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Go 1.22, SQLite, and Next.js: The "Boring" Back End

https://mohammedeabdelaziz.github.io/articles/go-next-pt-2
1•mohammede•2m ago•0 comments

Laibach the Whistleblowers [video]

https://www.youtube.com/watch?v=c6Mx2mxpaCY
1•KnuthIsGod•3m ago•1 comments

I replaced the front page with AI slop and honestly it's an improvement

https://slop-news.pages.dev/slop-news
1•keepamovin•8m ago•1 comments

Economists vs. Technologists on AI

https://ideasindevelopment.substack.com/p/economists-vs-technologists-on-ai
1•econlmics•10m ago•0 comments

Life at the Edge

https://asadk.com/p/edge
1•tosh•16m ago•0 comments

RISC-V Vector Primer

https://github.com/simplex-micro/riscv-vector-primer/blob/main/index.md
2•oxxoxoxooo•19m ago•1 comments

Show HN: Invoxo – Invoicing with automatic EU VAT for cross-border services

2•InvoxoEU•20m ago•0 comments

A Tale of Two Standards, POSIX and Win32 (2005)

https://www.samba.org/samba/news/articles/low_point/tale_two_stds_os2.html
2•goranmoomin•23m ago•0 comments

Ask HN: Is the Downfall of SaaS Started?

3•throwaw12•25m ago•0 comments

Flirt: The Native Backend

https://blog.buenzli.dev/flirt-native-backend/
2•senekor•26m ago•0 comments

OpenAI's Latest Platform Targets Enterprise Customers

https://aibusiness.com/agentic-ai/openai-s-latest-platform-targets-enterprise-customers
1•myk-e•29m ago•0 comments

Goldman Sachs taps Anthropic's Claude to automate accounting, compliance roles

https://www.cnbc.com/2026/02/06/anthropic-goldman-sachs-ai-model-accounting.html
2•myk-e•31m ago•4 comments

Ai.com bought by Crypto.com founder for $70M in biggest-ever website name deal

https://www.ft.com/content/83488628-8dfd-4060-a7b0-71b1bb012785
1•1vuio0pswjnm7•32m ago•1 comments

Big Tech's AI Push Is Costing More Than the Moon Landing

https://www.wsj.com/tech/ai/ai-spending-tech-companies-compared-02b90046
4•1vuio0pswjnm7•34m ago•0 comments

The AI boom is causing shortages everywhere else

https://www.washingtonpost.com/technology/2026/02/07/ai-spending-economy-shortages/
2•1vuio0pswjnm7•36m ago•0 comments

Suno, AI Music, and the Bad Future [video]

https://www.youtube.com/watch?v=U8dcFhF0Dlk
1•askl•38m ago•2 comments

Ask HN: How are researchers using AlphaFold in 2026?

1•jocho12•41m ago•0 comments

Running the "Reflections on Trusting Trust" Compiler

https://spawn-queue.acm.org/doi/10.1145/3786614
1•devooops•45m ago•0 comments

Watermark API – $0.01/image, 10x cheaper than Cloudinary

https://api-production-caa8.up.railway.app/docs
1•lembergs•47m ago•1 comments

Now send your marketing campaigns directly from ChatGPT

https://www.mail-o-mail.com/
1•avallark•51m ago•1 comments

Queueing Theory v2: DORA metrics, queue-of-queues, chi-alpha-beta-sigma notation

https://github.com/joelparkerhenderson/queueing-theory
1•jph•1h ago•0 comments

Show HN: Hibana – choreography-first protocol safety for Rust

https://hibanaworks.dev/
5•o8vm•1h ago•1 comments

Haniri: A live autonomous world where AI agents survive or collapse

https://www.haniri.com
1•donangrey•1h ago•1 comments

GPT-5.3-Codex System Card [pdf]

https://cdn.openai.com/pdf/23eca107-a9b1-4d2c-b156-7deb4fbc697c/GPT-5-3-Codex-System-Card-02.pdf
1•tosh•1h ago•0 comments

Atlas: Manage your database schema as code

https://github.com/ariga/atlas
1•quectophoton•1h ago•0 comments

Geist Pixel

https://vercel.com/blog/introducing-geist-pixel
2•helloplanets•1h ago•0 comments

Show HN: MCP to get latest dependency package and tool versions

https://github.com/MShekow/package-version-check-mcp
1•mshekow•1h ago•0 comments

The better you get at something, the harder it becomes to do

https://seekingtrust.substack.com/p/improving-at-writing-made-me-almost
2•FinnLobsien•1h ago•0 comments

Show HN: WP Float – Archive WordPress blogs to free static hosting

https://wpfloat.netlify.app/
1•zizoulegrande•1h ago•0 comments

Show HN: I Hacked My Family's Meal Planning with an App

https://mealjar.app
1•melvinzammit•1h ago•0 comments
Open in hackernews

Ask HN: How to gain a solid understanding of IMUs?

1•feefifoflux•1mo ago
My background is primarily software (Python, AI/ML, large-scale data). This is my first serious hardware-heavy product.

I’m working on a company concept that depends on embedded IMUs, and I’m trying to front-load learning so I don’t lock myself into poor architectural, software or component decisions early on, especially those pitfalls that someone with more knowledge/expertise would know how to avoid.

I understand “learning by doing” is essential, but I suspect there are canonical pitfalls and resources I should study before committing deeply to hardware.

Here are the parameters of the project:

* The IMU environment will be abusive, with vibrations and impacts. The vibrations and impacts are not the object of analysis (i.e. noise), but I do want to account for them so they do not pollute the data and design the platform so the platform survives.

* I will need low-power/sleep/wake-on-accel in order to achieve the desired battery life.

* The IMUs will transmit to a gateway via bluetooth in short bursts of less than 60 seconds, 10-20 times per day, and sleep the rest of the time.

* There could be 20-40 IMUs transmitting simultaneously.

* The production IMU platform needs to be very short, i.e. height = 3-6mm.

* The implementation requires that the batteries on board are not rechargeable, but last the life of the IMU unit, i.e. 2+ years.

* The way the IMU units are implemented, there should be an opportunity to sample the unit at rest for calibration purposes, e.g. biases, etc.

Here are some subject areas I have marked for further study/inquiry:

* Handling biases

* Kalman filtering

* Error propagation in single/double integration, i.e. velocity and position

* Low-power configuration

* Bluetooth communications

* Battery/power options that meet the 2+ year goal

I am seeking guidance/wisdom to better prepare myself for the core challenges I will face on the IMU/hardware portion of this project.

Specifically, I am seeking cherished, esteemed, favorite resources on the following subjects areas as well as the addition of any resources/subjects you deem important:

* Underlying IMU physics, i.e. first principles

* Handling bias/calibration

* Error propagation, single/double integration

* Kalman filtering for IMU data

* Bluetooth comms for IMUs

* Low-power/sleep configurations

* Battery/power options, i.e. under 5mm, 2+ years

* IATF-16949 compliant manufacturers and how it will benefit the project? Perspectives/opinions?

I have made the standard appeals to Google search and GPT, but I am not convinced I have found all the preliminary materials required for this project to succeed.

Here is an example of a resource that I think is informative, but again, I don't have the expertise to make that judgement definitively: An Introduction to Inertial Navigation by Oliver J. Woodman

FWIW, I am using the Seeed Studio XIAO nRF52840 Sense for prototyping. The inquiry above is for both prototyping and production.

Comments

jeffreygoesto•1mo ago
The iPhone uses Bosch sensors, you might want to check https://www.bosch-sensortec.com/products/motion-sensors/imus...