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Who is an ETL Developer?

An ETL developer performs the Extracting, Transforming, and Loading processes. They are involved with extracting business data from a diverse source system and then transforming the data (such as calculations, combining it, applying, and ensuring quality) and loading the transformed data into a data warehouse system in a safe environment.

Extraction: Extraction implies getting data from the source system and making it readily available (consolidated) in the needed data system.

Transforming: This step succeeds the extraction stage, which requires appropriately structuring the extracted raw data and then converting it into a quality form.

Loading: This is the last stage of the ETL process. It is the stage whereby the ETL developer oversees the loading of the transformed data into the required data source, mostly called the data warehouse system.

Skills required for ETL Developer

An ETL Developer is expected to have a good grasp of data analysis, design and programming skills, especially a broad knowledge of programming languages such as XML, JavaScript, and SQL.

General skills needed to become an ETL developer

A great organizational ability: This is needed to keep the projects at hand well-arranged and structured.

A high Problem-solving ability: ETL development comes with several unexpected challenges and problems. An ETL developer must have a thing for propounding solutions to problems on time.

Important Roles and Responsibilities of an ETL Developer

Here are the various roles played by ETL developers:

ETL Process Planning Management: At this stage, the ETL designer/developer is expected to work on the following:

Give a clear view of the ETL process and determine the data processing boundaries.

Gather and develop ETL tools and see to their implementation.

Test run all the needed tools and be sure they work pretty well.

Define business requirements: The business requirement will determine the volume of data extracted from different sources, data models, quality of the data, and as well as figuring out the best storage medium required for the data warehouse needed.

Determine data storage needs: The volume of data handled differs from company to company, so an ETL developer determines the amount of data the company deals with.

Building a data warehouse: Having a strong and secure data warehouse is very important for every business. It is the responsibility of an ETL developer to design a secured data warehouse where data can be efficiently loaded based on the company’s needs and requirements.

Ensure Data Quality: It is very important that data quality is maintained throughout the ETL processes. To achieve this, the ETL developers ensure that everything is put in place at the ETL transformation stage to eliminate errors and fix unstructured and unorganized data extracted from diverse sources at the extraction stage. The ETL developer also ensures that Data is loaded into the warehouse system and meets the business need and standards.

ETL Developer Salary

The average salary of ETL developers is rewarding. The senior position roles for experts and highly experienced ETL developers offer a greater salary than other IT roles.

In the United States, ETL has been considered a much more lucrative role because the computer science field is so massive in the states. The average ETL developer salary in the USA is $114,974 per year or $55.28 per hour. Beginner-level positions start at $99,000 per year, while experienced professionals in this field make up to $306,500 per year.

ETL Learning Material

ETL can be learned on several platforms. While many fancy their chances of enrolling in a physical class, others prefer online training. Different resources and training materials exist, such as the ETL certification course and the ETL testing course videos. ETL can be learned in the following formats.


Taught by top companies and universities.

You can apply your skills with hands-on projects.

Learn on your own schedule.

Course videos and readings.

Graded quizzes and assignments.

You will get a shareable Certificate upon completion.

Data Warehouse Fundamentals for Beginners is an online course that helps you to learn the techniques needed to build a data warehouse for your organization. You will learn to apply the key design principles of dimensional data modeling.

You’ll learn how to work with data warehousing architectures and dimensional data structures by learning all the best practices and techniques covered in this online course.


5 hours of on-demand video.

1 article.

Full lifetime access.

You can access it on mobile and TV.

Certificate of completion.

ETL Developers Books: This book is curated to guide aspiring Data Warehouse (ETL) developers to get ready experience in building and maintaining data warehouses.

This book is well-detailed, with dimensional modeling tools needed by an ETL developer

Application of ETL

There are several reasons for the use of ETL in business, it includes:

It supports data transformation verification as well as the required calculations, rules, and procedures.

A well-built and organized ETL system is important to the execution of any data warehouse project.

ETL process presents a platform to compare and analyze data using the source and target warehouse.

The adoption of ETL helps to carry out complex transformations and requires a storage data medium.

With ETL, it is possible to move data into a data warehouse and then transform and convert it to diverse formats using the same system.


ETL development refers to all processes migrating data from a multiple source system into a safe warehouse.

The full form of ETL developer is (Extracting, Transforming, and Loading processes) Developer.

An ETL developer is responsible for determining the storage needs of a business and the volume of data involved.

The job description of ETL developers suggests that they are responsible for data flow validation, creating and building a secured database warehouse that meets a given company’s needs and standards.

