Embedl's Blog on Deep Learning
The cost of running frontier AI models
Research groups pushing the limits of artificial intelligence are running into a new kind of barrier. The economic cost ...
Ultra-Efficient SLMs: Embedl’s Breakthrough for On-Device AI
Embedl has released a major milestone for efficient LLMs: introducing FlashHead, a training-free, hardware-friendly drop...
Intelligence per Watt: Edge versus Cloud
A new paper1 from a group at Stanford has set up new metrics to evaluate the energy efficiency of AI models: intelligenc...
EDGE AI Talks: Faster Time-To-Device with Embedl Hub
Watch EDGE AI Talks: Faster Time-To-Device with Embedl Hub, with Our Product Owner Andreas Ask. Edge AI is redefining ho...
Efficiency Is the Key to Sustainable AI
The recently announced strategic partnership between OpenAI and NVIDIA has spotlighted the issue of AI energy consumptio...
Hardware Aware Model Optimization
You probably hit a wall if you've ever trained a high-performing deep learning model and tried to deploy it to an embedd...
Agentic AI is Accelerating – But Can It Reach the Edge?
2025 is shaping up to be the year of agentic AI. Identified as one of the most transformative technology shifts on the h...
Llama 4 on the Edge: Overcoming Limitations of Deploying Mixture-of-Experts on Edge Devices
Introduction Mixture-of-Experts (MoE) has emerged as one of the most promising approaches for scaling up large generativ...