Google Cloud today announced that it will begin accepting select cryptocurrencies as payment for its online services.
This method will first be offered to a select few customers in the Web 3.0 space, according to the internet giant; this availability is expected to increase over time. The collection of crypto payments will be powered by Coinbase Commerce, which accepts the most popular digital coins: Bitcoin, Ethereum, Dogecoin, Shiba Inu, Litecoin and a few others, including stablecoin USDC.
The announcement was part of Google Cloud Next (GCN), a three-day event where the web advertising titan brags about its latest as-a-service offerings.
“Today we’re announcing a new partnership with Coinbase, which has selected Google Cloud to build advanced exchange and data services,” Google Cloud head Thomas Kurian briefly mentioned, among a series of other news. from GCN. “We will also allow certain customers to pay for cloud services through certain cryptocurrencies using Coinbase Commerce.”
We note that cryptocurrencies have generally declined in price since peaking around November last year. Bitcoin and Ethereum were flat at the time of writing, and Doge was up around a few percent. This volatility may well explain the exclusive availability of payment by select-cryptoin at the moment. The USDC, on the other hand, is pegged to the US dollar.
Coinbase also said it would use Google Cloud to use internet goliath network infrastructure and analytics, and to host a set of its backend systems. Meanwhile, Google will dive into Coinbase’s secure custody and reporting tools.
It’s basically a love of Google-Coinbase and an interesting advantage for the third player in the cloud industry. According to CNBC, Coinbase will move some of its software from Amazon Web Services to Google Cloud.
Also for GCN this week, Mandiant and Google explained why the latter bought the former for $5.4 billion and where it fits in. You can see that and security-related updates here. Let’s take a look at what else is happening at GCN.
Google Cloud announced OpenXLA, an open source project that can help developers build and run AI models on all kinds of hardware.
When building machine learning applications, you may end up tying to a particular framework or optimizing code for a particular accelerator, such as an Nvidia GPU or Google TPU, making it difficult to port to alternatives .
OpenXLA hopes to prevent this kind of lock-in, promising to be an open and universal compiler compatible with various frameworks and hardware backends. Sachin Gupta, Head of Infrastructure at Google Cloud, told GCN that the web giant will make OpenXLA open source its XLA compiler and decouple it from TensorFlow.
“ML development is often hampered by incompatibilities between frameworks and hardware, forcing developers to compromise on technologies when building ML solutions,” he explained in a blog post. “[OpenXLA] will address this challenge by enabling ML developers to build their models on top of the mainstream frameworks (TensorFlow, PyTorch, JAX) and run them with high performance on hardware backends (GPU, CPU and ML accelerators).”
The project is supported by AMD, Arm, AWS, Intel, Meta and Nvidia. Its developers will start by creating an open source community, extracting XLA from TensorFlow and creating StableHLO, which acts as a portability layer between machine learning frameworks and compilers.
Google also launched Vertex AI Vision. Vertex AI is a cloud-based service to help customers deploy pre-trained machine learning models or build their own more easily. The latest Vertex AI Vision feature aims to help companies deploy computer-aided products using their own data. Developers can start adding data by dragging and dropping files to be processed by Google’s AI models to perform tasks such as product recognition, object detection, or occupancy counting.
“We are now releasing Vertex AI Vision to extend the capabilities of Vertex AI so they are more accessible to practitioners and data developers,” said Gerrit Kazmaier, vice president and general manager of Database, Data Analytics and Looker, in a blog post. “This new end-to-end application development environment helps you ingest, analyze and store visual data: video streaming in manufacturing plants, for example, to ensure safety, or streaming from store shelves to improve inventory analysis, or following traffic lights for managing busy intersections.
Google claimed that Vertex AI Vision would help developers build computer vision products in minutes at a tenth of the cost of other platforms. ®