RemindMe! 3y “reply to this thread”.

Tweezers.

When you realize how many wars were averted because of them.

Most Arduinos don’t have enough horsepower to run a full assistant stack. They’re designed as limited resource microcontrollers.

Basically, here are some choices, depending on what your priority is:

• Run Micropython on the board. This gives you python, but no assistant.
• Run a microcontroller with limited wakeword recognition, as a front for an assistant service running elsewhere: https://www.home-assistant.io/voice_control/s3_box_voice_assistant/
• Run a more performant system like ESP-IDF which is based on FreeRTOS: https://github.com/espressif/esp-skainet (these get you closer to an assistant, but don’t get you python, though)
• Train a model separately, then run it on a Micropython with pytorch bindings: https://luvsheth.com/p/running-a-pytorch-machine-learning
• Alternate version: upytorch - https://github.com/ljk53/upytorch
• Lastly, an integration between Tensorflow-Lite and Micropython: https://github.com/mocleiri/tensorflow-micropython-examples (python and ML but not Arduino).

Depending on what you want to do, I’d suggest the easiest is #2, as a frontend to HomeAssistant, with the assistant running either on a beefy server or on the cloud.

Edit: “Arduino” actually can reference three different things:

• the branded boards from arduino.cc
• the software stack with C/C++ bindings running on top of a range of microcontrollers, or
• the company called Arduino.

If you have a classic Arduino board, they usually have very limited power and run on a basic Atmel processor. An ESP-32 processor is a bit beefier and can run Arduino software (as well as FreeRTOS). And to make things even more confusing, Arduino the company sells an Arduino-branded board that runs the Arduino software stack, but on top of different processors, including an ESP-32: https://docs.arduino.cc/hardware/nano-esp32/

You may want to watch out which version of “Arduino” you want to work with.

• Catch 22
• Hitchhiker’s Guide to the Galaxy (series)

ESPN video of her story: https://youtu.be/U6CoScOIK_I

https://www.espressif.com/en/news/ESP32-S3-BOX-3

There’s a model with a more expensive dock, or one without. The one without worked fine. But it had to be the Box 3 not Box 2. It worked pretty well and you could create custom images to indicate whether it was listening, thinking, etc.

Instructions here: https://www.home-assistant.io/voice_control/s3_box_voice_assistant/

The box isn’t powerful enough to run an LLM itself. It’s just good enough as an audio conduit. You can either use their cloud integration with ChatGPT, or now, Anthropic Claude. But if you had a powerful Home Assistant server, say an Nvidia Jetson or a PC with a beefy Nvidia GPU, you could run local models like Llama and have better privacy.

This is from earlier this year. I imagine they’ve advanced more since then.

Their LLM integration is super cool. I messed with it for a previous job. Way better than Alexa or Google Home.

https://arstechnica.com/gaming/2024/09/two-weeks-after-launch-sony-shooter-concord-goes-offline-and-offers-refunds/

“Team-based shooter eight years in the making had just 25,000 estimated sales.”

A few jobs ago, everyone hated the tech stack. The people who had come up with it had long left. I talked to everyone, then came up with a plan to transition to a modern stack. Got buy-in from management.

Half the people (and all who had said they hated the status quo) threatened to quit if we made the change.

Fortunately, it was just in time to collect the 1-year retention bonus. Life’s too short. Walked away.

Let’s hope no single person worked on that thing for the full 8 years under development. Would be crushed.

Installed RabbitMQ for use in Python Celery (for task queue and crontab). Was pleasantly surprised it also offered MQTT support.

Was originally planning on using a third-party, commercial combo websocket/push notification service. But between RabbitMQ/MQTT with websockets and Firebase Cloud Messaging, I’m getting all of it: queuing, MQTT pubsub, and cross-platform push, all for free. 🎉

It all runs nicely in Docker and when time to deploy and scale, trust RabbitMQ more since it has solid cluster support.

Since nobody’s brought it up: MQTT.

It got pigeonholed into IoT world, but it’s a pretty decent event pubsub system. It has lots lf security/encryption options, plus a websocket layer, so you can use it anywhere from devices, to mobile, to web.

As of late last year, RabbitMQ started suporting it as a supported server add-on, so it’s easy to use it to create scalable, event-based systems, including for multiuser games.

Wait until AGI!

AGI: Yes.

Wait until the sentient robots!

Sentient robots: Yes.

Wait until biological…

Biologics: Glub, glub. Yes.

How long before the students gamify it to see who can generate the most alerts?

She was the co-author of the second edition of Bunnie Huang’s New Essential Guide to Electronics, for those looking to make hardware in Shenzhen: https://arstechnica.com/gadgets/2023/12/a-new-essential-guide-to-electronics-by-naomi-wu-details-a-different-shenzen/

TLDR: People need to go touch grass.

Cleaning up the kitchen every night.

Used to leave dishes in the sink during college, then do them when it got full. Got a side job as a bartender, where you had to clean up every surface after the last shift, ready for people the next day. Applied it to home. Has stuck ever since.

Fortunately, married a woman who had the same habits. We’ve never gone to bed with a dirty kitchen, even after a group gathering.

Tried bash, Make, and awk/sed. All hit brick walls. Finally landed on pyinvoke. Two dependencies to install on any new machine. Never had problems. Also, easy to debug and modify as projects evolve.

Funny story: when SO first started, started answering questions in domains I had experience in. The gamification was fun. After a year, questions got repetitive, so stopped.

A few years later. Googling a tech question. Top answer. Checked. Looks good.

Scroll down. It’s my own answer from way back when.

First time I felt old.

Flashback to 5pm (a lifetime ago), and everyone at work switching to playing Marathon for next 30-60m to unwind before heading home.