What is Cognitive AI? Cognitive Computing vs Artificial Intelligence | AI Tutorial | Edureka
TLDRCognitive computing, a subset of artificial intelligence, focuses on mimicking human reasoning to solve complex problems, enhancing decision-making. It integrates technologies like machine learning, deep learning, and natural language processing to synthesize data and learn from interactions. Key applications span smart IoT, AI-enabled cybersecurity, content AI, healthcare analysis, and intent-based NLP, showcasing its potential to revolutionize various sectors.
Takeaways
- 🧠 Cognitive computing refers to technologies that enhance human intelligence by performing specific tasks and simulating human reasoning and behavior.
- 🌐 Cognitive systems learn and reason from interactions with humans and their environment, using better data and algorithms for improved analysis.
- 🤖 Cognitive AI works by synthesizing data from various sources, considering context, and using self-learning technologies like data mining and NLP.
- 🔄 Key attributes of cognitive computing include adaptability, interactivity, iterative problem-solving, and contextual understanding.
- 📊 Cognitive computing and AI share similarities in technologies like machine learning and deep learning but differ in their focus and application.
- 🤔 AI focuses on providing accurate results and making decisions, while cognitive computing simulates human thought processes to find solutions and supplements human decision-making.
- 💡 Cognitive AI applications span across sectors like smart IoT, AI-enabled cybersecurity, content AI, cognitive analysis in healthcare, and intent-based NLP for business management.
- 🏥 In healthcare, cognitive AI implements human-like reasoning for deductive, inductive, and abductive analysis in Life Sciences applications.
- 🔗 Cognitive AI in IoT connects and optimizes devices through enhanced situational awareness and smart, distributed data security.
- 📈 Content AI solutions learn and reason, integrating various personal attributes and contextual data for personalized content delivery.
- 📊 Cognitive analysis aids businesses in becoming more analytical in their management and decision-making, acting as a logical reasoning step beyond machine learning.
Q & A
What is cognitive computing?
-Cognitive computing refers to technologies that perform specific tasks to facilitate human intelligence. These are smart decision support systems that use better data and algorithms to analyze large amounts of information, simulating human reasoning and behavior to assist in making better human decisions at work.
How does cognitive AI work?
-Cognitive AI works by synthesizing data from various sources, weighing context and conflicting evidence to suggest suitable answers. It uses self-learning technologies like data mining, pattern recognition, and natural language processing to understand the way the human brain works, refining its pattern identification and data processing capabilities over time.
What are the key attributes of cognitive computing systems?
-Cognitive computing systems should be adaptive, interactive, iterative and stateful, and contextual. They must be flexible to understand changes in information, digest dynamic data in real time, interact with users and other systems, identify problems by asking questions or pulling in additional data, and understand, identify, and mind contextual data.
How does cognitive computing differ from artificial intelligence?
-Cognitive computing focuses on mimicking human behavior and reasoning to solve complex problems, while AI augments human thinking and focuses on providing accurate results. Cognitive computing supplements information for humans to make decisions, whereas AI is responsible for making decisions on its own, minimizing the role of humans.
What are some applications of cognitive computing?
-Applications of cognitive computing include speech recognition, sentiment analysis, face detection, and risk assessment. It is used in sectors like customer service, healthcare, and IoT to optimize devices and data, enhance cybersecurity, and perform advanced content analysis.
Can you provide an example to illustrate the difference between cognitive computing and artificial intelligence?
-In the context of career change, an AI assistant might assess a job seeker's skills and find a relevant job, negotiating pay and benefits on their behalf. In contrast, cognitive computing would suggest potential career paths, provide additional insights like education requirements and salary comparisons, but leave the final decision to the job seeker.
How does cognitive AI enhance the field of healthcare?
-Cognitive AI in healthcare uses human-like reasoning software functions to perform deductive, inductive, and abductive analysis for Life Sciences applications. It can help in diagnosing diseases, predicting patient outcomes, and personalizing treatment plans based on complex data analysis.
What is the role of cognitive computing in IoT?
-In IoT, cognitive computing helps in connecting and optimizing devices and data. As more sensors and devices are integrated, cognitive computing plays a key role in analyzing and making decisions based on the data collected from these devices, leading to smarter and more efficient IoT systems.
How does AI-enabled cybersecurity work?
-AI-enabled cybersecurity uses data security encryption and enhanced situational awareness powered by AI to provide robust defense against cyber threats. It involves smart, distributed data securing using an AI key, which helps in detecting and responding to security breaches more effectively.
