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National framework for microcredentials – Colleges and Institutes Canada
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How to win with generative engine optimization while keeping SEO top-tier
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Why agents are the next frontier of generative AI | McKinsey
- “agentic” systems refer to digital systems that can independently interact in a dynamic world.
- Gen AI agents eventually could act as skilled virtual coworkers, working with humans in a seamless and natural manner.
- a human user could direct a gen AI–enabled agent system to accomplish a complex workflow. A multiagent system could then interpret and organize this workflow into actionable tasks, assign work to specialized agents, execute these refined tasks using a digital ecosystem of tools, and collaborate with other agents and humans to iteratively improve the quality of its actions
- Google, Microsoft, OpenAI, and others have invested in software libraries and frameworks to support agentic functionality.
- shifting from being knowledge-based to becoming more action-based.
- The value that agents can unlock comes from their potential to automate a long tail of complex use cases characterized by highly variable inputs and outputs
- Agents can manage multiplicity
- Agent systems can be directed with natural language.
- Because agentic systems use natural language as a form of instruction, even complex workflows can be encoded more quickly and easily.
- done by nontechnical employees
- Foundation models can learn how to interface with tools, whether through natural language or other interfaces.
- control mechanisms are essential to balance autonomy and risk
- create a learning flywheel for ongoing improvement
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Saturday, August 10, 2024
Weekly Sporto bookmarks (weekly)
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