 Hello everyone! Welcome back to our channel. I hope you all are safe and sound. Remember the time when we used to give our toys special names as if they were our best friends. It's time to release those memories, but with a small AI twist. In this video, using Pictoblock's machine learning extension, we will make a project in which we will train our computer to first memorize the names of our soft toys and then recognize them and say their name out loud when we bring it in front of the camera. Pre-requisites are a laptop or a computer with latest version of Pictoblock's downloaded, a camera and a good internet connection. You can download the all new Pictoblocks from the link given in the description box below. Let's begin by training the models. Go to the Teachable Machine website. Click on the Get Started button. A new page will open up. Click the Image Project tile. Let's begin by adding the first class. As we will be adding our sample image using webcam, click on the Webcam button to start the camera. We'll first make the class recognize our first toy. Keep the toy in front of the camera and record the images. Make sure you capture the images from all the sites. Similarly, bring your other toys one after another in front of the camera and create the other classes too. Your training data is complete. It will look something like this at the end. Now that we have included the sample image, we need to train the model accordingly. Thus, click the Train Model button and wait for the model to get trained. You can have a look or test the trained model. Now that the model is perfect, let's export the model. Click on the Export Model button. A pop-up will open. Click the Upload My Model button. A shareable link will appear. Copy it. Now that the models are loaded, let's begin by writing the script. Open Pictoblocks. We will first add the machine learning extension. To work with the all-new AI and ML extension, you need to keep two things in mind. First, that you must sign in or log in in Pictoblocks from here. Second, you must have a good internet connection. Click on the Board button and select Avail. We now need to add the machine learning extension. Click on the Add extension button. Choose the machine learning extension. Now we need to load our model into Pictoblocks. Thus, click on Load Model. A dialog box will appear. Paste the copied link into the space given and click on Load Model. Wait for a little while till the models get loaded. You may now see that the machine learning blocks are loaded. To start executing the script, whenever the green flag is clicked, from the events palette, drag and drop when flag clicked hard block. As we need to recognize the toys from the camera feed, place the turn on video on stage with 0% transparency block from the machine learning palette. Snap a forever block from the control's palette. Place an if-else block below it. Now to check the identified class, place a greater than operator block from the operator's palette. From the machine learning palette, place Get Confidence of Class from Web Camera block into the first space and choose Stage from the drop-down. Place Identify Class from Web Camera block into the input space and choose Stage from the drop-down. Write 0.9 in the space given. To make Toby say out the name, place Think block from the looks palette. Write I think into the first input and 0.5 into the second. Place a say block below it. To make Toby say out loud the name, place a join block into the space given. Write this is into the first input from the machine learning palette. Drag and drop Identify class from Web Camera block into the second space and choose Stage from the drop-down. Into the else arm, place a say block and write show me your soft toy and I will recognize it into the first space and 2 into the second. Now that the script is ready, click the green flag to start. Make your own soft toy recognizer and share your videos with us in our picture blocks community on Facebook. If you like this video, give it a thumbs up and share it with your friends. Also subscribe to Stempedia and follow us on Facebook, Instagram and Twitter. Bye-bye, stay safe.