In order to maintain a partnership of humans and Artificial Intelligence (AI) we need to optimize individual and team performance along with creating a nimble and future proof enterprise.

Intelligent machines to automatically learn and improve from Artificial Intelligence experience, it is essential to develop sophisticated algorithms. We help companies to create smart systems to leverage smarter algorithms that can iteratively learn from existing data and reveal hidden insights without being programmed clearly.

AI is considered a technological “brain.” Often construed as a technology for extracting data, AI is really just a technology that assists in handling data and information. In other words, it’s a group of technologies and algorithms that help solutions make accurate decisions based on trends and past decisions. However, some AI technologies are simple and others are difficult. Overall, if a technology is helping to make a decision — without a user forcing or programming it to — it can be classified as artificial intelligence.

So, what is AI most useful for? Most experiences suggest that AI “decisioning” technologies are best used to cut down on time-consuming, manual tasks. AI takes decisions that usually take longer time by humans.  Here’s an example: if one step in a process takes 10 seconds to complete and is repeated 100 times per day, AI intervention can save 16.6 minutes a day on that single step. It’s easy to see how ROI can grow to be substantial as these seconds can turn into minutes (or even hours) of time savings. Complex processes seem to benefit the most from this technology.

AI cloud offerings including Amazon Machine Learning, Microsoft Cognitive Services, and Google Cloud Machine Learning can help organizations what might be possible with their data. Having the opportunity to try the algorithms and services of different providers can allow businesses to find what works and allows for scaling before committing. When something is found that scales to requirements, the resources of these large providers are there to back up the scaling with compute capacity.

Different AI provider platforms offer various styles of machine learning and AI. These variations can be more or less suited to an organization’s AI needs since organizations need to evaluate features and pricing to see what works for them. Cloud AI service providers can offer the specialized hardware needed for some AI tasks, like GPU based processing for intensive workloads. Purchasing the required hardware and software to start on-premise cloud AI is costly. Coupled with staffing and maintenance costs, as well as hardware changes for different tasks, makes AIaaS cost-prohibitive to many organizations.

Emulate the mechanics of the human brain to analyze data and create patterns to make critical decisions. Our purpose-built deep learning portfolio covers multi-layered artificial neural networking for developing advanced facial and object recognition systems, home automation solutions, AI-powered chatbots, and process automation solutions to redefine your businesses.

The moment; and yet I feel that I never was a greater artist than now. When, while the lovely valley teems with vapour around me, and the meridian sun strikes the upper surface of the impenetrable foliage.

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