李飞飞宣布谷歌云里程碑事件：推出Cloud AutoML

李飞飞在推特表示“在短短的几个月里，将尖端技术转化为数百万的产品，这是一个相当鼓舞人心的旅程！我们希望AutoML Vision是我们客户的第一选择。”

李飞飞Titter截图

据了解，谷歌Cloud AutoML系统基于监督学习，所以需要提供一系列带有标签的数据。具体来说，开发者只需要上传一组图片，然后导入标签或者通过App创建，随后谷歌的系统就会自动生成一个定制化的模型。

值得一提的是，Cloud AutoML是个开发者的利器，即便你不懂，也能训练出一个定制化的模型。

据悉，目前谷歌还没有公布Cloud AutoML的服务价格，开发者还需要等待。（定西）

【附李飞飞博客全文】

Cloud AutoML: Making AI aessible to every business

When e both joined Google Cloud just over a year ago, e embarked on a mission to democratize AI. Our goal as to loer the barrier of entry and make AI available to the largest possible munity of developers, researchers and businesses.

Our Google Cloud AI team has been making good progress toards this goal. In 2017, e introduced Google Cloud Machine Learning Engine, to help developers ith machine learning expertise easily build ML models that ork on any type of data, of any size. We shoed ho modern machine learning services, i.e., APIs—including Vision, Speech, NLP, Translation and Dialogflo—could be built upon pre-trained models to bring unmatched scale and speed to business applications. Kaggle, our munity of data scientists and ML researchers, has gron to more than one million members. And today, more than 10,000 businesses are using Google Cloud AI services, including panies like Box, Rolls Royce Marine, Kepie and Ocado.

But there’s much more e can do. Currently, only a handful of businesses in the orld have aess to the talent and budgets needed to fully appreciate the advancements of ML and AI. There’s a very limited number of people that can create advanced machine learning models. And if you’re one of the panies that has aess to ML/AI engineers, you still have to manage the time-intensive and plicated process of building your on custom ML model. While Google has offered pre-trained machine learning models via APIs that perform specific tasks, there's still a long road ahead if e ant to bring AI to everyone.

To close this gap, and to make AI aessible to every business, e’re introducing Cloud AutoML. Cloud AutoML helps businesses ith limited ML expertise start building their on high-quality custom models by using advanced techniques like learning2learn and transfer learning from Google. We believe Cloud AutoML ill make AI experts even more productive, advance ne fields in AI and help less-skilled engineers build poerful AI systems they previously only dreamed of.

Our first Cloud AutoML release ill be Cloud AutoML Vision, a service that makes it faster and easier to create custom ML models for image recognition. Its drag-and-drop interface lets you easily upload images, train and manage models, and then deploy those trained models directly on Google Cloud. Early results using Cloud AutoML Vision to classify popular public datasets like ImageNet and CIFAR have shon more aurate results ith feer misclassifications than generic ML APIs.

Here’s a little more on hat Cloud AutoML Vision has to offer:

Increased auracy: Cloud AutoML Vision is built on Google’s leading image recognition approaches, including transfer learning and neural architecture search technologies. This means you’ll get a more aurate model even if your business has limited machine learning expertise.

Faster turnaround time to production-ready models: With Cloud AutoML, you can create a simple model in minutes to pilot your AI-enabled application, or build out a full, production-ready model in as little as a day.

Easy to use: AutoML Vision provides a simple graphical user interface that lets you specify data, then turns that data into a high quality model customized for your specific needs.

“Urban Outfitters is constantly looking for ne ays to enhance our customers’ shopping experience," says Alan Roseninkel, Data Scientist at URBN. "Creating and maintaining a prehensive set of product attributes is critical to providing our customers relevant product remendations, aurate search results and helpful product filters; hoever, manually creating product attributes is arduous and time-consuming. To address this, our team has been evaluating Cloud AutoML to automate the product attribution process by recognizing nuanced product characteristics like patterns and neckline styles. Cloud AutoML has great promise to help our customers ith better discovery, remendation and search experiences."

Mike White, CTO and SVP, for Disney Consumer Products and Interactive Media, says: “Cloud AutoML’s technology is helping us build vision models to annotate our products ith Disney characters, product categories and colors. These annotations are being integrated into our search engine to enhance the impact on Guest experience through more relevant search results, expedited discovery and product remendations on shopDisney.”

And Sophie Maxell, Conservation Technology Lead at the Zoological Society of London, tells us: "ZSL is an international conservation charity devoted to the orldide conservation of animals and their habitats. A key requirement to deliver on this mission is to track ildlife populations to learn more about their distribution and better understand the impact humans are having on these species. In order to achieve this, ZSL has deployed a series of camera traps in the ild that take pictures of passing animals hen triggered by heat or motion. The millions of images captured by these devices are then manually analysed and annotated ith the relevant species, such as elephants, lions and giraffes, etc., hich is a labour-intensive and expensive process. ZSL’s dedicated Conservation Technology Unit has been collaborating closely ith Google’s Cloud ML team to help shape the development of this exciting technology, hich ZSL aims to use to automate the tagging of these images—cutting costs, enabling ider-scale deployments and gaining a deeper understanding of ho to conserve the orld’s ildlife effectively."

If you’re interested in trying out AutoML Vision, you can request aess via this form.

AutoML Vision is the result of our close collaboration ith Google Brain and other Google AI teams, and is the first of several Cloud AutoML products in development. While e’re still at the beginning of our journey to make AI more aessible, e’ve been deeply inspired by hat our 10,000+ customers using Cloud AI products have been able to achieve. We hope the release of Cloud AutoML ill help even more businesses discover hat’s possible through AI.