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Artificial intelligence is no longer a technology confined to research labs or futuristic discussions.Continue reading on Medium »
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Frank Morales Aguilera, BEng, MEng, SMIEEEContinue reading on AI Simplified in Plain English »
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DeepSeek quietly added one line to its changelog and a new model ID to its API:Continue reading on Medium »
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A practical, no-fluff breakdown of how to turn raw artificial intelligence into strategic, audience-ready content.Continue reading on Medium »
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I recently came across InfinitAI, an AI-focused platform that caught my attention because it s designed around making AI more accessible Continue reading on Medium »
In the HBS Foundry program, AI avatars provide feedback during practice pitches and board meetings.
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For much of the past two years, the general belief in enterprise AI has been that more autonomy equals better performance. Build agents that can plan, decide, and act across multi-step workflows, and give them as much room to run as possible. That assumption is now being tested at scale, in real production environments — and in a lot of deployments it s failing. The companies that end up benefiting from agentic AI won t necessarily be the ones that have given their agents the most flexibility. They re the ones who create AI agents with specific responsibilities and make sure they operate within clear rules.Two numbers tell you almost everything about where agentic AI stands in mid-2026. By Gartner s own forecast, more than 40% of the agentic AI projects running today won t survive to see 2028. Not because the models fall short; because of escalating costs, unclear business value, and inadequate risk controls. McKinsey s 2026 AI Trust Maturity Survey fits right alongside that prediction