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Deploying LLMs in High-Availability Architectures
In recent years, the integration of large language models (LLMs) into enterprise applications has dramatically accelerated due to their ability to understand, generate, and contextualize human language at scale. However, LLMs are resource-intensive and operationally complex, which presents a unique challenge when deploying them in high-availability (HA) architectures. High-availability systems are essential for mission-critical applications…
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Deploying LLMs with real-time compliance checks
The deployment of large language models (LLMs) has revolutionized industries ranging from customer support to legal research. However, with this transformative power comes a pressing need to ensure these models operate within ethical, legal, and regulatory boundaries. Real-time compliance checks during LLM deployment are not merely a technical feature—they are a critical safeguard that aligns…
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Design Considerations for Large Scale AI APIs
Developing and deploying large-scale AI APIs demands robust architectural planning, scalability considerations, and a deep understanding of machine learning systems, infrastructure, and user needs. These APIs often support thousands or millions of requests per day, with demands for low-latency, high-throughput responses. This article delves into the essential design considerations for building large-scale AI APIs that…
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Design for Production First_ Architecture Edition
Design for Production (DFP) is a principle that is traditionally applied in the world of manufacturing and industrial design, but its relevance has been expanding into other fields, including architecture. This concept involves considering the processes, tools, and resources available in the manufacturing phase during the design phase itself, ensuring that the final product is…
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Dealing with Scale-out vs. Scale-up Architectures
In the realm of IT infrastructure and system design, the debate between scale-out and scale-up architectures is pivotal for organizations striving to meet growing demands while optimizing performance and cost-efficiency. These two models represent fundamentally different approaches to resource management, and understanding their mechanics, advantages, and trade-offs is essential for building a robust, future-ready infrastructure.…
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Decision Logs as a Knowledge Management Tool
Decision logs are a valuable tool in knowledge management, serving as a systematic method for recording key decisions made during the course of a project, process, or within an organization. By documenting the rationale behind each decision, the stakeholders involved, and the impact of the decision, decision logs help preserve institutional knowledge, improve decision-making, and…
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Decomposing complex queries with LLMs
When dealing with complex queries, Large Language Models (LLMs) like GPT can be a powerful tool for breaking down the problem into more manageable parts. Here’s how LLMs can help in decomposing complex queries: 1. Identifying Key Components Complex queries often consist of multiple sub-questions or components. An LLM can break the query into smaller,…
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Defining KPIs for Software Architecture
Defining Key Performance Indicators (KPIs) for software architecture is essential to ensure that the architectural design aligns with the overall goals of the business and technical teams. KPIs provide a way to measure and evaluate the effectiveness, efficiency, and scalability of a software architecture over time. By monitoring the right KPIs, architects can identify potential…
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Defining the Architect’s Role on Cross-Functional Teams
In modern project environments, particularly within complex industries like construction, software development, and urban planning, the architect’s role has evolved significantly. Today, architects are often part of cross-functional teams, collaborating with professionals from various disciplines to achieve a cohesive and well-rounded solution. This collaborative approach fosters innovation, enhances problem-solving, and results in a more comprehensive…
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Deploying Foundation Models to Mobile Apps
Deploying foundation models to mobile apps is a growing trend, allowing users to leverage powerful AI capabilities directly from their smartphones. A foundation model, which is typically a large-scale AI model trained on massive datasets, can be adapted for use on mobile devices to enhance functionalities like image recognition, natural language processing, and real-time decision-making.…