{"id":32479,"date":"2018-11-13T15:12:54","date_gmt":"2018-11-13T20:12:54","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/made-by-google-powered-by-machine-learning\/"},"modified":"2018-11-13T15:12:54","modified_gmt":"2018-11-13T20:12:54","slug":"made-by-google-powered-by-machine-learning","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/made-by-google-powered-by-machine-learning\/","title":{"rendered":"MADE BY GOOGLE, POWERED BY MACHINE LEARNING"},"content":{"rendered":"

A NEW PRODUCT STRATEGY<\/strong><\/p>\n

The evolution of machine learning (ML) has driven Google to reconsider how it optimizes product performance and delivers meaningful user experiences. \u201cAll of Google was built because we started understanding text and webpages,\u201d CEO Sundar Pichai announced in his keynote address at Google I\/O 2017, the company\u2019s annual developer-focused conference. \u201cThe fact that computers can understand images and video has profound implications for our core mission.\u201d\u00a0[1] While working on consumer operations at Google, I witnessed the company shift its strategy from being mobile first to AI (artificial intelligence) first. Under this new strategy, Google has moved from turning phones into the \u2018remote controls\u2019 of ours lives to creating universally accessible products with smarter computing. [2] The strategy manifested most visibly in product development where further investment was made to build Google-branded hardware and leverage ML to make the technology as intelligent and intuitive as possible.<\/p>\n

With a huge user base and access to information, Google is well positioned to create these ML-led technologies. Google\u2019s mission is to organize the world\u2019s information and make it universally accessible and useful. [3]<\/span> Initially, this mission drove the company to create its well-known search engine and and an open source operating system (OS) for third-party hardware makers to power their products. While the approach is proven successful by the estimated 1.4 billion consumers using Android OS, Google is now building its own hardware products and integrating the hardware with its advanced AI and ML technology, notably marketed as the Google Assistant. [4]<\/span> Pairing software and hardware development has enabled Google to scale faster and build a distinct brand among competitors. Within two years, the company launched the Pixel smartphone, the Google Home smart speaker, and the Daydream VR headset. Offering a suite of hardware products merged with ML has deepened the user\u2019s integration with, and dependence on, the broader Google ecosystem. [5]<\/span><\/p>\n

\"\"<\/a>Source<\/a>: Google Blog, The Keyword (latest product launch: The Google Home Hub)<\/a><\/p>\n

The introduction of AI and ML has redefined the Google product experience and set the business up for continued success and expansion. Distinct to Google devices is the technology that gives users the power to easily and quickly access information. Whether from the home or in the palm of one\u2019s hand, Google more effectively meets users where they are. As information flows become more complex, Google relies on ML and AI to raise the most relevant data at the most relevant times. Now, billions of users rely on Google Photos to manage and share their memories, utilize Google Maps to find the most convenient parking spot, and rely on Gmail to automatically draft responses to unanswered emails — entirely from a Google device.<\/span><\/p>\n

HARDWARE BUILT FOR THE SHORT AND LONG TERM<\/strong><\/p>\n

The company\u2019s investment in hardware has proven to be a worthwhile investment, sparking changes in the organization\u2019s structure. Based on Google\u2019s financial statements, \u2018other revenues,\u2019 which includes sales from hardware, showed a 49% increase year-over-year (YoY) during Q1 2017, amounting to nearly $4 billion in revenues. [6]<\/span> To sustain this momentum in the short term, Google consolidated its hardware teams and chartered the group with the company\u2019s AI first strategy. A more visible example of this approach is highlighted by the reintroduction of Nest, which offers internet-connected thermostats, smoke detectors, and security cameras, from Alphabet back into Google. As speculated prior to the announcement, pulling Nest closer has enabled tighter integration of Google\u2019s AI and ML services with its hardware products and expanded its device offerings. [7]<\/span><\/p>\n

As ML and AI continue to serve as competitive advantages for Google\u2019s hardware, the company is also invested in remaining the industry leader of this technology for the long term. Google has dedicated an entire team, referred to as Google AI, to conduct research, find more opportunity to integrate ML and AI into products, and develop tools that broaden access to these technologies.<\/span>\u00a0[8] For example, the team built TensorFlow, an open-source ML library for research and production, to developers that want to quickly deploy computation across their platforms.<\/span>
\n<\/a><\/p>\n

