Artificial intelligence startups are in the shortlist of the most promising ones. The solutions powered by this technology allows for solving usual tasks in unusual but more effective ways. What’s more, there is an opportunity most developers would like to take advantage of – using a quite innovative AI API for their projects boost. OpenAI makes it possible, and in this article, we will explain how to use their API for your future software.
What Are Open AI and GPT-3?
Before we will find out how to use Open AI, let’s draw a clear line between OpenAI and GPT-3 since these two terms are often mixed up.
OpenAI is a research company that is engaged in studying the capabilities of artificial intelligence and looking for ways to use it for the benefit of humanity. The project was created by Elon Musk and other innovative entrepreneurs. The core mission of the organization is to develop such practices and approaches to artificial intelligence that will help coping with modern challenges (like data hacking, for example), and at the same time, prevent other companies and research institutes from using AI for malicious purposes.
GPT-3 (Generative Pre-trained Transformer), in turn, is a quite powerful machine learning algorithm that is shared via API, and enables developers to use it in their smart models programming. To date, GPT-3 is one of the smartest ML algorithms. It is capable of solving such tasks that just a few years ago, could be solved exclusively by a human. In some cases, the skills of the model go beyond the ones of the human, making it quite a demanded tool in AI powered project development.
GPT-3 Possible Use Cases
What can you do with GPT-3? Below are some use cases that you may take for your project inspiration and user experience boost.
- Text writing and storytelling. The times when artificial intelligence learns to create engaging interesting texts and stories is not that far off – it is already here. For example, The Guardian has already published a text generated by GPT-3. And here is a Better Writer project – a Grammarly like tool that is able to suggest content generation ideas as well.
- Translation. This is one of the most powerful features of the GPT-3 model. While machine translation isn’t an innovation, most of the translations apps and websites still require human check to edit generated texts. But this is not the case with GPT-3 since this tool learns from the previous experience, catches the context, and generates the most accurate translation an ML algorithm is capable of.
- Code writing. One of the Goals of Open AI is to create a program that can create other programs. And GPT-3 already knows how to create code by transforming English into CSS, JavaScript, and SQL.
- Answering questions. GPT-3 may also work as a personal assistant. Powered by advanced speech recognition capabilities, it can understand your voice commands and perform them. Here is one more innovative example – two AI models powered by GPT-3 talk about becoming humans.
- Music creation. GPT-3 is a rather creative machine learning model. For example, it may generate some music and become quite a helpful assistant for music creators, producers, and singers. Jarvis can be an option for this purpose.
- App design. Another amazing ability of GPT-3 is its design creation. All you need to describe is the element you want to receive (for example, a button with a call to subscribe to your newsletter) and the algorithm will create a snippet of the required code.
- Ideas generation. Generating new ideas can be a mind-blowing process but when GPT-3 comes to the fore, this task becomes easier. After analyzing huge data arrays on the current market environment, trends, and users’ sentiment, the algorithm makes a smart prediction-powered conclusion on what ideas will be demanded very soon.
- MVP development. Combining all the functions above, GPT-3 becomes quite a powerful but still affordable tool for MVP software development. It may generate a code that will power the front and back end of your future solution, and all that remains for you is to test your MVP with your future users.
What Kind of Apps This Technology Is Suitable For?
Considering such an impressive list of use cases, GPT-3 startups will be able to develop quite a lot of creative and useful ideas to use GPT-3 in their projects. To date, this technology seems to be the most promising for the solutions from the following industries:
- Entertainment and dating apps. GPT-3 may entertain your users forever, speaking to them with the voices of famous personalities, answering their questions, generating music, suggesting songs, movies and books, and much more. As for dating apps, it opens up the opportunity of the most perfect match ever, according to the parameters specified by users.
- Education. Perhaps, most students have already thought about the possibility to use GPT-3 for writing their essays instead of them, however, it can hardly be considered the only and the right way to use machine learning in education. Instead, it would be much more promising to use it for advanced and deep search, smart assistance, and further studying recommendations.
- Ecommerce. When it comes to an eCommerce website or a mobile app, GPT-3 can be quite useful as well. For example, it may power the most advanced recommendation engine, selecting goods that are perfectly tailored to user behavior, current trends, and other factors. It may also personalize other content, improving dwell time and SEO rankings.
- Search engines. GPT-3 may promise a completely new search experience. With the help of a browser-integrated plugin, the user may search for specific information on the website by typing the question in a natural language; the use of keywords is unnecessary in this case.
Related: Top 7 services in demand for internet users.
GPT-3 Possible Pitfalls
Despite innovative potential and the product ideas compilation for OpenAI’s GPT-3 that can be continued, there are still some concerns about its effective and seamless usage.
- GPT-3 can make mistakes. GPT-3 can sometimes have logic problems and make mistakes. And this is either the result of a programming loophole, or artificial intelligence has already learned one clearly human quality – the system does not want to admit that it does not know something or is mistaken. For example, GPT-3 repeatedly gave wrong answers to the trick questions from American history, claiming that certain individuals were presidents during a certain period.
- GPT-3 can generate offensive content. In addition to some of its logic flaws, the algorithm can also generate offensive content, especially on controversial topics like politics or religion. Therefore, if you plan to use it in these or related directions, it is better to control the AI work with the help of the human mind.
- GPT-3 is hardly predictable. The main concern regarding the capabilities of artificial intelligence also did not bypass GPT-3. Already, the system has gained enough power to make the consequences of its use difficult to predict.
How to Use GPT-3 in Your Product?
However, in the hands of a responsible entrepreneur, the technology can deliver ultimate benefit and value. Here is how to use Open AI models for your startup development.
- Develop your startup idea and validate it – If you aren’t going to use GPT-3 for your idea generation, then you should come up with it on your own and validate it with the help of market overview, target audience and competitors research, the proof of concepts, user acceptance testing, and focus group surveys.
- Decide on the task GPT-3 will solve for your project – The next step is to decide what task will GPT-3 perform in your project, and most importantly, how it will bring some novelty to the user experience. Try to employ your creativity, have one more look at the technology’s features and opportunities, and being guided by your research, come up with something new and valuable.
- Request Open AI API – Since the technology is quite demanded, you will join a waitlist after leaving your request. So, use this time for some more research, validation, and creativity boost. Also, find out Open AI pricing models to choose the one that suits your project needs.
- Integrate it into your MVP and test it – This is quite a standard step in LEAN-supported software development. Before investing in a full-fledged solution, test your MVP with your future users, use their positive response as proof for fundraising and keep the gained insights in mind at the next stage.
- Extend your features – At this stage, you will be able to turn your MVP into a full-fledged AI-powered software. However, keep in mind the possible pitfalls we’ve mentioned and don’t let them spoil your users’ experience.
Conclusion
Using an Open AI solution for your tech project can be quite a promising development strategy. However, make sure to use it wisely, staying compliant with the core company’s mission – create AI solutions that benefit humanity and streamline its progress.
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