Deep Learning Approaches for Video Compression

September 14, 2022

Typical video compression focuses on interframe or intraframe compression using pairs of electrical circuits such as quantizers-dequantizers, transforms-reverse transformers, and so on However, It has recently been discovered that the contribution of video data created in big data has risen. extensively. Interdisciplinary techniques are assisting in the exploration of numerous possibilities of compression of video Deep learning-based techniques have recently gained popularity.

In this blog, we will describe what video compression is, why it is necessary, the typical way to compress videos and the deep learning approach. 

What is Video Compression

Video compression is the technique of compressing a video clip such that it takes up less space than the original file and is easier to send across a network like the Internet. It is a video compression technique that shrinks video file formats by removing unnecessary and non-functional material from the original video file.

Why compress the Videos

The biggest issue of anyone reducing video footage is generally file size because huge files slow down easy uploads, file transfers, flawless internet streaming, and so on. This is because they require more storage space and bandwidth, which might be expensive or limited on a video hosting site. 

A basic 1080 HD video clip, for example, can take up around 11 GB of space for each minute of video. This fluctuates significantly depending on the frame, but it's more space than most people can afford for a one-minute film. Because of this, video compression is essential. Video compression reduces storage capacity requirements while increasing file transfer and transmission speeds. This makes video uploading and sharing easier, allowing viewers to enjoy a more smooth streaming experience.

How Video Compression is Achieved

Video compression is often accomplished by deleting repeating images, sounds, and/or sequences from a video. For example, a video may repeat the same backdrop, picture, or sound, or the data displayed/attached to the video clip may be insignificant. To lower the size of the video file, video compression will eliminate all such material. When a video is compressed, its original format is converted to a new one (depending on the codec used). To play the video file, the video player must support that video format or be integrated with the compression codec.

Figure: Video compression Approaches

Deep Learning Approach for Video Compression

For video compression, there are numerous deep learning-based approaches. DNN techniques are more effective because they have numerous epochs that update (depending on the quantity and complexity of data) hyperparameters that aid in model training. It will be prepared to retrieve real-world data. 

We have observed various successful DNN-based picture compression algorithms that leverage highly nonlinear transformations and an end-to-end training strategy. Image compression methods have shown to be quite effective. The nice thing about the deep learning-based solution is that it uses classical compression architecture and a neural network with non-linear representation.

The following are ways to video compression based on DNN. 

  1. The first technique is to create an efficient video codec by modifying the evolutionary algorithm to create an appropriate codebook for adaptive vector quantization. This will be used as an example. a neural network activation function To do this, a background subtraction method is employed. remove motion items from the frame It aids in the creation of a first context-based codebook. 

For lossless compression, Differential Pulse Code Modulation (DPCM) is used. wavelet coefficients that are significant Neural networks that use Learning Vector Quantization (LVQ) Lossy compression with low energy coefficients are utilized. Run Length is the final phase. RLE encoding is used to attain a greater compression ratio.

  1. The second approach is a self-learning system for removing geometry artifacts in video-based point cloud compression to increase compression efficiency (V-PCC). This is the initial method for carrying out this procedure. It yields encouraging results when it comes to removing geometric artifacts and reconstructing 3D films. Later on, CNN can be used to increase the accuracy of video occupancy maps.
  1. The third approach is based on ConvGRU, a convolutional recurrent neural network that combines the benefits of both CNN and RNN. The system's randomized emission phase ConvGRU-based design improves performance and can aid in additional optimization upgrades.
  1. DeepPVC, an end-to-end deep predictive model, is used in the fourth approach for video compression. It decodes video data in parallel and outperforms AVC and HEVC. 

Advantages of Video Compression

It's usually preferable to keep file sizes as small as possible, but there's more to video compression than that. 

Here are the three primary advantages of video compression. 

