In this day and age, “artificial intelligence” is a pretty household term, with the AI powered technology that is in your hands, like Siri in your phone, or on your countertop, like Google’s smart speaker, Google Home.
Each of these devices is powered by extensive research and artificial intelligence, and the research relies on data to create reliable and human compatible devices. The data used in this research can be genuine data collected from a number of sources, or it can also be synthetic data.
This begs the question: does synthetic data improve artificial intelligence, or weaken its abilities to be as “intelligent” and reliable as it is? The short answer is yes, synthetic data does very much improve artificial intelligence, and several fields are noting this and directly taking advantage of it to assist in their respective fields and the daily tasks involved.
Using synthetic data in artificial intelligence has the ability to fill in the gaps of datasets that stem from raw, real data. This allows the AI powered technology being researched and created to perform reliably across the board, even in the rarest of circumstances. Synthetic data could look like the creation of a “fake” medical case that isn’t actually in the true dataset, but is absolutely a possibility and needed in the AI’s system for recognition and problem solving when used in the medical field.
With the use of synthetic data, AI powered technology in several fields benefits the respective fields’ ability to broaden cases they can handle and the reliability of the way they are performed.
Here’s what will be covered in this article:
Synthetic data essentially is exactly how it sounds: not real, made up. Contrary to what your instincts about artificial intelligence might say, it’s actually a necessity to artificial intelligence. The reality for a lot of lab workers, marketers, and the like is that the real data they have gathered only captures a small bit of what they need for the technology to work the way it is meant to.
A helpful example of this practice that makes the whole concept easier to understand is the creation of self-driving cars. To test and vamp up artificial intelligence systems in self-driving cars, scientists and engineers rely on synthetic data. The car must be able to accurately respond to a plethora of different situations, like traffic and weather conditions, pedestrians, speeds, stoplights, and so much more.
It is near impossible to have a complete dataset that perfectly executes these situations, and to try to capture each of them for the AI system to recognize would take way too long to be worth it. Introduce synthetic data, these made-up scenarios and every possible way they could happen, and you have the ability to “train” artificial intelligent technology to be able to respond to each of these scenarios as well.
To gather this synthetic data, scientists, engineers and even users themselves really only rely on a computer that generates fake data or manufactured data. Some scientists use machine-based learning systems that are presented with the actual real data, and then learn the data well enough to create a synthetic version of it that is free of the inevitable hiccups that come with real datasets.
This synthesized data is then used to make artificial intelligence much more accurate, reliable, and useful for a variety of situations and users. The industries that usually benefit the most from using synthetic data are the medical and healthcare fields as well as financial services. With the large span of data covered, AI technology is better prepared for pretty much any circumstance there is out there. Data that is algorithmically created is also usually a lot more reliable, stable, and error-free, so the AI technology has no room for errors or incomplete datasets.
As summarized previously, the great gift that comes with this synthetic data is how it makes already powerful technology into something that goes much farther than human abilities. Artificial intelligence is the combination of several intelligent human beings, becoming an intelligence unique only to artificial intelligent technology. Pair that power and ability with synthetic data that covers every possible base, and the system is pretty foolproof.
So what exactly does that mean for specific businesses or fields who rely on data and benefit from recent artificially intelligent technology?
The medical field is one that is being incredibly impacted by this recent progress point in artificial intelligence. Already a field that has been using and growing from AI powered technology, having AI technology that has also been fine tuned using synthetic data is a pretty significant advancement.
Synthetic data used in AI technology designed for medical and hospital use can look like quite a few different things. Data gathered from real patients can only cover a limited spectrum of possible diagnoses as well as the signs and symptoms that can lead to that diagnosis. With synthetic data, a computer generates the infinite possibilities of symptom presentation, abnormalities in scans and testing, and the subsequent diagnosis that comes of them.
A recent and relevant example of how this synthetic data that is powered by artificial intelligence is when this Michigan neurology team increased their ability to recognize cancerous brain tumors while in the operating room from 68% to 96%, nearly perfect.
They were able to take data from other institutions and combine it with their own, as well as create a computer-generated dataset that was then used to aid in the diagnosis of brain tumors and cancers in patients undergoing surgery. The AI machinery used was able to increase the accuracy and rate of findings, making the process significantly smoother and successful for neurosurgeons and further proving the advantages of synthetic data in artificially intelligent tech.
There is also an upward trend of robotics teams and engineers using this synthetic data in their research and inventions, like the self-driving cars that are gaining popularity. With the ability to use computer generated data, these teams are able to move faster and more efficiently with their products and are able to have a more successful, broadened horizon for what those products can do.
As the popularity grows, the future of artificial intelligence in a broad range of fields are becoming more and more keen on using it in their own work as well.
With the knowledge about using synthetic data in conjunction with artificial intelligence, several different fields and areas of expertise are experimenting with synthetic data within their own technology.
As the research has shown synthetic data’s abilities to outshine the limits of real and gathered data, companies are reaching for the computer generated datasets to help improve their technology and consequently their services and workloads.
Ranging from marketing agencies, to security, social media, robotics, and even human resources departments, there are several industries turning the promising benefits of training smart tech using synthetic data. Without the confinements of only their personal gathered raw data, the synthesized data permits them to be able to create a smarter and more versatile smart system for their tech.
Using synthetic data on its own or in addition to the real, raw data that industries, providers, and workers have gathered opens a whole new world in artificial intelligent technology. Synthetic data has become recognized as the game changer that it is, and more and more industries are turning to using it themselves to further improve their technologies. As synthetic data improves the success and reliability of artificial intelligence, it’s becoming a no-brainer to include it in several industries. The future possibilities are endless!
