20 October 2024

AI Developer Meaning Machine appeared on a live Twitch broadcast on the 24th April. The broadcast was hosted by fellow indie developer Anything World.

Meaning Machine started with an AI program that commentated live on chess matches. Thieir website says “this eureka moment was adding live dialogue to dynamic real-time events (like boss battles).” They are also the minds behind the game ‘Dead Meat.’

-Meaning Machine

In the video Co-founder Ben Ackland and AI Development lead Dan Harbourne discussed their current innovations in AI for gaming.

Ben said: “Meaning Machine really is focussed on making games that push the boundaries of what we can do with modern tech. We try to make games and mechanics that weren’t possible even a year ago.

“We are handcrafting those in house. We’ve got a focus on conversation, on dialogue, on understanding whats going on in the game.”

Dan Harbourne said: “having the characters where yes, they can talk with you in an open way, and you can talk with them in an open way, and they have a backstory and all that. But also, they are able to perceive whats happening in engine and can react to things that happen.”

“That is the real differentiator between talking to a chatbot and developing the game like that.”

Gordon Co-founder of Anything World asked: “sometimes the larger gaming studios are a bit slow, I would have though microsoft or ubisoft would have made a game by now that was completely open. Why do you think that is?”

Harbourne replied: “we are seeing some of the big players make moves in some tech demos that came out. I think ubisoft had one that started to show this stuff.”

“The barriers are there are no tools that make it easy…actually giving game designers what they want rather than just open dialogue.”

What could all of this mean for gaming in the future? With the development of AI and the surge in virtual reality gaming, could we eventually be literally immersed in a virtual world? Being able to have unique conversations with NPC’s and mould the game world how we see fit.

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