An ETL developer must be to load data and be proficient in valuable technical skills such as SQL, JAVA, XML, and DOM, among others.

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Java Developer Roles Responsibilities Skills

Java Developers are the wizards of the digital realm, casting their expertly crafted code to bring innovative applications to life. They possess a unique combination of technical acumen & creative flair, weaving together lines of code to create seamless and intuitive user experiences. 

Java Development is not Only About the Code!

Java Development is like composing a symphony, each line of code a delicate note is woven together to create a harmonious masterpiece. Developers are the conductors, leading the performance of the virtual orchestra, directing the flow of information & bringing the digital world to life.

The power of Java lies in its versatility, it adapts to different types of projects, from small-scale applications to large enterprise systems. It is a language that can handle high-performance, high-availability, and high-scalability requirements, making it a popular choice for developing robust and reliable software.

Java Development is not just about writing code it’s a combination of creativity, logic, and problem-solving. Developers must be able to understand complex business requirements and translate them into elegant and efficient software solutions. They must constantly adapt to new technologies and frameworks, like a constant evolution of the language, to stay current and remain competitive in the ever-changing digital landscape.

The beauty of Java Development is that it allows developers to bring their wildest ideas to life, build something out of nothing, to shape the digital world as they envision it. They are true tech innovators, pushing the limits of what’s possible and creating the software that will shape the future.

Java Development is like Building a Castle out of Legos but Instead of Colourful Bricks

Developers use a powerful programming language, Java. With Java, developers can construct anything from basic programs to large-scale enterprise applications. The language is known for its “write once, run anywhere” paradigm, allowing for the creation of cross-platform compatible code. Java Developers can harness the full potential of this versatile language to build robust and scalable systems that can handle millions of requests per second.

Java Developers are the Architects of the Digital World

They are responsible for designing and building the structures that underpin the modern world. They play a crucial role in the development and maintenance of a wide range of software applications, from the web and mobile apps to enterprise systems and cloud-based services.

Roles of a Java Developer

They are the backbone of any project and are responsible for the design, development & implementation of new software features and systems.

They are the problem solvers, responsible for identifying and resolving complex technical issues that arise during the development process.

They are collaborators, working closely with cross-functional teams of designers, developers, project managers, and QA engineers to ensure projects are delivered on time and to the highest standards.

Responsibilities of a Java Developer

Writing efficient and high-quality Java code that conforms to industry standards and best practices.

Designing and developing scalable and maintainable software systems, using a variety of technologies and frameworks.

Collaborating with cross-functional teams to deliver innovative solutions that meet customer requirements and exceed expectations.

Continuously learning & staying up-to-date with the latest developments in Java and related technologies.

Skills of a Java Developer

Strong understanding of core Java concepts such as object-oriented programming, data structures & algorithms.

Experience with popular Java frameworks such as Spring, Hibernate & Apache Maven.

Familiarity with web development technologies such as HTML, CSS, JavaScript & JSON.

Knowledge Relational Databases, SQL (Structured Query language) and NoSQL.

Understanding of the principles of software development, including agile methodologies & continuous integration/delivery.

Java Developer Salary

A Java developer’s salary depends on the kind of projects they are working on, the technologies they are proficient in, their role, and the scope of their responsibilities. All things considered, your experience counts and can earn you a competitive compensation package. Your employment location may also have an impact on your compensation. The minimum salary for a junior Java developer in India is around 2,50,000 rupees, whereas senior or experienced Java engineers make significantly more.


A Java Developer is a true artist who, just like an artist with a brush and canvas, uses Java and its related technologies to bring their imaginative solutions to life. They are not only technically proficient but also possess a creative mindset which enables them to push boundaries and deliver truly exceptional software. They are the backbone of the digital world, shaping the way we interact with technology & improving the lives of people through the applications they build.

Overall, being a Java Developer is about creating something out of nothing, using the power of code to bring ideas to life, and solving problems that improve the lives of people. They are true technology craftsmen who shape the digital world with their unique & special skills.

What Is Sdet? Full Form, Meaning, Role And Responsibilities


SDET (Software Development Engineer in Test) in testing is an IT professional who can work equally and effectively in both development and testing roles. SDETs take part in complete software development process as well as software testing process. SDET professional’s knowledge is entirely focused on testability, robustness and performance of software testing and development process.

They are also able to play a contributory or reviewer role in the creation of designs for production software.

In this tutorial, we will learn-

Difference between SDET and Tester?

