Creating videos with artificial intelligence

Artificial intelligence (AI) provides us with new opportunities for creating videos. The variety of different types of video applications and features is rapidly increasing. One of the easiest ways of producing lectures or other video learning material is by generating virtual instructors, avatars, to present the content.

Is it sometimes inconvenient to make a video? Does it feel awkward to show up with your own face and voice? Instead of escaping and having an assistant to do the job, you can recruit an avatar. Or in fact create one with AI-based software like Colossyan, Synthesia, or D-ID. They may slightly differ in features, but all of them let you generate a realistic-looking virtual actor to give a talk with a preferred accent and tone. With some of the applications, it is also possible to make more fantasy-like characters or to customise an avatar with your own face and voice.

What is the video production experience like in practice? You can first look at the video below where the process is described, or sign up directly for a trial, type in a script, customise a character and background, add media, and generate an edited video. With a purchased plan you can tell a story through several scenes.  

If you are struggling with visuals or even the script, you can ask AI to help you with templates, ideas, or a draft based on a set of parameters like context, goal of the video, audience, presenter, and tone of the presentation. This type of prompt-to-video feature may speed up your work and still let you customise everything.  We asked Colossyan to create a video about the features of the text-to-video generators, and here is the result (unedited):  

How do learners regard avatars as teachers? A lot more research will be needed, but some studies have already indicated positive impact. For example, it was found in MIT that a virtual instructor can increase students’ motivation towards learning, cultivate positive emotions, and boost their appraisal of the AI-generated instructor. Since a student’s relationship with the instructor can have a significant impact on attitudes, motivation, and even learning results, an avatar resembling a person that a student likes or admires – or maybe a favourite cartoon or movie character – may inspire and even improve performance. (Pataranutaporn et al, 2022.)  – After all, wouldn’t you like to be taught by Einstein or Bill Gates? 😊 Well, of course we must respect everyone’s privacy and ask for consent to appear as an avatar.  

References:

Pataranutaporn, P., Leong, J., Danry, V., Lawson, A.P., Maes, P., Sra, M. (2022). AI-Generated Virtual Instructors Based on Liked or Admired People Can Improve Motivation and Foster Positive Emotions for Learning. Published in 2022 IEEE Frontiers in Education Conference, pp. 1-9.  

AI-Powered Course Material Production

Introduction: The Global Campus of the University of Helsinki is committed to exploring innovative methods for enhancing educational experiences. As part of this ongoing mission, our recent “AI methods in course material production” presentation at the university’s Learning Adventure showcased the potential of cutting-edge AI technologies in creating engaging and dynamic course materials. While our primary audience was the university community, we believe these insights hold value for all EdTech enthusiasts.

In this blog post, we’ll share key takeaways from our presentation, which encompassed five sections: Text, Images, Audio, Video, and Q&A.

  1. Text: Harnessing ChatGPT’s Potential. Kicking off our presentation, we introduced ChatGPT, an AI language model developed by OpenAI. By delving into the concept of prompting, we unveiled various techniques, including Chain of Thought (CoT) methods. Highlighting the effectiveness of role prompting, we showcased ChatGPT’s self-criticism and self-evaluation features as a means to generate meaningful responses.
  2. Images: Visualising Ideas with Midjourney. Transitioning to text-to-image (T2I) generation, we presented Midjourney as an exemplary case. Demonstrating seamless integration between Discord and Midjourney, we revealed the process of creating images through prompting in Discord. For a deeper understanding of the Midjourney case, we invite you to read our earlier blog post here.
    It’s worth noting that in addition to Midjourney, there are several other AI-based applications that allow for the creation of images through text. One notable example is DALL-E, which uses a transformer-based neural network to generate images from textual descriptions. And let’s not forget about StableDiffsusion, a new AI-based technology that allows for the generation of high-quality, realistic images by leveraging the power of diffusion models. With so many exciting applications available, the possibilities for creating images through text are truly endless.
  3. Audio: Bringing Text to Life through AI. Our third segment explored the realm of text-to-audio conversion. We shed light on AI tools and techniques capable of generating lifelike speech from written text, making course materials more engaging and accessible to auditory learners.
  4. Video: Creating Dynamic Learning Experiences with AI. In the penultimate section, we investigated AI’s potential in video production. Discussing the role of artificial intelligence in crafting compelling and informative videos, we emphasised the importance of delivering course content in a visually engaging manner. In addition to Synthesia and Colossyan, there are several other noteworthy applications that are worth exploring. One such application is D-ID, which is a deep learning-based technology that allows for the anonymisation and replacing of faces with natural or fantastical looking options in videos using AI-generated imagery. With the increasing demand for video content in today’s digital landscape, these and other AI-based text-to-video applications offer opportunities for teachers and students to create high-quality videos quickly and easily.
  5. Q&A: Encouraging Audience Interaction. To wrap up our presentation, we engaged the audience in group discussions, addressing questions and concerns stemming from the event. This interactive session fostered a deeper understanding of AI’s role in education and promoted collaboration within our university community. Participants were interested in for example if it was possible to produce materials in Finnish language with these new tools and yes, usually that is also possible.

