March was another astonishing month in the world of AI genies with the release of exponentially powerful updates (GPT4 released 14 March; Baidu released Ernie Bot on 16 March), new services and APIs. It is not surprising that by the end of the month, Musk-oil is being poured over the ‘troubling waters’ – will it work now the genie is out of the bottle? Its anyone’s guess and certainly it seems a bit of trickery is the only way to get it back into the bottle at this stage.
More importantly, and with immediate effect, the US Copyright Office issued a statement on 16 March in relation to the IP issues that have been hot on many lips for several months now: registrations pertaining to copyright are about the processes of human creativity, where the role of generative AI is simply seen as a toolset under current legal copyright registration guidance. Thus, for example, in the case of Zarya of the Dawn (refer our comments in the Feb 2023 Tech Update), whilst the graphic novel contains original concepts that are attributable to the author, the use of images generated by AI (in the case of Zarya, MidJourney) are not copyrightable. The statement also makes it clear that each copyright registration case will be viewed on its own merit which is surely going to make for a growing backlog of cases in the coming months. It requires detailed clarification of how generative AI is used by human creators in each copyright case to help with the evaluation processes.
The statement also highlights that an inquiry into copyright and generative AIs will be undertaken across agencies later in 2023, where it will seek general public and legal input to evaluate how the law should apply to the use of copyrighted works in “AI training and the resulting treatment of outputs”. Read the full statement here. So, for now at least, the main legal framework in the US remains one of human copyright, where it will be important to keep detailed notes about how creators generated (engineered) content from AIs, as well as adapted and used the outputs, irrespective of the tools used. This will no doubt be a very interesting debate to follow, quite possibly leading to new ways of classifying content generated by AIs… and through which some suggest AIs as autonomous entities with rights could become recognized. It is clear in the statement, for example, that the US Copyright Office recognizes that machines can create (and hallucinate).
The complex issues of the dataset creation and AI training processes will underpin much of the legal stances taken and a paper released at the beginning of Feb 2023 could become one of the defining pieces of research that undermines it all. The research extracted near exact copyrighted images of identified people from a diffusion model, suggesting that it can lead to privacy violations. See a review here and for the full paper go here.
In the meantime, more creative platforms used to showcase creative work are introducing tagging systems to help identify AI generated content – #NoAI, #CreatedWithAI. Sketchfab joined the list at the end of Feb with its update here, with updates relating to its own re-use of such content through its licensing system coming into effect on 23 March.
Nvidia’s progressive march with AI genies needs an AI to keep up with it! Here’s my attempt to review the last month of releases relevant to the world of machinima and virtual production.
In February, we highlighted ControlNet as a means to focus on specific aspects of image generation and this month, on 8 March, Nvidia released the opposite which takes the outline of an image and infills it, called Prismer. You can find the description and code on its NVlabs GitHub page here.
Alongside the portfolio of generative AI tools Nvidia has launched in recent months, with the advent of OpenAI’s GPT4 in March, Nvidia is expanding its tools for creating 3D content –
It is also providing an advanced means to search its already massive database of unclassified 3D objects, integrating with its previously launched Omniverse DeepSearch AI librarian –
It released its cloud-based Picasso generative AI service at GTC23 on 23 March, which is a means to create copyright cleared images, videos and 3D applications. A cloud service is of course a really great idea because who can afford to keep up with the graphics cards prices? The focus for this is enterprise level, however, which no doubt means its not targeting indies at this stage but then again, does it need to when indies are already using DALL-E, Stable Diffusion, MidJourney, etc. Here’s a link to the launch video and here is a link to the wait list –
A procedural content generator for creating alleyways has been released by Difffuse Studios in the Blender Marketplace, link here and see the video demo here –
We spotted a useful social thread that highlights how to create consistent characters in Midjourney, by Nick St Pierre, using seeds –
and you can see the result of the approach in his example of an aging girl here –
JSFilmz created an interesting character animation using MidJourney5 (which released on 17 March) with advanced character detail features. This really shows its potential alongside animation toolsets such as Character Creator and Metahumans –
Runway’s Gen-2 text-to-video platform launched on 20 March, with higher fidelity and consistency in the outputs than its previous version (which was actually video-to-video output). Here’s a link to the sign-up and website, which includes an outline of the workflow. Here’s the demo –
Gen-2 is also our feature image for this blog post, illustrating the stylization process stage which looks great.
