Exclusive | The Sudden Fall of OpenAI’s Most Hyped Product Since ChatGPT - WSJ
Exclusive | The Sudden Fall of OpenAI’s Most Hyped Product Since ChatGPT WSJ
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These startups both released groundbreaking induction stoves. Now they’re embroiled in a lawsuit
Impulse, a sleek induction stove that began shipping to customers last year, advertises itself as “ unlike any other induction stove ever made .” But that product is now at the center of a legal fight. Copper, another company making next-generation induction stoves , sued Impulse on Friday in federal court in Delaware for patent infringement. At the center of the dispute is a shared design choice: Both companies build stoves with batteries tucked inside, a feature that boosts performance, eases installation in homes without electrical upgrades, and doubles as energy storage to ease strain on the electric grid. It’s a novel idea, and one that Copper patented first. In a copy of the lawsuit obtained by Fast Company , Copper claims its founders began developing the technology as early as 2019
Long Term AI Memory by creator of Apache Cassandra
cortexdb.ai CortexDB is the long-term memory layer for AI systems — The problem is fundamental: today's AI agents are stateless. Every conversation starts from zero. The dominant approach to giving AI memory — having an LLM rewrite and merge your data on every single write — is lossy, fragile, and ruinously expensive. The LLM decides what to keep and what to throw away, replaces the original with a summary, and that decision is irreversible. Information it deemed unimportant today may be exactly what a future query needs tomorrow. CortexDB takes a fundamentally different approach: every piece of information is appended to an immutable event log and never overwritten. A lightweight LLM extracts entities and relationships asynchronously, but the original data is always preserved — if the ext
Prologue: After We No Longer Write Code by Hand, What Remains for Engineers?
1. A Question We Can No Longer Avoid See Figures 0-1 and 0-2 in this chapter. Over the past decade, software engineers have had a broadly stable understanding of themselves. We proved our value by writing implementations, reading systems, fixing bugs, refactoring, and aligning team collaboration. Even as job specialization became more detailed, that central image did not change: an engineer was, first of all, someone who personally built complex things. But once agents began to enter real development workflows, that image was quietly unsettled. Code implementation, test scaffolding, documentation patches, simple regressions, fault reproduction, and localized fixes—more and more steps that once depended on human hands began to be handed over to models. The change is uneven and far from comp
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Long Term AI Memory by creator of Apache Cassandra
cortexdb.ai CortexDB is the long-term memory layer for AI systems — The problem is fundamental: today's AI agents are stateless. Every conversation starts from zero. The dominant approach to giving AI memory — having an LLM rewrite and merge your data on every single write — is lossy, fragile, and ruinously expensive. The LLM decides what to keep and what to throw away, replaces the original with a summary, and that decision is irreversible. Information it deemed unimportant today may be exactly what a future query needs tomorrow. CortexDB takes a fundamentally different approach: every piece of information is appended to an immutable event log and never overwritten. A lightweight LLM extracts entities and relationships asynchronously, but the original data is always preserved — if the ext
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