For enterprise generative AI adoption, custom models are key

AI models like GPT-4 are in high demand, but establishing the optimized infrastructure to support them can be expensive and complex. There are many organizations facing the challenge of balancing security and compliance requirements while maintaining the computational power needed to run generative AI at a massive scale. For this reason, some organizations choose to host their systems in their own data centers.

Tabnine understands the challenges of acquiring the hardware necessary for these AI advancements. While our cloud solution provides a convenient and expedient option, we acknowledge that it may not meet the stringent security prerequisites of all our customers. In an article for TechTarget Business Technology, our CEO, Dror Weiss, discussed the obstacles associated with implementing generative AI in enterprise environments, including security, infrastructure demands, and integration with existing systems.

As we continue to push the boundaries of AI, we must remain cognizant of these challenges. For a comprehensive understanding of this topic, we invite you to read the full article.

If you’re an enterprise looking to integrate AI into your software development lifecycle, Tabnine is a great option.

You can boost your productivity by streamlining repetitive coding tasks and producing high-quality, industry-standard code with Tabnine Enterprise. Tabnine code suggestions are based on Large Language Models that are exclusively trained on credible open-source licenses with permissive licensing. You can also run Tabnine Enterprise on-premises or in a virtual private cloud (VPC), ensuring that you maintain full control over your data and infrastructure. For more information on how Tabnine Enterprise can benefit your organization, feel free to contact our enterprise expert.