Initialization on devices; shape inference and projections with strides

[lukstafi]

Report by Claude with main focus since start of July:

• Major Release 0.6.0 with comprehensive new features for deep learning
  • Added support for Bfloat16 and FP8 precisions, critical for modern ML training
    efficiency
  • Implemented convolution support with affine indexing expressions in projections,
    einsum notation, and shape inference
  • Added counter-based randomness via Threefry4x32 operation for reproducible random
    number generation
  • Introduced bidirectional precision inference (both top-down and bottom-up) for
    automatic type optimization
  • Enhanced %cd syntax with .forward, .backprop, .zero_grads support and automatic
    comment generation
• New Datasets and Examples
  • Added MNIST and CIFAR10 datasets (borrowed from Raven)
  • Created Names dataset with bigram use-case helper for language modeling
  • Implemented Half-moons synthetic dataset for classification tasks
  • Developed comprehensive test examples including bigram language models
• Performance and Memory Improvements
  • Fixed critical memory leak in builtins.c
  • Resolved bus error on large datasets
  • Migrated from heap-local to on-stack allocation by default
  • Improved virtual nodes and inlining to work across routines
  • Enhanced shape inference with better Total_elems constraint handling and LUB support
• Backend Stabilization
  • Fixed numerous CUDA backend regressions and missing constructs
  • Resolved Metal backend issues with session-level bugs
  • Added Float16 emulation for systems without native _Float16 support
  • Fixed host-device synchronization issues with proper devices_not_lagging_host
    semantics

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