From 80244e2d88fcb9e3c6ab017cdcfd043e6a9dd762 Mon Sep 17 00:00:00 2001
From: vato007
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