In this series, we examine how AI has been “creating” novel things
spoiler alert – it’s getting really good…
Welcome to my multi-part series on AI as a creator. In this series we aim to look at whether today’s artificial intelligence is capable of devising new works of arts.
We realize that Art is completely in the eye of the beholder, so what may be considered art to some is different than others. Our definition of art will be loose and we will use it to mean the following:
In today’s part of the series we are examining:
When we recently spoke to AI experts and thought leaders, their opinions varied as to whether AI has the potential to become a true creative partner or even the creator of solo works of art. While this debate will likely continue for some time, it’s clear that as digital content and delivery platforms continue infiltrating all forms of media and expression, the role of AI will undoubtedly expand.
When it comes to artificial intelligence, some people are worried that they might attack us or take our jobs. However, it turns out that they might also supersede us at making memes. A new deep neural network approach has demonstrated that AI can produce funny and relevant captions when given a meme image. What a time to be alive.
The algorithm is called “dank learning” after dank memes, a slang term that refers ironically to the most bizarre memes or memes that are now so overused that they have lost their original comedic value. That said, the program is capable of breathing new life into the memes of bygone days. The project was created by Stanford students Abel L. Peirson V and E. Meltem Tolunay.
This AI approach is known as machine learning. The software was not explicitly programmed to create memes, but to perform certain actions and create new outputs based on what it has learned. In this case, the team used about 2,600 unique memes, with up to 160 different captions. Based on this extensive library, the algorithm began generating memes.
And the memes created by the AI seem real. You can’t tell these and the non-AI generated ones apart at all. When 20 different memes were shown to five individuals from diverse backgrounds, they could hardly distinguish the real memes from the AI-generated ones and gave them similar ratings of hilarity.
It’s getting easier and easier to use AI to generate convincing-looking, yet entirely fake, pictures of people. Now, one company wants to find a use for these photos, by offering a resource of 100,000 AI-generated faces to anyone that can use them — royalty free. Many of the images look fake but others are difficult to distinguish from images licensed by stock photo companies.
The project’s Product Hunt page lists the team at Icons8, a designer marketplace for icons and photographs, as the creator of the project. The AI-produced images are intended to be used as design elements in anything from presentations to websites and mobile apps. Everything is free to use with link attribution back to generated.photos.
Over the course of the year, we’ve seen a number of AI projects generate fake AI faces, most notably ThisPersonDoesNotExist.com, a website capable of producing an infinite series of mostly-believable headshots. The faces found on generated.photos cover a variety of ages, shapes, and ethnicities, and they’re all consistently lit and consistently sized to make them useful for designers.
A new AI from Microsoft automatically generates to-do lists based on sent emails. Researchers from the University of Washington and Microsoft’s AI team announced the tool in a pre-print research paper.
The Smart To-Do tool uses AI to scan all outgoing emails for usable text, then converts these tasks into an automatically generated to-do list. Suppose you send an email to a customer saying that you will send a draft on Tuesday afternoon. The AI scans the email, registers the task and puts this task on the list with, for example, the title ‘send a concept to customer’, together with the time, in this case, Tuesday afternoon. In this way, the tool scans all emails and updates the list continuously.
We’ve seen that AI currently is able to create many things. This month we’ve examined AI as a creator or Art, Food, Music, Novels, Emails, Recipes and more, but what about AI creating code and AI. Is that even possible? In 2018, Bayou launched and is a deep-learning system that can write code for programmers and generate API idioms for complex databases. It teaches itself how to code through GitHub, training with millions of human programmers using Java. It can interpret and recognize high-level patterns in hundreds of thousands of Java programs through an artificial neural network method called Neural Sketch Learning. Developers can initialize variables that are intended to be used in the programming task or submit a query that includes names of API methods or the type of variables for the programming task.
As you can see, even AI generating AI is in the future. This is all at the start of “creation” by AI but expect that as more people become data and AI literate and as we see a shift from Computer Science and Software Engineering to AI Engineering, we’ll get there faster and faster.
So what do you do when all signs point to having to go to University to gain any sort of advantage? Unfortunately it’s the current state of affairs that most employers will not hire you unless you have a degree for even junior or starting jobs. Once you have that degree, coming to my Modular Lab Program, with 1000ml with our Patent Pending training system, the only such system in the world; is the only way to gain the practical knowledge and experience that will jump start your career.
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