SDET Manual Tester

Knows the entire system start to end Limited knowledge about the system

SDET is involved in every step of the software development process like

Designing, development, and testing.

QA is only involved in the testing life cycle of the software development process.

Highly skilled professional with development as well as testing knowledge. Software tester is only involved in preparing and executing the test cases

SDET can participate in test automation tool development and may make it for generic use. Not expected to develop test automation tools or frameworks.

SDETs need to perform duties like performance testing, automated generation of test data, etc. Only testing related task will be performed by the tester.

Know requirements and guidelines for the products No such knowledge expected from QA professionals.

When do you need SDET?

Today organizations are looking for a professional who can take part in software development. At the same time, he should also handle testing of the developed software. That’s why hiring SDET helps them as they can work for developing high-performance code or designing the testing framework.

Benefits of SDET professional:

SDETs professionals can automate the acceptance test by leveraging their coding skills

These professionals deal with end users or customers and their experiences. They already possessed engineering skills so they can also think like a developer.

Extensive code coverage through unit testing

Can build, deploy, run & manage the application individually

Influence the development, program management, & design teams on technical implementation and user scenarios

Industries in need of SDET

There is a trend among companies to adopt new technology and methodologies. Therefore, SDET software professionals are highly on demand. Software developer engineer in the test are mainly needed in the following fields:

Technical and Nontechnical skills

Following are some essential nontechnical skills for an SDET:

Communication skill

A SDET must have excellent verbal and written communication skill. Testing materials like test cases, plans, test strategies, bug reports created should be easy to read and comprehend.

Time Management & Organization Skills

An SDET job is very demanding especially during the release of code. A software tester must efficiently manage workload, have high productivity, time management skills

GREAT Attitude

To become good Software Development Engineer in Test, you must have a GREAT attitude. You should able to upgrade your technical skills with the changing technologies. Your attitude should have some level of independence. So that, you can take ownership of the task allocated without too much supervision.


To enjoy success in any IT professional, you must have a significant degree of the passion for it. A SDET should have a passion for testing, development, and designing.

Below given are some Technical skills expected from SDET:

Knowledge of C#,.NET, Java or other programming languages.

Experience of working “AGILE + DevOps” process management methodology.

SDET should have knowledge about various test method & corresponding tools like MS Test, NUnit, TestNG, Selenium WebDriver, etc.

SDET should have exposure to Behaviour Driven Development.

Able to find bottlenecks and thresholds in existing code with the help of automation tools.

Understanding of Object-Oriented Design

What are the roles and responsibilities of an SDET?

SDET should able to perform Test Automation and setting up frameworks on multiple application platforms like Web, Mobile, and Desktop.

Investigate customer problems referred by the technical support team.

Create & manage bug reports and communicate with the team.

Able to build different test scenarios and acceptance tests.

SDET needs to handle technical communications with Partners to understand client’s systems or APIs.

SDET also work with deployments teams and resolving any level issues for the system.

SDET should also able to set up, maintain, and operate test automation frameworks.

The above are key skills and responsibilities of SDET. They may vary with different companies.


The salary structure of a SDET varies from company to company. The average annual salary for a Software Development Engineer in Test (SDET) is ₹6,92,692 in India and $74,291 in the USA.

An SDET is also given health insurance, gratuity, and other perks.

Typical Work Day

On a daily basis, you will be busy understanding project documents, creating & executing test cases, reporting, and testing bugs. You will also put your inputs to designing team, suggest development team and other team building activities.

Career Progression

Your career progression as a SDET in typical CMMI level 5 company will look like following but will vary from company to company


A SDET professional is a mix of developer as well as a tester who has exposure to project management. This all in one type of skill set make the SDET jobs more challenging and highly demanding in the current market.

What Is The Role Of Documentation In Quality Management?

Documentation is stressed as an integral part of quality management in this article. When it comes to quality control, consistency in processes and procedures, as well as thorough documentation, play crucial roles. Documents such as policies, procedures, work instructions, quality plans, and records are discussed in this article as they pertain to quality management.

The significance of document control in quality management and its influence on the whole process is also emphasized, as are the benefits that accrue from using it to meet both regulatory and industry standards. The importance of writing down lessons learned and taking corrective and preventative measures is also covered. Additionally, the article discusses training and communication strategies for successful documentation, as well as the challenges and solutions for effective documentation in quality management.

Importance of documentation in quality management

When it comes to Quality Management, consistency in processes and procedures relies heavily on documentation. In order to maintain a high level of quality control, Quality Management systems rely heavily on documentation.