Conclusion: Embracing AI-powered tools like ChatGPT, Midjourney, and other text-to-audio and video production solutions is revolutionising the way we develop and deliver course materials. By adopting these innovations, we can create more engaging, accessible, and dynamic learning experiences for students across the globe.

AI is not taking away your job, it’s the person that adopts AI that is taking away your job!

ThingLink basics, tags

View of a laboratory in ThingLink.

 

Greetings, avid reader! Allow me to introduce you to the delightful world of ThingLink. Where the only limit is your own imagination! If you’re looking to add a touch of finesse to your images and videos, look no further than the humble tag. These interactive buttons bring your multimedia content to life and they’re the secret ingredient of ThingLink. In this blog post, I’ll give you a quick rundown of ThingLink in the form of a video.
BTW we used ThingLink for our very first project. You can read about it in our blog entry called Message from the future.

First of all, let’s define what ThingLink is. Simply put, ThingLink is an online platform that allows you to add interactive tags to your images and videos. These tags can include text, images, audio, and video, making your multimedia content much more engaging and interactive. Whether you’re a teacher, a student, or simply someone looking to add a touch of sophistication to your social media posts, ThingLink is the tool for you. Check out the following Miro board where I have put together a very simply yet effective sequence of slides to highlight what ThinLink is.

Now, why is this relevant for our context which is higher education and Edtech and at the end of the day the learners? Well, for one, it is a very intuitive tool and it gives students control over their own learning journey. No more dull lectures or tedious presentations. With ThingLink, students can interact with the material in multiple ways, truly grasping and internalising the information. And let’s be honest, who doesn’t love a bit of control? According to Yarbrough (2019) “more visuals are not only learner preferred, training and educational professionals have identified that visuals support efficient teaching.”

A ThingLink can be considered a version of an infographic. There are ample studies supporting the claim that infographics are very powerful tools. What makes infographics and in an extended way ThingLink too, so useful? Visuals tend to stick in long-term memory, they transmit messages faster and improve comprehension to name a few (Shiftlearning).

Here is a roughly 7 min video walking you through all the tags and how to create them. In Edit mode tags can can be dragged around the base image – you can even pull a line from under a tag and anchor it to a specific point. 

In a next tutorial blog post with video we’ll have a look the settings and dive into the immersive world of 360° images and videos in ThingLink.  

In conclusion, ThingLink is the tool you didn’t know you needed. With its interactive tags and multimedia-rich approach, ThingLink empowers students to take charge of their studies and reach their full potential. So what are you waiting for? Give it a go and see the magic unfold!

BTW when storyboarding the video I had a clear vision of how to implement text to speech (TTS) with an AI voice – little did I know how NOT easy this was  Stay tuned as at some point I will write a how to post about the process of producing the above video. 

Source:

Yarbrough, J. R. (2019). Infographics: In support of online visual learning. Academy of Educational Leadership Journal, 23(2), 1–15.