Wonder Dynamics launched on 9 March as a new tool for automating CG animations from characters that you can upload to its cloud service, giving creators the ability to tell stories without all the technical paraphenalia (mmm?). The toolset is being heralded as a means to democratize VFX and it is impressive to see that Aaron Sims Creative are providing some free assets to use with this and even more so to see none other than Steven Spielberg on the Advisory Board. Here’s the demo reel, although so far we’ve not found anyone that’s given it a full trial (its in closed beta at the moment) and shared their overview –
Finally for this month, we close this post with Disney’s Aaron Blaise and his video response to Corridor Crew’s use of generative AI to create a ‘new’ anime workflow, which we commented on last month here. We love his open-minded response to their approach. Check out the video here –
Genies are everywhere now. In this post, I’ll focus on some of the more interesting areas relating to the virtual production pipeline, which interestingly is becoming clearer day by day. Check out this mandala of the skills identified for virtual production by StoryFutures in the UK (published 2 March) but note that skills for using genies within the pipeline are not there (yet)!
Future of Filmmaking
Virtual Producer online magazine published an interesting article, by Noah Kadner (22 Feb), about the range of genie tools available for the film production pipeline, covering the key stages of pre-production, production and post-production. Alongside it, he gives an overview of some of the ethical considerations we’ve been highlighting too. Its nice to the see the structured analysis of the tools although, of course, what AIs do is change or emphasize aspects of processes, conflate parts and obviate the need for others. Many of the tools identified are ones we’ve already discussed in our blogs on this topic, but its fascinating to see the order being put on their use. I think the key thing all of us involved in the world of machinima have learned over the years, however, is that its often the indie creators that take things and do stuff that no one thought about before, so I for one will be interested to see how these neat categories evolve!
Bits and Pieces
It was never going to take long to showcase the ingenuity among users of genies: last month, whilst Futurism was reporting on the dilemma of ethical behaviour among users who have ‘jailbroken’ the ChatGPT safeguards, MidJourney was busy invoking even more governance over its use. MidJourney says its approach, which now bans the use of words about human reproductive systems, is to ‘temporarily prevent people from creating shocking or gory images’. All this very much reminds me of an AI experiment carried out by Microsoft almost seven years ago as we release this post, on 24 March 2016, and of the artist Zach Blas’ interpretation of that work showcased in 2017, called ‘Im here to learn so :))))))‘.
For those without long(ish) memories, Blas’ work was a video art installation visualizing Tay, which had been designed by Microsoft as a 19 years old American female chatbot. As an AI, it lived for just one day on its social media platform where it was subjected to a tyranny of misognyistic, abusive, hate-filled diatribe. Needless to say, corporate nervousness in its creative representation of the verbiage it generated from its learning processes resulted in it being terminated before it really got going. Blas’ interpretation of Tay, ironically using Reallusion’s CrazyTalk to animate it as an ‘undead AI’, is a useful reminder of how algorithms work and the nature of humanbeans. The link under the image below takes you to where you can watch the video of Tay reflecting on its experience and deepdreams. Salutary.
Speaking of dreams, Dreamix is a creative tool that uses an input video with a text prompt to create some other video output. In effect, it takes the user through the pre-production, production and post-production process in just one sweep. Here’s a video explainer –
In a not dissimilar vein, ControlNet takes an image generated in Stable Diffusion and applies a controller to inpaint the image in any style you’d like to see. Here’s an explainer by Software Engineering Courses –
and here’s the idea taken to a whole new level by Corridor Crew in their development of an anime film. The explainer takes you through the process they created from scratch, including training an AI –
They describe the process they’ve gone through really well, and its surely not going to be too long before this becomes automated with an app you can pick up in a virtual store near you.
Surprise, surprise, here is RunwayML’s Gen-1: not quite the automated app actually, but pretty close. Runway has created an AI that takes video input and an image with a style you would like to apply to it and with a little bit of genie magic, the output video has the style transferred to it. What makes this super interesting, however, is that Runway Studios is now a thing too – it is the entertainment and production division of Runway and aims to partner with ‘next gen’ storytellers. It has launched two initiaties worth following: an annual AI Film Festival, which just closed its first call for entries. Here’s a link to the panel discussion that took place in New York on 1 Mar, with Paul Trillo, Souki Mehdaoui, Cleo Abram and Darren Aronofsky –
The second initiative is its creative grants for ‘aspiring filmmakers from various backgrounds who are in need of production support’. On its Google formlet, it states grants take various shapes, including advanced access to the latest AI Magic Tools, funding allocations, as well as educational resources. Definitely worth bearing in mind for your next step in devising machine-cinema stories.
