Axelofwar 🎒

There is no "right" way to become a developer. I worried how I'd apply web2 learning from robotics, image-processing, and data tasks - to the web3 world of smart contracts 🦀, UI//UX, and infra. The more I learn, the more I realize there's space for devs of EVERY kind 🧵/

On the platform I’m building… think self hosted ML + Hermes - Traefik routing - FusionAuth RBAC - infiscal secret management - MlFlow, Ray, Voxel51, dagster job management - Grafana, Prometheus Dozzle observability - lots of other goodies The knowledge will pay for itself.

Why is everyone talking about the DGX Spark for unified memory but not the ASUS Ascent GX10? Now that I’m expanding my platform to robotics projects the context/token limits on the 3090 across multiple codebases is starting to hurt 🥲 Public mirror on github btw (active dev)

Arteta doing Arteta things lol you hate to see it 😂

Bournemouth Co-CEO at the Tampa fan fest having a chat about Iraola leaving??? I actually rate this tbf proper leadership not sending out someone else to answer the tough questions.

Having done a ton of experimenting with Qwen 3/3.5/3.6, Qwopus distilled 3.5, Nemotron 2/3, etc. on a 3090 with an ACTUAL codebase. GPU maxis are NOT wrong about capability - but I’m not seeing enough talk about memory/context/token management or skill/tool selectors. BIG gap.

If you send me a “Hey” message on Slack or teams, best believe I will be ignoring that message until then rest of the message is sent

@RickyJuuice 🫡

@axelofwar haha got it back!

Extraordinary video. Too many extraordinary things to count. Most won't understand

Twitter is less fun because you can no longer tell who is naturally dumb and who is trying to make rent from ragebait

software engineering is absolutely not being automated right now. I barely ever code any more but I have never been busier. now that coding is 80% automated, the limiting factor is my ability to design, comprehend, and safely change systems. it's insanely exciting

Ok, I think my experiment leaving AI working on stuff 24/7 ends here. It doesn't work. Code explodes in complexity, results are not that great, the AI can't get past hard walls (it is still completely unable to even *grasp* SupGen), and it is insanely expensive (spent ~1k over the last 2 days). The best results are on the JS compiler, mostly because it is familiar (compared to inets), but not worth losing control over the codebase. I think the dream of having AI's working on the background and making real progress on things that matter (i.e., truly new things) isn't here yet. It is still a machine hard-stuck on its own training data, incapable of thinking out of the box. It is great for building things that were already built. But not new things Also coding normally has the under-appreciated advantage that you're doing two things at the same time: building a codebase *and* learning it. AI's do only half of that. The other half is obviously impossible 🤔

“A masterplan Jared’s been working on for 2 years” (Oct 25) Kushner’s face when he revealed they planned rebuilding Gaza BEFORE Oct 7. This was always the plan - it was never about Hamas US special envoy Steve Witkoff & Trump son-in-law Jared Kushner.

The YouTube algorithm is recommending me videos about how cooked the cs new grad market is because I keep searching about how impossible home ownership is 😂😭 I knew it was bad out here but WOW affordability + new grad job market is COOKED. This jobs report bro is holding…🥶

My phone finally force updated to IOS 26 and I have not considered going back to android this much since 2016. Genuinely the worst UI I’ve ever used AND it tanked performance/battery. Get me out…

Gah damn it’s crazy what 6 days + (some) domain knowledge + @cursor_ai (Claude4.5 in @Copilot) + probably not a ton of sleep either 😅 can do. TLDR ⬇️ – Spun up self-hosted @MLflow + benchmarking – Fine-tuned YOLO at 1280px (eval against popular models informed me multi-scale was the move) – Realized 100+ epoch training on 5070 Ti was doable - 16gb VRAM a bottleneck doing ANYTHING during training w/o OOM – Migrated MLflow + Ray + @traefik + Auth/@grafana /Ops stack to an old 2070 box – Grabbed a 3090 Ti Founders on BF + reconfigured everything for dual-GPU – Set up @Tailscale so I can monitor/trigger training on vacation 😄 AI accelerates a lot, but some domain knowledge still pays off — and yeah - tokens + hardware ain’t cheap — but it’s a pretty accessible way to learn if school isn’t your style. Will continue to update 🙏🏽

3+ years of making computer vision tutorials YOLO11, RT-DETR, SAM 2, PaliGemma 2, Basketball AI, Qwen3-VL, and many others. all with links to papers, repos, blog posts, and YouTube tutorials. all in one place. link: github.com/roboflow/noteb…

Fun note - slept through my pc basically being bricked during initial training cuz of onnx-> yolo conversion + memory leaks in each epoch’s mAP50 calculation 😂 apparently WSL is using like 6.5GB of RAM for dev container/docker engine + filesystem stuff 💀 will be on Ubuntu soon

Focusing on PII Pro first as I find that more interesting atm. Playing with a YOLO model and some WF/CCPD/RF datasets. Trying to see how far I can go with dev containers + WSL before I setup partitioning. Dry training on 250k+ images surprisingly good before optimizations.

Finding great synergy with AI tools at work and use in my personal dev workflows. Started two projects recently: 1. Resume Factory - connect bootcamp/course certificate grads with real jobs 2. PII Pro - provide content creators tools to mask sensitive data in their videos

@kennaisiya_ann 👀

There is no "right" way to become a developer. I worried how I'd apply web2 learning from robotics, image-processing, and data tasks - to the web3 world of smart contracts 🦀, UI//UX, and infra. The more I learn, the more I realize there's space for devs of EVERY kind 🧵/