30 秒でわかる
In this August 2024 short, Matthew Berman describes NVIDIA ACE and the potential of AI-powered game characters. The video identifies him as an NVIDIA partner; its example of Mecha BREAK refers to an NVIDIA technology showcase.
- 1A local model for game charactersBerman says developers can use the Nemotron-4 4B model locally on RTX hardware as part of an AI character system.
- 2From speech to animated responseHe describes speech recognition, language processing, text-to-speech and facial animation as components that can make NPC interactions more lifelike.
- 3A game showcaseNVIDIA presented Mecha BREAK as a showcase of ACE digital-human technology. Berman also points viewers to an online NVIDIA digital-human experience.
ポイント
- NVIDIA ACE combines speech, language and animation technologies for digital characters.
- Nemotron-4 4B Instruct was presented as an on-device language model for game-character interactions on RTX systems.
- NVIDIA showcased the technology in a Mecha BREAK demo and offered a digital-human interaction experience online.
チャプターごとに整えた全文を読む
AI-powered game characters
Berman introduces NVIDIA ACE and his expectation that digital humans could change games.
Remember NVIDIA ACE and those striking digital humans? I think this kind of technology could change video games by making characters feel more alive. This video is part of an NVIDIA partnership, as disclosed in its description.
Model, speech and animation
He describes an on-device language model and the speech and facial-animation components of the character pipeline.
Game developers can use NVIDIA ACE to build AI-powered non-player characters. The Nemotron-4 4B Instruct model can run locally on RTX hardware, giving a character a language model for responding to a player.
The character pipeline can combine Riva automatic speech recognition, natural-language processing, text-to-speech and Audio2Face facial animation. Together, these components can turn spoken input into an answer with a moving face; the exact services and where they run depend on the implementation.
Mecha BREAK and online demo
He points to an early game showcase and NVIDIA’s online digital-human experience. The video description identifies him as an NVIDIA partner.
NVIDIA presented Mecha BREAK as an early showcase for its digital-human technology. The company’s 2024 showcase used an on-device language model and animation, with speech recognition on-device and voice synthesis in the cloud. I also point viewers to an NVIDIA online digital-human experience and its AI Decoded blog for more details.
同じチャンネルの記事
34:21EN
Matthew Berman· 2026年10月27日Matthew Berman Examines Anthropic’s IPO Filing, AI Growth and GovernanceMatthew Berman, Sam Altman · Forward FutureThe presenter reviews the S-1’s financial metrics, compute strategy and voting structure while questioning the tension between rapid AI development and safety.
0:26ENMatthew Berman· 2026年10月25日Sam Altman on Human Values and Problem-Solving in an AI WorldSam Altman · OpenAIIn a short interview excerpt, Altman considers the enjoyment of solving hard problems and the human role in interpreting results.
0:36ENMatthew Berman· 2026年10月25日Kimi K3.1 and a Rubik’s Cube Solver DemonstrationMatthew Berman · Forward FutureMatthew Berman shows a scrambled virtual cube being solved and gives the Kimi K3.1 test a favorable assessment.
0:21ENMatthew Berman· 2026年10月24日An AI-Generated Kimi Benchmark Chart Used Invented ScoresMatthew Berman · Forward FutureMatthew Berman asks for a graph of Kimi K3.1 Pro benchmarks, then discovers that the displayed figures are illustrative placeholders.
25:50ENMatthew Berman· 2026年10月24日Kimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.
32:20ENMatthew Berman· 2026年10月23日Who Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.