Shiftlearning. Blog post: Studies confirm the Power of Visuals in eLearning.

 

Harnessing AI – the Midjourney case

AI generated landscape

Let’s discuss AI generated imagery for a second.

What is it?

As an example I use Midjourney. Generating images using artificial intelligence (AI) tools such as Midjourney on Discord has the potential to revolutionise the field of visual content creation. Midjourney, an open-source platform, utilises machine learning algorithms to generate images based on user input. In short so called Convolutional Neural Networks (CNNs) create artistic imagery by separating and recombining image content and style. This process of using CNNs to render a content image in different styles is referred to as Neural Style Transfer (NST). This technology has many practical applications such as in graphic design, digital art, and scientific research. However, the ethical implications of AI-generated images must also be considered, more on this in a bit.

When using Midjourney on Discord, users can input a variety of parameters to generate images. This can include text, numbers, or even other images. The algorithm then processes this input and creates a unique image based on the parameters provided. This allows for a high degree of customisation and creativity when generating images. Additionally, Midjourney also allows the user to generate versions of those images, enabling thus a set of variations of the base image.

Here is a short video on how to use Midjourney via Discord.

One of the key benefits of using Midjourney on Discord is the community aspect of the tool. Users can share their input and generated images with others in real-time, allowing for a collaborative and interactive experience. This is particularly useful for designers and artists working on a project together, as it allows them to quickly and easily share ideas and feedback. Additionally, the Discord integration allows for easy sharing of the generated images, making it easy to share the final output with others.

Are there any issues?

One major advantage of using AI to generate images is its ability to produce a high volume of unique and varied content. This is particularly beneficial in fields such as advertising and graphic design where a steady stream of fresh and engaging visuals is essential. Furthermore, the use of machine learning algorithms in image generation allows for a high degree of customisation and creativity in the final output.

However, there are also valid concerns regarding the ethical implications of AI-generated images. One of the main concerns is the potential for AI-generated images to perpetuate harmful stereotypes and biases. For example, if an AI model is trained on a dataset that contains a disproportionate number of images of a certain race or gender, it may produce images that reinforce these stereotypes. Additionally, the use of AI-generated images in fields such as journalism and news reporting raises concerns about the authenticity and accuracy of the content.

A good example of what consequences training on a specific dataset can mean came up in a recent class action lawsuit in federal court in San Francisco, USA filed by a group of artists – the case is still on-going. Apparently

“text image generators were trained off of a data set called LAION, and they basically are billions of images that help to train the generators. And where artists take issue with it is that our images were put into these data sets and then used to create the generators without our consent.”

Source: NYTimes podcast: Hardfork, Jan 20 2023.

It is important to note that these concerns are not unique to AI-generated images, but rather are issues that have long been present in the field of visual content creation. However, the use of AI does amplify these concerns, and it is crucial that proper measures are taken to mitigate these risks. This can include using diverse and representative training datasets (with consent?), implementing robust ethical guidelines, and providing transparency about the source and authenticity of AI-generated images. In conclusion, the use of AI to generate images has the potential to greatly benefit various fields if implemented correctly.

Overall, Midjourney is a powerful tool for generating images on Discord. Its ability to process input from users and generate unique images, along with its editing tools and collaborative features, make it a valuable tool for a wide range of fields. Whether you’re a designer, artist, or researcher, Midjourney can help you create stunning visual content quickly and easily.

Prompts

Midjourney uses prompts to instruct the NST what the image is suppose to look like. It always starts with a forward slash and IMAGINE (/IMAGINE) and your descriptive text eg. I used the following prompt line for the owl in the right hand side column:

[/IMAGINE logo, funky, scifi, bioluminescence, owl on transparent background]

which resulted in this 4 image square (below). I then chose to Upscale #1 and Version #2 and ended up with a 1024×1024 px sized image of the owl I wanted.

For further reading on how to perfect your prompts to get the result you are happy with I suggest you head over to Midjourney’s Documentation page or check out PromptHero and while you are at it have a look at the Midjourney Community Showcase.

AI generated owl