To create a model that excels at everything must be substantially larger than any model designed to specialize in specific tasks—both in terms of parameters and the volume of data it has been trained on posing several practical challenges. Running a LLM also significantly impacts revenue due to higher operational costs and increased latency when compared to smaller, more focused models. Additionally, there's a critical existential risk: developing a LLM-based application while having no control over the underlying LLM you depend on.
Training and deploying small language models also present considerable challenges. Data acquisition and fine-tuning are bottlenecks due to the complexity of the techniques and tools required. Additionally, managing the necessary infrastructure is demanding, and the associated costs can be substantial.
SWIFT is one of the few companies developing AI applications with a fully integrated approach—covering everything from training and models to serving, integrations, and the final product—without relying on OpenAI. We deliver more secure, private, custom AI solutions that perform better than frontier commercial out of the box LLMs like ChatGPT.
Maintaining the highest security standards and integrity, our SWIFT AI generative products reference trusted sources ensuring authentic, accurate, and relevant generated AI Outputs. Furthermore, we never train on non-permissively licensed content, protecting our clients from legal risks, unlike Microsoft Copilot.
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