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                <h1 class="text-4xl md:text-6xl font-serif font-bold mb-6 text-gold-500">Insights</h1>
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                    Perspectives on engineering intelligent systems — from technical architectures to governance frameworks.
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                            <span class="bg-gold-500/10 text-gold-500 text-xs px-3 py-1 rounded-full">Featured</span>
                            <span class="text-platinum-400 text-sm ml-4">June 2023</span>
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                        <h2 class="text-3xl md:text-4xl font-serif font-bold mb-4">Engineering AI Observability</h2>
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                            Modern AI systems require new approaches to monitoring that go beyond traditional metrics. We examine the architectural patterns and tooling needed for production-grade observability.
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                            <span class="bg-navy-700 text-xs px-2 py-1 rounded">AI Engineering</span>
                            <span class="bg-navy-700 text-xs px-2 py-1 rounded">Observability</span>
                            <span class="bg-navy-700 text-xs px-2 py-1 rounded">Monitoring</span>
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                    <h2 class="text-2xl md:text-3xl font-serif font-bold text-gold-500">Latest Perspectives</h2>
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                                <span class="text-platinum-400 text-sm">May 2023</span>
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                            <h3 class="text-xl font-bold mb-3">Optimizing GPU Cloud Costs</h3>
                            <p class="text-platinum-400 mb-4">Practical strategies for reducing cloud GPU spend while maintaining performance for AI workloads.</p>
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                                <span class="text-platinum-400 text-sm">April 2023</span>
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                            <h3 class="text-xl font-bold mb-3">AI Procurement Best Practices</h3>
                            <p class="text-platinum-400 mb-4">How government agencies can structure AI acquisitions to ensure technical and ethical requirements are met.</p>
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                                <span class="text-platinum-400 text-sm">March 2023</span>
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                            <h3 class="text-xl font-bold mb-3">Red Teaming AI Systems</h3>
                            <p class="text-platinum-400 mb-4">Our framework for adversarial testing of production AI systems to uncover vulnerabilities.</p>
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                                <span class="text-platinum-400 text-sm">February 2023</span>
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                            <h3 class="text-xl font-bold mb-3">Technical Debt in AI Systems</h3>
                            <p class="text-platinum-400 mb-4">Identifying and addressing technical debt patterns unique to machine learning systems.</p>
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                                <span class="text-platinum-400 text-sm">January 2023</span>
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                            <h3 class="text-xl font-bold mb-3">Kubernetes for AI Workloads</h3>
                            <p class="text-platinum-400 mb-4">Architecture patterns and operational considerations for running GPU workloads at scale.</p>
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                                <span class="text-platinum-400 text-sm">December 2022</span>
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                            <h3 class="text-xl font-bold mb-3">AI Governance Frameworks</h3>
                            <p class="text-platinum-400 mb-4">Comparing technical implementations of emerging AI governance requirements.</p>
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