In the AI realm, the release of the open-source Falcon 180B model marks a pivotal milestone in AI evolution. A model of such colossal dimensions unlocks incredible opportunities for organisations that are able to deploy them, but just attempting to deploy it brings about a host of different challenges, from hardware limitations to complicated technical eccentricities.
Seamless scalability with multi-GPU
With our enhanced multi-GPU infrastructure, you can scale up your AI deployments with ease. This cutting-edge feature ensures that integrating behemoth models like the Falcon 180B is not just possible, but also remarkably efficient.
Distributing the AI inference workload across multiple GPUs isn’t just about being able to fit large models. Titan Takeoff’s upcoming multi-GPU deployment leverages on Tensor Parallelism to amplify your application’s inference speed across multiple GPUs. Expect your applications, whether leveraging Falcon 180B or other models, to operate at peak performance with Titan Takeoff.
From niche AI models to titans like Falcon 180B, Titan Takeoff’s adaptability ensures your deployment needs are always met.
The release of the Falcon 180B model represents the future of AI, and Titan Takeoff is committed to making that future more accessible. Our forthcoming multi-GPU deployment feature promises to be a game-changer for AI enthusiasts, developers, and businesses alike.
TitanML enables machine learning teams to effortlessly and efficiently deploy large language models (LLMs). Their flagship product, the Titan Takeoff Inference Server is already supercharging the deployments of a number of ML teams.
Founded by Dr. James Dborin, Dr. Fergus Finn and Meryem Arik, and backed by key industry partners including AWS and Intel, TitanML is a team of dedicated deep learning engineers on a mission to supercharge the adoption of enterprise AI.
A quick note about licensing — the Titan Takeoff Inference Server is free to use in personal/academic projects (please credit us if you write it up publically! 😉) — message us at email@example.com if you would explore using the inference server for commercial purposes.
Written by Blake Ho