Unlocking Generative AI: A Guide for Business Leaders
As a company leader or IT decision-maker, you may have been inundated with discussions on generative AI. If you're ready to implement a large language model (LLM) chatbot for your employees or customers, a crucial question arises: how do you launch it, and what costs should you anticipate?
Introducing DeepInfra
DeepInfra, founded by former IMO Messenger engineers, seeks to simplify this process for business leaders. The company offers to deploy models on private servers at a competitive rate of just $1 per million tokens, significantly lower than OpenAI’s GPT-4 Turbo at $10 and Anthropic’s Claude 2 at $11.02.
Recently launched from stealth, DeepInfra announced an $8 million seed round led by A.Capital and Felicis. Their focus is on providing a suite of open-source model inferences, including Meta's Llama 2 and CodeLlama, as well as customized versions of these models.
DeepInfra’s Value Proposition
While much attention has been given to the GPU resources needed for training LLMs, the importance of ample compute power for reliable performance—called inferencing—cannot be overstated. According to CEO Nikola Borisov, the real challenge lies in efficiently serving multiple concurrent users on the same hardware.
"The key is to manage multiple users accessing the server simultaneously. Each token produced by these models requires significant computation and memory bandwidth," Borisov explains. To ensure optimal performance, businesses must focus on maximizing efficiency to prevent servers from being overloaded with redundant computing tasks.
DeepInfra’s founders draw on their extensive experience managing vast server fleets worldwide to address these challenges effectively.
Endorsements from Top Investors
Borisov and his co-founders have garnered recognition for their programming expertise. Aydin Senkut, a well-known entrepreneur and managing partner of Felicis, praised their capabilities, stating, "They have incredible experience, potentially only second to the WhatsApp team in building efficient infrastructure that serves hundreds of millions."
This infrastructure efficiency allows DeepInfra to offer its services at lower costs, making it appealing in an environment where businesses often face escalating AI expenses. Senkut notes, “If a company can achieve a 10x cost advantage in AI, it can disrupt the market significantly.”
Targeting SMBs with Open-Source AI
DeepInfra's initial focus is on small-to-medium-sized businesses (SMBs) that seek affordable access to state-of-the-art open-source language and machine learning models. "Our target customers want reliable access to top-tier models without breaking the bank," Borisov states.
The company closely monitors advancements in the open-source AI community, ready to adopt emerging models specialized for various tasks, from text generation to computer vision and coding.
Borisov expresses a belief in the continued growth and versatility of open-source solutions: "As models like Llama are published, many will create their variants with minimal computational demands, fueling a collaborative ecosystem."
Privacy and Security
DeepInfra’s inference hosting service appeals particularly to enterprises prioritizing data privacy. "We do not store or utilize any prompts submitted; they’re discarded once the user session ends," Borisov assures, emphasizing their commitment to privacy.
By leveraging DeepInfra’s services, businesses can navigate the complexities of adopting generative AI solutions efficiently and cost-effectively, ensuring they remain competitive in a rapidly evolving landscape.
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