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Google Cloud Platform vs. AWS: Is the Answer Obvious? Maybe Not

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Click to learn more about author Jay Chapel.

Google Cloud Platform vs. AWS: What’s the deal? A while back, we also asked the same question about Azure vs. AWS. After the release of the latest earnings reports a few weeks ago from AWS, Azure, and GCP, it’s clear that Microsoft is continuing to see growth, Amazon is maintaining a steady lead, and Google is stepping in. Now that Google Cloud Platform has solidly secured a spot among the “big three” cloud providers, we think it’s time to take a closer look and see how the underdog matches up to the rest of the competition. 

Is Google Cloud Catching up to AWS?

As they’ve been known to do, Amazon, Google, and Microsoft all released their recent quarterly earnings around the same time the same day. At first glance, the headlines tell it all:

The obvious conclusion is that AWS continues to dominate in the cloud war. With all major cloud providers reporting earnings around the same time, we have an ideal opportunity to examine the numbers and determine if there’s more to the story. Here’s what the quarterly earning reports tell us:

  • AWS had the slowest growth they have ever had since they began separating their cloud reportings – up just 37% from last year.
  • Microsoft Azure reported a revenue growth rate of 59%.
  • Microsoft doesn’t break out specific revenue amounts for Azure, but Microsoft did report that its “Intelligent Cloud” business revenue increased 27% to $10.8 billion, with revenue from server products and cloud services increasing 30%.
  • Google’s revenue has cloud sales lumped together with hardware and revenue from the Google Play app store, summing up to a total of $6.43 billion for the last quarter. 
  • To compare, last year during Q3 their revenue was at $4.64 billion.
  • During their second-quarter conference call in July, Google said their cloud was on an $8 billion revenue run rate – meaning cloud sales have doubled in less than 18 months.
Source: Canalys

You can see here that while Google is the smallest out of the “big three” providers, they have shown the most growth – from Q1 2018 to Q1 2019, Google Cloud has seen growth of 83%. While they still have a ways to go before surpassing AWS and Microsoft, they are moving quickly in the right direction, as Canalys reported they were the fastest-growing cloud-infrastructure vendor in the last year. 

It’s also important to note that Google is just getting started. Also making headlines was an increase in new hires, adding 6,450 in the last quarter, and most of them going to positions in their cloud sector. Google’s headcount now stands at over 114,000 employees in total.

Source: Canalys

The Obvious: Google Is Not Surpassing AWS

When it comes to Google Cloud Platform vs. AWS, we have a clear winner. Amazon continues to have the advantage as the biggest and most successful cloud provider in the market. While AWS is growing at a smaller rate now than both Google Cloud and Azure, Amazon still holds the largest market share of all three. AWS is the clear competitor to beat, as they are the first and most successful cloud provider to date, with the widest range of services and a strong familiarity among developers.

The Less Obvious: Google Is Actually Gaining More Ground

While it’s easy to write off Google Cloud Platform, AWS is not untouchable. AWS has already solidified itself in the cloud market, but with the new features and partnerships, Google Cloud is proving to be a force to be reckoned with. 

Where Is Google Actually Gaining Ground?

We know that AWS is at the forefront of cloud providers today, but that doesn’t mean Google Cloud is very far behind. AWS is now just one of the three major cloud providers – with two more (IBM and Alibaba) gaining more popularity as well. Google Cloud Platform has more in store for its cloud business in 2020. 

A big step for Google was announced earlier this year at Google Cloud’s conference – Google Cloud Next – when the CEO of Google Cloud said they would be coming out with a retail platform to directly compete with Amazon, called Google Cloud for Retail. What’s different about their product? For starters, they are partnering with companies such as Kohl’s, Target, Bed Bath & Beyond, Shopify, etc. – these retailers are known for being direct competition with Amazon. In addition to that, this will be the first time that Google Cloud has had an AI product that is designed to address a business process for a specific vertical.