An ISO study found that improper documentation was the leading cause of non-conformities discovered during quality audits. Inadequate documentation was found to be the cause of 15% of all non-conformities in the study.

In addition to lowering the likelihood of defects and rework, thorough documentation can aid in the speedy detection and correction of quality issues. It also helps make sure workers have all the information they need to do their jobs effectively and efficiently.

Types of documents used in quality management

Quality Management relies on a variety of documents to guarantee that final outputs are up to par. Organizations can use these documents to ensure uniformity, monitor progress, and share relevant data with key constituents.

Policies, procedures, work instructions, quality plans, and records are some of the most important documents in Quality Management. Quality management policies determine the overall course and objectives, while quality management procedures spell out the specific actions to be taken. Quality plans describe how quality will be ensured throughout a project or process, while work instructions provide more detailed guidance on how tasks should be carried out. Records, like inspection reports and test results, are kept to document proof of adherence to quality standards.

Companies can use these records to make sure their goods and services are up to par, and to spot any flaws in their processes. Customers, regulators, and employees are just some of the audiences who benefit from receiving quality-related information, and they can all be reached through well-documented processes.

Document control and its impact on quality management

The term “document control” is used to describe the method used to keep track of documents from creation to destruction. To guarantee that all of an organisation’s processes and procedures are documented correctly and consistently, document control is an essential part of quality management.

There will be fewer opportunities for mistakes or discrepancies to creep in when everyone in the company has access to the same, up-to-date data thanks to diligent document control. It also aids in documenting and communicating any changes to processes or procedures so that everyone is aware of the modifications and can adjust their work accordingly.

In addition to aiding in compliance with regulatory requirements and industry standards, and making both internal and external audits easier, good document control is essential. Organizations can gain the trust of customers, suppliers, and regulatory agencies by showing that they are following standard operating procedures and protocols through meticulous record-keeping.

Standard operating procedures (SOPs) and their role in quality management

Important documents that detail the actions to take in order to accomplish a given task are called standard operating procedures (SOPs). Standard Operating Procedures (SOPs) play a vital role in Quality Management by guaranteeing that products or services are consistently provided that meet or exceed customer expectations.

Standard operating procedures (SOPs) are used to record the usual way of doing something, down to the tools, workers, and supplies required. This ensures that all parties follow the same procedures and produce the same results.

Standard operating procedures help businesses guarantee their procedures are consistent, repeatable, and scalable. This is significant because it facilitates the reduction of mistakes and variability, both of which enhance the quality of the end product or service. Standard operating procedures (SOPs) can also be used to spot trouble spots and uncover ways to boost effectiveness and productivity in a given process.

Documenting corrective and preventive actions (CAPAs)

Quality management relies heavily on the documentation of corrective and preventive actions (CAPAs). When problems or issues arise with a company’s products or services, corrective and preventive actions (CAPAs) are implemented.

CAPA documentation includes noting the nature of the issue, the steps taken to fix it, and any precautions taken to stop it from happening again. Having a written record of the steps taken by the company to enhance the quality of its goods or services is crucial.

The ability to monitor and assess the quality management processes, pinpoint problem areas, and implement solutions to prevent recurrences depends on the thorough documentation of Corrective and Preventive Actions (CAPAs). It also aids businesses in keeping track of their quality management efforts and meeting applicable regulations.

Challenges and solutions for effective documentation in quality management

The role of documentation in quality management cannot be overstated. Maintaining processes, procedures, and quality standards is easier with well-documented processes. Quality management documentation presents its own unique set of challenges, however, and these must be overcome.

Making sure the documentation is complete and correct is a major obstacle. This may take a considerable amount of time and energy from the documentation team. Establishing who is responsible for what and how often documentation is reviewed and updated is crucial.

Another difficulty is making sure all of the quality management documentation is readily available and understandable. This includes using straightforward language and making sure the document is straightforward to use.

Organizations can implement solutions such as software tools to automate documentation processes, training for employees on best practices for documentation, and a streamlined review and approval process for all documentation to meet these challenges.

Training and communication strategies for successful documentation in quality management

Quality management relies heavily on complete and accurate documentation. It aids in the efficient and accurate documentation of processes and procedures. It’s more challenging to find and fix problems without complete documentation.

Strategies for both training and communication must be implemented for quality management documentation to be successful. Employees can learn the value of documentation and how to do it properly through training. Template, software, and doc management system training fall under this category.

