Artificial Intelligence

ARTIFICIAL INTELLIGENCE

Artificial intelligence is the apparently intelligent behaviour by machines, rather than the natural intelligence (NI) of humans and other animals. In computer science, AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".

Machine Learning (ML) is the subfield of computer science that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model based on inputs and using that to make predictions or decisions, rather than following only explicitly programmed instructions.

ML “evolved from the study of pattern recognition and computational learning theory in artificial intelligence." It “explores the study and construction of algorithms that can learn from and make predictions on data—such algorithms overcome following strictly static program instructions by making data driven predictions or decisions, through building a model from sample inputs.”

For businesses, AI and ML can be used in the following ways:

  • Voice recognition
  • Voice search
  • Sentiment analysis
  • Flaw detection
  • Fraud detection
  • Recommendation engine
  • Facial recognition
  • Machine vision
  • Motion detection

Intelligencia has been working in the AI + ML field for several years now. We can explain all of the parameters to think about before making the substantial investment AI requires. Only one-in-three AI projects find success, so it's imperative to get honest opinions and accurate assessments before starting any AI project. 

Look-AI-like Marketing

Descriptive analytics is a preliminary stage of data processing that creates a summary of historical data to yield useful information and possibly prepare the data for further analysis. Data aggregation and data mining methods organize the data and make it possible to identify patterns and relationships in it that would not otherwise be visible. Querying, reporting and data visualization may be applied to yield more insight. Descriptive analytics is sometimes said to provide information about what happened. Seeing an increase in Twitter followers after a particular tweet, for example.

Natural Language Processing

Diagnostic analytics is a form of advanced analytics that examines data or content to answer the question, “Why did it happen?” It attempts to understand causation and behaviors by utilizing such techniques as drill-down, data discovery, data mining and correlations. Building a decision tree atop a web user’s clickstream behavior pattern could be considered a form of diagnostic analytics as these patterns might reveal why a person clicked his or her way through a website. Diagnostic analytics takes a deeper look at data to attempt to understand the causes of events and behaviors. 
 

Robotic Process Automation

Predictive analytics is an area of data mining that deals with extracting information from data and using it to predict trends and behavioral patterns. Predictive analytics is the use of statistics, machine learning, data mining, and modeling to analyze current and historical facts to make predictions about future events. Predictive analytics is an area of data mining that deals with extracting information from data and using it to predict trends and behavioral patterns. Often the unknown event of interest is in the future, but predictive analytics can look into past behavior as well.

Visual Search

Prescriptive analytics tries to optimize a key metric, such as profit, by not only anticipating what will happen, but also when it will happen and why it happens. Prescriptive analytics suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and shows the implication of each decision option. Prescriptive analytics can continually ingest a mixture of structured, unstructured, and semi-structured data to re-predict and re-prescribe, thus automatically improving prediction accuracy and prescribing better decision options every minute of every day.
 

A.I. + ML + DL SERVICES

Intelligencia can help businesses implement complex AI + ML solutions from the ground up. We can help you understand your data in ways that will simplify your AI + ML initiatives. We can also help you elucidate the complex AI + ML software landscape so that your AI initiatives doesn't fail (as 2 out of 3 normally do). Our modelers can help you build and maintain your models to ensure they are up-to-date and capturing the most relevant data to ensure your models are as optimized and as powerful as they can be.

Check with our team for more information about the services we offer.  

Intelligencia

We are here to help you navigate the complex world of analytics, AI, BI, CX, Cloud, DI, digital marketing, and social media implementations, showing you how open source technology can, potentially, augment your current software footprint and reduce cost. We understand ROI is king, above all else.

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