New Segment Anything Model Explained

by admin | Apr 9, 2023 | AI Guides

Introduction Blog for Segment Anything Model Working in YouTube

The Segment Anything Model (SAM) is a cutting-edge neural network-based approach that can be used to segment and label objects in images or videos. This model is trained on a large dataset of annotated images, where each pixel is manually labeled with the corresponding object category. The SAM model is capable of performing a wide range of tasks such as object detection, semantic segmentation, instance segmentation, and image/video editing.

The SAM architecture is a fully convolutional network that takes an image or video frame as input and generates a segmentation map, where each pixel is assigned a label indicating the object it belongs to. The model consists of an encoder-decoder network with skip connections, allowing it to capture both low-level and high-level features of the input image. The encoder network consists of several convolutional layers followed by max pooling, which progressively reduces the spatial resolution of the input image. The decoder network consists of several convolutional layers followed by upsampling, which increases the spatial resolution of the feature maps generated by the encoder.

The skip connections in the SAM model are used to connect corresponding feature maps from the encoder and decoder networks, which helps to preserve spatial information during the downsampling and upsampling operations. During training, the SAM model minimizes a loss function that measures the difference between the predicted segmentation map and the ground truth segmentation map. The loss function can be defined in various ways depending on the task at hand, such as cross-entropy loss, binary cross-entropy loss, or mean squared error.

Once the SAM model is trained, it can be used to segment objects in new images or videos. The input image or video frame is fed into the SAM model, and the model generates a segmentation map indicating the object labels for each pixel. This segmentation map can then be used for various applications such as object detection, semantic segmentation, instance segmentation, or image/video editing.

The Segment Anything Model has many potential applications in computer vision and image/video processing. Object detection is one of the most common tasks that can be performed using SAM. This task involves detecting and localizing objects in images or videos. Semantic segmentation, on the other hand, involves assigning a label to each pixel in an image or video. This can be useful for tasks such as image or video editing, where it is necessary to separate the foreground and background of an image or video. Instance segmentation is another task that can be performed using SAM. This task involves identifying and distinguishing between multiple instances of the same object in an image or video.

In conclusion, the Segment Anything Model is a powerful tool for segmenting and labeling objects in images or videos. Its ability to perform a wide range of tasks makes it a versatile model that can be used for many applications. The model’s architecture and training process make it capable of producing accurate and reliable results, making it an essential tool for anyone working in computer vision or image/video processing.

How did you find this please share your thoughts in comment below.

OpenAI Unviel ChatGPT-4

by admin | Mar 15, 2023 | AI Guides

OpenAI unveils GPT-4 with new capabilities, Microsoft’s Bing is already using it

Only a few months ago ChatGPT was launched and it changed many people’s perception of what AI can do. That was based on GPT-3.5 from OpenAI, which was also integrated into Microsoft’s Bing and Skype, Edge too. Now the company has confirmed that it has switched over to the new and more powerful GPT-4 model.

In fact, it did so a while ago – if you’re part of the Bing Preview then you have been using GPT-4 for the last five weeks (you can sign up for the preview here). This isn’t the plain GPT-4, by the way, but a version that has been customized by Microsoft for search.

So, what’s new in GPT-4? For starters, it is a “multimodal” model, which is fancy way of saying that you can attach images to your query, not just text. Here is an example of GPT-4 explaining a joke found on Reddit. Note that the output is text only (i.e. you can’t generate images like with Stable Diffusion, MidJourney, etc.).

The new model is smarter too, the OpenAI team tested it with practice exam books from 2022 and 2023. Note: the model doesn’t know anything after September 2021, so these exams (and their answers) weren’t part of the training data.

GPT-3.5 took the bar exam (which lawyers need to pass) and it scored in the bottom 10%. GPT-4 scored in the top 10%. The justice system isn’t ready for robo-lawyers yet, but they are on the horizon. GPT-4 also scored in the 88th percentile on the LSAT exam, v3.5 was in the 40th. For SAT Math, GPT-4 was in the 89th percentile, GPT-3.5 in the 70th. You can check out OpenAI’s announcement for more exam results.

The most important new feature in version 4 is “steerability”. Previously, ChatGPT was coerced into acting like a digital assistant by prepending some rules. It was possible to trick the AI into revealing those rules, e.g. here’s what Microsoft told “Sydney” to do as Bing (including not revealing its Sydney code name):

Microsoft and OpenAI have worked to hide such rules (to prevent so-called “jailbreaking”), but now there is a better way to do it – companies can control the AI’s style and task with a system message. Here’s an example:

It’s important to note that GPT-4 still has limitations, especially when it comes to facts. Like its predecessor, the model can make things up, these are called “hallucinations”. The new version is significantly better (scoring 40% higher on internal testing) than GPT-3.5 at sticking to the facts and not making logical mistakes, but it is still not perfect. Still, GPT-3 was released in mid-2020, GPT-3.5 arrived in early 2022 (a later enhancement was used for ChatGPT), so the pace of improvement is nothing short of incredible.

How to Access ChatGPT4

Now all we want to know is this – can we have a GPT-4 powered Cortana?