SET UP FOR SUCCESS<\/strong><\/p>\n

While there is no doubt AI and ML offers Google the opportunity to differentiate its products, the company will constantly need to prove the value of its technology. And as the the product line expands, the company will have to find creative ways to stand out among a crowded hardware market and will have to rely on the assumption that users are willing and able to integrate these products into their homes and lives. The large be on AI and ML raises many questions about the future of Google and the industry. Was it appropriate to invest heavily in hardware in order to grow and drive its AI first strategy? Or were there alternatives that could have placed Google on top of its competitors rather than among them in a crowded hardware market? Finally, in thinking about the long term impact of this technology, does Google have a role in humanizing AI and ML?<\/span>
\n<\/a><\/p>\n

(word count 795)<\/span><\/p>\n

 <\/p>\n

[1] \u00a0Google Developers, \u201cGoogle I\/O Keynote (Google I\/O ’17),\u201d YouTube, published May 17, 2017, https:\/\/www.youtube.com\/watch?v=Y2VF8tmLFHw, accessed November 2018.<\/span><\/p>\n

[2] \u00a0Google blog. Google, \u201cA personal Google, just for you,\u201d https:\/\/googleblog.blogspot.com\/2016\/10\/a-personal-google-just-for-you.html, accessed November 2018.<\/span><\/p>\n

[3] Google homepage. Google, \u201cAbout Google,\u201d https:\/\/www.google.com\/about\/, accessed November 2018.<\/span><\/p>\n

[4] Why Google’s wandering into hardware. (2017, May 2). Business Insider Intelligence. Retrieved from https:\/\/intelligence.businessinsider.com\/post\/why-googles-wandering-into-hardware-app-stores-reach-record-q1-tencent-plans-to-build-us-ai-lab-2017-5<\/span><\/p>\n

[5] Google Home Hub defines its take on the smart home. (2018, Oct 11). Business Insider Intelligence. Retrieved from https:\/\/intelligence.businessinsider.com\/post\/google-home-hub-defines-its-take-on-the-smart-home-foghorn-update-adds-edge-machine-learning-for-iiot-anki-integrating-alexa-into-consumer-robot-2018-10<\/span><\/p>\n

[6] Why Google’s wandering into hardware. (2017, May 2). Business Insider Intelligence. Retrieved from <\/span>https:\/\/intelligence.businessinsider.com\/post\/why-googles-wandering-into-hardware-app-stores-reach-record-q1-tencent-plans-to-build-us-ai-lab-2017-5<\/span><\/a><\/p>\n

[7] Alphabet considers giving nest a new home within google. (2017, Nov 30). Dow Jones Institutional News Retrieved from http:\/\/search.proquest.com.ezp-prod1.hul.harvard.edu\/docview\/1970480544?accountid=11311<\/span><\/p>\n

[8] Google AI. Google, \u201cTools for Everyone,\u201d https:\/\/ai.google\/tools\/, accessed November 2018.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

The introduction of AI and ML has redefined the Google product experience, driving further investment in hardware development and software integration. As information flows become more complex, Google relies on ML and AI to raise the most relevant data at the most relevant times. Now, billions of users rely on Google Photos to manage and share their memories, utilize Google Maps to find the most convenient parking spot, and rely on Gmail to automatically draft responses to unanswered emails — entirely from a Google device.<\/p>\n","protected":false},"author":11488,"featured_media":32634,"comment_status":"open","ping_status":"closed","template":"","categories":[765,4766,2246,346,2185,4765,344],"class_list":["post-32479","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-google","category-google-home","category-hardware","category-machine-learning","category-nest","category-pixel","category-product-development","hck-taxonomy-organization-google","hck-taxonomy-industry-technology","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"\nMADE BY GOOGLE, POWERED BY MACHINE LEARNING - Technology and Operations Management<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/made-by-google-powered-by-machine-learning\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MADE BY GOOGLE, POWERED BY MACHINE LEARNING - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"The introduction of AI and ML has redefined the Google product experience, driving further investment in hardware development and software integration. 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