Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace. We invite submissions with a focus on our favored technology topics areas: big data, data science, machine learning, AI and deep learning. Enjoy!
Vector data will be foundational for next-generation AI applications. Commentary by Avthar Sewrathan, AI Lead at Timescale
“The rise of large language models (LLMs) like GPT-4 and Llama 2 is driving explosive growth in AI applications powered by vector data. Developers need to efficiently store and query vectors to power next-generation AI systems. Vector data is useful for tasks like text and image generation, providing LLMs long-term memory beyond the current conversation, and giving LLMs relevant context from company-specific or private datasets (via retrieval augmented generation).
There are a myriad of vector databases in the market, with new ones popping up seemingly every week. This leaves developers facing a paradox of choice. Do they adopt new, niche databases built specifically for vector data? Or do they use familiar, general-purpose databases with extensions for vector support?
I have seen this dynamic before in other markets, namely time-series. Despite the existence of niche...
Read Full Story: https://news.google.com/rss/articles/CBMiQ2h0dHBzOi8vaW5zaWRlYmlnZGF0YS5jb20vMjAyMy8wOS8xMS9oZWFyZC1vbi10aGUtc3RyZWV0LTktMTEtMjAyMy_SAQA?oc=5
Your content is great. However, if any of the content contained herein violates any rights of yours, including those of copyright, please contact us immediately by e-mail at media[@]kissrpr.com.
