One thing that the movie predicted pretty well was our dependence on technology. Look at us today. We have personal voice-powered assistants to answer any question in a matter of seconds. Self-driving vehicles used to be a dream, but they are pretty much reality nowadays. 

Artificial intelligence advancements took off so quickly that we’re still not aware of all that’s been achieved. This technology is still in its infancy, but it’s getting us far.

We no longer need to imagine a future driven by technology. It’s already here.

How AI Is Being Used Today

AI in Customer Support

Source: Vocalcom.com

You see two online stores that offer the same product for the same price. Which one will you choose? You’re most likely to opt for the one that has a better online reputation, which resulted from a high-quality customer support system. You’ll see what store is better at sending packages ASAP and solving any issues that the customers complain about. If the support system is active 24/7, it will make a huge difference. 

Some of the best websites that sell products, services, or software rely on high-tech customer support systems. They still have representatives to answer the phone and write emails. However, chatbots work as AI customer assistants for answering simple questions.

If you’re checking out a custom essay writing service and you want to know about the deadline, price, or the status of your order, you’ll be able to use a 24/7 live chat to ask a question. In most cases, these simple questions are answered by a chatbot. Since AI is getting so sophisticated in a conversational context, the customers don’t even notice the difference. If a more complex issue arises, they are instantly referred to as a customer support representative.

This is a much quicker and more effective way of handling customer queries. On the other hand check Zypes IT Support in relation to computer networking and IT support.

AI in Marketing

Source: SocialMediaExplorer.com

How many times have you been in awe about Facebook or Google’s ads? It feels like your smartphone has been reading your mind or overhearing your conversations, so it suggests the exact type of product or service you wanted to check out.

No one is listening to your conversations.

AI-powered programs collect data. Whenever you use a website or search for something, they take note. Then, Facebook, Google, and other platforms use this data to serve an ad that really gets your interest. These in-depth insights enable them to develop more relevant marketing campaigns that hit all the right spots. 

Let’s take Coca-Cola as an example. The company constantly analyzes social media content to see how consumers use its products and adjust its marketing strategy accordingly. We’re talking about a huge volume of data that cannot be collected and analyzed manually. Artificial intelligence does that. It delivers reports, and then marketing teams decide what action to take.

AI in Healthcare

Source: InternetOfBusiness.com

This is possibly the most useful advancement of AI that concerns an average person. AI healthcare is no longer science fiction. It’s real, and it’s transforming the way we stay healthy.

 Smartwatches are part of the process. They measure vital signals and deliver feedback. They inspire us to stay active, but they will also inform us about raised blood pressure or irregular heart rates. 

Diagnostics are also more effective thanks to AI. According to the American Cancer Society, false results of mammograms are very common. Artificial Intelligence enables faster and much more accurate review and translation of mammograms. Thus, it reduces the need for unneeded biopsy. 

AI helps doctors and surgeons to make better decisions, too. Predictive analytics technology uses pattern recognition to compare a patient’s condition to a base of big data. It can identify the risk of developing a certain condition and suggest methods of treatment.

AI as a Personal Assistant

Source: FuturumResearch.com

“Hey Alexa, play Jimi Hendrix for me.” 

Amazon’s Alexa and Apple’s Siri are so nice to talk to. They do what we ask with great speed and efficiency. It’s easier to ask Siri to open the calculator on a Mac than to look for the app through all that clutter you accumulated over years of use. 

Voice assistants use a natural language user interface and voice queries to perform different tasks and answer questions. We haven’t seen all that they can do. This technology is already surprising, but it’s still in its early stages of development.

Smart Cars

Source: EconomicTimes.com

Autonomous vehicles make us feel like we’re already in the future. When are they going to float above the ground? Well, we still haven’t reached the Back to the Future stage, but we’ve certainly come far in the automotive industry. 

Self-driving cars are already on the streets. Tesla is the leader in this technology. The manufacturer’s full self-driving feature is expected to be released soon.

An autonomous car is a connected robotic vehicle that senses its environments and navigates through traffic to get you where you’re headed. It requires little human input. Can we please get to the point in the future when driving licenses are no longer needed? 

Self-driving cars bring us to another important implementation of AI in our daily lives: navigation. Even if we have a normal vehicle or we try to reach a place by public transport or walking, navigation software helps us get there through the shortest and quickest directions possible.

Home Robots

Do you remember The Jetsons? This cool cartoon made us dream about robots that would assist with cleaning and food preparation. Well, we have them today. Even if you don’t have a Roomba or an iRobot, you’ve certainly seen one. The AI vacuuming technology had humble beginnings. Today, many people can’t imagine their lives without it. Vacuuming may be a small task, but it means a lot when a device takes care of it on a daily basis. Vacuums aren’t the only robots in people’s homes. AI is also implemented in surveillance, pool cleaning, and kitchen utensils.

Drones

Source: DroneBelow.com

Did you know that Nicola Tesla was the father of drone technology? He had a vision for a radio-controlled boat, which would be navigated from a distance. This is where it all started.

