From 80244e2d88fcb9e3c6ab017cdcfd043e6a9dd762 Mon Sep 17 00:00:00 2001 From: vato007 Date: Mon, 10 Feb 2025 10:02:27 +1030 Subject: [PATCH] Update hobby projects, fix grammar in hobby projects --- index.html | 60 +++++++++++++++++++++++++++++++----------------------- 1 file changed, 35 insertions(+), 25 deletions(-) diff --git a/index.html b/index.html index 69a96ed..da4e9cc 100644 --- a/index.html +++ b/index.html @@ -267,29 +267,39 @@

Over the years I've hacked away at various personal projects. My preference is always to build, run and host applications locally, - which includes this page! + however I have come around to cloud services for public-facing + resources, such as CloudFlare, which is used to host this page!

- Recently my interesets have shifted slightly to large machine - learning models, and have messed around with Stable Diffusion - (mainly with - Invoke AI) and Large - Language Models such as the - Llama family. I have also - trained/finetuned LLMs in the past (BERT), however this has been - outside of my capability recently due to the growth in parameters. + I have used AI/ML in the past, as seen in my own Depth Prediction + implementation, and LLMs, where I fine-tuned BERT to perform Named + Entity Recognition, however recent models have gotten too large to + train at home. I also use local LLMs in LM Studio, to provide basic + information and coding assistance when learning a new framework. + Recently my interesets have shifted to designing applications that + can maximise throughput for large datasets and minimise response + time for queries/charts. I'm currently reading + Designing Data-Intensive Applications + to facilitate improvements in the Ingey project once core + implemetation is complete.

- Finally I've thoroughly enjoyed writing in Rust, mainly the - efficiency, ease of use and correctness that come from using this - programming language. One example was in the + Finally I've enjoyed writing new applications in Rust; the + efficiency, ease of use and correctness have been fantastic. One + example is in the Ingey - project, where I reduced the time taken for processing some demo - data on the costing product from ~1.5 hours to ~7 seconds on a - laptop/desktop, or ~36 seconds on a smartphone. This was mainly due - to not using SQL Server, and using a custom algorithm in overhead - allocation that significantly reduced memory consumption and the - number of required calculations. + project, where I reduced the time to perform reciprocal accounting + on a costing product from ~1.5 hours to ~7 seconds on a + laptop/desktop, or ~36 seconds on a smartphone. This was due to + avoiding non-bulk inserts into a relational database, and using a + custom algorithm in overhead allocation that significantly reduced + memory consumption and the number of required calculations. The + optimisations applied by Rust in release mode also had a significant + impact on performance, and is what facilitated easy deployment to an + iOS application.

Buf Piv

@@ -300,10 +310,10 @@

- This is a tauri application that makes it easy to edit json files - conforming to a protobuf definition. It works as a standalone - desktop application for the most complete experience, with browser - support to show tauri's versatility as well. + This is a Tauri + Angular application that makes it easy to edit + json files conforming to a protobuf definition. It works as a + standalone desktop application for the most complete experience, + with browser support to show Tauri's versatility as well.

A browser demo is available at @@ -319,7 +329,7 @@ This project originally involved communication between a Raspberry Pi and a Traxxas Slash using the Pi's GPIO to control the steering and throttle of the RC Car. This was mounted on some 3D printed - brackets.The steering and throttle are set using an iPhone/Android + brackets. The steering and throttle are set by an iPhone/Android application connected over WiFi.

Over time this worked as a base to explore other ideas, namely:

@@ -341,8 +351,8 @@

Recently there have been efforts to port the backend to Rust, with the 2D Lidar sensing and control completed. The Python BreezySLAM - implementation is currently unfinished, mainly due to distractions - from other projects + implementation is currently unfinished, mainly due to work on other + projects

Depth Prediction