SMS remains a staple in commercial interactions, but its limitations are becoming increasingly evident, particularly for brands seeking deeper buyer engagement. This has paved the way for the meteoric rise of Google RCS Business Messaging (RBM) as a powerful and dynamic alternative. In fact, the protocol has witnessed an astounding 684% surge in usage within …
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Although Large Language Models (LLMs) have shown promise for human-like conversations, they are primarily pre-trained on text data. Incorporating audio or video improves performance, but collecting large-scale multimodal data and pre-training multimodal LLMs is challenging. To this end, we propose a Fusion Low Rank Adaptation (FLoRA) technique that efficiently adapts a pre-trained unimodal LLM to …
Capital markets operation teams face numerous challenges throughout the post-trade lifecycle, including delays in trade settlements, booking errors, and inaccurate regulatory reporting. For derivative trades, it’s even more challenging. The timely settlement of derivative trades is an onerous task. This is because trades involve different counterparties and there is a high degree of variation among …
In today’s globalized marketplace, finding and understanding reviews in a customer’s preferred language across multiple languages can be challenging. BigQuery is designed for managing and analyzing large datasets, including reviews. In this blog post, we present a solution that uses BigQuery multilingual embeddings, vector index and vector search, to let customers search for products or …
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Computers have come so far in terms of their power and potential, rivaling and even eclipsing human brains in their ability to store and crunch data, make predictions and communicate. But there is one domain where human brains continue to dominate: energy efficiency.
Applying Quality of Service techniques at the application level Anirudh Mendiratta, Kevin Wang, Joey Lynch, Javier Fernandez-Ivern, Benjamin Fedorka Introduction In November 2020, we introduced the concept of prioritized load shedding at the API gateway level in our blog post, Keeping Netflix Reliable Using Prioritized Load Shedding. Today, we’re excited to dive deeper into how we’ve …
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We are excited to announce the availability of the Jamba-Instruct large language model (LLM) in Amazon Bedrock. Jamba-Instruct is built by AI21 Labs, and most notably supports a 256,000-token context window, making it especially useful for processing large documents and complex Retrieval Augmented Generation (RAG) applications. What is Jamba-Instruct Jamba-Instruct is an instruction-tuned version of …
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Are you an SRE (or SysAdmin, DevOps Engineer or Systems Architect?) grappling with the ever-growing complexity of modern systems? Generative AI, including Google’s Gemini for developers, offers a toolkit that can help streamline your operational tasks and boost efficiency. To help you get started, here’s a curated list of resources that will help you gain …
Read more “Free to be SRE — how to use generative AI to code, test and troubleshoot your systems”
This post is a continuation of Creating Natural Conversations with Amazon Lex QnAIntent and Amazon Bedrock Knowledge Base. In summary, we explored new capabilities available through Amazon Lex QnAIntent, powered by Amazon Bedrock, that enable you to harness natural language understanding and your own knowledge repositories to provide real-time, conversational experiences. In many cases, Amazon …
Insights from Product Reliability Engineers Intro Palantir’s platforms (AIP, Foundry, Gotham, Apollo) underpin mission-critical workflows throughout the world, whether it’s facilitating the resettling of over 100,000 refugees fleeing the war in Ukraine or reducing waiting times for life-saving cancer care. The Product Reliability Incident Management team’s core mandate is to address the highest-priority issues across …
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