What is intent-based NLP and how does it benefit businesses?
-Intent-based NLP is a cognitive computing application that helps businesses become more analytical in their approach to management and decision-making. It uses cognitive intelligence to perform logical reasoning and analysis, moving beyond traditional machine learning to assist in strategic business planning and decision-making.
How do cognitive computing and artificial intelligence complement each other?
-Cognitive computing and artificial intelligence complement each other by combining their strengths. While AI provides accurate results and makes decisions, cognitive computing enhances human decision-making by simulating human thought processes and providing supplementary information. Together, they can create more effective and intelligent solutions for various industries.
Outlines
🤖 Introduction to Cognitive Computing
This paragraph introduces the concept of cognitive computing, highlighting its ability to learn, reason, and interact with humans naturally. It emphasizes the technology's overlap with artificial intelligence and its application in various fields such as speech recognition, sentiment analysis, and risk assessment. The paragraph also outlines the session's agenda, which includes defining cognitive computing, exploring its workings, differentiating it from AI, examining a use case, and discussing its applications. The introduction sets the stage for a comprehensive understanding of cognitive AI and its significance in decision-making and problem-solving.
🧠 How Cognitive Computing Works
This section delves into the operational mechanics of cognitive computing systems. It explains how these systems synthesize data from multiple sources, weigh context and conflicting evidence, and utilize self-learning technologies like data mining, pattern recognition, and natural language processing to mimic the human brain's functioning. The paragraph also outlines the key attributes of cognitive systems, such as adaptability, interactivity, iterative and stateful problem-solving, and contextual understanding. It highlights the evolution of cognitive systems from structured and unstructured data analysis to anticipating new problems and modeling potential solutions.
🔍 Differences and Applications of Cognitive AI
This paragraph contrasts cognitive computing with artificial intelligence, highlighting their underlying technologies and their distinct roles in problem-solving. It explains that while AI focuses on providing accurate results, cognitive computing simulates human thought processes to find solutions. The paragraph also discusses the sector-specific applications of cognitive AI, such as customer service, healthcare, IoT, cybersecurity, content AI, and healthcare analysis. It concludes with a mention of intent-based NLP as the next step in AI evolution, emphasizing the growing importance of cognitive intelligence in business management and decision-making.
📚 Conclusion and Future Learning
The final paragraph wraps up the session by reiterating the significance of cognitive computing as a subset of artificial intelligence and its potential to transform technology. It encourages viewers to share their opinions and invites them to engage with more content on the channel for further learning. The paragraph ends with a call to action for viewers to like, comment, and subscribe for more informative content, reinforcing the educational value of the session.
Mindmap
Keywords
💡Cognitive Computing
💡Artificial Intelligence (AI)
💡Machine Learning
💡Deep Learning
💡Natural Language Processing (NLP)
💡Adaptive
💡Interactive
💡Iterative and Stateful
💡Contextual
💡Smart IoT
💡Cognitive Analysis in Healthcare
💡Intent-based NLP
Highlights
Cognitive computing is a system that learns, reasons, and interacts with humans naturally, without being explicitly programmed.
Cognitive systems learn and reason from their interactions with humans and their environment.
Cognitive computing overlaps with artificial intelligence and involves similar technologies.
Cognitive computing is about understanding and simulating human reasoning and behavior.
Applications of cognitive computing include speech recognition, sentiment analysis, and face detection.
Cognitive systems must be adaptive, interactive, iterative, stateful, and contextual.
Cognitive computing focuses on mimicking human behavior and reasoning to solve complex problems.
Artificial intelligence augments human thinking and focuses on providing accurate results.
Cognitive computing is used in customer service and healthcare, while AI is used in finance, security, retail, and manufacturing.
Cognitive computing helps humans make smart decisions by leveraging machines, while AI makes decisions on our behalf.
Cognitive AI is a combination of cognitive computing and AI that can perform logical reasoning and analysis.
Smart IoT is an application of cognitive AI that connects and optimizes devices, data, and IoT.
AI-enabled cybersecurity uses data security, encryption, and enhanced situational awareness to protect networks.
Content AI is a solution that learns and reasons, integrating various personal attributes and contextual awareness.
Cognitive analysis in healthcare uses human-like reasoning for Life Sciences applications.
Intent-based NLP helps businesses become more analytical in their approach to management and decision-making.
Cognitive AI is expected to change the world of technology by enhancing smart decision-making and problem-solving.