Google Cloud TPU
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Mochadocs is on a mission to provide people in companies and organizations with a solution that simplifies the process of creating, authorizing, signing, and managing all their contracts seamlessly, from creation to expiration. This comprehensive approach not only saves considerable time and money but also organizes all contractual data in a structured manner.
Furthermore, Mochadocs diminish the frustration and annoyance caused by incomplete contracts, difficulties in locating contracts and amendments, as well as the risk of missing crucial end dates. By providing a streamlined Contract Lifecycle Management experience, Mochadocs ensures that all contractual aspects are efficiently handled, offering peace of mind and efficiency to our users.
With our potent, user-friendly, and fully integrated suite of Contract Lifecycle Management features, individuals can effortlessly oversee their pertinent contract components both within and beyond their organization's scope.
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Mochadocs is the first Contract Lifecycle Management solution with a 100% data-driven approach. This means you are able to create flawless contracts. Sign in a timely manner. And have total control on all your contracts.
Based on our record, Google Cloud TPU seems to be more popular. It has been mentiond 5 times since March 2021. 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.
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
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
Actually, that's done with TPUs which are more efficient: https://cloud.google.com/tpu. Source: almost 3 years ago
TPU training uses Google silicon and is thus a true deep learning alternative to Nvidia. Source: almost 3 years ago
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
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
PactSafe - PactSafe offers a contract management application that enables clients to manage, track, implement, and deploy website legal agreements.
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.
Contractbook - Helping businesses scale with future-proof contracts
Amazon Forecast - Accurate time-series forecasting service, based on the same technology used at Amazon.com. No machine learning experience required.
ContractWorks - ContractWorks provides secure and easy-to-use contract management software that helps you gain control of your contracts.
