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This release transforms PING into a sophisticated newspaper-style digital publication with enhanced readability and professional presentation. Major Features: - New FeaturedPostHero component with full-width newspaper design - Completely redesigned homepage with responsive newspaper grid layout - Enhanced PostCard component with refined typography and spacing - Improved mobile-first responsive design (mobile → tablet → desktop → 2XL) - Archive section with multi-column layout for deeper content discovery Technical Improvements: - Enhanced blog post validation and error handling in lib/blog.ts - Better date handling and normalization for scheduled posts - Improved Dockerfile with correct content volume mount paths - Fixed port configuration (3025 throughout stack) - Updated Tailwind config with refined typography and newspaper aesthetics - Added getFeaturedPost() function for hero selection UI/UX Enhancements: - Professional newspaper-style borders and dividers - Improved dark mode styling throughout - Better content hierarchy and visual flow - Enhanced author bylines and metadata presentation - Refined color palette with newspaper sophistication Documentation: - Added DESIGN_BRIEF_NEWSPAPER_LAYOUT.md detailing design principles - Added TESTING_RESULTS_25_POSTS.md with test scenarios This release establishes PING as a premium publication platform for AI orchestration and contextual intelligence thought leadership. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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title, description, date, publishDate, author, tags, featured
| title | description | date | publishDate | author | tags | featured | ||||||||
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| Hierarchical Reasoning Models: A Quiet Revolution | HRM points to a future where intelligence comes from structure, not just size — and why that matters for CHORUS. | 2025-03-15 | 2025-03-15T09:00:00.000Z |
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As AI systems become more sophisticated, the focus is shifting from sheer model size to how knowledge is structured. Hierarchical Reasoning Models (HRMs) provide a framework where intelligence emerges from organization, not just raw computation.
The Case for Hierarchy
Hierarchical structures allow AI to process information at multiple levels of abstraction. High-level concepts guide reasoning across domains, while low-level details inform precision tasks. This organization enables more coherent, consistent, and scalable reasoning than flat, monolithic architectures.
Advantages of HRMs
- Scalability: Agents can reason across complex problems by leveraging hierarchy without exploding computational demands.
- Explainability: Layered structures naturally provide context and traceable reasoning paths.
- Adaptability: Hierarchical models can integrate new knowledge at appropriate levels without disrupting existing reasoning.
HRM in Practice
CHORUS is exploring how hierarchical memory and reasoning structures can enhance AI agent performance. By combining temporal context, causal relationships, and layered abstractions, agents can make decisions that are more robust, transparent, and aligned with user objectives.
Takeaway
Intelligence is increasingly about structure over size. Hierarchical Reasoning Models offer a blueprint for AI systems that are smarter, more adaptable, and easier to understand, marking a quiet revolution in how we think about AI capabilities.