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In 1956 at a Dartmouth Conference, thought leaders in Cognitive Computer Sciences, coined the term Artificial Intelligence (AI), the science and engineering of machines to exhibit intelligence. AI focuses on the design and development of software to enable computer systems to think, learn, and communicate. Computer Vision, a form of AI, focuses on enabling machines to understand high-level digital images, extracting useful information to gain visual understanding.
Artificial intelligence and Machine Learning development is divided into several sub-categories to address specific technical issues and venues. AI application development challenges focus around the emulation of human traits such as reasoning, knowledge, planning, learning, communication, perception. Platform development capabilities span several approaches to include statistical methods, computational intelligence, and versions of search and mathematical optimization, logic, probability, and economics.
Generative AI is an interactive computer-based decision-making tool that uses both facts and heuristics to solve difficult decision-making problems based on acquired knowledge. An expert system compared with traditional computer:
· Inference engine + Knowledge = expert system (Algorithm + data structures = program in traditional computer)
Development teams consist primarily of data scientists and DevOps experts. An initial step is to build an API – connector to grab and process data. A considerable amount of effort is dedicated to cleaning up existing data, as the overall platform success hinges upon data cleansing, munging and enrichment considering the potential for growth of external data sources, current data processing module must have a highly scalable architecture for rapid growth or expansion with existing and added sources onboard. Fully understanding the data is extremely important in driving development success, thus the data is run against a set of data modeling tools to establish descriptive statistics and comprehension of the given data.
The PCA (Principal Component Analysis) is conducted to understand weights and how key features affect outcome.
The 10 Rule - with PCA accomplished a model testing plan is devised starting with 10 "competitors" the list is distilled down to the four key models and amalgamated into an ensemble. Note: In predictive analytics and machine learning, ensemble methods incorporate multiple learning algorithms to obtain better predictive performance than can be obtained through constituent learning algorithms alone.
Vehicle Telematics has evolved exponentially from a rudimentary diagnostic reporting tool into a highly complex Omni-channel communications platform. Legacy Telematics platforms consisted of electro-mechanical sensory devices working in conjunction with on-board OS to aggregate data points and report on repeatable, predisposed functions through transceiver links to radio or satellite mediums.
Acquired Insights has invested a significant amount of technology capital into the development of their AI platform, Clarity.
Clarity is comprised of a highly sophisticated "Decision Engine" encompassing complex mathematical algorithms enabling light-speed predictive data analytics spanning multiple technologies including Telematics. Clarity's AI Decision Engine can process tremendous volumes of unstructured data (like video), automating once laborious manual processes, improving time to resolution and eliminating false positives.
ATSC development teams work closely with advanced AI tools to assist recruitment organizations in taking the guess work out of Sourcing & Recruitment utilizing Artificial Intelligence and Machine Learning Predictive Analytics to optimize Talent Acquisition & Employee Workforce Performance
customized data gathering Survey is embedded into each on-line application for candidate input. Applicant queries are designed to meet cultural and role expectations for each position sought within the organization providing distinguishable characteristics for each applicant
ATSC works closely with our clients to integrate Real-Time AI & ML capabilities with existing applicant tracking system (ATS) (i.e. iCIMS, Zoho, Workday, etc.) to deliver a robust, cost saving Talent Acquisition solution.
ideal Performance and Workforce Optimization solution. Real-Time Predictive Data Analytics:
A secure Artificial Intelligence Closed Loop Predictive Analytics platform that scans and processes information in structured and unstructured data repositories using all digital formats.
Through Big Data Analytics, AI, ML, and Deep Learning valuable insights are attained to help automate and improve process, mitigate risk, increase competitiveness and reduce operational cost.