A lot of companies think they have an AI problem. What they really have is a coherence problem across operating model, architecture, and capital allocation.
Today’s AI is still unreliable. Some researchers think solving that problem requires teaching AI systems to understand the world around them.
Revit-native AI eliminates 315 hours of facade coordination per project; Aufgang Architects among first partners ...
Recent experiments placing large language models in simulated nuclear crises have produced alarming headlines. “Bloodthirsty” ...
EU repairability rules aim to challenge planned obsolescence in smartphones by making devices easier to fix, potentially ...
SYNTHBODY(TM) introduces a new class of "smart drugs": protein therapeutics with built-in, multi-layered logic gates that actively change how they behave based on what they encounter in the body, a ...
It is being envisioned that the transition toward 6G networks would require a paradigm shift where in addition to the concept of "connected things" the ...
SYNTHBODY™ introduces a new class of “smart drugs”: protein therapeutics with built-in, multi-layered logic gates that ...
Meta's new hyperagent framework breaks the AI "maintenance wall," allowing systems to autonomously rewrite their own logic ...
As trade tensions reshape global alliances and channel partnerships, the chip industry’s resilience faces an unprecedented ...
Warehouse automation success is a software architecture problem, not a hardware problem. As automation density increases, ...
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