Jacob Wahbeh B1

Blog Post #1
Group E: Database, Network, Sociology, and Future

Network
https://www.nytimes.com/2018/01/14/technology/artificial-intelligence-chip-start-ups.html
Metz, Cade. “Big Bets on A.I. Open a New Frontier for Chip Start-Ups, Too.” The New York Times, The New York Times, 14 Jan. 2018, www.nytimes.com/2018/01/14/technology/artificial-intelligence-chip-start-ups.html

For our group, the concepts discussed work well together because they are all interrelated. With common goals and similar affects each of these topics are key to understanding whats in store for the future. As discussed in our previous class, a neural network is a perfect example of this relationship between network, sociology, and the future. A neural network is an example of machine learning from Artificial Intelligence, where intelligence is exchanged on a platform to other bots. In this article it talks about how big companies are investing in this technology and big players in China are developing new AI chips and accelerating new forms of AI. Although AI isn't the subject this neural network is just an example of how information is now being shared.

Sociology
https://www.nytimes.com/2018/01/11/opinion/trump-robots-electoral-college.html
Thomas. “Robots Can't Vote, but They Helped Elect Trump.” The New York Times, The New York Times, 11 Jan. 2018, www.nytimes.com/2018/01/11/opinion/trump-robots-electoral-college.html.

With new technology such as AI coming about it has a profound impact on society as a whole. The interactions that we have human-human can change with inclusion of robots and new technology. In this article it shows a reaction to this technology shift, where some become scared and vote more conservatively. Although I'm a supporter for this move, others can be very scared and this change and maybe with good reason.The competition in the work force as well as many other instances would be shared with this newfound AI technology.

Database & Future
http://www.thedrum.com/opinion/2018/01/15/how-technology-shaping-the-agency-model-the-future-and-what-marketers-should-do
https://www.genomeweb.com/applied-markets/consumer-genomics-databases-grow-new-users-observers-ponder-industrys-future
Petrone, Justin. “As Consumer Genomics Databases Grow With New Users, Observers Ponder the Industry's Future.” GenomeWeb, 12 Jan. 2018, www.genomeweb.com/applied-markets/consumer-genomics-databases-grow-new-users-observers-ponder-industrys-future.

a

As discussed last class companies like Amazon and Google have been collecting data on all our searches and purchase. But in this article, it talks about how this colossal of data could be the creation of cognitive consultants. This rise could lead to a very intricate understanding of trends . Another article here also looked at how this could help us understand our genomes and background. These two examples show both how this data collection can create mobility in our understanding before and after.


Responses:

Bach: I thought it was interesting how Sweden approaches AI much differently by embracing the technology. I think their approach is much more meticulous by applying them to dangerous work conditions first so they can train the people for new jobs. This was very interesting because AI isn't only relevant in China and the US but also worldwide. And how we approach this new technology is everything for how it affect society and advancement.

Sarina: I thought it was interesting how you looked into the actual military capabilities of AI technology. A big fear with this new technology is how the AI bots will approach these circumstances and if they would act individually of command. And it is a real concern moving forward because the thinking of AI is much different then our way of thinking as efficiency is the main goal. Elon Musk gave a quick circumstance in an interview that it was possible AI bots shot down the plane over Ukraine in order to efficiency resolve the Crimea conflict.

Blog Post 1

Amisial B-1

Three Tech Trends Shifting the BIM Industry in 2016

By Dennis Williams       

http://www.aecbytes.com/viewpoint/2016/issue_80.html

July 21, 2016

HVAC

In this article, some of the new advanced features in building information modeling (BIM) were discussed by informing how they are shifting the trend of this industry in a new age. Particularly, HVAC which is a field that I believe could be more explored to improve building efficiency and performance, decrease the impacts on the environment and increasing occupant comfort was well presented. In fact, I was interested on how the addition of these followings: smart thermostats, talking fridges, reactive lighting units, sensors and software to monitor occupant’s activities while adjusting room temperature, building GPS location to affect lighting and air conditioning in saving energy for when there is enough natural light for a side of the building, are changing our views regarding buildings. I think that it is only the beginning of a new era in HVAC because if we think for a moment in implementing similar features on bigger level such city, states, or countries; we could truly step into some radical changes for a brighter future.

