Category: LLM
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The Quiet Cost of Too Many Yeses: What AI Can Learn from Good Teachers
In the era of human education, there were teachers who stood out not because they rewarded every thoughtless answer, but because they listened, considered what a student offered—even in error—and then gently guided them toward better answers. The memory the writer shares — “I fondly remember teachers who didn’t immediately dismiss my answers with a…
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Kimi K2 Thinking: China’s New Contender in the LLM Reasoning Race
The global AI landscape has entered a phase of rapid escalation. Major players now outdo one another with an almost weekly cadence of new model releases—each “the best ever,” each more powerful, more capable, more efficient. And we users, fascinated and perhaps a little complicit, eagerly follow along, testing every new capability as the frontier…
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Bridging Context Engineering in AI with Requirements Engineering
How Emerging AI Research Could Reinvent Context Scenarios in Software Design Hey there, fellow software enthusiasts! If you’re like me, you’ve probably spent countless hours crafting context scenarios to nail down requirements in software development projects. These narrative-driven descriptions of user interactions in specific situations provide a rock-solid foundation for understanding what a system really…
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Transformers Are Injective: Why Your LLM Could Remember Everything (But Doesn’t)
The authors of “Language Models are Injective and Hence Invertible”, https://arxiv.org/abs/2510.15511, address a foundational question about transformer-based language models: do they lose information in the mapping from an input text sequence to their internal hidden activations? In more formal terms: is the model’s mapping injective (distinct inputs → distinct representations), and therefore potentially invertible (one…
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LLM-Guided Image Editing: Embracing Mistakes for Smarter Photo Edits
Imagine being able to tweak a photo just by telling your computer what you want. That’s the promise of text-based image editing, and Apple’s latest research takes it a step further. Apple’s team, in collaboration with UC Santa Barbara, has developed a new AI approach that lets users edit images using plain language descriptions. More…