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Drug discovery has traditionally been a reductive process—narrowing down, filtering out, and optimizing within established ...

Angelic Intelligence, as Stage III, proposes inverting the architecture entirely: embedding virtue directly into the computational subsrate from the first line of code, rather than layering ethical ...

The computing community has largely treated AI hallucinations as a model problem. The default path to reliability has been model improvement: better training data, larger context windows, retrieval ...

In physical systems where errors carry tangible consequences, AI creates value through reliability and first-time-right performance.

The energy innovation system transition is shifting focus from capacity expansion to system coordination, integration, and AI-driven grid optimization.

Trade instability, tightening freight capacity, and rising sustainability requirements are increasing cost pressure across transportation and logistics networks. New findings from Info-Tech Research ...

Adjusted EBITDA for Q4 was approximately $0.3 million, compared to $3.8 million in Q4 2024. Selling, general and administrative expenses were $6 million, flat year-over-year. Cash at year-end totaled ...

Abstract: Time-variant convex optimization involving nonlinear inequality constraints (TVCOINICs) is a challenging problem due to the nonlinearity and time-variant nature of its objective function and ...

Abstract: The development of orthopedic robots for epiphyseal surgery is still in its nascent stages, with lacking considerations for autonomous path planning and biological force. The objective of ...