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How to use an LMS for Effective Induction and Onboarding
Learn how to effectively use a Learning Management System (LMS) to enhance employee onboarding by defining goals, selecting the right platform, developing tailored content, and utilizing automation for a seamless experience.
The role of AI in building training courses
AI is transforming training courses by offering personalized learning paths, automating content creation, and providing real-time feedback, enhancing both the effectiveness and efficiency of educational programs.
Marketing Your Online Course for Success
The article offers strategies for effectively marketing online courses, focusing on defining target audiences, crafting compelling messaging, and leveraging social media and email campaigns. It also highlights the importance of partnerships and measuring results.
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How AI can support pupils with SEND
Explore how AI tools are aiding pupils with special educational needs and disabilities by simplifying text, breaking down tasks, and enhancing accessibility. Learn about the considerations schools should make before implementation.
AI policy and practice in further education
Further education colleges need distinct AI policies due to their unique mix of vocational courses, diverse age groups, and specific funding and inspection requirements. This guidance highlights the importance of tailored AI approaches in FE settings.
Turning AI Answers Into Shareable Documents
eLLM solves the issue of AI-generated answers being stuck in chat windows by allowing users to export them as structured documents like PDFs or Word files. This feature maintains formatting and structure, making sharing and filing seamless.
Getting Straight Answers with AI Instead of Hunting Through Policies
The article discusses how AI tools like eLLM can streamline finding answers within an organisation by searching accessible documents and providing direct answers with citations, saving time and reducing confusion from outdated documents.
Stopping the Shadow AI Problem
The article discusses the risks of "shadow AI," where staff use public AI tools without IT oversight, potentially compromising sensitive data. It suggests using local AI models like eLLM to keep data secure while still providing AI assistance.
AI Safeguarding and Oversight Without Slowing People Down
The article discusses the balance between AI safeguarding and usability, highlighting the need for oversight without excessive restrictions. It introduces eLLM, a system offering configurable query governance and reporting tools to ensure responsible AI use.
Keeping AI Spend Predictable
Organisations often face unexpected AI costs due to unplanned usage across departments. The eLLM system helps manage these expenses by routing queries to local models for everyday tasks, while reserving cloud models for more complex needs.
Growing Into AI Without a Rebuild
The article discusses how eLLM enables AI systems to scale incrementally without needing a complete rebuild, using local and cloud resources efficiently. It highlights the benefits of starting small and expanding capacity as demand grows.
Connecting Your Existing Tools to AI Safely
Learn how to safely connect AI assistants to existing tools with eLLM's Model Context Protocol, ensuring IT oversight, approval processes, and audit trails for sensitive actions. Discover more in the eLLM Knowledge Base.
Coding Assistance Without the Code Leaving the Building
The article discusses the challenges of using AI coding assistants in organisations, highlighting concerns about code security and offering a solution with eLLM's code API to keep code within the organisation's infrastructure.
An Assistant That Remembers How You Work
The eLLM assistant retains details about your role and preferences, eliminating the need to repeat information in every session. It offers a personal notebook for organising notes, ensuring a personalised and efficient user experience.
You're probably overpaying for AI and here's why
Many businesses overpay for AI by using a single provider for all queries, regardless of complexity. eLLM optimises costs by routing questions to the most suitable model, keeping data secure and providing detailed usage insights.