Artificial Intelligence (AI) is transforming the world—industry by industry, home by home.
Whether you’re a start-up or well-established company, you probably have some ideas about using AI to automate repetitive tasks, reduce costs, and make your core processes more efficient.
Turn your ideas into fresh, custom-built AI solutions with help from Taazaa.
What is AI?
Defining AI is a complex discussion, but a basic definition of AI is that it’s any software system that can perform tasks that previously needed human intelligence to be accomplished.
How “smart” AI systems are depends on how they learn.
A basic AI simply follows the rules it’s given in order to complete a task. Siri, Alexa, Cortana, and Google’s Assistant can help you do things like adding a task to your calendar, but they can’t deviate from their programming. They can’t learn on their own.
AIs that involve machine learning can apply complex algorithms to large data sets to quickly uncover patterns that would take human beings far longer to see. These systems learn to better perform the task they are given, such as alerting you when you’re about to lose a customer, identifying spam, and other similar tasks.
Deep learning AIs use layered machine learning to progressively analyze vast sets of complex data stored in neural networks. Deep learning AIs can learn complex tasks or multiple related tasks. For example, Google’s AlphaGo AI not only learned to play the incredibly complex game of Go, but even beat several professional players.
AI, machine learning, and deep learning can be used in several ways, depending on your needs.
Data mining is data analysis on steroids. Data analysis examines a dataset to measure results and test assumptions—for example, the effectiveness of a marketing campaign. Data mining, on the other hand, uses machine learning and statistical models to reveal hidden patterns in a large volume of data. The AI might comb through millions of records to detect and predict consumer behavior.
Natural Language Processing
Natural language processing (NLP) uses AI to give devices the ability to mimic human understanding of the text and spoken words. NLP makes it possible for the software to translate text from one language to another, turn dictated speech into text, and perform other language-based tasks.
Examples of NLP include voice-operated GPS systems, digital assistants like Siri and Alexa, customer service chatbots, and similar applications. Enterprise-level organizations use NLP solutions to improve operations, increase productivity, and simplify critical processes.
Computer vision uses artificial intelligence to allow devices to analyze, interpret, and take actions based on digital images, video, and other visual data.
Common uses of computer vision include facial recognition, quality control, and self-driving vehicles, but new uses for this technology are being discovered every day.
Robotic Process Automation
Robotic process automation (RPA) refers to the ability to build, deploy, and manage software “robots” that mimic human interactions with software. These software robots perform tasks that are repetitive yet require intelligence—interpret what’s on a screen, complete the right keystrokes, and perform a wide range of defined actions. The advantage over humans performing these tasks is that software robots can do it faster and more accurately.
A good example of RPA is the use of software to analyze digital resumes submitted by job applicants, flag the ones qualified for the position, and send automated rejection notices to the others.
Predictive analytics uses statistical algorithms and machine learning to analyze historical data and identify the probability of future outcomes. This type of analysis has been around for a long time, but AI has made it highly accurate.
Predictive analytics has seen wide use across many industries, but the best-known use for it is credit scoring—processing a customer’s credit history, loan application, customer data, and other related historical information about that customer, and then determining the likelihood of them making future credit payments on time.
Need a team with experience in artificial intelligence, machine learning, or deep learning? We can help!
AI Development Platforms
We can help you develop AI solutions on the top platforms.
Azure Machine Learning
Microsoft’s Azure Machine Learning platform makes it possible to quickly create and deploy predictive models as analytics solutions. Azure offers tools for building complete predictive analytics solutions in the cloud, including a large algorithm library and a studio for building models. Azure also makes it easy to deploy a model as a web service.
Amazon Web Services (AWS)
AWS offers a wide variety of AI, machine learning, and deep learning services and frameworks. The technologies available to developers are the same tools that power Amazon Alexa and the rest of Amazon’s suite of services.
Google AI Platform
Google’s AI Platform is a managed service that makes it simple to build machine learning models that work on any type and amount of data. Google offers several tools for building AI solutions, including the TensorFlow framework that powers Google products like Google Photos and Google Cloud Speech.
Get Help with AI Development
AI development can be complex, and you may not always have the knowledge to go it alone. If you need a team to support you, we’d love to help.