Whilst we sit back and wait for the AI generated films to bubble to the top of our algorithmically controlled YouTube channel, or at least, the ones where Google tools have been part of the process, we bring you a new-old classic. Welcome to FrAIsier 3000. This is described as a parody show that combines surreal humor, philosophical musings and heartfelt moments from an alternate dimension, where an hallucinogenic FrAIsier reflects on the mysteries of existence and the human condition. Wonderful stuff, as ever. Here’s a link to episode 1 but do check out episode 2, waxing lyrically on ‘coq au vin’ as a perfect example of the balance between the dichotomy of discipline and carefreeness (and our feature image for this post) –
If you find inspiring examples of AI generated films, or yet more examples of genies that push at the boundaries of our virtual production world, do get and touch or share in the comments.
This week, we highlight some time-saving examples for generating 3D models using – you guessed it – AIs, and we also take a look at some recent developments in motion tracking for creators.
All these examples highlight that generating a 3D model isn’t the end of the process and that once its in Blender, or another animation toolset, there’s definitely more work to do. These add-ons are intended to help you reach your end result more quickly, cutting out some of the more tedious aspects of the creative process using AIs.
Blender is one of those amazing animation tools that has a very active community of users, and of course, a whole heap of folks looking for quick ways to solve challenges in their creative pipeline. We found folks that have integrated OpenAI’s ChatGPT into using the toolset by developing add-ons. Check out this illustration by Olav3D, whose comments about using ChatGPT for attempting to write Python scripts sum it up nicely, “better than search alone” –
Dreamtextures by Carson Katri is a Blender add-on using Stable Diffusion which is so clever that it even projects textures onto 3D models (with our thanks to Krad Productions for sharing this one). In this video, Default Cube talks about how to get results with as few glitches as possible –
and this short tells you how to integrate Dreamtextures into Blender, by Vertex Rage –
To check out Dreamtextures for yourself, you can find the Katri’s application on Github here and should you wish to support his work, subscribe to his Patreon channel here too.
OpenAI also launched its Point-E 3D model generator this month, which can then be imported into Blender but, as CGMatter has highlighted, using the published APIs takes a very long time sitting in cues to access the downloads, whilst downloading the code to your own machine to run it locally, well that’s easy – and once you have it, you can create point-cloud models in seconds. However, he’s running the code from Google’s CoLab, which means you can run the code in the cloud. Here’s his tutorial on how to use Point-E without the wait giving you access to your own version of the code (on Github) in CoLab –
We also found another very interesting Blender add-on, this one lets you import models from Google Maps into the toolset. The video is a little old, but the latest update of the mod on Github, version 0.6.0 (for RenderDoc 1.25 and Blender 3.4) has just released, created by Elie Michel –
We were also interested to see NVIDIA’s update at CES (in January). It announced a release for the Omniverse Launcher that supports 3D animation in Blender, with generative AIs that enhance characters’ movement and gestures, a future update to Canvas that includes 360 surround images for panoramic environments and also an AI ToyBox, that enables you to create 3D meshes from 2D inputs. Ostensibly, these tools are for creators to develop work for the metaverse and web3 applications, but we already know NVIDIA’s USD-based tools are incredibly powerful for supporting collaborative workflows including machinima and virtual production. Check out the update here and this is a nice little promo video that sums up the integrated collaborative capabilities –
As fast as the 3D modelling scene is developing, so is motion tracking. Move.ai which launched late last year, announced its pricing strategy this month at $365 for 12 months of unlimited processing of recordings – this is markerless mocap at its very best, although not so much if you want to do live mocap (no pricing strategy announced yet). Move.ai (our feature image for this article) lets you record content using a mobile phone (a couple of old iPhones). You can find out more on its new website here and here’s a fun taster, called Gorillas in the mist, with ballet and 4 iPhones, released in December by the Move.ai team –
And another app although not 3D is Face 2D Live, released by Dayream Studios – Blueprints in January. This tool allows you to live link a Face app on your iPhone or iPad to make cartoons, including with your friends also using an iPhone app, out of just about anything. It costs just $14.99 and is available on the Unreal Marketplace here. Here’s a short video example to wet your appetite – we can see a lot of silliness ensuing with this for sure!