Google doesn’t appear to be stopping at just retail – Google Cloud’s new CEO, Thomas Kurian, said they are planning to build capabilities to assist companies in specialized industries (e.g. health care, manufacturing, media, and more). 

Google’s stock continues to rise. With nearly 6,450 new hires added to the headcount, a vast majority of them being cloud-related jobs, it’s clear that Google is serious about expanding its role in the cloud market. In April of this year, Google reported that 103,459 now work there. Google CFO Ruth Porat said, “Cloud has continued to be the primary driver of headcount.” What’s more, Kurian understands that Google is lagging behind the other two cloud giants, and plans to close that gap in the next two years by growing sales headcount. 

Deals have been made with major retailer Kohl’s department store, and payments processor giant PayPal. Google CEO Sundar Pichai lists the cloud platform as one of the top three priorities for the company, confirming that they will continue expanding their cloud sales headcount. 

In the past few months, Pichai added his thoughts on why he believes the Google Cloud Platform is on a set path for strong growth. He credits their success to customer confidence in Google’s impressive technology and a leader in machine learning, naming the company’s open-source software TensorFlow as a prime example. Another key component to growth is strategic partnerships, such as the deal with Cisco that is driving co-innovation in the cloud with both products benefiting from each other’s features, as well as teaming up with VMware and Pivotal. 

Driving Google’s growth is also the fact that the cloud market itself is growing so rapidly. The move to the cloud has prompted large enterprises to use multiple cloud providers in building their applications. Companies such as Home Depot Inc. and Target Corp. rely on different cloud vendors to manage their multi-cloud environments. 

Home Depot, in particular, uses both Azure and Google Cloud Platform, and a spokesman for the home improvement retailer explains why that was intentional: “Our philosophy here is to be cloud-agnostic, as much as we can.” This philosophy goes to show that as long as there is more than one major cloud provider in the mix, enterprises will continue trying, comparing, and adopting more than one cloud at a time – making way for Google Cloud to gain more ground.

Multi-cloud environments have become increasingly popular because companies enjoy the advantage of the cloud’s global reach, scalability, and flexibility. Google Cloud has been the most avid supporter of multi-cloud out of the three major providers. Earlier this year at Google Cloud Next, they announced the launch of Anthos, a new managed service offering for hybrid and multi-cloud environments to give enterprises operational consistency. They do this by running quickly on any existing hardware, leverage open APIs and give developers the freedom to modernize. There’s also Google Cloud Composer, which is a fully managed workflow orchestration service built on Apache Airflow that allows users to monitor, schedule, and manage workflows across hybrid and multi-cloud environments.

Google Cloud Platform vs. AWS – Why Does It Matter?

Google Cloud Platform vs. AWS is only one of the battles to consider in the ongoing cloud war. The truth is, market performance is only one factor in choosing the best cloud provider. As we always say, the specific needs of your business are what will ultimately drive your decision. 

What we do know: the public cloud market is not just growing – it’s booming. Referring back to our Azure vs. AWS comparison, the basic questions still remain the same when it comes to choosing the best cloud provider: 

  • Are the public cloud offerings to new customers easily comprehensible?
  • What is the pricing structure and how much do the products cost?
  • Are there adequate customer support and growth options?
  • Are there useful management tools?
  • Will our DevOps processes translate to these offerings?
  • Can the PaaS offerings speed time-to-value and simplify things sufficiently, to drive stickiness?

Right now AWS is certainly in the lead among major cloud providers, but for how long? We will continue to track and compare cloud providers as earnings are reported, offers are increased, and price options grow and change. 

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Source: https://www.dataversity.net/google-cloud-platform-vs-aws-is-the-answer-obvious-maybe-not/

Big Data

WHT: A Simpler Version of the fast Fourier Transform (FFT) you should know

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WHT: A Simpler Version of the fast Fourier Transform (FFT) you should know

The fast Walsh Hadamard transform is a simple and useful algorithm for machine learning that was popular in the 1960s and early 1970s. This useful approach should be more widely appreciated and applied for its efficiency.


