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Google Cloud AI is used for computer vision-related workloads company-wide for image classification and other related use cases.
- Google Cloud AI was easy to set-up without need for lot of customization and configuration.
- It integrates very well with the Google BigQuery and Google PubSub that makes it easy to have a ready to use pipeline from data ingestion to analysis.
- Google Cloud AI has out of the box CV algorithms and video processing modules/APIs that makes is easy to use for image/video processing application and use cases.
- Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
- Customization of existing modules and libraries is harder and it does need time and experience to learn.
- Google Cloud AI can do a better job in providing better support for Python and other coding languages.
Google is a is a great program to use where I am currently working because throughout the time of working we have tried multiple programs and we do not trust them like this company. It keeps all of our data and information safe from any risks that may be out there and could harm us.
- Storage of information
- Speed
- Design of the program and layout
- More security features for us to keep unauthorized users out.
January 23, 2019
We use the AutoML Natural Language part of the Google Cloud AI products. The NLP processor offered helps us understand user intent, sentiment, and perform other analysis on raw text received through multiple frontends for some of our experimental products. We also use the Cloud Vision API for street sign recognition, surveying, among other uses of converting text in images to text our backend can process and catalog.
- New products - Google is constantly releasing and adding new products to this API, it seems to be on of the fastest-growing products for this.
- Speed - The API is a lot faster than most of the alternative Computer Vision and general-use Machine Learning APIs out there.
- Comprehensive results - The results the API returns for most of the products don't require recurring API requests for processing. Everything is included and organized exactly in the JSON response as mentioned in their documentation for most of these Cloud AI products.
- The documentation format for this API is much better than some of Google's other documentation.
- Hard to find what to use - To find the right products, you need look closely at the details of each API, and find which suits your purposes. This can be easily fixed by creating a main page that details all of the products simply.
- Expensive - The API costs can quickly add up, especially during the setup process and as engineers figure out the usage of the API.
- No playground or training - There is a lack of an "API playground" or training sessions that could make onboarding engineers to this API much easier.
July 11, 2018
This tool is being used in our organization by a specific management team, we are using the speech Cloud API. The truth is, to our team of researchers in the behavior field, it has been extremely useful. The savings in the hours-man equation is something wonderful. Now an activity that took us weeks of time invested before, we can do it in hours. And of course, now we dedicate more time to developing activities carried out with the result of our investigations in relatively short time, thanks to this application.
- good conversion from the voice to the text
- speed in the conversion from voice to text
- time-saving in the conversion activity
- analysis of the results of the conversion in real time
- really this application so far has been very useful.
- we believe that it could be better using other forms apart from the microphone.
- I believe that this application can be merged with another in a way that throws general data on the topics investigated.
January 17, 2019
Some of the Google Cloud AI solutions are being used across the entire organization. We started using the translate function in Legal, Finance, and our global offices. Many of the team were not happy about the change in our Gmail, which we use globally with the new smart version of the inbox with smart reply, but now we really like it. I use it every day. We also use the voice search quite a bit in Google search, and it seems better than competitors.
- Smart reply and its AI suggestions make the organization think more carefully about their e-mail responses in Gmail. We were skeptical at first but it really works well for many instances.
- We do a lot of business and contracts in Western Europe and South America, so the translate solutions make this much easier for our banking paperwork.
- When we go to meetings or during a meeting, we often use the Google voice search to save time on research and filtering ideas or analysis.
- It is great that it helps shortcut and boost productivity, but AI is very much in infancy so it comes back with some crazy responses.
- Not sure how secure the Google Cloud AI is with fraudsters and cybercriminals. Not that we have seen compromises, but building trust all of the time is crucial.
- I always support the need for more training, procedures or on the spot tips for cloud applications. This would make it more seamless, especially since tech is changing so rapidly. It's hard to keep up, so we all need some help to make it 'smoother'.
March 20, 2018
We are using Google Cloud AI as our AI cloud platform for our machine learning projects. These are company-wide efforts that cover multiple business goals, and are aimed at deploying in-house built machine learning algorithms to very large data sets that are constantly increasing via scouring from the web and via APIs.
- Very high performance
- Massive scalability
- Easy-to-use machine learning models
- More transparency on future roadmap of AI services and areas of focus.
Google Cloud AI Scorecard Summary
What is Google Cloud AI?
Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.
Categories: MLOps, Machine Learning
Google Cloud AI Technical Details
| Operating Systems: | Unspecified |
|---|---|
| Mobile Application: | No |
Frequently Asked Questions
What are Google Cloud AI's top competitors?
Amazon SageMaker, IBM Watson Studio on Cloud Pak for Data, and Azure Machine Learning Studio are common alternatives for Google Cloud AI.
What is Google Cloud AI's best feature?
Reviewers rate Support Rating highest, with a score of 7.2.
Who uses Google Cloud AI?
The most common users of Google Cloud AI are from Enterprises and the Information Technology & Services industry.