Blog
Engineering updates and perspectives from our team
Your AI Model is Already Free
Most deployments follow the same pattern: you build and train on GPUs using a de-facto standard environment based on CUDA for R&D. Then, almost by habit, you may assume deployment also has to be CUDA-centric if you want high performance.
That assumption is expensive. It nudges you into architecting y
Cervell and the Changing Shape of AI Infrastructure
AI infrastructure is no longer defined by how much raw compute you can deliver, but by how efficiently you can run it at scale. Hyperscalers are under pressure from ballooning inference costs, memory bottlenecks, and the thermal and power ceilings of their datacenters. Adding TOPS alone doesn’t solve the problem. What matters is keeping pipelines full, racks utilized, and workloads flexible across different tiers of deployment.
AI runs on vectors
A key trend in AI recently has been the emphasis on vectorizing data. That is not a technical recommendation, but rather a fundamental shift in enterprise data and AI strategy. To thrive in the new industrial revolution, companies must transform into AI-powered organizations, rethinking how data flows, scales, and drives decision-making.
One Instruction Stream, Infinite Possibilities: The Cervell™ Approach to Reinventing the NPU
AI is evolving faster than the chips designed to run it. Models like large language transformers and generative networks are shifting rapidly–while silicon development cycles remain long and rigid. Traditional NPUs, built around proprietary instruction sets and opaque compilers, simply can’t keep up.That’s why Semidynamics built Cervell™, a new kind of Neural Processing Un
Vision-Language Models (VLM) – the next big thing in AI?
AI has changed a lot in the last ten years. In 2012, convolutional neural networks (CNNs) were the state of the art for computer vision. Then around 2020 vison transformers (ViTs) redefined machine learning. Now, Vision-Language Models (VLMs) are changing the game again—blending image and text understanding to power everything from autonomous vehicles to robotics to AI-driven assistants. You’ve probably heard of the biggest ones, like CLIP and DALL-E, even if you don’t know the term VLM.Here’s the problem: most AI hardware isn’t built for this shift. The bulk of what is shipping i