  1. Requires less storage space: Video files that have been compressed are smaller and lighter in size. Video codecs such as H.264/AVC and H.265/HEVC, for example, can decrease original raw video data by up to 1,000 times. This means that raw video material of terabytes or gigabytes can be reduced into megabytes.
  1. Faster reading/writing of files: Because the movies are smaller in size and demand less bandwidth, video hosting services can process them quickly and simply (i.e., convenient uploads plus faster and smoother transmissions). This keeps the video from taking forever to load or crashing while playing. As a result, even consumers with slow internet connections may enjoy trouble-free video quality.
  1. Increased file transmission speed: The faster the transfer, the smaller the file size. Assume your device's file transmission speed is consistent at 100 Mbps. Keeping this in mind, moving 500 GB of raw video footage from one hard disc to another would take around an hour and a half. Assume the compression codecs employed reduced the data to 5 times their original size, or 100 GB. This means that the transfer will now take 18 minutes rather than 90 minutes.

Conclusion

According to the findings, CNN is a commonly utilized image or video compression technology. And apart from CNN, Recurrent Neural Networks (RNN) and Generative Adversarial Networks (GAN) both can be utilized for this purpose. Autoencoders (AE) are also recommended for compression.

With all of the advantages that Deep Learning has to offer, namely in the video compression process. There are also various obstacles, such as the encoder search problem, reduced resolution, compression efficiency, support for new formats, more sophisticated compression, and time efficiency. However, with time and additional study, these issues may be rectified, and we may be able to accomplish much more in the field of video compression.

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Comparison between Cloud-Based and On Premises GPUs

Cloud GPUs vs On Premises GPUs

Cloud GPUs are typically more powerful than on-premises GPU instances. The cost of renting a cloud GPU is generally lower than the cost of purchasing an on-premise GPU. 

Cloud platforms offer fast access to high performance compute and deep learning algorithms, which makes it simpler to start using machine learning models and get early insights into your data. 

Cloud GPUs are better for machine learning because they have lower latency, which is important because the time it takes a neural network to learn from data affects its accuracy. Furthermore, cloud GPUs allow users to take advantage of large-scale training datasets without having to build and maintain their own infrastructure.

On Premises GPUs are better for machine learning if you need high performance or require access to cutting-edge technologies not available in the public cloud. For example, on-premises hardware can be used for deep learning applications that require high memory bandwidth and low latency.

Cloud GPUs: Cloud GPUs are remote data centers where you can rent unused GPU resources. This allows you to run your models on a massive scale, without having to install and manage a local machine learning cluster.

Lower TCO: Cloud GPUs require no upfront investment, making them ideal for companies that are looking to reduce their overall capital expenses. Furthermore, the cost of maintenance and upgrades is also low since it takes place in the cloud rather than on-premises.

Scalability & Flexibility: With cloud-based GPU resources, businesses can scale up or down as needed without any penalty. This ensures that they have the resources they need when demand spikes but also saves them money when there is little or no demand for those resources at all times.

Enhanced Capacity Planning Capabilities: Cloud GPU platforms allow businesses to better plan for future demands by providing estimates of how much processing power will be required in the next 12 months and beyond based on past data points such as workloads run and successes achieved with similar models/algorithms etc... 

Security & Compliance : Since cloud GPUs reside in a remote datacenter separate from your business' core systems, you are ensured peace of mind when it comes to security and compliance matters (eigenvector scanning / firewalls / SELinux etc...) 

Reduced Total Cost Of Ownership (TCO) over time due to pay-as-you-go pricing model which allows you only spend what you actually use vs traditional software licensing models where significant upfront investments are made.

Cloud GPUs: Cloud GPUs offer significant performance benefits over on-premises GPUs. They are accessible from anywhere, and you don't need to own or manage the hardware. This makes them a great choice for data scientists who work with multiple data sets across different platforms.

Numerous Platforms Available for Use: The wide variety of available platforms (Windows, Linux) means that you can run your models using the most popular machine learning libraries and frameworks across different platforms without having to worry about compatibility issues between them.

