Matthias C. Berger

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Matthias C. Berger

Matthias C. Berger

@SbgMatthias

I like to put data in motion • Building software • Firetail and Movebank developer • CEO at @SbgSeDe • Keen to solve your challenges with animal tracking data

Munich Katılım Kasım 2022
175 Takip Edilen224 Takipçiler
Matthias C. Berger
Matthias C. Berger@SbgMatthias·
🐦 Also open-sourcing this one out of years of private internal tooling: movebank-mirror 0.0.1. A CLI + library that pulls Movebank studies to a local file/folder structure and keeps them in sync. Per-study JSON metadata, per-(tag, sensor type) CSVs. Resumable. Friendly to the live API. 👉 github.com/mcb77/movebank… #Movebank #OpenScience #JavaDev
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Matthias C. Berger
Matthias C. Berger@SbgMatthias·
Animal movement data taught me something I didn't expect. Two things I keep coming back to: 1. Cleaning messy data forces clarity. You cannot hide behind a pretty dashboard when the pipeline breaks. 2. Building tools like Firetail and Movebank means you must stay close to the raw data yourself. The moment you only review others' work, you lose the instinct.
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Florin Pop 👨🏻‍💻
Florin Pop 👨🏻‍💻@FlorinPop17·
They didn’t pay me to write this but I want to thank the sponsors for making this @HackerResidency possible! 🙏 For the full month of May, me and a dozen other founders are able to lock in on our businesses in a beautiful villa in Da Nang, Vietnam 🇻🇳 An experience of a lifetime, so thank you! 🙏 @creem_io @NotionHQ
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Matthias C. Berger
Matthias C. Berger@SbgMatthias·
Finally, the on-ramp near Heraklion Airport onto the E75 heading east. I can feel the relief. I wonder where we’ll set up HQ? #Crete
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Matthias C. Berger
Matthias C. Berger@SbgMatthias·
@Omaofweb3 The worst I've seen: 17 stakeholders and one developer working half-time. So I would say it's the dev.
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Big Oma💙
Big Oma💙@Omaofweb3·
who’s really the backbone of a project ? - community - founder/team - developers - testers - investors - marketer - validators
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Matthias C. Berger
Matthias C. Berger@SbgMatthias·
I'm a developer who spends a lot of time building tools for animal tracking data, now having the chance to move into AI for SMEs. To all the data engineers out there... What "hard lesson" would you give yourself before diving into messy data silos? The stuff nobody warns you about.
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Ritesh Roushan
Ritesh Roushan@devXritesh·
Unpopular opinion: Python is a terrible first language. It teaches you: - Ignore types - Ignore memory - Ignore compilation - Ignore performance Then you hit a real job and: "Why is this slow?" "What's a pointer?" "Types? I just use 'any'" Learn C first. Suffer early. Everything else becomes easy.
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Matthias C. Berger
Matthias C. Berger@SbgMatthias·
The delivery time on amazon.de is also very vague: “April 21 - June 3”. It looks like Elektor does indeed ship internationally. In any case, you can choose from a wide range of countries in the store. I was redirected directly to elektor.de/products/maste…. The item was shipped from a distribution center in the Netherlands.
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Matthias C. Berger
Matthias C. Berger@SbgMatthias·
I’ve been wielding a soldering iron since I was 7. But FPGAs (and even GALs) were always something I looked at with trepidation. By chance, this great book by @bml_khubbard popped up on my timeline. I have to say, I’m thrilled, because this book hits just the right note. I’m looking forward to taking my first steps with the Artix-7 board.
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Matthias C. Berger
Matthias C. Berger@SbgMatthias·
Just tested the new NVIDIA DGX Spark for the first time today and it's a great device! 🔥 And it's small! I immediately ran a real head-to-head against our RTX 5090 on the exact same workload. - The RTX 5090 is roughly 6× faster in raw tokens/sec - The DGX Spark still delivered a very usable 35 tokens per second on Qwen Coder Next 80B At first the speed gap felt noticeable... but then you realize what's actually happening. The 5090 is an absolute speed demon when the model fits comfortably in 32 GB VRAM. The DGX Spark, however, brings 128 GB of unified memory. That single difference changes everything. I could load the full 80B model with room to breathe: longer context, lighter quantization without constant memory gymnastics, no compromises. This isn't about winning the pure performance crown. It's about making frontier-scale local AI actually practical on your desk. And it's quiet, private, no cloud bills, no latency and no data leaving the building. The DGX Spark isn't trying to replace high-end GPUs. It's redefining what "usable" means for serious developers and researchers. Already planning my next experiments. Can't wait to push it further. Anyone else got their hands on the DGX Spark yet? #DGXSpark #NVIDIA #LocalAI #CodingAgents
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Matthias C. Berger
Matthias C. Berger@SbgMatthias·
~ $ beep beep: Error: Could not open any device WTF! This worked since the dawn of time.
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