Not necessarily machinima but for those interested in more serious facial mocap, Weta has been talking about how it developed its facial mocap processes for Avatar, using something called an ‘anatomical plausible facial system’. This is an animator centric system that captures muscle movement rather than ‘facial action coding’ which focusses on identifying emotions. Weta stated its approach leads to a wider set of facial movements being integrated into the mocapped output – we’ll no doubt see more in due course. Here’s an article on the FX Guide website which discusses the approach being taken and for a wider ranging discussion on the types of performance tracking used by the Weta team, Corridor Crew have bagged a great interview with the Avatar VFX supervisor, Eric Saindon here –
Now the AI genie is in full flight, we’ve been anticipating the exponential growth in interest in creative applications – and also in the ethical and moral questions being asked. This month, we have not been disappointed! We start our review with some of the tools we’ve seen emerge and finish with a review of the legal situation that’s been taking shape over the last month, since our January update on the topic.
It takes Text-to-???
It seems most of the online world has bought into the hype around ChatGPT, and who can blame folks for wanting in on the action – it reached a million users faster than any platform has previously in the history of the internet ie., 5 days. Whilst it appears that Google and others have for once been caught sleeping on the job, Microsoft has stolen a march and helped OpenAI monetize its premium chat service for a mere $20/month (just a week after the extended partnership was announced and only if you are US-based) from which each partner will no doubt benefit massively. In the meantime, there has been a huge number of Chrome browser extensions launched based on ChatGPT for everything from search using voice commands, article summaries, writing Excel formulae, email assistance, LinkedIn comments management, to SEO optimization and a heap of other useful-ish applications. Go to the Chrome web store and search for the ones that will help with your creative pipeline – I’m sure someone somewhere will have thought of it before you.
I found a few uses for the YouTube summary assistants of which there are a couple of options, this being one (by Glasp) –
After adding the extension, it took a couple of seconds in total to transcribe the video, copy the text into my ChatGPT account and summarize an hour long interview I did with John Gaeta last year. This is the summary of that interview, which is a pretty good overview of what was discussed albeit the first part is almost verbatim from the intro –
The video is an interview with John Gaeta, who is known for creating the famous bullet time shot in the “Matrix” films. He won the Best Visual Effects Oscar for his work on the Matrix and co-founded Lucasfilm’s immersive entertainment division called ILMxLAB, where he acts as the Executive Creative Director. In the interview, he talks about his experience in creating a demo for the Sony PlayStation super computer, which was shown at Siggraph in 2000. He also mentions his interest in building big and complicated projects while also making entertainment products. Gaeta explains how the bullet time shot was a result of a philosophy they had during the Matrix trilogy of creating methods that might be used if one was making virtual reality. He also touches on how the rise of the internet and gaming helped audiences comprehend the shot better and how it carried on the underlying premise of the Matrix itself. (ChatGPT)
and here’s the full interview –
If, like me, you’re after nuggets and detail (my day job is as a researcher), then this won’t really help you but if you just want to get a sense of what’s being discussed, and you’re reviewing lots of material from various channels, or want a quick summary for promo, then its really a great way to generate an overview.
Creatively, though, we’re far more interested in the potential for Text-to-Otherstuff, such as 3D assets, video and 3D environments. Towards that end, although targeting game asset dev, Scenario.gg is a proposition (launched in 2019) that closed a round of significant seedcorn investment in January. With its creators’ backgrounds in gaming, AI and 3D technology, Scenario’s generative AI creates game assets using both image and text promps, albeit currently outputs are 2D images (see below). Its aim is to support creation of high fidelity assets, 3D models, sounds & music, animations, environments and more, based on users’ uploads of their own content (image and text description). The ownership model on generated content is interesting, which pushes the IP issue back to users since only images you have the right to use can be uploaded.
Scenario believes its product will cut creative production time for game artists (those who choose to work with AI). It surpassed .5M created images on 21 January, so is clearly gaining momentum. This is an interesting development, given comments by Aura Triolo (an Independent Games Festival 2023 judge and animation lead at Ivy Road) in an article covering AI devs for metaverse and games here (by Wagner James Au on his New World Notes blog, published in mid December). Triolo makes the point that time savings probably won’t be worth the effort given how much additional work is required to refine 3D models that AI generates, particularly in AAAs (as in the use of AI for procedural generation). That may well be true in a context where automation tools have been used for some time but this type of toolset will surely benefit thousands of indies, and not just in gaming but also machinima and virtual production. Time will tell.
