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Artificial Intelligence (AI) & Machine Learning (ML)
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Artificial Intelligence (AI) & Machine Learning (ML)
Leverage Technology For Better Decisions
Leverage Technology For Better Decisions
Artificial Intelligence (AI)
Artificial intelligence (AI) refers to the capability of a computer system to mimic human cognitive functions, such as learning and problem-solving. Through AI, computers can use math and logic to simulate the reasoning that people would use to learn from new information and make decisions. From learning-enabled software to autonomous cars and smart robots to Information of Things (“IoT”) applications, AI is expanding its reach throughout the world.
AI business intelligence and analytics capabilities have become a focus at global corporations. The reason: these tools can provide valuable insights to enhance revenue and profitability. The adoption of AI has also been boosted by the increased volume and heightened complexity of data within global companies.
Artificial Intelligence – Trends & Attributes:
While AI and machine learning (“ML”) are closely connected, they’re not the same. ML is a branch of AI and computer science that focuses on the use of data and algorithms to imitate the way humans learn, gradually improving accuracy over time. This close connection is why AI vs. ML is really about how AI and ML can complement each other to create business value.
AI and ML: Process
AI and ML: Process
- Step 1: Build an AI system using ML and other techniques.
- Step 2: Create ML models by studying patterns in the data.
- Step 3: Optimize the ML models based on patterns in the data.
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Step 4: Repeat and refine the process until the models’ accuracy is high enough for the tasks that need to be accomplished.
AI and ML: Capabilities
Companies in almost every industry are discovering new capabilities and opportunities based on the powers of AI and ML. Myriad new uses have emerged – as well as enhancements to existing processes such as:
- Predictive analytics: Predicting trends and behavioral patterns by discovering cause-and-effect relationships in data sets.
- Recommendation engines: Leveraging data analysis in order to recommend products that might interest customers.
- Sentiment analysis: Identifying and categorizing positive, neutral, and negative attitudes that are expressed in text or other mediums of communication.
AI and ML: Applications
INSTANT® is deploying AI and ML for a range of benefits to clients in various categories and functions, such as:
- Retail: Optimizing inventories, building recommendation engines, and enhancing the customer experience with visual search.
- Banking and Finance: Predicting financial risk, detecting fraud, and enabling more proactive decision-making.
- Sales and Marketing: Facilitating personalized offers, optimizing campaigns, forecasting sales trends, analyzing customer sentiment, and predicting customer behavior (including churn).
- Transportation: Improving the efficiency of routes and forecasting traffic using predictive analytics.
- Manufacturing: Optimizing supply chain logistics, production scheduling, distribution scheduling, predictive maintenance, and more.
