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obulpathi

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Born and brought up in India, did my Ph.D. in Big Data from the University of Florida.

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Goodbye Gas Fees 5 years ago

What makes you think Solana is Centralized? It runs over 2000 nodes. The number is currently is less than that of Ethereum node count, as the demand is less.

It also would be a fair comparison to compare what is existing today. So, please don't say that Ethereum 2.0 will be far more efficient. By that time Solana would have made great strides too. So, let's compare what is existing today. Ethereum 2.0 is being touted for several years and still not ready. We can compare Ethereum 2.0, when it's ready and there, but not now.

Goodbye Gas Fees 5 years ago

I don't buy the argument: "ETH fees was meant to be high!". Its the same as saying "ETH is meant to be unusable for people other than whales."

Goodbye Gas Fees 5 years ago

Why use L2 when one can have a better experience with much lower fees (Solana, Avalance, Flow & Near). The new generation Blockchains like Solana and Avalance are far better than Ethereum. They are going throgh some growing pains, other wise, they beat Ethereum to dust in terms of speed, latency and performance. Solana takes a second to confirm a transaction, with 0.00025$ fees and can support more than 100,000 tx/s. While Ethereum take a minute to confirm a transaction and cost about 100$ and can only process about 15 tx/s. Also, Ethereum is about 1000 times more energy hungry than Solana.

For fundamentals, this resource by Varsity (kind of like Robinhood of India) is pretty good. It uses India's stocks as examples and deals in Rupees and not in Dollars.

After learning the basics, I would recommend "The 80/20 Investor" book. The book has very good advice how to buy stocks, market bubbles and building the circle of competence.

They actually pushed ChromeOS and web services (GMail, Inbox, Docs, Sheets, ... ) pretty hard and realized that its not the way to go forward. While for lightweight tasks (like emailing and docs) it works pretty well, for heavy tasks (like video editing) and most importantly, as a development platform, chrome os din't do well.

So they pivoted to Fuchsia OS. A new OS to provide seamless experience across several devices (in home or in vehicle while commuting. Some of the resource can be living in cloud). Its a sort of networked OS. Streaming music to your Google Home, let me fetch that music form the Fuchsia Desktop's cache and stream it to Google Home, rather than fetching it all the way from Cloud.

With out applications, OS is not much of use. Here comes Flutter. Let the developers make apps for Android and iOS in Flutter (currently over 50k apps on Google Play store) and have them run the same app on Fuchsia OS. I believe it will take probably another year or two for Google to bring in Fuchsia to Pixelbook. Let's hope so! I would like an OS as open as Linux, with macOS like user experience.

I don't know when this happened. Give GKE a try, it's really amazing. Blows EKS out of water. As per the flexibility is concerned, once you learn how to use Google Services, you can get the flexibility with simplicity. AWS services are too complex and even things like billing require a PhD degree in finance to optimize for anything non-trivial.

Or use Google Cloud, which has 90% good parts. Documentation can be a bit pain, but the services themselves are rocksolid. There are no 3/4 queuing services, just one. GKE rocks! Cloud Console is a breath of fresher, compared to AWS. Cloud Shell makes it easy to bypass firewalls for logging into instances and no messing with public keys. It's all managed for you. Use firebase if you are looking specifically for Web and Mobile Apps. Scaling to millions of users or Petabytes of data is no big deal and you don't have to rearchitect everytime your customer base grows by 10x.

What are some good use cases for a .dev domain? For example, .ai for Artificial Intelligence, .io for startups. One thing that comes to my my mind is .dev is good for developer tools and related projects. Any other projects or products that .dev domain can be used for? Thanks!

Used to buy lots of things from Amazon. About couple of years ago, shifted to buying things from Costco and it's been a great experience. Everything I get is authentic, they only sell the best products and heard they treat their employees nicely. I stopped doing hours of review research to find out if the products are legit and if reviews were not fabricated.

