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Artificial Intelligence(Deep Dive)

Updated: 3 hours ago



Artificial intelligence (AI) in the broadest sense refers to any human-like behavior displayed by a machine or system. Whether you are talking about deep learning, strategic thinking, or another species of AI, the source of its use is in situations that require lightning-fast responses. With AI, machines can work efficiently and analyze vast amounts of data almost immediately, solving problems through supervised, unsupervised, or reinforced learning.


Artificial intelligence can be a very powerful tool for both large corporations generating significant data and small organizations that need to process their calls with customers more effectively. AI can make business processes vastly more efficient, complete tasks faster, eliminate human error, and much more. Artificial intelligence is classified into two main categories: These being, AI that’s based on functionality and then AI that’s based on capabilities.


A computer “learns” when its software is able to successfully predict and react to unfolding scenarios based on previous outcomes.


There are four steps for building a machine learning model, and these are as follows:

1. Select and prepare a training data set necessary to solve the problem. This data can be labeled or unlabelled. 2. Choose an algorithm to run on the training data.

  • If the data is labeled, the algorithm could be regression, decision trees, or instance-based.

  • If the data is unlabelled, the algorithm could be a clustering algorithm, an association algorithm, or a neural network.

3. Train the algorithm to create the model. 4. Use and improve the model.


Sectors Currently Making Use of AI

  1. Healthcare

The contribution of the technology giants like Microsoft, Google, Apple, and IBM in the healthcare sector holds significant importance for the industry. AI is currently being applied for a wide range of healthcare services, including data mining for identifying patterns and then carrying out more accurate diagnosis and treatment of medical conditions, medical imaging, medication management, drug discovery, and robotic surgery amongst others.


2. Retail & Ecommerce

Retail and E-commerce is perhaps the only space where the application of AI is the most observable to most of the end-users. Being a competitive space, retail organizations always look out for ways to find patterns in consumer behavior and in doing so gain a competitive advantage.


3. Food Tech

Systems have been developed to enable food processors to help food-processing companies automate food analysis tasks such as measuring the size, shape, and color of french fries or analyzing the fat content in meat. In the agriculture space, a firm named companies are using AI to analyze the effects of variables such as UV light, salinity, heat, and water on basil. With this data, they are developing methods to raise better crops.

AI applications are also starting to be used in the farming sector where we have seen a surge in the use of intelligent tractors and intelligent plucking machines.

4. Banking and Financial Services

AI uses cases in this space are many. In lots of scenarios, human agents are being replaced by intelligent software robots for processing loan applications almost instantly. Similarly, Robo-financial advisors are sifting through multiple levels of data in split seconds to recommend the right investment decisions for customers.


In investment banking, machine learning (ML) & artificial intelligence (AI) can be broadly deployed across the front, middle and back-office functions. As well as across various asset classes where decision-making processes can be enhanced with enriched and predictive analytics.


Furthermore, AI-based chatbots are being used in the Insurance sector to improve the customer experience and create insurance plans and products based on customers’ data. Another important application of AI in the finance sector is fraud detection.


5. Travel

Machine learning and predictive analytics help travel companies increase their conversion rates by identifying customer behavior and purchasing patterns. The travel industry also uses chatbots to improve customer service.


6. Real Estate

AI-powered bots enable brokers and agents to find matches for people looking to buy, rent or sell their properties.

Also, AI-based chatbots can operate all hours of the day and help real estate website visitors find answers to their queries at any time.


7. Entertainment and Gaming

AI is helping program producers and broadcasters identify which shows or programs they should recommend to individual users based on their activity. This helps Netflix and Amazon provide a more personalized experience to users. Similarly, in the music industry, companies like Apple and Spotify use AI to understand users’ engagement patterns and recommend the right music to the right people and at the right time. In gaming, AI is used to control the actions of non-player characters (NPC) that play a role in advancing the game’s storyline.


8. Manufacturing

The manufacturing industry is leading the way in the application and adoption of AI technology. AI is being employed across several lines and layers of operations, from workforce planning to product design, thus improving efficiency, product quality, and employee safety.


In factories, AI is used to do amongst other things predictive maintenance on critical machinery. Robots also play an integral role in the manufacturing process of many products. And in quality control, AI algorithms are used to identify potential product quality issues.


9. Logistics and Transportaition

The logistics and transportation industry is on the cusp of an AI revolution. The use of machine learning and predictive analytics has already transformed supply chain management. Many warehouses use AI-powered robots for sorting and packaging products in warehouses. AI algorithms are also being used to find the quickest shipment route and support the last-mile delivery. For 4PL, the next AI step is surely a technology that selects various service providers and routes based on client's freight data, whilst also factoring in historic service levels. And continuosly optimizing that going forward. It may prove extremely difficult to remove the human factor entirely, but parts of the supply chain process are already subject to disruption from AI technologies.

In the transportation industry, self-driving vehicles will probably be the next big thing. Although they are still in the research and trial stage in many countries, AI-based self-driving will potentially replace manual driving and make driving on roads safer.

Source: (Hulett Packard and Leeway Hertz)

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