The State of Emerging Technology

Every quarter we step back from the bench and read the horizon. The signal this cycle is convergence: technologies that grew up in separate silos are suddenly talking to each other, and the interesting work is happening at the intersections.

Three currents worth watching

• On-device AI crossing into the browser — WebGPU puts a real compute path inside every tab.
• Spatial computing leaving the demo stage — interfaces that assume depth and presence, not flat rectangles.
• Edge + cloud loops maturing — inference at the edge, learning in the cloud, models that improve without a redeploy.

A WebGPU kernel in the browser

// a compute shader runs on the GPU, inside a normal web page
const adapter = await navigator.gpu.requestAdapter();
const device  = await adapter.requestDevice();

const pipeline = device.createComputePipeline({
  layout: 'auto',
  compute: {
    module: device.createShaderModule({
      code: `
        @group(0) @binding(0) var<storage, read_write> data: array<f32>;
        @compute @workgroup_size(64)
        fn main(@builtin(global_invocation_id) id: vec3<u32>) {
          if (id.x >= arrayLength(&data)) { return; }
          data[id.x] = data[id.x] * 2.0;
        }
      `
    }),
    entryPoint: 'main',
  },
});

The next platform is not a new device. It is the old device doing something it could not do a year ago.— Lab Director

The practical takeaway: build for swappable compute. The model that runs in the cloud today will run on the edge next year and in the browser the year after. Architectures that treat compute as a location, not a commitment, will age the slowest.