Encoder-Free AI explained: The architecture behind Google’s Gemma 4 12B

A vast majority of multi-modal AI systems function as a relay race. For example, an image will come in through the Vision Encoder, be transformed into a language the Language Model understands and ...

Google's new open source Gemma 4 12B analyzes audio, video — and runs entirely locally on a typical 16GB enterprise laptop

For enterprise leaders aiming to decentralize their AI workloads, Gemma 4 12B offers a rare combination of edge-friendly efficiency and frontier-class reasoning.

Context compression finally works in production: new research cuts LLM input 16x without the accuracy hit

LCLMs compress LLM context before decode — 8.8x faster at 16x compression, beating every KV cache method tested. Open-sourced by NYU and Columbia.

Google drops Gemma 4 12B: A game-changing AI that runs on your laptop

India, June 7 -- Google has announced the launch of Gemma 4 12B, a dense multimodal model featuring a unified, encoder-free ...
Semiconductor Engineering

NPU Acceleration For Multimodal LLMs

Transformer-based models have rapidly spread from text to speech, vision, and other modalities. This has created challenges for the development of Neural Processing Units (NPUs). NPUs must now ...