The ability to effectively communicate is also crucial. A successful documentation process relies on clear and concise communication between all parties involved. One way to accomplish this is by encouraging and facilitating honest and open communication amongst team members, as well as setting clear expectations for documentation.

Bob Mansfield Reduced Role To Focus On Chips, Senior Execs Given New Responsibilities

Apple executive Bob Mansfield’s unexplained departure from Apple’s leadership team is due to the long-time engineer’s desire to focus on chipset design plus future products and less on executive duties, according to sources with knowledge of the change.

As part of Mansfield’s leave from the executive team and role change to “special projects” under Apple CEO Tim Cook, Mansfield’s former duties as Senior Vice President of Technologies have been split between two Senior VPs: Hardware chief Dan Riccio and Operations head Jeff Williams, according to these sources.

Dan Riccio will now oversee antenna design for Apple’s mobile devices in addition to hardware engineering for the WiFi components in all of Apple’s products. Interestingly, Tim Cook primarily brought Mansfield out of his mid-2012 retirement to assist in the transitioning of Apple’s antenna and wireless teams over to Dan Riccio.

As Senior Vice President of Technologies, Mansfield was also in charge of Apple’s special projects engineering teams. In his new role, sources say, Mansfield will continue to contribute to special projects (such as the iWatch), and Jeff Williams will assist in overseeing management for these groups.

With Riccio in charge of antenna design, overall hardware engineering for all iPhone and iPad products will likely be increasingly seamless. This is because all components of the products will be engineered under one roof instead of between both the Technologies and Hardware teams. Perhaps Williams’ contribution to special projects is key for the future manufacturing of these products. Williams is the executive in charge of ensuring Apple’s suppliers and factory partners are building Apple’s products up to standard.

Mansfield, in his new role, will actually be fulfilling mostly what Cook said he would as Technologies SVP:

Bob Mansfield will lead a new group, Technologies, which combines all of our wireless teams across the company in one organization, allowing us to innovate in this area at an even higher level. This organization will also include all of our semiconductor teams, who have some very ambitious plans.

With the new role, Mansfield will focus on chips while being able to distribute executive and management duties to Riccio and Williams. As a wealthy, long-time executive who made an attempt at retirement last year, the reduced role with increased focus on actual interests makes sense. It is also a fitting compromise (instead of leaving the firm altogether) for a company that has been paying millions of dollars per month to retain Mansfield. The role is also logical as Apple has “very ambitious plans” under Mansfield to turn away from Intel chips in Macs.

With Mansfield’s connection to chips and the distribution of other teams to other executives, it seems likely that Apple has no imminent plans to instate a new Senior Vice President of Technologies. Indeed the role itself was created specifically for Mansfield last fall.

According to a source familiar with the former Technologies team, there has been a lack of formal internal communication regarding the reasoning behind the management shift. However, the company did make the new executive roles clear to these employees. Even with the lack of communication, sources say that the change is not unprecedented. Over the last couple of months, Mansfield is said to have been increasingly focused on chips (and some aspects of wireless) while delegating his other teams to other executives.

Sources with knowledge of Mansfield’s line of thinking also say that the executive would very much like to retire on his new California coast “castle.” Though, even with that in mind, these people believe that Mansfield will never fully separate himself from Apple. The executive is dedicated to the company and would like to contribute to Apple in some fashion even in retirement, these people say. Perhaps a former Apple manager sums up Mansfield’s thinking best: “[Mansfield] really has the entire company’s best interests at heart.”

Top graphic created by Michael Steeber

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What Is Generative Ai And Why Is It Important?

Definition: What is Generative AI?

As the name suggests, Generative AI means a type of AI technology that can generate new content based on the data it has been trained on. It can generate texts, images, audio, videos, and synthetic data. Generative AI can produce a wide range of outputs based on user input or what we call “prompts“. Generative AI is basically a subfield of machine learning that can create new data from a given dataset.

If the model has been trained on large volumes of text, it can produce new combinations of natural-sounding texts. The larger the data, the better will be the output. If the dataset has been cleaned prior to training, you are likely to get a nuanced response.

OpenAI Playground

Similarly, if you have trained a model with a large corpus of images with image tagging, captions, and lots of visual examples, the AI model can learn from these examples and perform image classification and generation. This sophisticated system of AI programmed to learn from examples is called a neural network.

At present, GPT models have gotten popular after the release of GPT-4/3.5 (ChatGPT), PaLM 2 (Google Bard), GPT-3 (DALL – E), LLaMA (Meta), Stable Diffusion, and others. All of these user-friendly AI interfaces are built on the Transformer architecture. So in this explainer, we are going to mainly focus on Generative AI and GPT (Generative Pretrained Transformer).

