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Add “, yet” to the headline and come back in a year or two.
Currently AI may fail to produce a video game, but so was the case for images, videos, and texts only a few years ago.
Failure is a good thing because it’s preceded by attempt.
I am astonished by an established, commercial website having good structure.
It looks like a documentation website. Sidebar with clear categories and navigation. I really like it.
“Replacing Talent” is not what AI is meant for, yet, it seems to be every penny-pinching, bean counting studio’s long term goal with it.
sed “s/studio’s/tech industry c-suite’s/“As an engineer, the amount of non-engineering idiots in tech corporate leadership trying to apply inappropriate technical solutions to something because it became a buzzword is just absurdly high.
The article doesn’t say much. So I checked the source for more information. It doesn’t say much more, but IMO in a much better way, in two concise paragraphs. In the sourced financial report, it is in the intro, two paragraphs:
An example R&D initiative, sponsored by the Innovation team was Project Ava, where a team, initially from Electric Square Malta, attempted to create a 2D game solely using Gen AI. Over the six-month process, the team shared their findings across the Group, highlighting where Gen AI has the potential to augment the game development process, and where it lags behind. Whilst the project team started small, it identified over 400 tools, evaluating and utilising those with the best potential. Despite this, we ultimately utilised bench resource from seven different game development studios as part of the project, as the tooling was unable to replace talent.
One of the key learnings was that whilst Gen AI may simplify or accelerate certain processes, the best results and quality needed can only be achieved by experts in their field utilising Gen AI as a new, powerful tool in their creative process. As a research project, the game will not be released to the public, but has been an excellent initiative to rapidly spread tangible learnings across the Group, provide insights to clients and it demonstrates the power and level of cross-studio collaboration that currently exists. Alongside Project Ava, the team is undertaking a range of Gen AI R&D projects, including around 3D assets, to ensure that we are able to provide current insights in an ever- evolving part of the market
The central quote and conclusion being:
One of the key learnings was that whilst Gen AI may simplify or accelerate certain processes, the best results and quality needed can only be achieved by experts in their field utilising Gen AI as a new, powerful tool in their creative process.
Which is obvious and expected for anyone familiar with the technology. Of course, experiments and confirming expectations has value too. And I’m certain actually using tools and finding out which ones they can use where is very useful to them specifically.
The overall point may be relatively obvious, but the details are not.
Which steps of which processes is it good at, and which not? What can be easily integrated into existing tooling? Where is is best completely skipped?
Yes, exactly. That’s what I was referring to in my last sentence.
Huh, would you look at that.
