London, UK; 12th January 2022: TurinTech, the UK company which empowers businesses to build efficient and scalable AI by automating the whole data science lifecycle, has announced its greener AI platform- evoML- which reduces AI’s carbon emissions by 50%.
With the average carbon footprint of AI equivalent to five times the lifetime emissions of an average car, TurinTech is the first company to optimise model code efficiency for quicker inference speed, which lowers memory and energy consumption and reduces carbon emissions. It also uses multi-objective optimisation to help businesses speed up the end-to-end data science process from months to weeks, while also increasing the flexibility of model deployment.
Its multi-objective optimisation empowers businesses to build and enhance their models on-demand based on specific criteria. Businesses can therefore roll out AI to various clouds and devices at scale, while also maintaining accuracy and efficiency.
Last year, TurinTech’s product was used by hundreds of users, on more than 5,000 datasets and developed over 100,000 models. Using evoML, companies can overcome AI challenges by building optimal AI easier and faster.
Leslie Kanthan, CEO and co-founder at TurinTech, commented: “With evoML, businesses can have accurate machine learning models which are faster and consume less computing resources, all while increasing operating speed and reducing energy usage. Successfully scaling AI means building AI quicker, running AI faster, and deploying AI greener. That’s what we’re committed to at TurinTech.”
Ed Stacey, managing partner at IQ Capital, Forbes Contributor, added: “A first and essential step in deploying optimal ML in production is to optimise machine learning models and integrate them using scalable production code into the rest of the IT stack. Companies like TurinTech are early pioneers offering this capability.”
TurinTech recently announced its partnership with leading database company Exasol and has been selected as part of Tech Nation’s Applied AI 3.0 Cohort.