By Sean O’Connor, a science and technology author and investigator.

The fast Walsh Hadamard transform (WHT) is a simplified version of the Fast Fourier Transform (FFT.)

The 2-point WHT of the sequence a, b is just the sum and difference of the 2 values:

WHT(a, b) = a+b, a-b. 

It is self-inverse allowing for a fixed constant:

WHT(a+b, a-b) = 2a, 2b 

Due to (a+b) + (a-b) = 2a and (a+b) – (a-b) = 2b.

The constant can be split between the two Walsh Hadamard transforms using a scaling factor of √2 to give a normalized WHTN:

WHTN(a, b) = (a+b)/√2, (a-b)/√2 WHTN((a+b)/√2, (a-b)/√2) = a, b 

That particular constant results in the vector length of a, b being unchanged after transformation since a2+b2 =((a+b)/√2)2+ ((a-b)/√2)2 as you may easily calculate.

The 2-point transform can be extended to longer sequences by sequentially adding and subtracting pairs of similar terms, alike in the pattern of + and – symbols they contain.

To transform a 4-point sequence a, b, c, d first do two 2-point transforms:

WHT(a, b) = a+b, a-b WHT(c, d) = c+d, c-d 

Then add and subtract the alike terms a+b and c+d:

WHT(a+b, c+d) = a+b+c+d, a+b-c-d 

and the alike terms a-b and c-d:

WHT(a-b, c-d) = a-b+c-d, a-b-c+d 

The 4-point transform of a, b, c, d then is

WHT(a, b, c, d) = a+b+c+d,  a+b-c-d, a-b+c-d, a-b-c+d 

When there are no more similar terms to add and subtract, that signals completion (after log2(n) stages, where n is 4 in this case.)  The computational cost of the algorithm is nlog2(n) add/subtract operations, where n, the size of the transform, is restricted to being a positive integer power of 2 in the general case.

If the transform was done using matrix operations, the cost would be much higher (n2 fused multiply-add operations.)

Figure 1.  The 4-point Walsh Hadamard transform calculated in matrix form.

The +1, -1 entries in Figure 1 are presented in a certain natural order which most of the actual algorithms for calculating the WHT result in, which is fortunate since then the matrix is symmetric, orthogonal and self-inverse.

You can also view the +1, -1 patterns of the WHT as waveforms.

Figure 2.  The waveforms of the 8-point WHT presented in natural order.

When you calculate the WHT of a sequence of numbers, you are really just determining how much of each waveform is embedded in the original sequence.  And that is complete and total information with which you can fully reconstruct any sequence from its transform.

The waveforms of the WHT typically correlate strongly with the patterns found in natural data like images, allowing the transform to be used for data compression.

Figure 3.  A 65536-pixel image compressed to 5000 points using a WHT.

In Figure 3, a 65536-pixel image was transformed with a WHT, the 5000 maximum magnitude embeddings were preserved, and then the inverse transform was applied (simply another WHT.)

The central limit theorem (CLT) tells you that adding a large quantity of random numbers results in the Normal distribution with its characteristic bell curve.  The CLT applies equally to sums and differences of a large quantity of random numbers.  As a result, C.M. Rader proposed (in 1969) using the WHT to quickly generate Normally distributed random numbers from conventional uniformly distributed random numbers.  You simply generate a sequence of uniform random numbers, say between –1 and 1, and then transform them using the WHT.

Similarly, you can disrupt the orderly waveform patterns of the WHT by choosing a fixed randomly chosen pattern of sign flips to apply to any input to the transform.  That is equivalent to multiplying the WHT matrix H with a diagonal matrix D of randomly chosen +1, -1 entries giving HD.  The disrupted waveform patterns in HD then fail to correlate with any of the patterns seen in natural data.  As a result, the output of HD has the Normal distribution and is actually a fast Random Projection of the natural data.  Random projections have a wide number of applications in machine learning, such as locality sensitive hashing, compressive sensing, random projection trees, neural network pre and post-processing etc.

