Create objectives.md

objectives.md

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+TENSOR - Temporal Engine for Neurual Search and Optimization runtime
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+TENSOR explores whether transformer-native computational paradigms can evolve into generalized computational substrates capable of compressing fragmented forecasting, search, optimization, and temporal reasoning systems into unified tensor-native runtimes.
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+Core Thesis
+TENSOR investigates whether transformer-native computation can absorb or compress forecasting, optimization, search, planning, routing, and temporal reasoning systems into unified tensor-native runtimes.
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+Primary Hypotheses
+• Attention mechanisms may function as generalized latent computational operators.
• Transformer-native runtimes may reduce orchestration overhead and memory movement.
• Unified tensor runtimes may eventually outperform fragmented software stacks.
• Transformer-native architectures may align naturally with future hardware fabrics.