Artificial Intelligence (AI)

Leave AI Alone

By Andrew Burt       

https://www.nytimes.com/2018/01/04/opinion/leave-artificial-intelligence.html

January 4, 2018

This article addresses the controversies regarding AI and discusses the general concerns about implementing regulations on AI; while this last idea is the most challenging for our generation, I must admit that I totally support such opinions. Since, AI has been in used around the 1900s, it was never properly defined, and even currently, the industry is struggling to accurately define it because AI does not represent one single technology or development. On the other hand, I have enjoyed the multiple uses of AI such as 3D printing, financial algorithms, and self-parking and looking forward to new inventions, however, while some might argue that it is too premature to start regulating AI; It would be beneficial to start investing more resources into analyzing the different impacts of AI in the world. It has been reported that AI performed higher in multiple human intelligence areas, so the question remains: will we compete against them or increase our intellectual capacity to better use them?

Comments: 

Carlos,

I have enjoyed your approach on the 3D printing, your information on the main advantages were efficiently presented; however, one the main advantages retains my attention: reduced costs. I have enjoyed the benefits of 3D printing, but I think in some areas, it increases costs in some part of the construction. Compared to developed environment, when there is no need for using the materials produced; it is used most of the time as a markup for future development or construction.

Allison,

Your post on robotics is quite enjoyable, and honestly by implementing autonomous on-site robot, the construction industry would maintain its edge in the world of inventions. I totally agree that such methods will efficiently facilitate the construction process. However, my concern is what is the impacts on human involvement within the construction industry, and since they do not have the inspiration to create or design; what will be our point of view of this aspect. Lastly, I don’t think that we are fully prepared to step into this new era and their implication on a more general level is far beyond 10 years.

Nay Ye Oo,

Your writing on computers related to the future is very interesting; one could clearly see that the trend of this industry for the past decades has been the creation of more portable and comfortable computers while maximizing their performance. The same observation could be made about cellphones, but one thing that got my attention was the multiple or limiting features that most of them have. This genuinely makes me think about what are the consequences or impacts for such computers.

Mark O - B1 Post

AI:

Wilson, Jim and Metz, Cade. “Busting the Myths about A.I. Invading Our Lives.” The New York Times. 2017 Dec. 13.

<https://www.nytimes.com/2017/12/13/technology/personaltech/busting-myths-ai.html>

I was attracted to this article based on the title - my mind instantly associates A.I. with robots gradually outsmarting humans and taking over the planet. Hence, it is refreshing to read a NY Times article assuring that the dawn of the A.I. anarchy will not be occurring soon. The article is written as a question and answer with a technology reporter, Cade Metz, who is located in San Francisco and reflecting on the tech/A.I. that he uses and has written about. Metz marvels at the advances in the voice assistants in the past five years, but his ultimate conclusion is that “the improvements have been enormous. But there is still a very long way to go.” He discusses that the goal of voice assistants to understand conversational speech, and the current assistants do a decent job at recognizing speech, but not understanding. With regard to visual A.I., Metz discusses that computer vision techniques can be flawed in recognition which is problematic if A.I. is to be used for security cameras or autonomous cars. As opposed to my initial fears of robot overlords (which is discussed in the article to a degree), the issue that Metz presses to be more urgent is the shift in job markets that will result from automation. We saw an example of this in class with the masonry-laying robot. However, what scares me most about A.I. ebbing into the workforce is the prospect of A.I. overtaking design positions. Structural engineers rely more and more heavily on structural analysis software, and although it is years away from fruition, the thought of software autonomously producing a complete set of design documents seems plausible to me and is very unnerving. I do not believe the construction industry will reach a point where A.I. is trusted enough to stamp and send out a set of drawings, but I do think A.I. will progress to the point of completing and detailing an entire design autonomously.

Computer:

Wod, Marcus.  “The Plan to Build a Skyscraper that Doesn’t Cast a Shadow.”  Wired.com.n  2015 Mar. 13.

<https://www.wired.com/2015/03/plan-build-skyscraper-doesnt-cast-shadow/>

Without saying, computers have become a stable in nearly all applications, especially in the field of engineering. Under the computer tag, an article was listed that discusses the design of a building that will reflect light in such a way to minimize/eliminate its shadow. What I found most impressive in the article is that the architects simply entered their desired restraints into a software, such as building area and maximized light to the ground. In turn, the software iteratetd through all the possible outcomes and spat out the viable shapes that satisfy the restraints. Design at the press of a button! I think this example shows the immense power that computers hold in crafting solutions to particular problems, especially with buildings.

