#AI use cases are narrow: a specific outcome needs to be achieved with your model. So why use oversized, slow general-purpose #LLMs that do an "okay" job on your task? 🤔 Teams that are serious about #production GenAI understand that small task-specific models (#SLMs) deliver the best possible performance for their use case with a much smaller, more #efficient footprint. 👣 We're honored to be recognized by Gartner as a GenAI #CoolVendor for leading the charge in small task-specific model training and serving. 😎 Check out Gartner's latest Cool Vendors report to learn more 👇 Thank you Arun Chandrasekaran, Manjunath Bhat, Arup Roy and George Brocklehurst for all of your great research! 👏
It was a privilege to lead Gartner's "Cool vendors in AI engineering" research. If you are unfamiliar, it is a research document where we highlight promising start-ups that IT leaders should consider on their shortlist. I am thankful to my co-authors, Manju, Arup and George for their support. To stay competitive, it's becoming more essential to consider partnerships with emerging startups. Numerous startups globally deserve attention. Without a readiness to take risks, enterprises and governments will miss out on unique opportunities to capitalize on. The cool vendors highlighted in this research have demonstrated innovative capabilities that are not yet widely adopted. These vendors, along with other startups, will need to find ways to enhance their offerings in an increasingly competitive space. Congrats to Anyscale, deepset, Predibase, unstructured.io and Sentient.io profiled in this research. Gartner clients can access this research from the portal. #AI #GenAI #startups #coolvendors #Gartner