What do AI, 48 hours and Second Life have in common? Not a lot, beyond some stunningly creative pieces that we found for you this week!
AI films are now beginning to come through and we have two very interesting ones for you to take a look at. The first is created/prompted by Matt Mayle (our feature image for this post) and has been made using Elevenlabs (voice), Runwayml’s GEN2 (animation) and ChatGPT4 (text concept) and is described an ‘AI assisted short’, called The Mass (released 26 April) –
The second is called The Frost, by Waymark Creative Labs (released 5 June). This has a distinct aesthetic to it, encapsulates a curious message, and overall reflects the state of AI animation at this stage, but its nonetheless a gripping piece. Its been created with DALLE-2 and D-ID –
Our next pick was made in 48 hours (well, with a bit of tweaking on top) and has been made in Unreal Engine, called Dude Where’s My Ship by Megasteakman. To be frank, the speed of its creation does show in the final quality of film, but its nonetheless an interesting development, especially given that I was a regular judge on the 48 Hour Filmmaking Contest a few years ago. The machinima version of that contest was managed and supported by Chantal Harvey for several years and its astonishing to think that this is the next generation of that process –
Finally, this week, a film made in Second Life, which lends itself to flash production, based on content from a plethera of creators on whom its content relies. The film is called The Doll Maker (released 27 May) and has been made by FeorieFrimon using various models and Paragon Dance Animations movements to a Beats Antique music composition called Flip –
Hot on the heels of our discussion on AI generators last week, we are interested to see tools already emerging that turn text prompts into 3D objects and also film content, alongside a tool for making music too. We have no less than five interesting updates to share here – plus a potentially very useful tool for rigging the character assets you create!
Another area of rapidly developing technological advancements is mo-cap, especially in the domain of markerless which lets face it is really the only way to think about creating naturalistic movement-based content. We share two interesting updates this week.
Nvidia has launched an AI tool that will generate 3D objects (see video). Called GET3D (which is derived from ‘Generate Explicit Textured 3D meshes’), the tool can generate characters and other 3D objects, as explained by Isha Salian on their blog (23 Sept). The code for the tool is currently available on Github, with instructions on how to use it here.
Google Research with researchers at the University of California, Berkeley are also working on similar tools (reported in Gigazine on 30 Sept). DreamFusion uses NeRF tech to create 3D models which can be exported into 3D renderers and modeling software. You can find the tool on Github here.
Meta has developed a text-to-video generator, called Make-A-Video. The tool uses a single image or can fill in between two images to create some motion. The tool currently generates five second videos which are perfect for background shots in your film. Check out the details on their website here (and sign up to their updates too). Let us know how you get on with this one too!
Runway has released a Stable Diffusion-based tool that allows creators to switch out bits of images they do not like and replace them with things they do like (reported in 80.lv on 19 Oct), called Erase and Replace. There are some introductory videos available on Runway’s YouTube channel (see below for the Introduction to the tool).
And finally, also available on Github, is Mubert, a text-to-music generator. This tool uses a Deforum Stable Diffusion colab. Described as proprietary tech, its creator provides a custom license but says anything created with it cannot be released on DSPs as your own. It can be used for free with attribution to sync with images and videos, mentioning @mubertapp and hashtag #mubert, with an option to contact them directly if a commercial license is needed.
Reallusion‘s Character Creator 4.1 has launched with built in AccurRIG tech – this turns any static model into an animation ready character and also comes with cross-platform support. No doubt very useful for those assets you might want to import from any AI generators you use!
Motion Capture Developments
That every-ready multi-tool, the digital equivalent of the Swiss army knife, has come to the rescue once again: the iPhone can now be used for full body mocap in Unreal Engine 5.1, as illustrated by Jae Solina, aka JSFilmz, in his video (below). Jae has used move.ai, which is rapidly becoming the gold standard in markerless mocap tech and for which you can find a growing number of demo vids showing how detailed movement can be captured on YouTube. You can find move.ai tutorials on Vimeo here and for more details about which versions of which smart phones you can use, go to their website here – its very impressive.
Another form of mocap is the detail of the image itself. Reality Capture has launched a tool that you can use to capture yourself (or anyone else or that matter, including your best doggo buddy) and use the resulting mesh to import into Unreal’s MetaHuman. Even more impressive is that Reality Capture is free, download details from here.
