Connect with us

Artificial Intelligence (AI)

Leveraging the Power of AI for Digital Asset Management

Leveraging the Power of AI for Digital Asset Management. Digital asset management is a process to store, organize, retrieve, and share digital assets.

mm

Published

on

Leveraging the Power of AI for Digital Asset Management

Artificial Intelligence (AI) technologies are in the process of integrating into every field of work, including marketing workflows. AI, however, is not a replacement for a human workforce.

Instead, AI capabilities support your work by automating repetitive tasks, thus enabling marketers and developers to do more in less time. In this article, you’ll learn how AI improves digital asset management (DAM) tasks, and how to implement AI in DAM ecosystems properly.

1. What Is Digital Asset Management?

What Is Digital Asset Management

Digital asset management (DAM) is a process you can use to store, organize, retrieve, and share digital assets. DAM uses a centralized content library that is accessible by employees, contractors, clients, and stakeholders. Assets stored in a DAM include images, audio, video, documents, and original files.

2. AI and Digital Asset Management

Artificial intelligence (AI) is the use of machine learning to perform tasks that were previously only capable of manual human effort. You can use AI technologies to automate and facilitate a variety of functions within DAM systems. AI can help organizations and teams retain control over significant amounts of data with less effort.

3. AI Technologies That Power Dynamic DAM Systems

AI Technologies That Power Dynamic DAM Systems

Several AI technologies can be incorporated into DAM systems. The most commonly integrated technologies are covered below.

a) Smart Tagging

A tag is a piece of metadata that you use to classify and identify assets. Cards are used for searching, tracking, and sorting assets within your DAM. Smart tagging is the use of AI to apply these tags. It is based on API services offered by organizations such as Microsoft, Google, and Amazon.

These services use image recognition to determine the content of media and suggest appropriate tags. Image recognition technologies scan images to identify specific characteristics associated with a category or classification. AI then weighs these characteristics to determine the most likely content of the picture.

Some DAM systems enable you to incorporate business intelligence and marketing data to categorize assets with tags better. This can allow you to distribute content across multiple media channels automatically reliably.

b) OCR

Optical Character Recognition (OCR) is an AI technology you can use to identify text inside images. You can use it to extract text from images and convert that text to an editable document. Extracting text from images is not a new capability, but previously it could only be performed on images with defined structure or layout. OCR uses the same image recognition strategies that are used for smart tagging.

Modern AI, however, enables you to extract text more dynamically. This is possible because AI algorithms can learn from feedback supplied from previous text extractions. This feedback is applied to future removals, refining the sensitivity and accuracy of the OCR algorithm.

c) Natural Linguistics Processing (NLP)

NLP is a field of AI that deals with how computers process and analyze linguistic information. It is commonly used in speech to text conversion and chatbots. In a DAM system, you can use NLP to extract speech content from video or audio files. This content can then be used to create transcripts, subtitles, and captions. It can also be used as a guide for speech removal from files.

NLP capabilities incorporated in DAM systems can also enable you to serve content according to requests in a variety of languages. This can be accomplished through translations of search requests.

4. Best Practices for Implementing AI in a DAM

When incorporating AI into your DAM systems, there are several best practices you should follow. Below are the essential methods to start with.

a) Keep AI-Generated Metadata Separate

You should find a way to identify AI metadata separately from user-generated data. This enables you to verify the accuracy of your AI more efficiently and to ensure that tags are appropriate. By keeping metadata separate, you can ensure that your tagging is as reliable as possible and that user-generated tags are not automatically overwritten.

b) Track AI Like Your Users

You shouldn’t provide users unfettered access to your DAM; this is as true for AI. You need to be able to track the actions of your AI services and vendors to ensure the integrity of your data. Tracking can also help you identify when AI is not working correctly or if it is causing conflicts with other integrations or users.

c) Ensure That You Can Filter AI-Generated Metadata

You should be able to filter whether or not AI-generated metadata is used for searches, content serving, or analytics. Some users may not trust AI-generated data or may prefer to use only specific AI sources. Likewise, users may wish to use only AI-generated metadata created after an algorithm has been refined.

d) AI-Generated Metadata Should be Convertible

Many DAMs enable you to convert embedded metadata into a regular asset attribute, such as a keyword. This ability should extend to AI-generated metadata. Convertibility can help you ensure that AI-generated information remains available even if AI services are removed or changed. You may also wish to set protocols that automatically convert metadata once enough users have approved it.

e) Use Feedback to Improve Your AI Accuracy

Any AI services you use should improve over time. This could mean that algorithms are refined with each analysis or suggestion or that algorithms are periodically retrained. Sources of feedback can include manual audits, accumulated user verification of accuracy, or asset use statistics.

