Artificial Intelligence
What is Artificial Intelligence?
Artificial Intelligence (AI) describes the scientific approach of computers or machines dealing with the simulation of human intelligence. The ideal feature of it is the ability to rationalize and take actions that have the best chance of achieving a specific objective. The goals of AI include learning, reasoning, and perception.
“By 2029, computers will have emotional intelligence and be convincing as people.” – Ray Kurzweil
Machine Learning (ML)
Machine learning is a branch of artificial intelligence. Machine learning enables IT systems to identify patterns and patterns and develop solutions based on existing data sets and algorithms. It is so to say artificial Intelligence generated from experience. The insights gained from the data can be generalized and used for new problem solutions or for the analysis of previously unknown data.
Deep Learning
Deep learning is a special method of information processing. It is part of machine learning and uses neural networks. For the production of artificial intelligence, training methods are used that use and analyze large amounts of data.
The functionality is inspired in many areas by the learning process of the human brain. Algorithms for Deep Learning are hierarchically structured – towards increasing complexity and abstraction.
The more complex the network becomes, the better the performance will be improved. While deep learning is currently mostly under human supervision, the goal is to create neural networks that can train themselves and learn independently.
Computer Vision
Computer vision is the theory underlying artificial intelligence systems’ ability to see, identify and understand their surrounding environment. It is like imparting human intelligence and instincts to a computer.
It basically simulates and automates these elements of human vision systems using sensors, computers, and machine learning algorithms.
Natural Language Processing (NLP)
Natural Language Processing deals with the interaction between computers and humans using the natural language. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable.
Most NLP techniques rely on machine learning to derive meaning from human languages. One of the well-known examples of this is email spam detection, Personal assistant applications such as Siri, Cortana, and Alexa or language translation via Google Translate
Robotics
Robotics focuses on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. Recently machine learning has been used to achieve certain good results in building robots that interact socially (Sophia the Robot).
“The year 2029 is the consistent date I’ve predicted, when an artificial intelligence will pass a valid Turing test — achieving human levels of intelligence. I have also set the date 2045 for singularity — which is when humans will multiply our effective intelligence a billion fold, by merging with the intelligence we have created.” – Ray Kurzweil
Programming languages and tools that we use to develop AI applications
- Python
Python is considered to be one of the best AI development languages due to its simplicity.
- Pytorch
Pytorch, which is an open-source library provides a rich ecosystem of tools and libraries to support development in computer vision, NLP and more.
- TensorFLow 2.0
TensorFlow is an open-source framework developed by Google, which is used to create and integrate large scale AI and Deep Learning Models. It has recently been updated to TensorFlow 2.0.
- Keras
Keras is an open-source neural-network library written in Python. It is capable of running on top of TensorFlow and designed to enable fast experimentation with deep neural networks.
- Metaflow
A cloud-native open-source Data Science framework developed by Netflix.
Artficial Intelligence in layers source: deloitte.com
Benefits of using AI Solutions
How can Artificial intelligence impact your business?
Deploying AI technology correctly will make your business stay ahead of competition. Keeping in mind, AI does not replace the human, it augments the abilities of the human:
- Save time and reduce costs by automating and optimising work processes and tasks
- Increase productivity and operational efficiencies
- Faster and more intelligent business decisions based on outputs from cognitive technologies
- Identify opportunities and maximise sales
- Avoid mistakes and ‘human error’
- Leverage valuable insights to predict customer needs and offer them a unique and enhanced personalised experience
- Collect vast amount of data to generate quality leads and grow your customer base
- Develop expertise by providing analysis and intelligent advice
Data Analysis
To leverage the full potential of AI, it is essential to invest in a team of experienced data analysts. Data analysis serves to collect, process and perform statistical analyses of data. The goal is to translate numbers and data into plain English in order to help organizations and companies understand how to make better business decisions.
Whether it be market research, sales figures, logistics, or transportation costs, every business collects data. Our team of analysts will take that data and figure out a variety of things, such as pricing, logistics or product-life-cycle-management.
The surge of more enduser-friendly AI-based solutions and tools increases the enterprise adoption and also considerably reduces their costs.
The future of Artificial Intelligence Our vision and analysis
Enterprise-friendly AI
There are plenty of success stories that prove the value of AI. Organizations that extend traditional business processes and applications to machine learning and cognitive interactions can considerably improve the user experience and productivity.
The surge of more enduser-friendly AI-based solutions and tools increases the enterprise adoption and considerably reduces costs.
Use cases
Artificial intelligence is already impacting our daily lives in a significant way. AI is no more science fiction and is already being adopted by public and private organisations globally. For instance, farmers are leveraging AI to forecast their crop yield, AI is used by financial institutions to predict credit risks and enhance customer experience, by manufacturers to streamline supply chain, & predictive maintenance, and retailers to provide personalised customer journeys.
- Credit Risk Scoring
- Fraud Prevention
- Personalization
- Data intelligence / Sentiment Analysis
- Document search and analysis
- Algorithmic Trading
- Market Analysis
- Product/content recommendations
- Data filtering & analysis
- Search engines
- Visual search & image recognition
- Social trends & sentiment analysis
- Product categorisation
- Product pricing
- Audience targeting & segmentation
- Programmatic ad targeting
- Sales forecasting
- Chatbots & conversational AI
- Speech recognition
- Optimize Sales Strategy
- Lead Scoring and Prioritization
- Recommendations
- Performance and Productivity Enhancement
- Predictive Analytics through Business Intelligence
- Customer Identification
- AI Assistant
- Customer Experience -> Customer Journey
- Chat Bot
- Product Recommendations -> Full Personalisation
- Customer Interaction Analytics
- Diagnosis Processes
- Treatment Protocol Development
- Drug Development
- Personalized Medicine
- Patient Monitoring and Care
- Improve Patient Satisfaction
- Satisfy Staffing and Workforce Needs
- Reduce Length of Stay
- Crop and Soil Monitoring
- Early Crop Desease or Pest Detection
- Agricultural Robots
- Predictive Analytics and Crop Yield Forecast
- Manage and Track the Health of crops
- Driver Identification
- Assisted Driving
- Autonomous Driving
- Mobilitiy as a Service
- Driver Recognition
- Driver Monitoring
- Telematics and predictive maintenance
- Infotainment Control
- Smart Manufacturing
Potential
Artificial Intelligence is becoming an integral part of our daily lives, which will go on to influence in much wider terms, in everything that we do. The more AI is adopted by businesses and public institutions, humans and machines start to collaborate more closely.
The transformational benefits of AI for both businesses and societies are immense and it will ultimately fundamentally shape the way we work in the future.
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