Our time on earth has been brief but full of human advancements, especially, throughout the last couple of centuries. Particularly after the Industrial Revolution. But as the industrial revolution, jump-started the mechanical world. The Internet jump-started the digital realm, which is currently learning the ropes of AI technology. Good or bad, it is here to stay and to revolutionize the way we view and create content.
Table of Content
- What is Generative AI Content?
- Benefits and Disadvantages of Generative AI
- Best Way to Use Generative AI?
- 7 Famous AI Tools
What is Generative AI Content?
Generative AI refers to a form of artificial intelligence that can generate diverse content forms like text, images, audio, and synthetic data. AI technology is much older than you think, it was first used in the 1950s to play video games like checkers. But now it can do special things like writing books, SEO blogs, creating art forms, and more.
Generative AI content is created through machine learning of existing data. Additional prompts can also be added, and metrics can even be set to use Generative AI for a specific industry.
Benefits and Disadvantages of Generative AI
Before one can learn to level up their content creation with Generative AI. You must first understand what generative AI’s capabilities are.
Let’s start with the benefits of using Generative AI:
This was one of the first things anyone including me would notice when using Generative AI creation tools. Whatever is asked of the AI-generating tool is done in a matter of seconds. A task that would take a human being 4 hours can be done in less than 2 minutes through AI. One such example is that of chatGPT, ask it a question and it will answer right away. Ask it to write a blog and it will write it in under a minute. However, the usefulness of what it has produced can be questionable at times. Sometimes, you will get exactly what you wanted, and other times you might have to tweak a little or a lot.
2. Lowers Cost
Even if your AI can not produce exactly what you need, it can assist you in helping you create something that can. Good content requires research and fact testing, something AI can do for you. It can also edit your existing documents for grammar, punctuality, and passive voice errors. This all helps you do more with less. Meaning, that you don’t need to hire as many employees as you once needed to. So, company owners can focus on quality and hire better employees when on a tight budget.
3. Aids in Creativity
Writer’s block or artist block is a real phenomenon, something anyone in the field has suffered from. During this period productivity can often become limited, but here is where generative AI earns its reputation. AI uses existing data to create unique ideas, which can be a form of inspiration for the creatives. Moreover, AI can also help you detect if your unique ideas are unique or not. If you were to start searching the web yourself, it may take you months to find something relevant to your idea. AI can do this in a few hours, minutes, or even seconds depending on your niche.
4. Ensures Quality
While human beings are prone to making silly mistakes, Generative AI has been trained not to. Generative AI content is created according to the basics of English grammar, ensuring that your documents are grammatically accurate. Moreover, it ensures an even tone throughout the created content. Moreover, since the AI models are trained on almost the entire internet’s information. It can provide examples and facts about faucets you never knew existed.
Now let’s look at some of the downsides of using AI.
1. Data Inaccuracy and AI Hallucinations
It is important to understand that though Generative AI technology is robust, it is still fairly new to the market. More than often, AI is unable to distinguish fact from fiction. There is so much data on the internet to discover through, that machine learning can often be based on inaccurate data. Obviously when identified these inaccuracies will be prompted out. But for now, users need to fact-check Generative AI-created documents. For example, company chatbots when asked about the company’s revenue would randomly pluck a number from thin air saying something like $13 million. While the actual profit could be way south of $500,000 instead. Famous chatbots like ChatGPT would take credit for a quote produced by a famous author. So a person has to keep their guard up when dealing with AI Generative content.
2. Legal Issues (Copyright Infringement)
Though this is a rare phenomenon, but is still a distinct possibility. It is important to remember that AI is based on existing databases and prompts. They rarely produce something unique, but actually paraphrase existing information from a variety of sources. The introduction of chatGPT to the public demonstrated how it can be used dishonestly for academic and workplace purposes. A study by Harvard Business explained how this is an active issue that can get worse with time. There are also chances that AI can gain access to personal files like private cloud data by accident. This can potentially put the user at risk of intellectual property infringement or privacy violations. But I would like to remind the users that this is a rare phenomenon and you can easily avoid it, by just paying attention.
3. Difficult to Use for Some
Most people lack the understanding of using Generative AI and are unable to properly reap its benefits. This can often result in the system being impractical for many. Small businesses for that reason may avoid its integration in existing systems. Free tools like ChatGPT and Dall-E have constraints. Dall-E lets users create 50 images in the first month of its use, then limits you to 15 a month. ChatGPT often suffers from downtime, during peak use hours and is prone to AI hallucinations. Paid services are usually better, and take information from real-time. Currently, there are so many AI companies, some specific to certain industries, that it gets difficult to choose the right option. The testing versions for these apps barely contain enough services to properly test before you pay. Users are currently not 100% comfortable relying on Generative AI.
