Google introduced its Cloud AutoML tool to answer that very question. The purpose of Google's AutoML is to bridge the gap between the possibilities of machine learning and artificial intelligence, and all the businesses that don't have the right skillsets to build their models from scratch.
Before now, we did already have access to pre-trained machine learning models on the Google Cloud Platform in the form of APIs. Unfortunately, many companies still found those systems too tricky to use, without specific experts capable of translating the technology required for machine learning. That's why Google decided that they needed something more straightforward - something that would offer the easiest possible point of entry for modern organisations: Cloud AutoML.
The Cloud AutoML service makes it easier for anyone to integrate machine learning abilities into their applications in less than a day. What could be better than a 24-hour route to smarter apps?
Why Did Google Create Cloud AutoML?
Artificial intelligence is everywhere these days. From the intelligent virtual assistants like Google Home that can order pizza for you on demand, to the analytics tools that predict your customer's behavior. Unfortunately, only a handful of today's businesses actually have the AI skills and budgets required to start investing in artificial intelligence and machine learning themselves.
Google wanted to open up some new entry points to disruptive technology, for companies that didn't have the resources to start from scratch with machine learning, but still wanted to experiment with the solutions that this new concept can offer.
As a simple path to AI and machine learning, Cloud AutoML allows companies with no pre-existing expertise to build intelligent applications and models using transfer learning and learning2learn algorithms from Google. The result is that pretty much anyone can create their own innovative machine learning model, regardless of what their experience level might be. Already, companies like Disney are using the Cloud Vision service from AutoML to make the search feature on their online store more intuitive.
The Basics of Cloud AutoML
Cloud AutoML is the most exciting product available in the Google Cloud Platform's portfolio of machine learning and AI tools. The service allows you to train your own high-quality machine learning models, with minimal background knowledge or expertise. Features include:
Incredible performance: Cloud AutoML gives developers access to Google's proprietary technology, which they can use to enhance and develop state-of-the-art applications. Google makes fast predictions with accuracy so that you can innovate more rapidly within your business.
Simple GUI: Google wants to make it easier for anyone to get involved with machine learning and artificial intelligence. With that in mind, they've built AutoML to include a simple graphical user interface which you can use to train, deploy, and improve your AI models based on custom data.
High-quality training data: Using the human labeling service offered by Google, you can create the best possible resources for teaching your machine learning models. The service involves getting real people to annotate and clean data labels, so your machines get the most accurate information possible.
Complete integration: The Cloud AutoML service integrates fully with all the other services available on the Google Cloud, including the Cloud Machine Learning Engine. Because everything works seamlessly together, you can store your training data in the Google Cloud, generate a prediction through your ML model, and use cloud TPU to help your models run more effectively.
Powered by Google's cutting-edge technology: To help you accelerate your machine learning adventures, Google doesn't just offer access to human labeling strategies. You also get access to all of Google's transfer learning technology, which the business uses to create their incredible models.
Understanding the AutoML Process for App Creation
AutoML from the Google Cloud gives anyone the opportunity to create intelligent applications using Google technology. The process of building your ML app is easy. From importing your data into the training model to accessing your design, everything is available through a simple drag-and-drop interface. Google handles all of the complicated parts of AI and machine learning training on your behalf. That means you can just sit back, relax and enjoy the benefits.
Since the market for machine learning experts and data professionals is sadly quite small these days, Google's AutoML could be the perfect way to get ahead of the curve. If like most businesses, you simply don't have the expertise you need to get started with disruptive technology on your own, then Google's custom ML models unlock the door to a previously inaccessible world of exciting opportunities.
Since the announcement of Cloud AutoML at the beginning of this year, Google has been rolling their solutions out in stages. The first feature to emerge was the Cloud AutoML vision strategy, which allows companies to create machine learning models for visual recognition. Now, there's even a deep-dive solution for images, called Cloud Deep Learning VM Image. Throughout the year, Google has also continued to bring new AutoML features into the mix, like AutoML Natural Language, and AutoML translation.
Google AutoML Cloud Vision
Google's AutoML Cloud Vision is the service that Google customers can use to pull powerful insights from their images. In the past, pre-trained APIs were available on the Google Cloud to help developers pull information from visual data. However, today, AutoML vision allows for more flexibility for companies who want to build their visual models from the ground up.
Whereas the Cloud Vision API gave developers a broader view of the context in an image by providing them with ML models in the form of a REST API, the AutoML Vision beta gives Google users the chance to train their high-quality models. Once you've instructed your own machine learning model, you can embed it into any application or tool you like. All you need to do is upload and label images for the ML system to learn from, and your own AI will scale over time, adapting to understand your app and your customers.
