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Google CLOUD AUTOML VS Google Cloud TPU

Compare Google CLOUD AUTOML VS Google Cloud TPU and see what are their differences

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Google CLOUD AUTOML logo Google CLOUD AUTOML

Train custom ML models with minimum effort and expertise

Google Cloud TPU logo Google Cloud TPU

Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.
  • Google CLOUD AUTOML Landing page
    Landing page //
    2023-07-30
  • Google Cloud TPU Landing page
    Landing page //
    2023-08-19

Category Popularity

0-100% (relative to Google CLOUD AUTOML and Google Cloud TPU)

Google CLOUD AUTOML

Google Cloud TPU

Data Science And Machine Learning
50 50%
Data Science And Machine Learning
50% 50
AI
100 100%
AI
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Technical Computing
72 72%
Technical Computing
28% 28

User comments

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Social recommendations and mentions

Google CLOUD AUTOML might be a bit more popular than Google Cloud TPU. We know about 6 links to it since March 2021 and only 5 links to Google Cloud TPU. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google CLOUD AUTOML mentions (6)

  • Is there going to be engines dedicated to creating AI?
    There are several no-code AI websites that you can use like Amazon SageMaker, Apple CreateML or Google AutoML. Source: about 1 year ago
  • How AWS and GCP Compare: The Top 5 Differences
    GCP, on the other hand, offers two top options: Google Cloud AutoML, for beginners, and Google Cloud Machine Learning Engine, for handling tasking projects. GCP also provides Tenserflow and Vertex AI complicated machine learning abilities. - Source: dev.to / over 1 year ago
  • Discussion Thread
    Just outsource the work to Google or Amazon. Source: over 2 years ago
  • Is GitHub Copilot a Threat to Developers? (Spoiler: It’s Not
    We can also note the appearance of Machine Learning, creating dynamic processes over data that would have been tedious to analyse, either by hand or through specific code. This enables writing potentially complex behaviours with a few lines of code in some cases. Even then, there is some automation of it to the point where you only have to provide data to get working results. - Source: dev.to / almost 3 years ago
  • Are there any ready-to-use image AI programs for dummies?
    You might want to check out automl Google AutoML. Source: almost 3 years ago
View more

Google Cloud TPU mentions (5)

  • Pathways Language Model (Palm): 540B Parameters for Breakthrough Perf
    According to https://cloud.google.com/tpu, each individual TPUv3 has 420 Teraflops, and TPUv4 is supposed to double that performance, so if that guess is correct, it should take a few seconds to do inference. Quite impressive really. - Source: Hacker News / about 2 years ago
  • The AI Research SuperCluster
    You can also rent a cloud TPU-v4 pod (https://cloud.google.com/tpu) which 4096 TPUv-4 chips with fast interconnect, amounting to around 1.1 exaflops of compute. It won't be cheap though (excess of 20M$/year I believe). - Source: Hacker News / over 2 years ago
  • Stadia's future includes running the backend of other streaming platforms, job listing reveals
    Actually, that's done with TPUs which are more efficient: https://cloud.google.com/tpu. Source: almost 3 years ago
  • Nvidia CEO: Ethereum Is Going To Be Quite Valuable, Transactions Will Still Be A Lot Faster
    TPU training uses Google silicon and is thus a true deep learning alternative to Nvidia. Source: almost 3 years ago
  • Server Question
    The server choice really depends on how much CPU and RAM the requests take, how many users will be hitting the server, etc. You can start with a $5/month Digital Ocean server (or AWS or Google) and see if that works for you. Or you can outsource the server administration to Amazon or Google if you don't want to deal with it or need specialized tpu hardware. Source: about 3 years ago

What are some alternatives?

When comparing Google CLOUD AUTOML and Google Cloud TPU, you can also consider the following products

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.

machine-learning in Python - Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Amazon Forecast - Accurate time-series forecasting service, based on the same technology used at Amazon.com. No machine learning experience required.

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