Featured image by Gerd Altmann from Pixabay
As we push forward in an evolving digital landscape, artificial intelligence is one of the most important technologies changing industries around the world. Because of the disruptive nature of AI technology, it powers numerous new business opportunities. Let’s talk about the benefits of AI-powered business solutions and how they are keeping businesses competitive.
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AI Assistant Technology
Among the most familiar uses of artificial intelligence in our daily lives are AI-powered assistants. Alexa, Siri, and Google Assistant are good examples. These assistants provide users with information at home by way of smart speakers or while on the go on mobile devices.
However, AI assistants have more uses than just aiding consumers in their everyday lives. They can also assist businesses with managing their operations. They can help automate complex workflows, assist with the hiring process, improve sales and customer service experiences, and more.
Real world problems are the target of modern AI solutions for enterprise. Customer service AI chatbots are becoming more humanlike, leading to significant improvements in the customer service industry. Shopping assistance is also in demand. This feature can suggest items to customers based on their shopping history and other data. The realistically conversational nature of these interactions continues to improve each year.
The advances in machine learning over the past few years have resulted in many beneficial applications of AI assistants. Computer vision has also improved, enabling AI assistants to better recognize objects. Natural language processing has resulted in far more humanlike interactions between AI assistants and their users.
A thought-provoking future for retail is the concept of autonomous checkouts. One of the prime examples of this is Amazon Go, a store without cashiers. Guests walk in, grab what they need, and leave. AI technology then charges their cards for the amount they owe. This technology is powered by computer vision and a network of IoT sensors. Based on the information from cameras and the sensors, AI is hard at work tracking what customers leave the store with.
There are several reasons why autonomous checkouts are in the works. For one, fully autonomous or semi-autonomous stores require less staff. Oftentimes during busy hours of operation, retail stores need to request assistance from other team members on the sales floor to assist at checkout. Because they are busy helping guests check out, there are fewer workers on the floor stocking products and taking care of other store needs. Autonomous checkout reduces this challenge substantially. This allows workers to focus on other aspects of the store’s operations.
However, this technology is challenging to implement on a larger scale at the moment due to the steep requirements in IoT infrastructure and processing power. Smaller-scale versions like a smaller section of a store or a vending machine-like device may be more feasible for small to mid-scale businesses. Regardless of scale, these kinds of projects require a great deal of expertise in machine learning.
No-Code AI Platforms
Artificial intelligence platforms can be difficult to develop. This is because they can often require deep technical knowledge in data science and experience creating machine learning algorithms. However, no-code AI platforms are emerging that allow even smaller-scale businesses to utilize artificial intelligence to their advantage. Thanks to a much faster time-to-market, lower costs, and simplicity, no-code AI solutions are an attractive option.
However, it’s important to note that even with no-code AI platforms, the process of creating the solution still shares some key elements with traditional AI development. For example, no-code AI programs still require data collection and analysis. The higher the quality of data, the better the results.
Generative Adversarial Networks
Creating unique images, text, sound, and other content lies typically exclusively in the realm of human creativity. However, generative adversarial networks (GANs) disrupt this idea by enabling AI programs to create unique content of their own based on training data.
GANs work by generating content and then analyzing that content to see if it fits criteria set by the training data. Through creating and eliminating unwanted results, the program can generate unique images, text, and more.
There are a number of real-world applications where GANs can be utilized. For example, generating hundreds of unique images such as human models wearing a variety of clothing is a simple task for a GAN program.
Artificial Intelligence and the Metaverse
The development of the metaverse offers another set of challenges to overcome, especially if we adhere to the visionary view that the metaverse could be a far more immersive version of the internet than the one we rely on today.
One of the largest challenges is finding a way to more fluidly create AR and VR experiences. Tracking the head and hands is easy, but tracking an entire body is much harder. Producing large digital environments is also difficult at scale. But artificial intelligence can make these tasks much easier.
Simply put, AI has the potential to make VR experiences more immersive, providing a number of fresh opportunities for businesses. These might include VR/AR shopping, social media, enhanced telework, virtual events, and more.
The Future of AI for Businesses
It’s important for business owners to think about where artificial intelligence may go next and how it will evolve in the future. Since companies around the world are leveraging this technology today to remain competitive, it’s fair to conclude that artificial intelligence will continue to grow in use and as well as to advance.
It’s also important to consider that other technologies that are closely related to AI, such as data science, will also continue to grow and evolve. Since AI is reliant on high quality data, data science and data collection technologies will also improve. One of these technologies is the Internet of Things. Through IoT sensors, artificial intelligence applications can receive real-time data in manufacturing, retail, and other settings.
More importantly, the future of AI will be determined by how entrepreneurs choose to implement the technology. Often, innovations are made through combining multiple technologies together in new, unique ways that disrupt the market. It’s up to businesses now and in the future to decide what they want the future of AI to look like.
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About the Author
Oleksii Tsymbal, Chief Innovation Officer at MobiDev, contributed this article.
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