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How to Build on Artificial Intelligence from Current Gaps in Data

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Decades ago, artificial intelligence was a thing of the future meant for the generations to come after us. Now, artificial intelligence is present in almost all areas of modern technology and digital transformation. Advancements are being made every day to make our lives easier and push us to be more efficient workers.

Along with consumer applications like Siri and Alexa, companies across subdivisions are increasing the utilization of AI’s power in their operations. There’s no question that AI promises considerable benefits from its significant additions to productivity growth and innovation for businesses. But how can your business build on artificial intelligence from current gaps in data?

The Importance and Use of Big Data

Data collection has always been a key component of business, but with the power of AI we can access data in a conscious and useful way than ever before. The collection is easy, and with digital storage, data is mined for real value. But even with this abundant resource, no amount of research will improve a company without proper strategies and an adaptable crew. 75% of companies struggle to utilize big data even when it’s available to them. But why?

  • Sheer volume: Organizations collect data from an infinite number of sources- social media, business transactions, machine-to-machine- and in the past, there was not technology powerful enough to store this much information
  • Shocking velocity: Big data is delivered in real time with every tap, swipe and click. Artificial intelligence is imperative to handle the incredible analytics speed.
  • Extensive variety: Raw data can be computed to various formats. You can display structured numbers next to text documents, graphs, emails, audio, video, financial transaction record, and more.

Artificial intelligence is the break every company needs. Modern technology is faster and more efficient than ever before. Implementing AI could accomplish a month’s worth of work in just a few moments. Large processors paired with lightning-fast internet means AI systems can take on the volume, velocity and variety generated by big data and translate it into something valuable.

Applying Deep Learning

Deep learning implements machine learning that is much like an artificial neural network that relatively model the way neurons interact in the brain. 

For deep-learning, there are a variety of neural network model techniques (ex: deep reinforced learning) that have evolved more recently as tangible value-cases surface. One of the more compelling applications of deep reinforced learning was in the pharmaceutical and bio-pharmaceutical industry where this modeling technique can be used to optimize chemical reactions. Allowing scientist to reduce the trial-and-error inherently related with some of the research and development activities.  Optimizing the reagent quantities and compositions based on a positive feedback method upon analyzing the resulting outcome. Such platforms are ultimately providing not just granular enhancements in time savings but are leading to faster product-to-market efforts by enhancing various R&D and logistical processes for the pharma and biopharma industries.

As you can see it isn’t what can AI do for your company it is simply a matter of when. AI can apply to so many facets of most any business applying is your choice on what may make the best business case. AI applications:

  • Human Resources
  • Customer Service
  • Operations Management
  • Manufacturing
  • Security
  • Logistics
  • Quality Control
  • Technology Applications
  • Business Process Management
  • ERP
  • Marketing
  • Client Engagement
  • Project Management

Cost & Time Benefit

There are distinct types of machine learning: supervised learning, unsupervised learning, and reinforcement learning- all designed for certain tasks. These neural networks are trainable brains. This AI technology works much faster than a human can and never sleeps. Utilizing this intelligent automation will help your business grow, stay organized, and remain on top of your competition. Your business can save time and money spent on hiring extra employees and outsourcing for special projects.

Quality Results

Repetitive tasks and data processing often come with human error. Why? Humans need rest to re-fuel. It’s easy to make a simple mistake when your tired or hungry. With deep learning, your AI operative doesn’t need rest and there’s no need to worry about mistakes. New information is taken from the web, data inputs, or any source its programmed to, and produces accurate, high-quality results. Your software robots can recognize more data and images, comprehending spoken language, resolving problems and work more efficiently. With basic improvements to perceptive automation, some employees may become concerned about their jobs, but it puts them in a position for growth.

With more innovative machine learning making its way into the workplace, it requires employers to train or hire employee to use the new software. AI will change the workplace as we know it. The technology will take over repetitive job responsibilities and leave workers to focus on more critical tasks.

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Topics: Big Data, Machine Learning, Artificial Intelligence, AI

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