The features of Google Cloud AutoML Vision include:
- Simple image search: With Cloud AutoML vision, you can make the images in your content more searchable across broader scenes and topics. State of the art performance comes from access to Google's cutting-edge AI technology, which is an industry leading service in today's marketplace.
- Custom model training: Training the ultimate Google Vision models from scratch. AutoML makes it easier to integrate your own AI into your system with minimal machine learning knowledge.
- Support from real-life people. If you've got images to help you build your machine learning model, but you don't have the labels that your AI would need to understand those pictures, Google can help. The Google AutoML service provides a team of real people who can review your customized instructions and classify your images for you. This service means that you get training data with the same quality that Google uses in its products.
- Full Integration: Not only does AutoML vision come with access to the state-of-the-art Transfer Learning technology used by Google, but it gives you a more streamlined Google cloud experience too. Cloud AutoML, just like many of the other features available through the GCP, is fully integrated with a selection of other Google Cloud services, from cloud storage to analysis.
Google Cloud AutoML Natural Language
For a truly innovative app driven by machine learning and artificial intelligence, you need more than just a system that can recognize and understand images. Human language is inherently complex, which is why there have been so few natural language understanding services available up until now. Fortunately, Google's Natural Language AutoML service means that today's businesses can finally tap into models that unlock the structure and meaning of works through powerful easy-to-build algorithms.
Unlike the Google Cloud Natural Language APIs, which gave developers REST APIs that they could access to unlock pre-trained machine learning models, the AutoML service means that you can create your custom AI systems.
Once you've built your machine learning models, you can use the Google Cloud Natural Language service to extract useful information from massive text documents. You can even use natural language to get to the bottom of customer sentiment analysis, by reading through the comments that people leave on forums and social media channels. With speech-to-text technology integrated as part of the Google Cloud Platform experience, app administrators could even add automatic transcription into their apps, which creates documents out of customer and client conversations. Features of AutoML Natural Language include:
Natural custom-built models: Train your machine learning models with minimal effort and unlock the potential of your machine learning strategy.
Google technology: Like the other AutoML services from Google, Natural Language leverages state-of-the-art technology from Google, to train the most accurate and insightful models.
Content classification: Create labels to customize the models in your natural language framework or tap into the human labeling service from Google for enhanced accuracy.
Google Cloud AutoML Translation
What if you could automatically translate any language in a matter of seconds?
Google Cloud's Translation service is unlocking the full power of machine learning and artificial intelligence to answer that question. The Cloud Translation service gives companies the chance to embed translation models into their applications, which dynamically switch one language to another.
Like the other services available on Google AutoML, the translation service started off in an API format, available through the RESTful system. Now, of course, you can take your Translation strategies to the next level, by creating your model on Google's platform.
The Translation service from Google translates strings of data into any supported language available on your application. Because you're training your model yourself with AutoML, there's no limit to what you can potentially translate, as long as you have enough data to teach your AI models with. You can even implement language detection options for instances in which the source language might not be distinct, to begin with. This technology comes from Google's translate feature, which you've probably used before.
To start using the AutoML Translation feature, all you'll need to do is upload translated language page into the Google Cloud system and teach your AI models to understand both languages at once. The AutoML Translation service can scale dynamically to support the demands of your business, and the simplicity of the interface means that you can design a high-quality translation model for any app within a short amount of time. Features of AutoML translation include:
Language support for a wide range of different language pairs. You can quickly make an application that connects with customers and colleagues from countless different countries.
Custom training with minimal effort: Create your custom AI models with very little prior knowledge in machine learning. Google gives you access to their state-of-the-art systems, so entering the ML market is easy.
Programmatic access: If you'd prefer to use a model that's already been built by a team of industry experts, then you can always use the Google REST API instead. Sample code is available online for a selection of different programming languages.
Full integration: Like many other solutions from the Google Cloud, the Translation AutoML service integrates with solutions across the entire Google cloud service, including speech to text - so you could potentially translate customer conversations.
Accessing One of a Kind Machine Learning with Google
According to Google, AutoML is the only system available on the market that offers the same level of simple access to AI and machine learning. Of course, there are other companies out there that are experimenting with allowing customers to customize their own pre-trained machine learning models, although most don't offer the same level of granular personalization as Google.
Today, anyone can sign up to request access to one of the machine AutoML solutions available in Beta. To find out more about machine learning and Google, remember to reach out to the experts here at Coolhead Tech. We're happy to help!