WHY IT MATTERS: Digital Transformation

There’s an old saying that the first fifty years of the car industry were about creating car companies and working out what cars should look like, and the second fifty years were about what happened once everyone had a car - they were about McDonalds and Walmart, suburbs and the remaking of the world around the car, for good and of course bad. The innovation in cars became everything around the car. One could suggest the same today about smartphones - now the innovation comes from everything else that happens around them.

A curated list of awesome Deep Learning tutorials, projects and communities.

The AI Index is an open, not-for-profit project to track activity and progress in AI. It aspires to be a comprehensive resource of data and analysis for policymakers, researchers, executives, journalists and others to rapidly develop intuitions about the complex field of AI.
AI is the new electricity, and is transforming multiple industries. The AI Index will help current generations track and navigate this societal transformations. It will also help future generations look back and understand the AI's rise.

This guide is for anyone who is curious about machine learning but has no idea where to start. I imagine there are a lot of people who tried reading the wikipedia article, got frustrated and gave up wishing someone would just give them a high-level explanation. That’s what this is. The goal is be accessible to anyone — which means that there’s a lot of generalizations. But who cares? If this gets anyone more interested in ML, then mission accomplished.

What AI can — and cannot — do for your organization.

Google cloud vision API allows developers to analyze the content of images.

Find out how you can make use of Google's machine learning expertise to power your applications. Google Cloud Platform (GCP) offers five APIs that provide access to pre-trained machine learning models with a single API call: Google Cloud Vision API, Cloud Speech API, Cloud Natural Language API, Cloud Translation API and Cloud Video API. Using these APIs, you can focus on adding new features to your app rather than building and training your own custom models. In this session we'll share an overview of each API and dive into code with some live demos.

The AlphaGo Zero agent destroyed the original AlphaGo that beat Lee Sedol 100-0 after just three days of training.

Creating and maintaining a platform for reliably producing and deploying machine learning models requires careful orchestration of many components—-a learner for generating models based on training data, modules for analyzing and validating both data as well as models, and finally infrastructure for serving models in production. This becomes particularly challenging when data changes over time and fresh models need to be produced continuously. Unfortunately, such orchestration is often done ad hoc using glue code and custom scripts developed by individual teams for specific use cases, leading to duplicated effort and fragile systems with high technical debt. We present the anatomy of a general-purpose machine learning platform and one implementation of such a platform at Google. By integrating the aforementioned components into one platform, we were able to standardize the components, simplify the platform configuration, and reduce the time to production from the order of months to weeks, while providing platform stability that minimizes service disruptions. We present the case study of one deployment of the platform in the Google Play app store, where the machine learning models are refreshed continuously as new data arrive. Deploying the platform led to reduced custom code, faster experiment cycles, and a 2% increase in app installs resulting from improved data and model analysis.

A new idea is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn.

Explore TensorFlow Playground demos. See how they explain the mechanism and power of neural networks, which extract hidden insights and complex patterns.

Instacart is saving minutes per delivery by sorting shopping lists using deep learning. Emojis help to define the problem and outline both a simple and a more complex deep learning architecture.

Teachable Machine, an experiment that makes it easier for anyone to explore machine learning. Teach a machine using your camera – live in the browser, no coding required.

Tech giants including Baidu and Google spent between $20B to $30B on AI in 2016, with 90% of this spent on R&D and deployment, and 10% on AI acquisitions. AI investment has turned into a race for patents and intellectual property (IP) among the world’s leading tech companies.

ARK Invest aims to identify large-scale investment opportunities resulting from technological change. We believe innovation is key to growth. From a broad spectrum of disruptive innovations, Big Ideas represents our annual breakout of technologies that we believe will accelerate significantly in the months ahead.

Have you looked at Google Trends? It’s pretty cool — you enter some keywords and see how Google Searches of that term vary through time. I thought — hey, I happen to have this arxiv-sanity database of 28,303 (arxiv) Machine Learning papers over the last 5 years, so why not do something similar and take a look at how Machine Learning research has evolved over the last 5 years?

Thanks to machine learning, it’s becoming easy to generate realistic video, and to impersonate someone.

Systems able to recognize sounds familiar to human listeners have a wide range of applications, from adding sound effect information to automatic video captions, to potentially allowing you to search videos for specific audio events. Building Deep Learning systems to do this relies heavily on both a large quantity of computing (often from highly parallel GPUs), and also – and perhaps more importantly – on significant amounts of accurately-labeled training data. However, research in environmental sound recognition is limited by currently available public datasets.
In order to address this, we recently released AudioSet, a collection of over 2 million ten-second YouTube excerpts labeled with a vocabulary of 527 sound event categories, with at least 100 examples for each category.

• 70% of retail decision makers globally are ready to adopt the Internet of Things to improve customer experiences.
• 73% of retailers rate managing big data as important or business-critical to their operations.
• 78% of retailers say it is important or business-critical to integrate e-commerce and in-store experiences, so an omnichannel experience is delivered to every customer.
• 87% of retailers will deploy mobile point-of-sale (MPOS) devices by 2021, enabling them to scan and accept credit or debit payments anywhere in the store.
• 90% of retailers will implement buy online, pickup in store by 2021.

YouTube-BoundingBoxes is a large-scale data set of video URLs with densely-sampled high-quality single-object bounding box annotations.

The data set consists of approximately 380,000 15-20s video segments extracted from 240,000 different publicly visible YouTube videos, automatically selected to feature objects in natural settings without editing or post-processing, with a recording quality often akin to that of a hand-held cell phone camera.

All these video segments were human-annotated with high precision classifications and bounding boxes at 1 frame per second.

Maybe you’ve downloaded TensorFlow and you’re ready to get started with some deep learning?

But then you wonder: What the hell is a tensor?

Perhaps you looked it up on Wikipedia and now you’re more confused than ever. Maybe you found this NASA tutorial and still have no idea what it’s talking about?

The problem is most guides talk about tensors as if you already understand all the terms they’re using to describe the math. Have no fear! I hated math as a kid, so if I can figure it out, you can too! We just have to explain everything in simpler terms.

These principles were developed in conjunction with the 2017 Asilomar conference (videos here), through the process described here. Artificial intelligence has already provided beneficial tools that are used every day by people around the world. Its continued development, guided by the following principles, will offer amazing opportunities to help and empower people in the decades …

Raffi Khatchadourian on Nick Bostrom, an Oxford philosopher who asks whether inventing artificial intelligence will bring us utopia or destruction.