Post 1, Shuyuan Zhang

AI
After reading the latest reviews and news about the developments of artificial intelligent nowadays on Evernote, I am curious about how is it created and how is it works. So I researched this topic and found some basic explanations to help us understand the general principle of AI.

There are several methods to build an AI. They are Deep Learning, Machine Learning and Generative Adversarial Nets (GAN). The GAN is one of the most advanced and popular approaches for complicated tasks. Most of the researchers and practitioners in this field are making efforts to learn and improve this system. A GAN is composed of two major parts—generator and classifier. The generative model is converting random data to true data and the discriminative model is classifying fake data from true data. They are against and competing with each other. At the same time, they are growing together.

For example, if we want to create an AI painter that is able to draw an apple, we will need to start with training two models. The discriminative model will get some initial inputs such as pictures of apples. This will require another developing techniques called Pattern Recognition. It is because there is no two apples are exactly the same and it is impossible for us to input every single apple in the world to our discriminative model. So pattern recognition can help the computer to find the pattern of how an apple looks like. On the other side, our generative model is getting little inputs about apples. For instance, we only tell it that an apple is about 1-3 cubic centimeters and the color is varying from green to red on the chromatogram. And then we can start running it. At the beginning, the generative model will create some ridiculous stuff such as a pure green cubic or a blood red sphere. It will send its work to the discriminative model. The discriminative model could easily claim this data as fake and start up another create- classify loop. After running this loop for billions of times until the discriminative model is deceived by generative model, then we can say that we successfully made an artificial intelligent painter that is better than human artists in some degree.


Database & Future

According to above discussion, I realized that other topics for group E for this assignment are all having some connections. For example, database system is the key components for discriminative model since it is collecting data as the initial inputs for this model. Database system is not only collecting but also organizing and processing raw data that makes the pattern recognition process a lot easier. Network and sociology are providing support to this system from different aspects as well.

[1]Generative Visual Manipulation on the Natural Image Manifold.Jun-Yan Zhu.ECCV 2016.

[2]Generative Adversarial Networks.Goodfellow. 

[3]Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.Alec Radford. [4]Deep multi-scale video prediction beyond mean square error.Michael Mathieu. 

Comment 

Thomas Sisson

I am shocked when I read your MX3D article. I didn’t realize that our 3D printing techniques are so mature and advanced that it can be used in construction filed in real life. And I agree with you that this can push the boundaries of conventional concrete to be used in projects that are more architecturally complex in shape. Your work in ‘Future’ session inspired me as well. My post is about AI but I only focused on this technique it self. You mentioned some connections between AI and our field that makes me start to think this way.

Dee Dee Strohl

Your article about HVAC & Sensor is interesting. It is a convenient way to manage your house/ office and can effectively increase equipment’s efficiency. I am thinking in the future, if most of buildings are having sensor system installed and AI technique is mature enough. We don’t even need an app to manage this system by ourselves. HVAC equipment with AI will finish all of the work for us and a great amount of energy will be saved. Both of our energy and environment problems will be mitigated.

Milligan

I like the video about software you posted. Before I watch that and read your discussion, I thought we only use software in the design phase behind a computer. But with the development of mobile devices, we are able to use apps during construction phase on filed. This can make the project manager or construction engineer perform their work in a more safety and effective way.