Software:

Tanz, Jason.  “Andy Rubin Unleashed Android on the World. Now Watch Him Do the Same with AI.”  Wired.com. 2016 Feb. 09.

<https://www.wired.com/2016/02/android-inventor-andy-rubin-playground-artificial-intelligence/#slide-7>

Andy Rubin is an incredible developer who created Android and headed Google’s mobile internet efforts, until he left Google to start his own company. Tanz’s article largely recounts Rubin’s constant innovation and unwavering determination to bring his visions of the future into the realities of today. One of the more eye-catching aspects of the article to me was the included timeline that cites Rubin to be pioneering preliminary versions of social networking (1981), mobile phones (1992), self-driving cars (2004) all before the research and development of these technologies were mainstream. As the article calls him, he is an impatient futurist. Pairing with the discussion of AI above, Rubin foresees A.I. being the focus of the next technological era. However, Rubin is aiming to build his neural network database differently than the other tech players. His vision is to send a fleet of robots (sensing machines) out in the world to feed his A.I. database firsthand with immersive data. To do this, Rubin’s company, named Playground Global, invites developers to use Playground’s advanced engineering sensors and hardware to fulfill their ideas. With this setup, Rubin can fuel the creativity of other developers while sending his sensors out into the world to build his database of data. I am anxious to see the A.I. that is developed from Rubin’s platforms; his thoughts and goals sound good in theory, but I have yet to be convinced that they will work in reality. Regardless, it was quite interesting to read about a developer with such an excitement and vision for where tech can be in the future.

Future:

Metz, Cade.  “Building A.I. That Can Build A.I.”  The New York Times.  2017 Nov. 05

<https://www.nytimes.com/2017/11/05/technology/machine-learning-artificial-intelligence-ai.html>

In the same A.I. spirit as the other articles, Metz writes about a prospective tool that is in development for the future of A.I. The article states that only 10,000 people in the world have the expertise required to develop A.I. - which is leaving the large tech companies to scramble for qualified developers. Hence, AutoML is a pursuit of some tech giants such as Google. ML is explained in the article to stand for machine learning, which means that AutoML would describe machines that are capable of coding A.I. This does not currently exist. The most prevalent concern discussed with A.I. was the automation of jobs, which would cause a shift the workforce. If AutoML becomes advanced enough, coders would be coding themselves out of a job. I appreciate that Google’s solution to the lack of qualified computer experts is: “we can code computer experts!” - however, coding computers with artificial intelligence to generate more computers with A.I. will propagate into a fleet of self-improving A.I. I find this to cross the line of what should be done with A.I.

Comments:

To Andrew Maita:

Most of the articles I read for this round of posting pertained to A.I., one of which focused on building a sensory database for robots to encounter and understand the world around them. I don’t know too much about the 3D printers used for buildings, but I believe they are typically stationed in one location and set up to print around themselves. I could easily see 3D printers advancing into a mobile system with sensors that allow the system to move around the footprint of the building and print as needed. I also think it will only be a matter of time until we can 3D print all of the materials needed for a complete building - I would not be surprised if eventually we can 3D print the rebar as the machine builds up the concrete.

To Zac Arnold:

Having programs with the ability to identify code violations is super useful in my eyes. I always envision designing my own house one day, but know that I would mess up something with the architectural codes and restraints. To the same effect, I agree with you that avoiding something that is obviously catastrophic in a design seems like an intuitive “decision-making” ability for the software.

As you say in your sociology section, some people welcome the automation and others have reservations. I typically have reservations. I think automation can easily be taken too far. One of the articles about A.I. that I read discussed how Google is aiming to develop A.I. that can program more A.I. I think this level of automation, where coders are coding themselves out of a job, takes automation too far; yet, it is the same effect as automating cars on the street and putting taxi drivers out of a job.

To Jordan Shuster

I agree with you that robotics and automation has the potential displace large quantities of people from their current jobs. As I have posted before, A.I. coders are trying to code computers that are capable of developing more A.I. software (AutoML). In the same effect as eliminating jobs from the unskilled and lower-class workers, programmers are trying to program themselves out of a job. From an objective standpoint, a well-coded software and machine would be the more efficient and economical option for many jobs. If we keep leaning into reliance on machines, I do not know what will happen to the workers who are displaced from their job. Who knows... as A.I. for business applications becomes more prevalent (as you discuss with your Google Cloud ML), perhaps everybody will have the business chops at their disposal to thrive as successful entrepreneurs.

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.