Meta AI has published a paper that discusses taking their text-to-video (MAV) generator one step further to 4D (NeRFs or neural radiance fields), referring to it as MAV3D (Make-a-Video-3D). It optimizes scene appearance, density and motion consistency from text-to-video, generates a view from any camera location and angle and can be composited into any 3D environment. MAV3D does not require any 3D or 4D data. It is not yet available as a tool to use but here’s the paper to read. We look forward to hearing more about this in due course.
Text-to-fashion? Well, maybe not just yet, however ReadyPlayerMe, which is a cross platform avatar creator, has a new feature on its recently launched ‘labs’ web platform. Currently in beta and free, it allows you to customise avatar outfits using DALL-E’s generative AI art platform for text prompts. After faffing for a few minutes, I created this (but the hair is still a mess!) –
Text-to-music is an interesting area. There are no doubt going to be lots of training issues emerge with this type of AI, however, what fascinates me with Google‘s MusicLM is the ability to generate music from rich captions, using a ‘story mode’ (with a sequencer) and even from descriptions of paintings, places and epochs. I don’t think I’ve ever heard anything quite like the piece it generated for Munch’s The Scream, using a description by Iain Zaczek – not exactly melodic but certainly evocative of the artwork. It will also let you hum something and then apply a specific instrument to hear it played back, apparently. There is currently no API through which you can test your own ideas, however, but go to the github page here and check out the samples reported in the paper. Google it seems is only making the dataset of MusicCaps comprising 5.5k music-text pairs available, which includes rich text descriptions provided by human experts, and has obviously decided to let someone else create the API and take the rap with it. It will no doubt be one of many in due course, but there are some great ideas presented in the paper worth checking out.
Curation and Discovery
Curating content is one of the perenial problems of the internet – and its a problem that is getting more challenging because even with so much effort being put into the creator toolsets, no one is really paying much attention in the creator context of how work can be discovered (unless of course there is advertising embedded in it, which is a whole different agenda). One can only hope that when advanced AIs are embedded within search engines, new opportunities for content discovery will emerge – sadly, however, I suspect this will result in an even deeper quagmire, leaving it to the key platforms to find a way through. Related to which, Artstation has now improved its AI search and browsing filters – it can hide artwork generated with AI in search and marketplaces and thereby ‘make it easier to discover and connect with creators most relevant to you’, but strangely it doesn’t promote only work created with AI in search.
On the matter of curation, a website for AI generators has launched, called All Things AI – AI developers can submit their tool to the site for its potential inclusion. The site has been developed by Rick Waalders, and whilst there are numerous AI tools and services on the site, there’s not much information yet about its creator or indeed reviews of the AIs themselves. If the site takes off, it might just be the place to find the apps you want – time will tell. Until then, blogs such as Pinar Seyhan-Demirdag‘s Medium post, dated 11 January, are great sources for curated content. In this post, Pinar lists more than a dozen 3D asset and scene generation models – a very useful summary, thanks. Now, what we really need is a Fandom wiki for AIs…!
The Legals are Circling
What a busy month it has been in lawyerland.
On 17 January, in San Francisco US, a class action suit was filed on behalf of three artists. It claims that Stability AI’s Stable Diffusion and DreamStudio, MidJourney and DeviantArt have colluded in the use of an AI that has been trained on scraped content that infringes the rights of copyright holders (the AI being created by a company called LAION which has connections to Stability AI) and that the results of its application by users has a detrimental impact on the artists making profit from their own work as a consequence. One of the legal team has written a detailed blog about the action here, and here is the link to the action, should you want a quick scan through its 46 pages. The following day, 18 January, Getty Images stated that it has commenced proceedings against Stability AI in the High Court of Justice in London –
… Stability AI infringed intellectual property rights including copyright in content owned or represented by Getty Images. It is Getty Images’ position that Stability AI unlawfully copied and processed millions of images protected by copyright and the associated metadata owned or represented by Getty Images absent a license to benefit Stability AI’s commercial interests and to the detriment of the content creators.
