Posts tagged ai

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The Geometric Memory: Teaching AI Without Breaking It
aimemorygeometry

The Geometric Memory: Teaching AI Without Breaking It

What if adapting a model did not mean rewriting its weights? WarpKernels treat memory as geometry: freeze the backbone, learn a tiny local metric, and tilt the representation space.

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Curvature Tensors Need Better Pictures
physicsgeometryai

Curvature Tensors Need Better Pictures

A reading note on Lee C. Loveridge's geometric interpretation of the Riemann tensor, Ricci tensor, scalar curvature, and why physical intuition matters.

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HRM-Text-1B and Efficient Pretraining
aimodelsresearch

HRM-Text-1B and Efficient Pretraining

Sapient's HRM-Text-1B is a useful signal: architecture and training objective can still move the efficiency frontier, not just model size.

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Supervisable AI Systems
aiagentsmemory

Supervisable AI Systems

The next useful AI systems will not just be more capable. They will be easier to inspect, correct, and trust while they work.

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Modern CSS Is Quiet Infrastructure for AI UIs
cssaiui

Modern CSS Is Quiet Infrastructure for AI UIs

The more capable AI systems become, the more their interfaces need to expose memory, intent, risk, and control with calm precision.

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Compute, Memory, and the Next Bottleneck in AI
aicomputememory

Compute, Memory, and the Next Bottleneck in AI

Compute keeps expanding, but the next useful frontier is not just bigger clusters. It is memory, agency, safety, and measurement.

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Papers I Am Reading on Agents, Memory, and Alignment
papersaimemory

Papers I Am Reading on Agents, Memory, and Alignment

A practical reading map for intent learning, grokking, memory, drift, and the safety problems that appear when agents persist over time.

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Physics Concepts Every AI Engineer Should Know
physicsaimemory

Physics Concepts Every AI Engineer Should Know

Entropy, drift, attractors, and signal velocity are not just metaphors. They are useful tools for thinking about memory, intent, and safer agents.

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