The Power Of AI Across Industries

During the last few years, it is hard to imagine of a more buzzed around— or highly competitive — technology than artificial intelligence. As more businesses are pushing for new ways to implement deep learning and data science and reap the benefits of robotics, an AI boom is obviously not coming: it’s already here. If your company or organisation has been looking for realistic, efficient ways to implement AI in your business, there may never have been a better time. Here’s how companies employ AI in three sectors to make a tangible difference in their business.

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AI does not fall under a single technology category. It is instead the culmination of advanced technology. Companies are beginning to harness these technologies ‘ capabilities to enhance their competitive advantage. Recent advances in AI technologies have begun to change the way major business markets work, and they are only growing in speed and scope. To give you insights into the realities of AI’s actual impacts and possibilities, let’s take a look at some key industries that are being revolutionized by AI technologies.

e-commerce

While users keep pushing back toward pop-up ads and “creepy” ad monitoring, marketers turn to AI as the solution to building personalized product recommendations and optimizing shopping interactions in ways that feel natural, not invasive. Organizations that are at the forefront of this emerging technology are using AI and deep learning to enhance image search and suggestions on “You Might Also Like” to both anticipate what a customer wants but also help them extend their palette. And it is not just the front-end experience that is being enhanced: AI also makes inroads for fraud detection and security in e-commerce, inventory management, supply chain optimization and more. 

The internet of things is here, and technologist Taylor Romero is first in line to bring these new advances into his wife’s barbershop & clothing store. Brick-and-mortar stores are in competition with online retail, but might the internet save his family shop? Join Taylor has he pulls back the curtain on the future of IOT-integrated retail.

Finance

AI has the potential to change the way information is handled by banks. Banks have been using robotic process automation (RPA) to process structured data in areas such as arbitration and restructuring. Therefore, financial institutions will be able to use AI to complete quarterly earnings reports and reconciliations between businesses. They will play an active role in the policy roles as well. AI technologies will help organizations to complete the real-time financial analysis, asset allocation and forecasting. It affects how financial advisors and investment firms handle prospective customers.

We’ve seen fully automated bot beats us in Go, one-on-one Poker and Dota II, now what’s going to happen for trading financial markets? Listen to an Deep Learning trading agent that over-performs us in trading FX markets. Marshall has been trading FX markets for 5 years. As a Master in Finance graduate from Brandeis International Business school, he combines his insight in financial markets with a passion for machine learning and expertise in programming, striving to build the first game-changing A.I. trading system to disrupt the markets.

Healthcare

It is not difficult to imagine a world in which scientific riddles and potentially insolvent illnesses are a thing of the past, and healthcare companies see AI as the key to unlocking solutions in unfathomably massive data sets. Of example, organizations like Owlet use smart garments to capture hundreds of thousands of hours of data on child health at night and transfer the data to the cloud. 

We need tools that can help us – both clinicians and patients – make better healthcare decisions. Yet in order to do so, those tools need to “think like we do” … and the key to natural intelligence is not simply X better than Y, but rather sequences of decisions over time. To best assist us, our clinical computing tools should approximate the same process. Such an approach ties to future developments across the broader healthcare space: cognitive computing, smart homes, cyborg clinicians, and robotics.

Transportation

It’s impossible to talk about AI in transportation without talking about self-driving cars — it’s a multi-billion dollar market for the automotive industry as well as a challenge that continues to be difficult to solve technically and ethically. Uber uses autonomous delivery trucks as a safe self-driving test case; highways account for only 5 percent of U.S. roads, making delivery driving a more readily feasible option than consumer applications. Additionally, AI may also hold the key to improving traffic management and maximizing public transport. And as one Stanford study projected, AI is likely to impact the performance of city infrastructure by providing improved statistical behavioral simulations of the activities of individuals.

What if traffic flowed through our streets as smoothly and efficiently as blood flows through our veins? Transportation geek Wanis Kabbaj thinks we can find inspiration in the genius of our biology to design the transit systems of the future. In this forward-thinking talk, preview exciting concepts like modular, detachable buses, flying taxis and networks of suspended magnetic pods that could help make the dream of a dynamic, driver-less world into a reality.

Start Small

The development of a fast output benchmark is key, according to Aryafar. The shortest, fastest machine learning model that you can apply to produce to create correlation is often the one that will deliver actionable results and insights. Furthermore, some of AI’s biggest players make it easier than ever to get started in machine learning, from no-code to simple APIs.

Making ethical practices a priority

Prioritizing and maintaining public safety is vital to AI’s continued success. While many organizations are trying to incorporate AI committees, interdepartmental debates on corporate best practices and AI guidelines remain critical to the appropriate use of AI, including ensuring that those responsible for using the system are on the same page. 

Acquire the best and brightest

As the displicine expands, AI tasks are still taking shape, so Humpherys advises ensuring the team is in a state of constant learning. Skills are perishable, and before it ever starts, siloing your data scientists and experts in machine learning will impede your innovation. Moreover, having a diverse workforce for AI is vital to ensuring that algorithms have no built-in prejudice from the outset. 

AI is a new frontier, and sometimes it may seem easier not to engage with it at all than grappling with complex ethical issues. But as more companies create feasible, creative use cases and extend our conceptions of what we can do with AI, it will become more difficult to ignore.

Key Takeaways

Does this mean that humans should be afraid that artificial intelligence technology would make them obsolete? Yes, but it does mean that it is now time for companies, enterprises, and experts to get involved and help plan the future of work to maintain or develop their competitive edge. Putting the skills of AI to work for you will allow you to make better decisions, make more efficient use of resources, reduce risk, and innovate faster. Those who embrace AI technologies and learn how to use it now will become tomorrow’s leaders.

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