Check if you have specific tags that are consistently rejected, or assets that you know are relevant that aren’t’ being returned. Both of these situations can indicate a fault in your AI and can help you target areas for improvement.

5. Conclusion

AI enhances DAM systems with capabilities that save time and enable personalization. By delegating repetitive tasks to the machine, you can free up your time and focus on sophisticated and creative jobs. In many cases, once you set up an organization system, the AI mechanism will take care of the grunt work of classifying the assets. You can then set up a dynamic process that delivers personalized, and sometimes hyper-personalized, content to users.

Gilad David Maayan is a technology writer who has worked with over 150 technology companies, including SAP, Samsung NEXT, NetApp, and Imperva, producing technical and thought leadership content that elucidates technical solutions for developers and IT leadership.

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

Artificial Intelligence (AI)

How To Get Started With Artificial Intelligence

Artificial Intelligence, among other emerging technologies, is becoming central to the continuous technical revolution, and it is evolving. Therefore it is important to learn about the fundamentals of Artificial Intelligence to understand how it changes and affects different industries.

mm

Published

on

Why learning Artificial Intelligence is the best choice

Artificial Intelligence, among other emerging technologies, is becoming central to the continuous technical revolution, and it is evolving. Therefore it is important to learn about the fundamentals of Artificial Intelligence to understand how it changes and affects different industries.

It’s no wonder, then, that the AI industry is full of job openings — so many of them, in reality, that the area now fronts a different challenge: There are too many jobs roles and few fitted applicants. On the upside, that means it provides a virtually assured and well-paying profession for those who have got the right skills.

In this article, we wish to know all about AI, how to get started with Artificial Intelligence, why learning Artificial Intelligence is the best choice, and how to get an ideal job.

1. What is Artificial Intelligence?

Artificial Intelligence strives to imitate and transcend the ability of the human mind using nothing but devices.

The fundamental purposes of Artificial Intelligence are:

  • Expedite up repetitious methods by using humanoids or machines instead of human being
  • Out-think human minds through training and memory
  • Identify patterns and make judgments swiftly and efficiently

Artificial Intelligence strives to develop devices that conceive and reason instead of operating in a comparatively bound space with pre-built systems, methods, and results. Smart Artificial Intelligence devices identify patterns and memorize earlier events and learn from them, making each following judgment more intelligent, rational, and more original.

How To Get Started With Artificial Intelligence

AI is a significant model change in advanced computing and requires a profoundly systematic and logical way to devise machine systems that conceive and learn. In simple words, develop humanoids that are not just robots.

And though it may seem strange, AI abilities are all over the place. A few examples of Artificial Intelligence systems include speech, face and fingerprint identification (available on all smartphones and home devices), email spam blockers, virtual assistant (Siri, Alexa), customer assistance using catboats, Expert systems, game playing, an intelligent humanoid automaton, etc.

3. How to Get Started with Artificial Intelligence

Step-1: Pick a topic you are interested in

Initially, choose a topic that is interesting for you. It will assist you in staying motivated and committed in the training process. Concentrate on a specific problem and seek a solution, rather than just aimlessly reading about everything you can get on the internet.

step-2: Get a prompt solution

The aim is to get any basic solution that includes the query. You require an algorithm that will process information into an acceptable structure for machine learning, prepare a simple model, give a decision, and assess its working.

step-3: Enhance your simple explication

Once you have a simple explanation, it is time for some creative skill. Work on improving all the elements and assess the modifications to conclude whether these changes are worth your effort and time. For example, sometimes, developing preprocessing and data refining gives a tremendous gain on investments than advancing a training model itself.

Step-4: Share your Solution

Publish your solution and share it to get assessed. This will help acquire relevant guidance about your study from other intellects and add up the initial experience in your portfolio.

