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Why microservices might be finished as monoliths return with a vengeance
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Getting started with AI agents (part 2): Autonomy, safeguards and pitfalls
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Getting started with AI agents (part 1): Capturing processes, roles and connections
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3 leadership lessons we can learn from ethical hackers
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Our brains are vector databases — here’s why that’s helpful when using AI
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AGI is coming faster than we think — we must get ready now
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Here are 3 critical LLM compression strategies to supercharge AI performance
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Enter the ‘Whisperverse’: How AI voice agents will guide us through our days
Why multi-agent AI tackles complexities LLMs can’t
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The great AI masquerade: When automation wears an agent costume
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Generative AI isn’t coming for you — your reluctance to adopt it is
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How (and why) federated learning enhances cybersecurity
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The AI edge in cybersecurity: Predictive tools aim to slash response times
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The human factor: How companies can prevent cloud disasters
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LLMs can’t outperform a technique from the 70s, but they’re still worth using — here’s why
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The ‘strawberrry’ problem: How to overcome AI’s limitations
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Skeptical about AI? It’s normal (and healthy)
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Onboarding the AI workforce: How digital agents will redefine work itself
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Why AI is a know-it-all know nothing
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Why prompt engineering is one of the most valuable skills today
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‘Harvest now, decrypt later’: Why hackers are waiting for quantum computing
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Have we reached peak human?
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Why data science alone won’t make your product successful
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What does it cost to build a conversational AI?
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AI orchestration: Crafting harmony or creating dependency?
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Get ready for a tumultuous era of GPU cost volatility
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Introducing AI’s long-lost twin: Engineered intelligence
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Why we need to check the gen AI hype and get back to reality
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AI and employment: Echoes of the past or a new paradigm?
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Living with trust issues: The human side of zero trust architecture
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Is the next frontier in generative AI transforming transformers?
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The economics of GPUs: How to train your AI model without going broke
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From data to insight to action: The very human challenges of AI transformation
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LLM progress is slowing — what will it mean for AI?
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Gen AI’s awkward adolescence: The rocky path to maturity
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In the age of gen AI upskilling, learn and let learn
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