Today, we have drones that film concerts, weddings, and music videos. That's the use that the general audience is most aware of. But not all of us know that drones are also used for delivering small items, surveilling dangerous areas, monitoring wildlife, law enforcement, and aerial combat. They are being used more than we assume.

That’s Not All!

It’s safe to say that artificial intelligence is part of everyone’s life, whether we’re aware of it or not. If you just saw an ad for a product you really wanted, it was delivered thanks to artificial intelligence. If you asked Siri to do something for you, you interacted with AI. 

When we get deeper into the topic, we realize that more impressive implementations of AI are all around us. With its powerful capabilities for machine learning, predictions, and autonomous work, it’s driving our future in a direction we never thought possible. 

Artificial intelligence is still not very advanced. The technology is in its early days, but what matters is that we have a strong foundation to build on. Truly intelligent systems will become more common in the future. They will be able to learn on their own, and they will improve every part of our lives, from research to healthcare to home maintenance. 

Isn’t that the kind of future that we’d all like to live in?

Featured image via Finance.Yahoo.com

A prominent part of medical innovation is the discovery of new diseases, treatments, and medication through an evidence-based exploration known as a clinical trial. Developers and researchers taking part in clinical studies are upheld by high standards imposed by regulatory bodies, making clinical data quality a pivotal component of its success. 

In this article, you'll learn how researchers maintain or improve their clinical data management (CDM) practices with the help of a metadata repository.

What Is A Metadata Repository?

Data is the most significant measure of a clinical trials success. Without science supported by accurate data, a clinical study could fail. Clinical researchers can use a metadata repository to house all types and complexities of data. Essentially, it is a database that stores data about other data.

According to Formedix, building an efficient metadata repository is beneficial in clinical research in many ways, such as building studies faster, improving their quality, and reducing the overall costs of the study build. However, you can only attain these benefits if you use your metadata repository correctly.

With this in mind, here are some ways to manage your clinical trial data with a metadata repository:

1. Choose The Right Clinical Data Repository Software 

Clinical study software assists the entire research from conception to finish, which involve processes such as collection and analysis of clinical study data, metadata management, CRF (case report form) design, and protocol management. For a well-rounded tool for your clinical study, consider choosing from these three types:

• Integrated Clinical Study Automation Software: This type of clinical trial software focuses on automating certain parts of a clinical trial. It is an integrated, cloud-based tool that assists with metadata management, standards governance, and more, with built-in Clinical Data Interchange Standards Consortium (CDISC) compliance and validation features.
• Electronic Data Capture System EDC: An EDC allows users to collect patient data during clinical research. They focus on data collection, analysis, storage, and integration with electronic health records a leading advantage over other software types.
• Clinical Trial Management System CTMS: Lastly, the CTMS software is used for planning and analyzing clinical trials end-to-end. Although they cater to the entire clinical research process, a CTMS is often integrated with the first and second software types. 

Regardless of which type you choose, keep in mind that they're all automated and work well with metadata repositories. Therefore, you can achieve improved data quality, clinical trial efficiency, and fewer resources consumed. 

2. Establish Governance

A successful clinical trial should be governed by standards, principles, and regulations to achieve quality studies, prevent misconduct, and promote good practice. A critical part of data governance is metadata management. 

Some challenges in clinical data management are due to some ill-fitting organizational standards. Building a seamless governance process offers understanding and control of your clinical trial workflow, increasing the compliance and accuracy of your clinical metadata. 

A huge benefit of data governance is its customizability for your company's process, allowing researchers to create an organizational life cycle for standards that evolve over time. Since organizational measures are kept in one place, they can also be reused for new clinical studies to fit research-specific requirements. Reusing these resources can help maintain data quality and consistency. 

3. Improve Your System's Traceability 

The strength and reliability of a clinical study highly depend on the source data and reproducibility of clinical processes conducted. How is this specific piece of information derived? Where did you store the new data? An essential step of building an excellent clinical study is possessing traceability, which means you should trace your data on the entire workflow, including its origin, location, and application.

Using a metadata repository is an excellent practice in maintaining and improving clinical data traceability. Document statements can be drawn back to the raw data when information is stored and tracked in this database. 

Meanwhile, the pharmaceutical landscape uses blockchain technology to improve the traceability of medications in the clinical trial supply chain. This allows patients and associated individuals to join the network to record data, moving logged information to appropriate systems with access to view, edit, and store the specific data. Aside of enhancing traceability, using the blockchain mechanism in clinical trial supply chains boosts the study's validity and assures completeness of the entire process. 

Key Takeaway 

Streamlining a clinical trial process isn't as easy as you might think. Thanks to technological advancements like the design and implementation of metadata repositories, healthcare institutions can perform safer and better-quality clinical trials that appropriately target diseases and health conditions. By implementing these practices into your own clinical studies, hopefully, you'll be able to deliver more progressive solutions to health challenges in the present and future.