 All right, we did all sorts of stuff this week. Yeah, for top secret, I'm going to play five videos back to back. Actually, more, let's see, three and three. Sorry, six videos back to back, and then we're going to look at a leak. So take it away past us. Go past me. All right, ladies, what is this? OK, here I've got a different clue board. Do you remember is our micro-bit shape board with an NRF 52-840 Bluetooth and lots of sensors. What are these sensors? We're going to use this with Google's TensorFlow Lite for microcontrollers web demo. So when I click Launch Experiment, this is the Air Snare. And then down here, I click Connect. And then you'll see it shows up as a wireless Bluetooth web device I compare. And here's the neat thing. So after I've paired it, it will transfer over the TensorFlow model. And you can see here it's saying downloading. It transferred the model over so it can use the accelerometer to do motion detection. And then once it's loaded, I can do this demo where when I move to the side or up, I can do the little kick snare demo. And then down, side, up. Works great, Bluetooth. All right, ladies, what is this? I'm testing out a sample I just got. This is kind of neat. It's kind of like a weatherproof alarm, like panel mountable thing, but it has a USB on the end. Like this kind of gets this. And then there's a tower light version of the same thing. So these are USB alarms. So if I plug it into USB, it actually shows up as a serial port, as you see here. And then what I can do is I can run a little bit of Python code that just sends serial command data that makes the lamp blink or turn on. So it could be good for just you want to have a simple notifier that's nice and durable. And then there's also the tower light, which has a piezo in it as well. So you can hear it beeping. It also does like blink modes and stuff. So I think this can be nice if you want to have an alarm, but you don't want like a full Arduino and LED and new pixel setup. Just plug and play. All right, ladies, what is this? OK, we're testing out two macro pads, three by four key pads with RGB LEDs. And one of them is a lot faster. This one's a lot faster than this one. Because we're using the new native keypad vector and matrix keypad support. So basically, if you have a bunch of keys connected up to GPIOs or in a matrix, the scanning is happening in C, not in Python. So it's a lot faster. So if you look up here, you'll see this is doing the whole scan and outputting the text and drawing the screen, all this stuff at four milliseconds. The actual scanning is much shorter. And then over here, you'll see doing it in pure Python. It takes about eight milliseconds. But you still get the same performance. It's just this one is much, much faster, twice as fast, in fact. So it'll be great for DIY keyboard and macro pad projects. All right, lady, what is this? OK, this is a five by six ortho keypad with break apart keys so you can snap the keys apart. And I'm testing it as the full grid of 30 keys, five by six and a matrix. And these are diode matrix together so you can see all the rows and all the columns coming out here to a feather M4 that's running micro-circuit Python, which is a fork of micro-Python. And as you look up here, I'm testing out this new PR where we have native support for C vector and matrix keypads. So all this scanning and event handling is handled in C, so it's really fast. So I can turn on and off these keys and do all the Neopixels super fast and easy in circuit Python. It's going to be great for custom keyboards. Getting going. Beep, beep, beep, beep. All right, lady, what is this? Hey, it's a Sunday night. And I spent a bunch of this weekend working on getting my ATtiny817 dev board. It's actually a val board for the ATtiny817 underneath here. And I've put a shield on top to make wiring easier. And I've got a little bit of this little bento box of electronics. And I've got here some Neopixels wired up. And this Arduino compatible is sending I-squared C commands over these wires to this client, which is going to read them and then do stuff. So it's like a little I-squared C to anything, you know, Swiss Army knife. So this potentiometer is being read over I-squared C and then being written back to the Neopixel brightness. So that's like this little demo. So I got analog input to I-squared C working and then I-squared C to Neopixels working. So that's what I did this weekend. So far, so good. Very glowy. The cut's up. Yep, it's right here. All right, lady, what is this? Hey, I'm testing out Jepler's latest code release. Look at us. We're trapped inside of a camera. This is a ESP32-S2 Kaluga kit, which is an ESP32-S2, you know, Wi-Fi processor that we have Circuit Python support for. And what's really nice about it is it comes with like a display and buttons and a camera port because the ESP32-S2 can do some like native camera stuff by kind of taking advantage of the I2S peripheral. Yeah, the I2S peripheral. And what we've got here is actually Circuit Python library that's reading the data from the OV2640 and capturing the bitmap and then refreshing the displays. This is all happening in Circuit Python thanks to the hardware support Jepler added for capturing frames from a camera. This is 320 by 240. It's pretty cool. Nice work, Jepler. Okay, and then you have this. This is one of your leaked products. Yeah, well, this is the ortho brick apart that I showed, but I'm actually, it's like, I had to make an update to it and like I had to update it 30 times. It took a while, but it's sent out. So hopefully when it comes back, we'll be good to go. We'll get it in the store. That's not secret.