Follow steps one-four for other queries as well.

Pick other problems and follow the same steps for all tasks. If you have commenced with tabular data form, choose a query that includes operating with pictures or unorganized text. It is also vital to study how to form enigmas for machine learning accurately.

Finish a Kaggle competition

This competition enables you to examine your abilities, working on the same problems several other engineers work on. You will be asked to undertake various ways, picking the most efficient explications. This competition can also prepare you for collaboration as you communicate with people on the panel, exchanging your thoughts and learning from others.

Apply machine learning professionally

You have to decide what your career aims are and build your portfolio. If you are not yet ready to apply for machine learning jobs, seek more projects that will make your portfolio effective.

Artificial Intelligence (AI)

4. Why learning Artificial Intelligence is the best choice

The understanding of Artificial Intelligence initiates lots of new openings. It is sufficient to comprehend the basics of this technology to learn how machine tools work. As you study more about AI, you get an opportunity to grow as a developer who will build high-level AI applications. There are infinite opportunities in this domain.

For those who desire to start learning Artificial Intelligence, It has many options available. The internet enables everyone to enroll in online classes. Some of the courses focus on students who already have a specific level of technological expertise and converge on coding. In contrast, other Artificial Intelligence and machine learning online paths will help even those who do not have knowledge and beginners in the programming and engineering field.

5. How to take a job in Artificial Intelligence?

Humanoids may be arriving for some tasks, but they will create new job roles as well. Here are some ways to enhance your application, whether you are operating in the domain required to fill.

1. Check out the best online courses for ai and machine learning

Similar to many tech-based areas, there are numerous online courses for ai and machine learning topics, letting someone learn more about the area as a whole or gain more specialized knowledge. Some options offer ai certification online that can reinforce a resume.

2. Join outside organizations

Acquiring from others in the field can assist you in enhancing your abilities, so check out social meetups. Getting associated with organizations that allow data scientists to work on the new data, exercising and improving the skills while studying from their companions.

3. Add Quality industry experience.

Many of the in-demand AI jobs positions are technical by nature, but understanding how to interpret those advancements to other businesses or customers is crucial for any business.

4. Put a habit of reading a lot.

Those working in the Artificial Intelligence field should always be studying, and reading is a way to do that. Read a lot. Not just about your domain but all the related sectors.

5. Be prepared to grasp

AI is a swiftly advancing field, so be ready to examine as many experiences and opportunities in AI as feasible.

Keeping up to date on the most advanced research in AI is very important. There is so much progress befalling each day. This may involve seeking opportunities inside the current working place or outside. Make sure that you do not get restricted into one area.

Apart from having the standard skill-set and education, these are additional methods to be a powerful applicant for these profitable jobs.

Conclusion

Since its beginning, Artificial Intelligence has been performing a requisite role in the technology sector, advancing the quality of living across multiple enterprises. And speaking about what tomorrow endures, it is difficult to foretell. However, the way AI is developing, It appears the innovations in the following times will be fabulous.

These inventions will only be prosperous when there are well-qualified people and serve in Artificial Intelligence. Suppose you have a desire to work with this wondrous technology. In that case, it is time you check out the online classes for Artificial Intelligence which can assist you in growing an expert in the Artificial Intelligence field.

Continue Reading
Advertisement
Advertisement
Business11 hours ago

How To Maximize Cloud Computing For Your Business

Business4 days ago

Getting Better ROI On Your Salesforce Marketing Cloud With Ready To Use Solutions

Automotive4 days ago

What Are Parking Management Systems? What is the Importance?

Gadgets4 days ago

Best Smartwatch For Gifting in 2021

Internet5 days ago

App Marketing Strategies: Crucial Things You Should Know

Business1 week ago

Technological Inventions You Can Write Your Essay About

Automotive1 week ago

Maruti Car Insurance Renewal in 5 Easy Steps Online

Business2 weeks ago

3 Ways to Create a Successful Hybrid Work Model

Business2 weeks ago

7 IT Enhancements For A Top Performing Business

Workforce3 weeks ago

How to Efficiently Improve Employee Attendance and Workforce Management

Advertisement

Trending