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Report abuseπ± Apple Platforms β’ π€ Edge AI β’ π§ Connected Hardware β’ βοΈ Developer Infrastructure
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Applied systems engineer building products across native software, AI models, hardware, and infrastructure.
I build end-to-end systems: native applications, on-device inference, cameras and BLE devices, model-training pipelines, web services, and the infrastructure needed to test and ship them. My strongest work starts with a product or hardware capability and connects every required layer until it works outside a demo.
- On-device and edge AI: quantization, local model runtimes, perception, tracking, and multimodal systems
- Apple platforms: Swift/SwiftUI products, macOS automation, iOS testing, signing, release, and App Store operations
- Wearables and alternative interfaces: smart glasses, BLE, camera/audio relays, silent speech, and sensor-driven interaction
- Agent infrastructure: composable tools, MCP servers, evaluation, orchestration, and machine-to-machine workflows
| Area | Projects |
|---|---|
| Camera-enabled interfaces | Transcription β Open-Alterego, Robotic reasoning β cosmos-framework, Human vitals β rPPG |
| Connected hardware | BluetoothHID, ESP32-S3 Camera Firmware, Pi BLE Keyboard |
| Developer and AI tooling | xcode-mcp, structured-prompts |
Larger product systems and internal platform monorepos are mostly private. Older experiments are being consolidated into explicit archives so the public account has a clearer canonical map.
Privacy-focused iOS media processing: metadata removal, watermarking, and fail-closed visual masking.
An AI companion and audio-journaling product focused on personal advocacy, augmentation, and reflection.
A sleep-cycle utility built around 90-minute timing and practical wake-time planning.
Shipping these products has included native implementation, screenshots and localization, signing, CI, TestFlight delivery, App Store Connect automation, and post-release iteration.
Exploring camera-based physiological sensing for phones and wearable cameras.
An earlier real-time self-classification framework and hardware demonstration.
Silent-speech and non-vocal communication research, including visual speech recognition, personalization, and deployment paths for Apple devices.
Reusable service handlers for multiple AI providers, streaming, WebSockets, and provider-specific capabilities.
A small prompt-template registry for predictable, testable LLM interactions.
- Build the thinnest end-to-end system that can be tested in the real environment.
- Keep hardware, model, application, and infrastructure boundaries replaceable.
- Automate repeated workβespecially testing, deployment, screenshots, signing, and releases.
- Extract reusable packages after an interface has become real, not merely hypothetical.
- Treat AI coding agents as implementation multipliers; verify the resulting system with tests, device evidence, and operational checks.
| Platform | Link |
|---|---|
| X | @simulationapi |
| Website | ebowwa.xyz |
| Hugging Face | huggingface.co/ebowwa |
| Ollama | ollama.com/ebowwa |
| GitHub | @ebowwa |
Ship end-to-end. Verify on real systems. Extract what becomes reusable.
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