MISSION
Our industry-first optimiser delivers more capable models faster while saving millions of hours of compute, megawatts, and dollars.
PROBLEM
Arms race to build the biggest LLMs
Our industry-first AI-driven optimiser enables our customers to train more capable AI models with less data and compute, by delivering substantial boosts in sample efficiency. This leads to significant performance gains and training-time speed-ups, empowering teams to iterate - and innovate - faster. And because our optimiser is itself a Foundation Model, customers can fine-tune it to be even more effective on the networks and datasets they care about.
100B
(USD)
AI models by 2027, projected by leaders and experts in the field.
100M
USD
or more total training costs for GPT-4 and similar LLMs.
10x
Surge in costs for each new generation of models.
24MWh
PER DAY
Average energy consumption of a data centre cluster for operating GPUs during training and inference, raising concerns about energy grid sustainability.
15M
KG CO2
Estimated carbon emissions produced during a single training run for certain frontier LLMs, equivalent to the annual emissions of 3200+ average cars
COMING SOON
A revolutionary foundation model to optimise AI
About us
At Inephany, we’re reimagining how ML models learn, adapt, and perform. Instead of accepting the inefficiencies of today’s AI systems, we’re building tools that help teams train smarter. We believe progress comes from doing things better, not just bigger.
Inephany is pioneering advanced AI-powered optimisation techniques for improving the efficiency of neural networks and LLMs at both training and serving time.. This includes the Transformers used for Generative AI, the RNNs used for financial time series modelling, or the CNNs used for object recognition in self-driving cars.
Want to join our waitlist?
Drop us a line
waitlist@inephany.com