Google Keynote Address

Initially, when I watched the Google IO 2017 Keynote I was blown away by its attractive presentation of upcoming products and mesmerized by the innovativeness, diversification of different product’s purpose and lastly how dominant Google was. Let me first tell you about the key announcements of these products and explain the commonalities of these different products that informed me how much at the forefront of all technological company giants Google is. By the end of this you may even be scared of threats capitalism poses in letting companies grow to be the size of Google.

The keynote began with simple animation with paired with uplifting music and bright colors in a video that symbolized an entrepreneur’s journey. The title of the animation ‘What will your idea become?”, is a sketch encouraging individuals to follow their passions wherever it might take them and to embrace this process. Soon after Sundar Pichai begins stating how popular Google has become, upcoming products and improvements to other products Google has been working on.

Each Google member on the executive team explained how the common man would use their upcoming products like they themselves have. I identified this as one of Google’s strengths in the fact that they are capable of serving a product capable of understanding who it is talking to and what is seeing to billions of people in a simplistic manner for people from diverse backgrounds and all ages to understand. For example, one of the speakers explains how their machine systems have learned to be conversational. It could recognize speech and infer the person it was speaking to (one of the speakers asks the machine to call his mom— the machine calls his mother instead of his wife’s mother). Next, another key announcement was how machine learning on devices had been developed to the point where it could think for itself by recognizing traits in pictures such as gender, age, expressions. Moreover, these improvements in machine learning were extended to improving computer vision and image recognition to the point where pictures could be altered and understood by the computer. Google Images allows the user to point their camera at a flower and the machine is able to identify what flower is in front of the user.

The commonalities in all of these products were based on that fact that whatever Google was going to create is then going to be used by over 1 billion users. So every speaker emphasized how much time and money Google spends in the building of assets such as AI First Data Centers that optimize the usability of products and allow them to be used on such large scales while not sacrificing performance. Secondly, another commonality was that each product could infer what the user needed to know at that time. For example, when using Google Images just by taking a picture of a sign advertising an upcoming show a window would pop up prompting the user if they might want to buy tickets to a concert of that band or listen to their music.

The weakness of Google stems from the fact that its customer base is so large, any product it develops must have the backbone to support its 1 billion users. This causes several problems for Google. The first being that this product needs to be simplified and tailored for every demographic in the 1 billion users (something such as Google Assistant must hypothesize what a 17-year-old girl may want to watch to a 55-year-old man). Secondly, the research and development of the product must not be complicated enough to the point where only highly qualified engineers can work on its development. For example, this has been seen in the computer’s deep learning process when Google Assistant was being developed to be conversational. The product was originally very challenging to develop and build even for a specialized engineer, it would require developers with PhDs to build the product. Lastly, because Google serves such a large consumer base any product that is developed must be free from small bugs that would detract and frustrate a small portion of users. For example, if the YouTube website was wrongly recommending videos to users that did not appeal to their interests then if a small fraction of these users switched to Vimeo for their means of online entertainment Google would be losing millions of customers.

In conclusion, the Google Keynote address made me excited of the advancements we are making in technology. It amazes me that machines are able to decipher what they are seeing in front of them as well as make conversation with a specific person all while learning from their mistakes. I guess we need a big company with the assets capable of doing this research but at what cost? Google scares me.