I came to US about 10 years ago. Finished my PhD and spent about 4 years in Software Industry. Saved some money. US has taught me a lot about entrepreneurship and software. Now moving to India for good to work on my own startup, spend more time with my hobbies and to stay close with my parents who are in their 60's. It took me more than an year to convince my parents (hardest to convince was my Mom) and my Wife. Looking back, I feel that is one of the best, courageous and hardest decisions I have taken in my life.

Also thanks to YC for accepting my Startup in to their Startup School Advisor Track. Namaste!

Yep, same problems with many other services:

* Kinesis Streams: Writes limited to 1K/sec and 1 MB / shard, reads limited to 2K/shard. Want a different read/write ratio? Nop, not possible. Proposed solution: use more shards. Does not scale automatically. There is another service called Kinesis Streams that does not offer read access to streaming data.

* EFS: Cold start problems. If you have small amount of data in EFS, reads and writes are throttled. Ran into into some serious issues due to write throttling.

* ECS: Two containers can not use same port on same node. Anti pattern to containers.

AWS services have lots of strings attached and minimums for usage and billing. Building such services (based on fixed quotas) is much easier than building services which are billed purely pay per use. This complexity + cost optimization pressures lead to complexity and require more human resources and time as well. AWS got good lead in Cloud space, but they need to improve their services without letting them rot.

Quoting from the article: "This accomplishment would not have been possible for our three-person team of engineers to achieve without the tools and abstractions provided by Google and App Engine."

Talking about the use case from the article, they release the puzzle at 10 and need to have infra ready to serve up all the requests. On AWS, you need to pre warm load balancers, increase the quota of your Dynamo DB, scale up instances so that they can withstand the wall of traffic, ... and then scale down after the traffic. All this takes time, people and money. Adding few other things author mentioned: Monitoring/Alerting, Local Development, Combined Access and App Logging ... will take focus from developing great apps to building out the infrastructure for apps.

Adding more context. Sorry for missing it out in first place. I mostly work in Big Data Space. Google Clouds Big Data stuff is built for Streaming / Storing / Processing / Querying / Machine Learning at Internet Scale data (PubSub / Bigtable / Dataflow / BigQuery / Cloud ML). AWS scales to terabyte level loads. But, beyond that, its hard and super costly. Google's services autoscale to Petabyte levels / millions of users smoothly (for example BigQuery / Load Balancers). On AWS, it requires pre warming / allocating capacity beforehand and that costs tons of money. In companies working at that scale, that usual saying is "to keep scaling, keep throwing cash at AWS". This is not a problem with Google.

Sorry to not add context. I was referring to the use case the author of article was talking about: running a website: You need to stitch: ELB / EC2 / Database / Caching / Service Splitting / Auth / Scaling / ... Where as on Google Cloud, App Engine covers most of the points.

Two things keep coming up while comparing GCP and AWS:

* This accomplishment would not have been possible for our three-person team of engineers with out Google Cloud (AWS is too low level, hard to work with and does not scale well).

* We’ve also managed to cut our infrastructure costs in half during this time period (Per minute billing, seamless autoscaling, performance, sustained usage discounts, ... )

Even better are Google managed services (PubSub / Dataflow / Datastore), which scale up and down based on usage (cloud native products) and thus save money automatically compared to their equivalents in AWS (Kinesis / Kinesis Analytics / DynamoDB) which does not autoscale.

I don't think so. GCP's bill is usually about 50% of AWS's bill for same application, if you run it full hour (from my personal experiences and from several others as well: https://thehftguy.com/2016/11/18/google-cloud-is-50-cheaper-...). GCP has lot more cost saving features like seamless scalability, custom shapes, sustained discounts and so on. If you workloads span less than hour, GCP can offer more then 50% savings.

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 strong contender in Cloud Computing Space. With Cloud TPU and Cloud ML, Google has leaped few years ahead of other AWS and Azure.

Google.ai 9 years 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 seriously impressed by TPUs!

Google.ai 9 years 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!