Author: safety
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trippler at PyConAU
I was thrilled to be back for my second PyCon AU – with a wonderfully diverse and inclusive group of technologists – presenting on trippler in a talk titled An EV Trip Planner for Australia. I got a great feedback, including a suggestion to incorporate the many very Australian BIG things we might encounter on…
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Basketball shot clock human state machine
I’ve only come to basketball as a parent, and in that capacity I often find myself on shot clock duties, as one of the few people who seems to enjoy – or at least tolerate – the shot clock. Perhaps I tolerate – or even enjoy – the shot clock because I imagine myself a…
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trippler for Aotearoa New Zealand
Planning to present my PyCon AU talk to an internal audience at MYOB, I realised the title An EV trip planner for Australia, while entirely appropriate for an Australian conference on Python, wasn’t as inclusive as it could be for the members of a technology organisation encompassing Australia and Aotearoa New Zealand. So trippler now…
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Reflecting on UI polish
I’ve been meaning to give the trippler UI a glow up for MY2025 and my PyCon AU selection finally provided the impetus. In previously envisioning migrating to a Javascript front-end (vibe coded?), I was possibly making the next step bigger than it needed to be, as I’ve managed to squeeze a bit more out of…
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GenAI in Data Platforms
I was part of a panel on the Impact of GenAI on Modern Data Platforms recently, hosted by the Data Engineering Melbourne meetup. It was great to chat with MC Ryan Collingwood and fellow panellists Rahul Trikha, Peter Barnes and Tony Nicol in front of a large and curious crowd. Like the crowd, I felt…
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Effective ML Teams in Korean
We received our copies of the Korean translation of Effective Machine Learning Teams this week!
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Team Topologies x EMLT
To provide more resources around the excellent conversation we had with Matthew Skelton on the Stream of Teams podcast in late 2024, we collaborated on an article summarising our chat, which was based on the final chapter of Effective Machine Learning Teams (EMLT). The article titled Team Topologies in action: Effective structures for Machine Learning…
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22 rules of generative AI, 2 years on, Ghibli intermission
This update comes at the peak of the Ghiblification fad. There’s nothing new here and yet I found the release of and response to GPT 4o image generation, including mechanistically crushed and artificially reconstituted Ghibli, particularly shocking. So here’s a retrospective case study for the recent review of rule #10 (labelling ingredients) and a longer…
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Waste not Programmable
Programmable 2025 Melbourne featured a fantastic program, heavy on practical data & AI in an apt reflection of the times. It was also a great chance to catch up with many in the Melbourne tech community. I presented my 7 Wastes of Data Production talk. In the spirit of continuous improvement, I made some minor…
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22 rules of generative AI, 2 years on, part 1
How has my original post on 22 rules of generative AI aged in a period of rapid change? Are these solution considerations as enduring as I thought? Let’s reflect on the original advice and developments in the meantime. Apologies again for minimal references as I timeboxed the writing. In general, evidence should be discoverable/verifiable with…