How Generative AI can potentially disrupt gaming

What is Generative AI?

Generative AI is a category of machine learning where computers can generate original new content in response to prompts from the user

Today text and images are the most mature applications of this technology, but there is work underway in virtually every creative domain, from animation, to sound effects, to music, to even creating virtual characters with fully fleshed out personalities.

Assumptions

  • The amount of research being done in general AI will continue to grow, creating ever more effective techniques
  • Of all entertainment, games will be the most impacted by Generative AI
  • There will be a generative AI model for every asset involved in game production
  • Price of content will drop dramatically

Predictions

  • Learning how to use Generative AI effectively will become a marketable skill
  • Lowering barriers will result in more risk-taking and creative exploration
  • A rise in AI-assisted “micro game studios”
  • An increase in the number of games released each year
  • New game types created that were not possible before AI
  • Value will accrue to industry specific AI tools, and not just foundational models
  • Run AI needs deep understanding of a particular audience, and needs to be able to identify targets for monetization

Recommendations

  • Start exploring Generative AI now
  • Look for market map opportunities
  • Some parts of the market are crowded, like Animations or Speech & Dialog, but other areas are wide open
  • Entrepreneurs interested in this space should focus their efforts on areas that are still unexplored

Current state of the market

  • A market map to capture a list of companies we’ve identified in each of these categories where we see Generative AI impacting games

Concept Art

  • Generative AI tools are excellent at “ideation” or helping non-artists, like game designers, explore concepts and ideas very quickly to generate concept artwork, a key part of the production process.
  • 2D Images
  • Tools like Midjourney, Stable Diffusion, and Dall-E 2 can generate high quality 2D images from text.

Market Map

  • Artwork
  • Models
  • Textures
  • Animation
  • Level design and world building
  • Generative AI models that can capture animation straight from a video
  • Can also be used to apply filters to existing animations
  • The following concepts were generated by Midjourney using the prompt, “A game level in the style of…”

Audio and Sound Effects

  • Sound and music are a huge part of the gameplay experience, and companies are beginning to see companies using Generative AI to generate audio to complement the graphics side.
  • Real-time generative AI models can generate appropriate sound effects, on the fly, slightly differently each time, that are responsive to in-game parameters such as ground surface, weight of character, gait, footwear, etc.
  • Speech and Dialog
  • Generate dialog on-the-fly.

NPCs or Player Characters

  • Many startups are looking at using generative AI to create believable characters you can interact with, partly because this is a market with wide applicability outside of games
  • Hundreds of companies build general purpose chatbots, many of them powered by the GPT-3 like language models
  • A smaller number are specifically trying to build chatbots for the purpose of entertainment

All-in-one platforms

  • Runwayml brings together a broad suite of creator tools in a single package

Conclusion

  • This is an incredible time to be a game creator
  • It’s even possible to one day imagine an entire personalized game, created just for the player, based on what the player wants

Read the original piece on a16z website.