Getty Images believes artificial intelligence has the potential to stimulate creative endeavors. Accordingly, Getty Images provided licenses to leading technology innovators for purposes related to training artificial intelligence systems in a manner that respects personal and intellectual property rights. Stability AI did not seek any such license from Getty Images and instead, we believe, chose to ignore viable licensing options and long‑standing legal protections in pursuit of their stand‑alone commercial interests.
No more specifics are available on the Getty case. The latter comments are particularly interesting, however, given its stance with creative contributors whom it has banned from uploading AI generated content, something we highlighted in our December blog post.
On the US class action, notwithstanding the technicalities of its description of how the AI works (which some have already questioned as being incorrect), the action is primarily about two aspects of copyright infringement – one related to a company which is ‘licensing images’ for use in training the AIs (that a couple of the image generating companies are using); the other is the specific use of an artist’s name to generate an image ‘in the style of …’ which suggests that person’s specific work, tagged presumably with their name, has been used without their permission to train the AI. Those using the images ‘in the style of x’ are referred to as ‘imposters’ whom it is being argued are contributing to the fake economy (which different governments are currently trying to control). The suit is not against the imposters but those who allow imposters to profit.
The action holds that the companies ‘scraping’ the images (which is a metaphor for how images are actually used in the diffusion process) could provide a means to seek permission from those artists used but it has not done so because it is ultimately expensive and takes time to do. The action is for compensation of damages for lost revenue and damage to brand identity of artists. The premise for this is that the companies being sued are generating huge amounts of money that is not finding its way to those contributors whose work is used in the training processes. The money flows are therefore the areas where the ‘fair use doctrine’ is being brought to bear.
The substantive legal issue, however, seems to centre on transformative works (from derivative works). Corridor Crew has produced a nice summary in a video with California State attorney Jake Watson explaining how AI probably DOES transform the work sufficiently for its use of copyrighted images to constitute FAIR USE. So it still comes down to what fairness means in terms of money flows, ultimately. Here’s the video –
And for a line by line commentary on another perspective of the class action blog post by one of the artists’ legal team, a response has been created by a group of ‘tech enthusiasts uninvolved in the case, and not lawyers, for the purpose of fighting misinformation’. I hesitated to include this link, especially since the author/s are anonymous and the contact link is to an ancient Simpsons video sniping at profiteering lawyers, but it makes some interesting points and is well referenced.
It generally sounds like there is a fix to this problem, and its one we’ve highlighted in previous posts on this topic, where AI generator platforms pay artists to use their work… oh, wait, isn’t Shutterstock already doing that, working with OpenAI’s DALL-E? Yes, and here is its generator – it pays the artists (I couldn’t find how much) and users pay for the images downloaded ($19/month for 10 images or 1 video). The wicked problem here, Techcrunch argues, is will folks be willing to pay for AI generated artwork, suggesting yes they will if the generator service has the best selection, pricing, discovery, and overall experience for the user and the artist. And, DreamStudio Pro is already a paid for service that folks are using.
Or, you can opt out of your art being included in Stable Diffusion’s AI, using the third party HaveIBeenTrained web service by an artist-based startup called Spawning. It looks as though there have been a few problems using this service according to the comments, such as being able to tag anyone’s imagery, but even more surprising was that not many seem to have viewed the support video in comparison to all the hoo-haa in the media on this topic. Check out this video –
Alternatively, you can just head over to LAION’s website and opt out there (scroll to the bottom of the page), following the long-winded GDPR processes under the EU reparation system.
In the meantime, Artstation has updated its T&Cs to make it clear that scraping, reselling or redistributing content is not permited and furthermore, it has committed to not licensing content to AI generator platforms for training purposes. Epic’s stance is always interesting to note, but its business model is not tied to just this one type of offer as the other platforms are.
And finally on the legals this month, we were intrigued to note that the US Copyright Office appeared to have cancelled the registration of the first AI generated graphic novel, called Zarya of the Dawn (our feature image for this article, by Kristina Kashtanova), claiming it had ‘made an error’ in the registration process… turns out that they are still ‘working on a response’, stating their portal is in beta. This was not before the artist had made an extensive response to the apparent cancellation through her lawyer, Van Lindberg. Its worth taking a few minutes to read the claims for originality, using MidJourney to support her creative processes, here. In sum, the response states –
… the use of that tool does not diminish the human mind that conceived, created, selected, refined, cropped, positioned, framed, and arranged all the different elements of the Work into a story that reflects Kashtanova’s personal experience and artistic vision. As such, the Work is the result of human authorship…
So this is yet another situation where the outcome is awaited. More next month for sure!