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October 4, 2022

Impact of the Strong Dollar: Cloud Costs Increasing, Be Indian Buy Indian

Indian SMEs and startups are feeling the effects of the high dollar. These businesses use hyperscalers(MNC Cloud) who cannot modify their rates to account for the changing exchange rate. For certain companies, even a little shift in the currency rate may have a significant effect on their bottom line. Did you know, when the INR-USD exchange rate moved from 60 to 70 in December 2015, it had an impact of around 20% on Digital Innovation?

As the rupee is inching closer to 82 per dollar, the strong dollar has directly impacted the costs of cloud services for Indian businesses. The high cost of storage and computing power, along with bandwidth charges from overseas vendors, has led to a huge increase in the effective rate of these services. This is especially true for startups and SMEs that rely on cloud computing to store and process user data. With the strong dollar continuing to impact the cost of cloud services, it is essential for Indian companies to evaluate their options and adopt local alternatives wherever possible. This blog post will discuss how the strong dollar impacts cloud costs, as well as potential Indian alternatives you can explore in response to this global economic trend. 

What is a Strong Dollar?

A strong US dollar($) is a term used to describe a situation where a US’s currency has appreciated in value compared to other major currencies. This can be due to a variety of factors, including interest rate changes, a country’s current account deficit, and investor sentiment. When a currency appreciates, it means that it is worth more. A strong dollar makes imports more expensive, while making exports cheaper. Strong dollars have been a growing trend in the past couple of years. As the US Federal Reserve continues to hike interest rates, the dollar strengthens further. The rising value of the dollar means that the cost of cloud services, especially from hyperscalers based in the US, will rise as well. 

Increase in Cloud Costs Due to Strong Dollar

Cloud services are essential for modern businesses, as they provide easy access to software, storage, and computing resources. Cloud services are delivered over the internet and are typically charged on a per-use basis. This makes them incredibly convenient for businesses, as they can pay for only the resources they actually use. Cloud computing allows businesses to scale their resources up or down, depending on their current business needs. This makes it suitable for startups, where demand is uncertain, or large enterprises with global operations. Cloud computing is also inherently scalable and allows businesses to quickly react to changing business needs. Cloud computing is a very competitive industry and providers offer attractive prices to attract customers. However, these prices have been impacted by the strong dollar. The dollar has strengthened by 15-20% against the Indian rupee in the last few years. As a result, the costs of services such as storage and bandwidth have increased for Indian companies. Vendors charge their Indian customers in Indian rupees, taking into account the exchange rate. This has resulted in a significant rise in the costs of these services for Indian companies.

Why are Cloud Services Becoming More Expensive?

Cloud services are priced in US dollars. When the dollar is strong, the effective price of services will be higher in Indian rupees, as the cost is not re-adjusted. There are a couple of reasons for this price discrepancy. First, Indian customers will have to pay the same prices as American customers, despite a weaker Indian rupee. Second, vendors have to ensure that they make a profit.

Possible Indian Alternatives to Cloud Services

If you're looking for a cost-effective substitute for services provided by the U.S.-based suppliers, consider E2E Cloud, an Indian cloud service provider. When it comes to cloud services, E2E Cloud provides everything that startups and SMEs could possibly need.

The table below lists some of these services and compares their cost against their US equivalents. 

According to the data in the table above, Indian E2E Cloud Services are much cheaper than their American equivalents. The difference in price between some of these options is substantial. When compared to the prices charged by suppliers in the United States, E2E Cloud's bandwidth costs are surprisingly low. Although not all E2E Cloud services will be noticeably less expensive. Using Indian services, however, has an additional, crucial perk: data sovereignty.

Conclusion

The price of cloud services will rise as the US Dollar appreciates. Indian businesses will need to find ways to counteract the strong dollar's impact on their bottom lines. To do this, one must use E2E Cloud. The availability of E2E Cloud services in INR currency is a bonus on top of the already substantial cost savings. An effective protection against the negative effects of a strong dollar.

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September 28, 2022

Actions CEOs can take to get the value in Cloud Computing

It is not a new thing to say that a major transition is on the way. The transition in which businesses will rely heavily on cloud infrastructure rather than having their own physical IT structure. All of this is due to the cost savings and increased productivity that cloud technology brings to these businesses. Each technological advancement comes with a certain level of risk. Which must be handled carefully in order to ensure the long-term viability of the technology and the benefits it provides.