We’d love to hear how you get on with any of the tools we’ve covered this week – hit the ‘talk’ button on the menu bar up top and let us know.
In this month’s special report, we take a look at some of the key challenges in using creative AI generators such as DALL-E, MidJourney, Stable Diffusion and others. Whilst we think they have FANTASTIC potential for creators, not least because they cut down the time in finding some of the creative ideas you want to use, there are some things that are emerging that need to be considered when using them.
Firstly, IP is a massive issue. As noted in this article on Kotaku (Luke Plunkett), the recent rise of AI-created art has brought to the fore some of the moral and legal problems in using it. In terms of the moral issues, some are afraid of a future where entry level art positions are taken over by AI and others see AI-created art as a reflection of what’s already occuring between artists – the influence of style and content… but this is an argument that came to the fore when computers were first used by artists back in the 1960s. Quite frankly we are now seeing some of the most creative work in a generation come to fruitition that just would not have happened without computational assistance. Take a look at the Lumen Prize annual entries, for example, to see what the state of the art is with creative possibilities of AI and other tech. Tracy even directs an Art AI Festival, aiming to showcase some of the latest AIs in creative applications, working in collaboration with one of the world’s leading creative AI curators, Luba Elliott.
As to the legal issues, these are really only just emerging and in a very disjointed and piecemeal way. It was interesting to note that Getty Images notified its contributors in an email (21 Sept 2022) that “Effective immediately, Getty Images will cease to accept all submissions created using AI generative models (e.g., Stable Diffusion, Dall‑E 2, MidJourney, etc.) and prior submissions utilizing such models will be removed.” It went on to state: “There are open questions with respect to the copyright of outputs from these models and there are unaddressed rights issues with respect to the underlying imagery and metadata used to train these models. These changes do not prevent the submission of 3D renders and do not impact the use of digital editing tools (e.g., Photoshop, Illustrator, etc.) with respect to modifying and creating imagery.” This is hot on the heals of a number of developments earlier in the year: in February 2022, the US Copyright Office refused to acknowledge that an AI could hold copyright of its creative endeavour (article here). By September 2022, an artwork created with MidJourney by Jason Allen that won the Colorado State Fair contest was causing a major stir across the art world as to what constitutes art, as outlined in this article (Smithsonian Magazine) and this short news report here –
Of course, the real dilemma is what happens to artists, particularly those at the lower end of the food chain. By way of another example, consider the UK actors’ union Equity’s response to recent proposals by the Government to include a data mining exemption for audio-visual content in its proposed new AI regulation. Why that’s interesting is because already a number of organizations that would otherwise employ these artists, say as graphic designers or concept artists, are rapidly replacing them with AI generated images – Cosmopolitan used its ‘first AI generated cover’ in June 2022 and advertising agencies the world over are doing likewise (Adage article). Some image users have even stated that in future they will ONLY use these tools as image sources, effectively cutting out the middle man, and indeed the originator of the contributory works. So, of course Getty is not going to be happy about this… and neither are the many contributors to their platforms.
And so here is the nub of the problem: in the rush that is now going to follow Getty’s stance (and probably others with similar influence to follow), how will the use of AI generators be policed? This has pretty serious consequences because it has implications for all content including on YouTube, in festivals and contests around the world – how would creative works like The Crow be judged (see our blog post here too)? It certainly places emphasis on the role of metadata and statements of authorship, but it is also as good an argument we can think of for using blockchain too! The Crow for example briefly mentions the AI generator tool it has used, which is freely available to use on Google CoLab here, but it doesn’t show the sources of the underlying training data set used.
We contend, the only way to police the use of AI generated content is actually by using AI, say by analysing pixel level detail… and that’s because one of Getty’s points is no doubt going to be how their own stock images, even with copyright claims over them, have been used in training data sets. AI simply cuts out the stuff out that it doesn’t want and voila, something useful emerges! So, unless there is greater transparency and disclosure among the creators of AI generators AS A PRIORITY on where images have been scraped from and how they have been used, there is going to be a major problem for all types of content creators, including the machinima and virtual production creator using these tools as a way to infuse new ideas into their creative projects, and as the ability to turn 2D image into 3D object becomes more accessible to a wider range of creators. Watch this space!