This week, we highlight some character development tools, NeRFs, NFTs and environments for machinima and virtual production.
Beginning with the awe-inspiring toolset of Unreal Engine’s MetaHumans, the organization has released a FREE three-hours long online course for beginners on real-time animating with Faceware Analyzer and Retargeter tools. Here’s a taster of what you can expect –
A creator we’ve featured a number of times (his tutorials are awesome), JSFILMZ (our feature image) has posted a taster of MetaHuman’s Live Drive from Facegood, which launched in December. The demo shows straight from camera to Unreal but what’s amazing is the price for the head-mounted hardware of <$500! This obviously isn’t free but its good value compared to some of the other facial tracking hardware on the market, and Jae compares those to give you an overview of what you get for the money. The Facegood software itself, Avatary, is free though, which produces some impressive animations. Check out Jae’s introductory overview below, and then pick up his tutorials on each of the components he discusses on his channel –
Move.ai has launched its iPhone beta application for free markerless mocap (requires two phones). Ultimately, this isn’t going to be free to use so make the most of the beta sign-up opportunity – the official launch takes place in March 2023 and their main target in the first instance is professional studios, which will put this out of reach for many indies. This article gives you a quick overview (by 80.lv), and this short video explainer introduces their store –
And finally, on characters this month, we highlight Inworld AI. This organization is creating interactive conversational characters that can be exported and shared across various platforms, either as avatars or the underlying chatbot (think smart NPCs). Some of you may recall John Gaeta mentioned this in our interview with him last year, and since then, Inworld has become part of the Walt Disney Company’s Accelerator Programme, been awarded an Epic MegaGrant and raised a pot of money from investors. The application of the software is vast – everything from games to marketing, as well as machinima and virtual productions too… and that’s because of how the characters can be moulded. Inworld states: ‘When crafting your character’s brain, you are able to use the Studio to tailor many elements of cognition and behavior, such as goals and motivations, manners of speech, memories and knowledge, and voice‘. Inworld released a nice tutorial in December, link below. Its definitely one to try out –
We found a nice short on Neural Radiance Fields (aka NeRFs) by Corridor Crew, using the Luma AI app, which is truly stunning for recreating realistic anything. They highlight some of the key challenges, and present a very interesting test with a chrome ball – surely it is never going to possible to create this kind of object with dynamic reflections and all…? Check it out here –
As Corridor Crew states, this is clearly one of the next big tech things in image capture for CGI.
The fluid waters of NFTs continues to muddy. This article (by NFT Now) highlights some of the recent class action law suits being brought against creator platforms, suggesting that the markets are being artificially inflated by celebrity endorsers, although this is surely true for so many other products too? Its more an argument about the nature of the endorsement process and the stake in the investment that the endorser has that’s the issue here seemingly. One of the main challenges here is the fundemantal role of community in NFTs, which is always going to mean there is a very fine line on ‘insider trading’. Its also interesting to note that IP owners are now becoming more actively involved in this nascent space. Once again, whenever the legals get involved, everyday creatives are the losers, so whilst some of the actions highlighted are less directly relevant, the outcomes of the legal disputes ultimately will be, so we’ll keep tracking this.
Finally, we want to highlight a couple of environments for you.
Firstly, Half Life Alyx has a new mod, courtesy of Corey Laddo! Corey has created a mod that allows you to view the game in the role of Alyx Vance. Its designed to be a free of charge for owners of the game, and provides a 4-5 hour experience for ‘average players’. Great if you want to shoot content from a first person perspective. You can support Corey on his Patreon account, should you want to give him something for his effort. Download the mod from Steam here. Meantime, here’s a taster for you –
Secondly, Damien shared a new sandbox environment that will be launching soon (well, we think it will since its apparently been in dev since 2012), called Outerra World by Microprose. This looks amazing, and will allow you create any kind of realistic 1:1 scale terrain simulation, which you can share and navigate using any asset that the community creates and shares too. Here’s the link to the Steam page (to add your details to the waitlist).
If you have comments or thoughts on any of the techs this week, do go ahead and comment.