And CEOs are the primary motivators and decision-makers in any major shift or technological migration in the organization. In the twenty-first century, which is a data-driven century, it is up to the company's leader to decide what and how his/her organization will perform, overcome the risk and succeed in the coming days.

In this blog, we are going to address a few of the actions that CEOs can take to get value in cloud Computing.

  1. A Coordinated Effort

As the saying goes, the more you avoid the risk, the closer it gets. So, if CEOs and their management teams have yet to take an active part or give the necessary attention that their migration journey to the cloud requires, now is the best time to start top-team support for the cloud enablement required to expedite digital strategy, digitalization of the organization, 

The CEO's position is critical because no one else can mediate between the many stakeholders involved, including the CIO, CTO, CFO, chief human-resources officer (CHRO), chief information security officer (CISO), and business-unit leaders.

The move to cloud computing is a collective-action challenge, requiring a coordinated effort throughout an organization's leadership staff. In other words, it's a question of orchestration, and only CEOs can wield the baton. To accelerate the transition to the cloud, CEOs should ask their CIO and CTO what assistance they require to guide the business on the path.

     2. Enhancing business interactions 

To achieve the speed and agility that cloud platforms offer, regular engagement is required between IT managers and their counterparts in business units and functions, particularly those who control products and competence areas. CEOs must encourage company executives to choose qualified decision-makers to serve as product owners for each business capability.

  1. Be Agile

If your organization wants to benefit from the cloud, your IT department, if it isn't already, must become more agile. This entails more than simply transitioning development teams to agile product models. Agile IT also entails bringing agility to your IT infrastructure and operations by transitioning infrastructure and security teams from reactive, "ticket-driven" operations to proactive models in which scrum teams create application programme interfaces (APIs) that service businesses and developers can consume.

  1. Recruiting new employees 

CIOs and CTOs are currently in the lead due to their outstanding efforts in the aftermath of the epidemic. The CEOs must ensure that these executives maintain their momentum while they conduct the cloud transformation. 

Also, Cloud technology necessitates the hire of a highly skilled team of engineers, who are few in number but extremely expensive. As a result, it is envisaged that the CHRO's normal hiring procedures will need to be adjusted in order to attract the proper expertise. Company CEOs may facilitate this by appropriate involvement since this will be critical in deciding the success of the cloud transition.

  1. Model of Business Sustainability 

Funding is a critical component of shifting to the cloud. You will be creating various changes in your sector, from changing the way you now do business to utilizing new infrastructure. As a result, you'll have to spend on infrastructure, tools, and technologies. As CEO, you must develop a business strategy that ensures that every investment provides a satisfactory return on investment for your company. Then, evaluate your investments in order to optimise business development and value.

  1. Taking risks into consideration 

Risk is inherent in all aspects of corporate technology. Companies must be aware of the risks associated with cloud adoption in order to reduce security, resilience, and compliance problems. This includes, among other things, engaging in comprehensive talks about the appropriate procedures for matching risk appetite with technological environment decisions. Getting the business to take the correct risk tone will necessitate special attention from the CEO.

It's easy to allow concerns about security, resilience, and compliance to stall a cloud operation. Instead of allowing risks to derail progress, CEOs should insist on a realistic risk appetite that represents the company plan, while situating cloud computing risks within the context of current on-premises computing risks and demanding choices for risk mitigation in the cloud.

Conclusion

In conclusion, the benefits of cloud computing may be obtained through a high-level approach. A smooth collaboration between the CEO, CIO, and CTO may transform a digital transformation journey into a profitable avenue for the company.

CEOs must consider long-term cloud computing strategy and ensure that the organization is provided with the funding and resources for cloud adoption. The right communication is critical in cloud migration: employees should get these communications from C-suite executives in order to build confidence and guarantee adherence to governance requirements. Simply installing the cloud will not provide value for a company. Higher-level executives (particularly the CEO) must take the lead in the digital transformation path.

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