References

Walsh (Hadamard) Transform:

Normal Distribution:

Random Projections:

Other Applications:

Related:


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Source: https://www.kdnuggets.com/2021/07/wht-simpler-fast-fourier-transform-fft.html

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Must-Know Text Operations in Python before you dive into NLP!

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Text Operations in Python | Must-Know Text Operations in Python for NLP





















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Source: https://www.analyticsvidhya.com/blog/2021/07/must-know-text-operations-in-python-before-you-dive-into-nlp/

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Canada’s Rogers Communications beats quarterly revenue estimates

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(Reuters) -Canada’s Rogers Communications Inc on Wednesday reported second-quarter revenue that beat analysts’ estimates, helped by a pick up in advertisement sales and as its cable business benefited from a pandemic-driven shift to remote work and entertainment.

The requirement of high-speed broadband networks to carry on remote work helped the telecom operator negate the slow recovery from its wireless business.

The return of live sport broadcasting also played a positive role in boosting the Toronto-based telecom operator’s revenue.

The company’s total revenue rose to C$3.58 billion ($2.82 billion) in the quarter ended June 30, compared with analysts’ average estimates of C$3.56 billion, according to IBES data from Refinitiv.

Earlier in March, Rogers said it would buy Shaw Communications Inc for about C$20 billion ($16.02 billion), aiming to double down on its efforts to roll out 5G throughout the country.

Revenue for its cable unit, which includes internet, phone and cloud-based services, rose 5% during the quarter

Quarterly net income rose to C$302 million, or 60 Canadian cents per share, from C$279 million, or 54 Canadian cents, a year earlier.

($1 = 1.2686 Canadian dollars)

(Reporting by Tiyashi Datta in Bengaluru; Editing by Shailesh Kuber)

Image Credit: Reuters

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Source: https://datafloq.com/read/canadas-rogers-communications-beats-quarterly-revenue-estimates/16522

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Climate friendly cooling tech firm gets $50 million from Goldman Sachs

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By Jane Lanhee Lee

(Reuters) – Chemicals used in air conditioning, freezers and refrigeration have long hurt the environment by destroying the ozone layer and polluting water sources, but technology is starting to change the way we keep cool.

Phononic, a startup based in Durham North Carolina using a material called bismuth telluride to make so-called cooling chips, on Wednesday said it raised $50 million from Goldman Sachs Asset Management.

When electricity runs through the chip the current takes heat with it leaving one side of the chip to cool and the other to heat up, said Tony Atti, Phononic co-founder and CEO.

The chips can be as small as a fraction of a fingernail or as big as a fist depending on how much coolants are needed and have been used to create compact freezers for vaccine transportation or for ice-cream at convenience stores like Circle K, he said. A more recent and fast growing use is to prevent overheating in lidars, laser-based sensors in autonomous cars, and optical transceivers for 5G data transmission, said Atti.

“The historical refrigerants that had been used for vapor compression systems, they are both toxic and global warming contributors,” said Atti. While the global warming impact had been reduced, refrigerants still had issues with toxicity and flammability.

Atti said while the bismuth telluride powder itself is toxic, when it is processed into a semiconductor wafer and made into a chip, it is “benign” and can be recycled or disposed as its meets all chip safety and disposal standards.

The cooling chips are manufactured in Phononic’s own factory in Durham and for mass production the company is working with Thailand based Fabrinet. The freezers for vaccines and ice-cream are built in China by contract manufacturers and carry the brands of Phononic’s customers or in some cases are co-branded, he said.

The funding will be used to build out high-volume manufacturing and to expand Phononic’s markets and product line.

Atti declined to share the latest valuation of Phononic but said it was “north of half a billion dollars”. Previous investors include Temasek Holdings and private equity and venture capital firm Oak Investment Partners. 

(Reporting By Jane Lanhee Lee; editing by Richard Pullin)

Image Credit: Reuters

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Source: https://datafloq.com/read/climate-friendly-cooling-tech-firm-gets-50-million-goldman-sachs/16521

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