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Artificial intelligence (AI) has become a phenomenon that has gathered increased traction over the last few years. Information technology itself has advanced at a rapid pace, as the average smartphone has more computing power than the spaceship that took the first man to the moon, according to ZME Science.
This has caused a global movement toward information technology, both personally and commercially. It is no wonder that the first trillion-dollar company here in the U.S. is based on internet-connecting devices. Now, the next wave seems to be artificial learning — machines that have the ability to use data in an effort to replace unnecessary human tasks.
This article has been written with the purpose of answering specific questions or problems that a business may encounter.
How Do I Increase Data Entry Efficiency?
Data entry is often a dreaded task, becoming somewhat monotonous and tedious. Manual loading is often a cause of dramatic inefficiencies, as human intellect is wasted on a task that requires nothing more than a simple mechanical process.
Machine learning has been applied in an effort to reduce the need for human interaction with data. With the use of algorithms and particularly optimized calculational technology, data entry has been changed from a tedious task to a seamless automated experience.
How Do I Reduce The Overall Spam In Communications Applications?
Having the confidence that communications programs are operating efficiently is important for any business. The reduction of spam is important for both efficient communications with internal and external parties and network health.
Certain spam filters now come with machine learning capabilities, which adjust to the latest spam attempts. Thus, mail servers are protected from clutter and viral attacks. Google boasts one of the best performing software with 0.1% spam rate thanks to a unique machine learning model.
How Can I Improve My e-Commerce Offering?
The internet provides a unique way through which businesses can access potential customers. Many have seen the almost infinite possibilities dating back as early as the 1990s when internet-based business models were overvalued by investors.
Today, e-commerce has become something of a no-brainer. Some startups have even foregone a physical location in favor of having an online presence.
Recommendations are based on artificial intelligence. It is most commonly used on sites such as YouTube and Netflix. One sees this in the recommended selection of videos and movies that these brands offer. However, the utility of the tech need not stop there, as websites can be altered in accordance with customer needs, increasing the chances of repeat purchases or the sale of complementary goods or services.
Can Artificial Intelligence Change the Medical Sector?
Larger pools of data allow AI to apply a diagnostic prescription to a variety of tasks. Naturally, given a data source sufficient in size, artificial intelligence may become increasingly better at providing medical help to those who require a quick diagnosis.
In the near future, there may be a way to synergize smartphone devices and medical AI in an effort to create a mobile version of the technology. This allows patients to track their symptoms, get a diagnosis and perhaps even a prescription for certain ailments. One example highlighted on mHealth Intelligence is how mobile technology "aims to make lab-on-a-smartphone a common tool for detecting and treating diseases."
How Can I Better Marketing Endeavors?
Marketing is often made difficult due to the unpredictability of potential clients. Moreover, discovering whether those clients are worth the acquisition cost, in the long run, is another variable entirely.
Enter AI, as the advanced analytics and predictive capabilities allow marketers to leverage statistical data in order to target clients with increased accuracy. This aids in market segmentation, customer lifetime value and churn prediction.
With the help of machine learning, the results are increasingly effective, achieving a better cost-benefit ratio over time.
Can AI Help In Finance?
Due to the high-data nature of financial institutions, the collection and usage of such information may often become overwhelming. When paired with a need for an accurate historical record and a highly quantitative data stream, the task seems even more daunting.
Machine learning has been applied to this endeavor with varying success. However, the future seems bright for the marriage of AI and financial data. Many are even predicting automated underwriting, and algorithmic trading already exists in some corners of the market.
How Can AI Help In Manufacturing?
The efficiency of production is the name of the game in the manufacturing sector, as many relatively small economical processes add up into decreased average costs. This is the underlying premise of the industrial revolution.
AI serves to find inefficiencies in a factory, locate overall weaknesses in the chain of production and pinpoint where technological innovation may be needed. It has also been effectively used to determine how best to maintain the working area, thus keeping the flow of production fully operational at all times. Improvements through the use of sensors, historical data and environmental analysis, machine learning technology can be exponential.
Can I Use Big Data For Image Recognition?
In short, the answer is yes. Big data has become an important tool that fuels analytical technology, taking it to the next level. For those in the tech industry, image recognition may be an important tool that takes an app or platform to the next level.
Certain companies such as Facebook and Instagram have already employed a version of it, and Apple smartphones lay claim to an elementary version of the technology.
With the dramatic switches in the commercial world — an environment that is increasingly dynamic — it is important to minimize the number of inefficiencies that come from non-automated operations. In the long run, AI has the potential to replace many cost-heavy operations, which may result in entirely new business models.
First published on Forbes