4. Quality Filter Missing
Generative AI models are usually trained using unlabeled data. However, these sources can often be unreliable and untrustworthy. Data collected is a combination of data matching and mixing, with some paraphrasing. Leading companies such as OpenAI, Facebook, and TikTok enlist contract workers to undertake tasks like data categorization and the creation of training data. This practice gives rise to concerns regarding the consistency and trustworthiness of the data, which ultimately reflects in the generated outcomes. These challenges are yet to be addressed. For this reason, people are often unable to monetize AI-generated content, and their content is usually banned under copyright infringement. These problems need to be addressed, and parameters and filters need to be implemented to mine usable data. AI models need to be trained based on quality metrics which will be quite challenging to produce.
Best Way to Use Generative AI?
The key to using Generative AI properly is to remember that it is a tool to aid you in creating something. It is not a replacement for expert employees. People expecting too much from Generative AI is the main problem. They expect AI to do their work for them and in that case, rarely supervise what it is producing.
Here is how you can reap the maximum benefits of generative AI Technology:
1. For Marketing Content
Content marketing be it a copy or a graphic requires constant creativity. But whenever you feel a dry spell coming in, AI can always help you stay at the top of your game. Generative AI is regularly being used to create text, images, videos, and audio. For example, AI can create blog posts for you, content for social copies, research hashtags, write product descriptions, and create very realistic artwork. It can produce voices for voiceovers, and can even help predict market demand patterns.
1.1 Limitations and Utilization
Always remember that a credible team member and field expert is there to review the AI generative content. Remember AI has its limitations, for example in product descriptions, it may provide you with a base that you can use to create a final description. Obviously, AI does not have any form of affiliation with your products or clients. Hence it will only provide visuals, content, and audio that is generalized. And an expert can mold it into something useful later on. This form of Human and AI collaboration will help you market with smaller budgets and in given time constraints.
2. Customer Service & ChatBots
Since Generative AI is trained on a database, you can easily train it on a specific industry. Moreover, the model can also be trained on specific company-related commands. You can utilize this form of generative AI on websites and on text support. Certain companies are also experimenting with AI assistants that talk and mimic human emotions. This will 100% improve your response time and will remove most of the clutter for you.
2.1 Limitations and Utilization
There will definitely come a point where AI might not be able to handle complicated or personalized queries. Hence there should always be an option where if need be customers can contact human support teams.
3. Email Responses and Email Marketing
Those working in email marketing have to deal with a bulk of emails. A majority of those emails are cold calls, which is where AI-generated emails really work their magic. While your team handles all the conversion-based emails, AI can help bring them to you. AI can write templates that are more personalized and include the companies or person in question’s name. Also, AI can also incorporate images, audio, and videos into emails. Not only that, AI can also interact with your CRM data, so you can easily view client history and data.
3.1 Limitations and Utilization
An employee must always be available to review the emails generated by AI. It’s important to do so to ensure that it does not contain anything offensive to new cultures and to maintain the accuracy of data. Being too nonchalant can have embarrassing consequences.
4. Creating Websites and Coding
Now AI on its own can not create a fully functioning website. But it can aid developers in doing so and doing it quickly. AI can help you detect errors in coding in quick time, which may take developers days and weeks to manually do. It can ensure that the code is written and not copied and pasted by your developer. It can help you build databases, align pages, and work on backend functionalities. Creating code using generative AI is achievable through a method called neural code generation. This approach entails training a neural network on an extensive collection of code instances. Subsequently, the fine-tuned network can be employed to produce code that exhibits similarities in both structure and functionality to the examples it was trained on.
4.1 Limitations and Utilization
Remember to have an expert employee handle this type of AI generative technology. Only a seasoned professional will be able to identify the mistakes AI can potentially make. Consider a full-stack developer for this purpose.
7 Famous AI Tools
Here are some common and widely used AI tools.
An AI model developed by OpenAI that can answer questions and produce humanized responses. Very dynamic and has multiple uses, based on prompts.
Created by OpenAI, this model can create images and artwork based on received prompts.
3. Google Bard
Trained on the PaLM large language model, this is Google’s answer to OpenAI’s chatGPT. It can answer and create content based on queries.
Created by a San Francisco-based company, Midjourney can create visuals and artwork based on prompts received.
Still in development by Elon Musk, little is known right now, but a lot is expected.
6. Llama 2
A virtual assistant that is similar to ChatGPT 4.
7. Github Copilot
This is an AI-powered coding tool.
Generative AI is here to stay and to constantly improve upon its use. These tools are particularly useful for marketing firms, students, social media influencers, and coders alike. As time progresses we will see more functionalities come into play and more use cases for AI. However, it is important to be aware of its limitations. So as to be able to properly utilize it.