Amazon


How AI Could Change Amazon: A Thought Experiment

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What happens to Amazon's strategy as their data scientists, engineers, and machine learning experts work tirelessly to dial up the accuracy on the prediction machine? That said, one can imagine a scenario where Amazon adopts the new strategy even before the prediction accuracy is good enough to make it profitable because the company anticipates that at some point it will be profitable. Today, in the case of AI, some companies are making early bets anticipating that the dial on the prediction machine will start turning faster once it gains momentum. In 2016, GM paid over $1B to acquire AI startup Cruise Automation, and in 2017, Ford invested $1B in AI startup Argo AI, and John Deere paid over $300M to acquire AI startup Blue River Technology – all three startups had generated negligible revenue relative to the price at the time of purchase.


The Surprising Repercussions of Making AI Assistants Sound Human

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But striking a balance between these two extremes remains a significant challenge for voice interaction designers, and raises important questions about what people really want from a virtual assistant. The ability to intonate will make digital assistants capable of similarly nuanced expression. You've probably heard the design maxim form should follow function. Amazon's efforts to make Alexa sound as human as possible suggest that users expect their artificially intelligent sidekicks to do more than turn on their lights or provide a weather forecast.


Amazon has developed an AI fashion designer

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The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.


Amazon has developed an AI fashion designer

#artificialintelligence

The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.


warehouse-robots-learning.html?smid=tw-share

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"It figures out the best way to grab each object, right from the middle of the clutter," said Jeff Mahler, one of the researchers developing the robot inside a lab at the University of California, Berkeley. Inside Amazon's massive distribution centers -- where sorting through stuff is the primary task -- armies of humans still do most of the work. The Berkeley robot was all the more remarkable because it could grab stuff it had never seen before. Mr. Mahler and the rest of the Berkeley team trained the machine by showing it hundreds of purely digital objects, and after that training, it could pick up items that weren't represented in its digital data set.


Amazon has developed an AI fashion designer

#artificialintelligence

The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.


Amazon has developed an AI fashion designer

#artificialintelligence

The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.


Artificial intelligence will create new kinds of work

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Digital workers classify e-mail queries from consumers, for instance, by content, sentiment and other criteria. But consumers and companies will also expect ever-smarter AI services: digital assistants such as Amazon's Alexa and Microsoft's Cortana will have to answer more complex questions. Accordingly, Ms Gray and Siddharth Suri, her collaborator at Microsoft Research, see services such as UpWork and Mechanical Turk as early signs of things to come. The printing press created new work for the wood engravers in Augsburg, but they quickly discovered that it had become much more repetitive.


Amazon's Alexa passes 15,000 skills, up from 10,000 in February

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Amazon's Alexa voice platform has now passed 15,000 skills -- the voice-powered apps that run on devices like the Echo speaker, Echo Dot, newer Echo Show and others. In the meantime, Amazon's Alexa is surging ahead, building out an entire voice app ecosystem so quickly that it hasn't even been able to implement the usual safeguards -- like a team that closely inspects apps for terms of service violations, for example, or even tools that allow developers to make money from their creations. In the long run, Amazon's focus on growth over app ecosystem infrastructure could catch up with it. In addition, Google Home has just 378 voice apps available as of June 30, Voicebot notes.


Machine learning platforms comparison: Amazon, Azure, Google, IBM

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Data scientists who want to build machine learning models and put them into production have no shortage of available tools, but choosing the right one comes with some thorny decisions. Note that many open source tools are available for machine learning, as well as other vendor offerings, but we focused exclusively on vendor cloud platforms that span the entire machine learning lifecycle from data ingestion to model development to production. The market for machine learning platforms is heating up, and all of the leading vendors are looking to nab their share. Several vendors have beefed up their offerings in recent months and now offer simple, cloud-based platforms for getting started with machine learning and developing models that can quickly be put into production.