obulpathi

9 ms·

31.
Deep Learning Library for Web by Google(pair-code.github.io)
6 points by obulpathi 9y ago|0 comments
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A hardware-accelerated machine intelligence library for the web(pair-code.github.io)
59 points by obulpathi 9y ago|7 comments
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by obulpathi 9y ago
AI is the future of Computing. TensorFlow has established itself as the standard for machine learning. It has an amazing community, and love from researchers as well. TensorFlow, along with Kubernetes, are positioning Google Cloud as a stro
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by obulpathi 9y ago
The comment is a fun poke. Please don't take it literally! NVidia's new Volta GPU has Tensor cores that I think are very similar to what was in first generation TPU. I read the TPU papers and blogs published recently and I am seri
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by obulpathi 9y ago
NVidia announces they are building new generation TPU's and two days later Google announces that they have them in Google Cloud. God Speed!
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by obulpathi 9y ago
> You don't emit logs? I emit logs. I mentioned that in my above comment as well. > So your code assumes that the network/storage/DB are fault-free? No, it does not assume that the network/storage/DB are fault
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by obulpathi 9y ago
To me, the definition of Serverless is this: Developer writes code and the management of resources for running that code is taken care of by a Serverless platform. As a developer, I don't have to deal with servers, disks, networks, log
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by obulpathi 9y ago
> This kind of sounds like you've never managed a production system, sorry. Don't be sorry. Instead, challange me with specific problems you have and I will show you how to build solutions. > how do you process and manage li
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by obulpathi 9y ago
With Google Cloud, Serverless has been a reality from 2015! And welcome to Serverless to those coming from AWS. Here is how Google Cloud achieves serverless. Ingesting Data: PubSub. Scales to millions of messages instantaneously, no need to
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by obulpathi 10y ago
This is awesome news! Good to see Cloud Native Foundation growing to address the needs in Cloud Computing space.
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by obulpathi 10y ago
Thanks! And yes, as you mentioned, the problem is that it works only for inserts. I use Datastore as my primary database. So requesting for supporting Datastore from Datastudio.
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by obulpathi 10y ago
That's exactly my issue. I have a crawler that collects data and stores into Datastore. I need to periodically scoop up the snapshots and export them into BigQuery, then run the visualizations. I want my visualization to be live and al
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by obulpathi 10y ago
Awesome! Datastore connector, please!! Cloud Datastore is the ideal NoOps and Serverless storage solution for projects from small to large. It would be great if you can build a connector for it.
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by obulpathi 10y ago
Lets not assume that Google buys storage from Seagate. Google makes its own hardware for many things (networking, TensorFlow custom ASIC). Also I don't think that have that many number of customers.
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by obulpathi 10y ago
By the time the other company builds infrastructure, some other company would have built the product that Snap wants to build.
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by obulpathi 10y ago
If you are doing just one or two things at a massive scale (Dropbox storing files), it makes sense. But, we are talking about Snap Inc, the infrastructure, and services it needs. A single high-speed intercontinental fiber cable costs 400 Mi
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by obulpathi 10y ago
I don't know.
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by obulpathi 10y ago
Nop. By user I mean per person, not company. Now take a deep breath and think about the scale of Google Cloud.
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by obulpathi 10y ago
I guess that speaks about the scale at which they are operating in Google Cloud. Diane Green mentioned in a recent conference that one of their healthcare customers collect about 2 PB / user. Lot of companies struggle with managing &#x
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by obulpathi 10y ago
Expert on Cloud Computing here. Short answer is "No". Here is why. Google Cloud has infrastructure that scales to petabytes of data and millions of users. Google primary uses this infrastructure for storing, processing and communi
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by obulpathi 10y ago
> I'm not at all, that example was pulled at random as an example. Then give me an example of what you are looking for and I will give you a solution > My company certainly likes to do things in a unique way. And every company ha
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by obulpathi 10y ago
If you are looking for a solution for mobile analytics: https://firebase.google.com/docs/analytics/ If you want a customizable solution, you connect the tools. Pub/Sub for streaming, Dataflow for processing d
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by obulpathi 10y ago
> "We need to do X" and they say "Here is product Y that connects to product Z, but you need to write your own connector." And each product has it's own pricing structure (one by CPU usage, one with flat fees, on
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by obulpathi 10y ago
Google Cloud and AWS are pretty much equivalent in terms of feature parity: https://cloud.google.com/free-trial/docs/map-aws-google-clou... . There are few (10% os services maybe?) that are not available on other p
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by obulpathi 10y ago
I worked with both Google Cloud and AWS. Having read Gartners Magic Quadrants on Cloud, I really question Gartners competency on understanding what Cloud really means. There is no question that Google Cloud is years ahead of AWS (ease of us
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by obulpathi 10y ago
I am very happy to let you know that perspective is informed and correct too! Google Cloud is far better than AWS. Especially in things like Ease of use, scalability, big data, machine learning, NoOps, pricing Google Cloud beats AWS by mile
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by obulpathi 10y ago
Agree 100%. For instances, you have standard, high memory and high CPU and custom. Super easy to make sense of rather than crawling through webpages to understand what each type of instance mean. For example: AWS has r, t, m, g, p instance
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by obulpathi 10y ago
> Many of these solutions are unavailable below a certain scale This was true before Google Cloud. With Google Cloud, you can enjoy these benefits whether you are an individual developer with a sub 100$ monthly budget / a mom n pop
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by obulpathi 10y ago
Give Google Cloud ML a try. With Google Cloud ML, one does not need GPU instances or any other cluster. Just submit your ML job from your computer. Cloud ML will train your model and bill you for the by training resources. No need to spin u
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by obulpathi 10y ago
I completely agree with this. But, what I found more impressive about Google Cloud is that it requires a far fewer number of people to get things done compared to AWS. AWS believes in providing fundamental building blocks rather than framew

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