Creating a successful application isn’t just about ensuring that all of the components work; the layout and design of the application are also crucial. The design must be professional and engaging, and the layout should be easy for users to navigate. Design components, such as animations and navigation transitions, can also enhance the usability of the application.
When you think about the future of artificial intelligence (AI) technology, it’s likely that you don’t think of auto-completion. However, you probably should. In July 2020, OpenAI released a beta testing version of GPT-3, a new auto-completion program that could very likely define the next decade of AI programming.
In this blog post, I will introduce you to OpenAI’s GPT-3 model, and present the strengths, limitations, and potential for this new technology.
What is GPT-3?
Generative Pre-trained Transformer 3 (GPT-3) is AI technology developed by OpenAI, a company founded by Elon Musk and dedicated to AI investigation. It is the third model in OpenAI’s GPT series of autoregressive language tools.
GPT-3 is a language model that uses deep learning to create human-like text. Like other language processing systems, GPT-3 predicts the probability of the sequence of words based on the given text and automatically provides the most likely answer. It is similar to the auto completion you see when you type something in the Google search bar or in the messaging application on your phone.
How it Works
When GPT-3’s application programming interface (API) receives a small piece of text, it returns text based on the entry. The entry can be formulated as a phrase, a task, a question, or any kind of expression.
GPT-3’s auto-completion success is based on the amount of data from which it is able to gather statistical information. GPT-3 has access to data from a wide range of sources, including data sets, common crawl, books, news, and internet web pages. Where GPT-2, GPT-3’s predecessor, had 1.5 billion parameters to analyze, GPT-3 has 175 billion parameters. To put it in perspective, the entirety of the English Wikipedia only makes up about 0.6 percent of GPT-3’s dataset.
Concurrency is not something that most people think about on a daily basis; however, it benefits most of us throughout our day. Whenever we ask our technological devices to perform multiple tasks, either within one application or across multiple applications, our device is using concurrency to make it happen. Thanks to concurrent programming, our devices are able to multitask at the same rate that we do.
Most organizations with a web application will inevitably need to make a decision regarding their current front-end framework. I’ve personally been involved with two projects that have come to this crossroads. One of the two applications was written in AngularJS, the other in Backbone.js. In both cases, the organization decided that the best course of action was a full rewrite using React and Redux. In the case of the AngularJS app, a gradual migration approach was considered and I was lucky enough to have the opportunity to investigate this possibility.
A mobile app is a great way to bring new ideas to life, add value for your customers, or boost awareness of your business—but only if you can build a quality mobile experience without breaking the bank. And nailing down the cost of an app in advance isn’t exactly easy. App development costs can range from trivial to extreme, depending on a host of factors such as what your app does, how users will interact with it, and how you plan to staff the project.
What’s your favorite chocolate chip cookie recipe? I bet you could ask that question to 5 different people and get 5 totally different recipes… brown sugar vs white sugar, cake flour vs all purpose, dark chocolate vs milk chocolate. All of these recipes result in a chocolate chip cookie but the process by which we get there is a matter of personal preference. If you were to ask multiple developers to solve a problem, it’s doubtful that any two developers write identical code. It’s not that any one solution is necessarily better than the others… the resulting code is likely just a matter of personal preference.
While we may not be seeing a DeLorean turned time machine anytime soon, a vehicle with capabilities similar to those of KITT from Knight Rider isn’t so far fetched.
I had the privilege of attending this year’s San Francisco Smashing Conference in early April where I listened to presentations from founders, designers, and front-end developers.