By: Kevin Gardner, Data Floq


Artificial Intelligence: Why it's Evolving Faster than Ever

In the 1950s and 1960, experts predicted that artificial intelligence would grant computers human-like capabilities in the 20th century. In reality, AI’s growth veered in a direction that didn’t resemble human-like thinking, a trend that continues today. In spite of this, AI has advanced dramatically over the past few years, and it’s improving at a pace not seen since the early days of computing. Here are a few reasons why AI keeps getting smarter.

More Data, More Demand

AI isn’t getting smarter in a vacuum. Necessity leads to innovation, and the explosion in collected data is demanding more powerful and smarter AI systems. Big Data has been one of the major trends in recent years, but users quickly found that the data they collected simply couldn’t be processed effectively using older AI systems. Advances in machine learning, in particular, have allowed computers to comb through data and extract valuable information.

Similarly, neural networks, which have been theorized since the 1940s, have advanced rapidly over the years. The Internet of Things and cloud computing depend heavily on AI systems to fuel automation, predictive maintenance and machine learning. As these trends show no signs of slowing down, it’s generally believed that the AI boom is still in its early stages.

Cooperative Development

In the past, companies competed through their proprietary AI systems. Today, however, many have moved more toward open solutions. This follows a general trend; open source software now dominates many areas, and, alongside cloud computing, open source is becoming preferred across a range of fields. Many of the most popular AI tools are free and open source.

For example, Spark ML is widely used both in academics and in industry. Contributors, both paid and volunteer, are fueling growth in popular AI frameworks. Spark, for example, has nearly 1,800 contributors maintaining a code base of more than 1.4 million lines. The value of these contributions is difficult to measure, but it’s hard to see how proprietary solutions can remain competitive as more enterprises and academic institutes turn toward open solutions.

A New Frontier

In the past, data science was generally viewed as somewhat dull for those without a strong love of mathematics, and many talented individuals and entities paid it little attention. As the field matures, however, a growing number of software developers and IT experts are turning toward AI in general. Data science is now at the forefront of modern computing, and being able to analyze data and separate the signal from the noise is an exciting field to be in.

Furthermore, AI demands varying types of expertise. Mathematicians are needed to ensure algorithms are correct, and IT professionals make sure systems are able to handle the seemingly insatiable demand for networking and computational power. Not all of this interest is purely due to intrigue in the field itself; recent findings show that demand for data scientists is booming, and developers with the right skills can earn excellent salaries right from the start.

Powerful Capabilities

Companies looking to invest in AI in the past often had to pay for expensive servers and other equipment. The rise of cloud computing, however, makes it far easier to tap into powerful computational capabilities, letting companies of all sizes experiment with AI at a relatively low cost. Furthermore, major cloud providers offer numerous solutions for AI, making deployment easier as well. It’s worth noting that major cloud platforms are among the leaders in developing new AI technologies. All of the major providers have an interest in artificial intelligence and contributing their work to open frameworks benefits them by letting others offer improvements.

Although AI hasn’t brought the type of change speculated in science fiction of the past, it’s increasingly being viewed as the new frontier of modern computing. Where this future leads is difficult to predict, but there’s no doubt that interest will be high for the foreseeable future.

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