What Are the Different Types of Generative AI Models?

Amongst all the Generative AI models, GPT is favored by many, but let’s start with GAN (Generative Adversarial Network). In this architecture, two parallel networks are trained, of which one is used to generate content (called generator) and the other one evaluates the generated content (called discriminator).

Basically, the aim is to pit two neural networks against each other to produce results that mirror real data. GAN-based models have been mostly used for image-generation tasks.

GAN (Generative Adversarial Network) / Source: Google

Next up, we have the Variational Autoencoder (VAE), which involves the process of encoding, learning, decoding, and generating content. For example, if you have an image of a dog, it describes the scene like color, size, ears, and more, and then learns what kind of characteristics a dog has. After that, it recreates a rough image using key points giving a simplified image. Finally, it generates the final image after adding more variety and nuances.

What Is a Generative Pretrained Transformer (GPT) Model

Google subsequently released the BERT model (Bidirectional Encoder Representations from Transformers) in 2023 implementing the Transformer architecture. At the same time, OpenAI released its first GPT-1 model based on the Transformer architecture.

Source: Marxav /

So what was the key ingredient in the Transformer architecture that made it a favorite for Generative AI? As the paper is rightly titled, it introduced self-attention, which was missing in earlier neural network architectures. What this means is that it basically predicts the next word in a sentence using a method called Transformer. It pays close attention to neighboring words to understand the context and establish a relationship between words.

Through this process, the Transformer develops a reasonable understanding of the language and uses this knowledge to predict the next word reliably. This whole process is called the Attention mechanism. That said, keep in mind that LLMs are contemptuously called Stochastic Parrots (Bender, Gebru, et al., 2023) because the model is simply mimicking random words based on probabilistic decisions and patterns it has learned. It does not determine the next word based on logic and does not have any genuine understanding of the text.

How Google and OpenAI Approach Generative AI?

Both Google and OpenAI are using Transformer-based models in Google Bard and ChatGPT, respectively. However, there are some key differences in the approach. Google’s latest PaLM 2 model uses a bidirectional encoder (self-attention mechanism and a feed-forward neural network), which means it weighs in all surrounding words. It essentially tries to understand the context of the sentence and then generates all words at once. Google’s approach is to essentially predict the missing words in a given context.

Google Bard

In contrast, OpenAI’s ChatGPT leverages the Transformer architecture to predict the next word in a sequence – from left to right. It’s a unidirectional model designed to generate coherent sentences. It continues the prediction until it has generated a complete sentence or a paragraph. Perhaps, that’s the reason Google Bard is able to generate texts much faster than ChatGPT. Nevertheless, both models rely on the Transformer architecture at their core to offer Generative AI frontends.

Applications of Generative AI

We all know that Generative AI has a huge application not just for text, but also for images, videos, audio generation, and much more. AI chatbots like ChatGPT, Google Bard, Bing Chat, etc. leverage Generative AI. It can also be used for autocomplete, text summarization, virtual assistant, translation, etc. To generate music, we have seen examples like Google MusicLM and recently Meta released MusicGen for music generation.


Apart from that, from DALL-E 2 to Stable Diffusion, all use Generative AI to create realistic images from text descriptions. In video generation too, Runway’s Gen-1, StyleGAN 2, and BigGAN models rely on Generative Adversarial Networks to generate lifelike videos. Further, Generative AI has applications in 3D model generations and some of the popular models are DeepFashion and ShapeNet.

Limitations of Generative AI

While Generative AI has immense capabilities, it’s not without any failings. First off, it requires a large corpus of data to train a model. For many small startups, high-quality data might not be readily available. We have already seen companies such as Reddit, Stack Overflow, and Twitter closing access to their data or charging high fees for the access. Recently, The Internet Archive reported that its website had become inaccessible for an hour because some AI startup started hammering its website for training data.

Apart from that, Generative AI models have also been heavily criticized for lack of control and bias. AI models trained on skewed data from the internet can overrepresent a section of the community. We have seen how AI photo generators mostly render images in lighter skin tones. Then, there is a huge issue of deepfake video and image generation using Generative AI models. As earlier stated, Generative AI models do not understand the meaning or impact of their words and usually mimic output based on the data it has been trained on.

It’s highly likely that despite best efforts and alignment, misinformation, deepfake generation, jailbreaking, and sophisticated phishing attempts using its persuasive natural language capability, companies will have a hard time taming Generative AI’s limitations.

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