activities that can compromise the integrity, confidentiality, and availability of information in digital systems. |
| Model-based reflects agents | type of ai agent remembers a bit of the past to make better decision. |
| Personalized Medicine | term refers to the approach in healthcare that tailors medical treatment to the individual characteristics of each patient, often based on genetic |
| Revolutionized Communication | This phrase describes the significant transformation in how people connect and share information, |
| Utility-based | Type of AI agent that chooses action not just to reach the goal, but to pick the best or most useful way. |
| Thinking Rationally | An approach to AI that uses logic to think correctly and make decisions. |
| Five Evolution of Technology in proper order | Five Evolution of Technology in proper order |
| Prehistoric Tools | The earliest technologies involved simple tools made from stone, wood, and bone |
| Agricultural Revolution | The development of agriculture around 10,000 BCE marked a significant technological shift, allowing for the cultivation of crops and the |
| Industrial Revolution | Beginning in the 18th century, Industrial Revolution introduced mechanization leading to mass production of goods such as steam engine, spinning jenny, and etc. |
| Electrical and Electronic Advances | The late 19th and early 20th centuries saw the advent of electricity, leading to the innovations such as the light bulbs, telephone, and later, radio and |
| Digital Revolution | This era transformed how information is processed, stored, and shared, leading to the rise of the information age. |
| 1. AI 2. Internet of Things (IoT) 3. Blockchain 4. Quantum computing | Four Future of Innovation |
| 1. Personalized Medicine (Genomics) 2. Telemedicine and remote monitoring 3. Medical devices and AI diagnostics | Three Technology in Medicine |
| Six Learning Algorithms | Six Learning Algorithms |
| 1. Decision Trees | Make decision by yes/no questions and splitting the data into branches. |
| 2. Neural Networks | inspired by the human brain, made of “neurons” that pass information. |
| 3. Bayesian Learning | uses probability and statistics to make prediction based on past knowledge. |
| 4. Support Vector Machines (SVM) | finds the best boundary (line or plane) that separates different group of data. |
| 5. K-means clustering | groups similar data points into cluster without using any labels. |
| 6. Q-Learning | A reinforcement learning method where the agents learn what action to take to get the most reward. |
| 1. Simple reflex agents 2. Model -based reflex agents 3. Goal-based agents 4. Utility-based agents 5.Learning agents | Five types of AI |
| 1. Supervised Learning – labeled data 2. Unsupervised Learning – No labels 3. Reinforcement Learning – Learn by reward | Three types of Machine Learning |
| Veracity | The Big Data characteristics that refers to the reliability and trustworthiness of data. |
| Big Data Approach | It uses all data not just samples. |
| Predictive Analysis | The type of Big Data analytics that answers the question “What is likely to happen?” |
| Mayer-Schornberger | He describe Big Data as society’s ability to harness information in novel ways for valuable insights. |
| Application Layer | In IoT architecture, this layer is responsible for what the user sees and interacts with. |
| Big Data | It is extremely large and complex sets of information that go beyond what traditional tools can handle. |
| AIoT | Future trends combines Artificial Intelligence with IoT to enable smarter decision-making. |
| Healthcare | IoT application involves wearable devices and remote monitoring. |
| Perception Layer | In IoT architecture, this layer consists of devices and sensors that collect data. |
| Predictive Analysis | It uses past data to guess the future. |
| 1. Discover patterns that were impossible with small data. 2. Automated decisions 3. Enhance efficiency across industry | Three Opportunities of Big Data |
| 1. More automation and AI-driven analytics. 2. IoT feeding data streams 3. Potential regulation of Data privacy 4. Quantum computing | Four Future of Big Data |
| 1. Improves Quality of Life 2. Increases Business Efficiency 3. Support sustainable solutions 4. Enhance decision making with real-time data | Benefits of IoT |
| 1. Improves decision making 2. Create new business models 3. Predics behavior and trends 4. Personalize services | Why Big Data matters? |
| 1. Sensing 2. Connectivity 3. Data processing 4. Action | Four characteristics of IoT |
Created by:
JonasTiglao28