Delete roadmap.md
diff --git a/docs/roadmap.md b/docs/roadmap.md
deleted file mode 100644
index 44197a4..0000000
--- a/docs/roadmap.md
+++ /dev/null
@@ -1,59 +0,0 @@
-# IREE Roadmap
-
-## Winter 2019
-
-Our goal for the end of the year is to have depth in a few complex examples (such as streaming speech
-recognition) and breadth in platforms. This should hopefully allow for contributions both from Googlers
-and externally to enable broader platform support and optimizations as well as prove out some of the
-core IREE concepts.
-
-### Frontend: SavedModel/TF2.0
-
-MLIR work to get SavedModels importing and lowering through the new MLIR-based tf2xla bridge.
-This will give us a clean interface for writing stateful sample models for both training and inference.
-The primary work on the IREE-side is adding support for global variables to the sequencer IR and
-sequencer runtime state tracking.
-
-### Coverage: XLA HLO Ops
-
-A majority of XLA HLO ops (what IREE works with) are already lowering to both the IREE interpreter and
-the SPIR-V backend. A select few ops - such as ReduceWindow and Convolution - are not yet implemented and
-need to be both plumbed through the HLO dialect and the IREE lowering process as well as implemented
-in the backends.
-
-### Sequencer: IR Refactoring
-
-The current sequencer IR is a placeholder designed to test the HAL backends and needs to be reworked to its
-final (initial) form. This means rewriting the IR description files, implementing lowerings, and rewriting
-the runtime dispatching code. This will enable future work on codegen, binary size evaluation, performance
-evaluation, and compiler optimizations around memory aliasing and batching.
-
-### Sequencer: Dynamic Shapes
-
-Dynamic shapes requires a decent amount of work on the MLIR-side to flesh out the tf2xla bridge such that
-we can get input IR that has dynamic shapes at all. The shape inference dialect also needs to be designed
-and implemented so that we have shape math in a form we can lower. As both of these are in progress we
-plan to mostly design and experiment with how the runtime portions of dynamic shaping will function in
-IREE.
-
-### HAL: Dawn Implementation
-
-To better engage with the WebGPU and WebML efforts we will be implementing a [Dawn](https://dawn.googlesource.com/dawn/)
-backend that uses the same generated SPIR-V kernels as the Vulkan backend but enables us to target Metal,
-Direct3D 12, and WebGPU. The goal is to get something working in place (even if suboptimal) such that we
-can provide feedback to the various efforts.
-
-### HAL: SIMD Dialect and Marl Implementation
-
-Reusing most of the SPIR-V lowering we can implement a simple SIMD dialect for both codegen and JITing.
-We're likely to start with the [WebAssembly SIMD spec](https://github.com/WebAssembly/simd/blob/master/proposals/simd/SIMD.md)
-for the dialect (with the goal of being trivially compatible with WASM and to avoid bikeshedding). Once
-we have at least one lowering to executable code (either via codegen to JITing) we can use
-[Marl](https://github.com/google/marl) to provide the work scheduling. This should be roughly equivalent
-to performance to Swiftshader however with far less overhead. The ultimate goal is to be able to delete
-the current IREE interpreter.
-
-## Spring 2020
-
-With the foundation laid in winter 2019 we'll be looking to expand support, continue optimizations and tuning,
-and implement the cellular batching techniques at the core of the IREE design.
