Demystifying SDC: When, How, Why to Use

October 29, 2020

Most companies these days use cloud services (or Smart Dedicated Compute) to improve the performance of their IT services.

After all, cloud servers are used for fast processing, data storage, a relatively high level of performance, data security, privacy, and higher levels of control and efficiency. It is operated on physical hardware but managed and controlled by the cloud service providing company. Further, it saves a lot of cost while reducing the investment done in high-end devices for storage and managing them. The best part of all: it is more user-oriented and focuses on saving a lot of work.

Cloud-based servers are more efficient as they save a lot of capital required for buying physical servers and the cost spent on buying extra space for their installation. Let us look at some of the benefits of cloud-based computing.

How Do Cloud Servers Work?

In total, there are two basic types of cloud servers: the primary one is physical and the secondary one is a virtual cloud server. The virtual cloud server has multiple virtual software options with the likes of Hyper-V, Parallels, Xen, and many more.

The cloud servers consist of special software systems called virtualization software that divides a physical (bare metal) server into multiple virtual servers. Each of this virtual server is then allotted to the customer to store data and power operations through it.

Benefits of Cloud Computing

Cloud computing provides a wide range of advantages to companies. Some of these cloud computing advantages include: -

  • It processes and stores an enormous chunk of information smoothly.
  • It has all the basic features of an on-premise server.
  • It reduces the expenditure on hardware.
  • It offers different interesting services like hosting plans that can be scaled as per the users' needs.
  • It has functions that provide multiple automated services on the users’ demand through an API.
  • It also reduces the extra space needed to keep the hardware for storage.
  • It improves security and speed.
  • It provides automation and high deployment.
  • It offers various security options like antivirus software, firewalls, monitoring, and protection from host intrusion.
  • It fastens execution and makes it more effective.

What is Smart Dedicated Compute (SDC)?

As the competition increases day by day, acquiring customers and their trust is becoming even more difficult. Company services and speed play an important role in building trust and gaining more and more customers. Thus, fast and efficient processing is necessary for market competitiveness. That’s where SDC fits in.

SDC (Smart Dedicated Compute) is an ultimate cloud solution for companies to upgrade for higher speed, reliability, higher flexibility, seamless execution, and maximum optimization to improve their IT services to top-level performance. It is best suited for CPU-intensive workloads. It’s a private dedicated cloud designed for a particular company, and simultaneously provides the flexibility of a public cloud server.

Benefits of Smart Dedicated Compute (SDC)

Smart Dedicated Compute can bring an edge to your company in this cut-throat competitive world. It provides computing of higher standards at very ordinary prices that will help your business in catching the pace and growing better. Smart dedicated Compute will provide you a rich experience and give you many benefits. Some of the benefits of using Smart Dedicated Compute for your company are: -

.

  • It’s highly scalable and upgrades are easily possible.
  • Your data is accessible from all around the world.
  • It offers fast service, higher security, and seamless speed.
  • Predictable and smooth performance is provided to the user with the help of dedicated pinned cores.
  • Superfast deployment time that helps in performing an array of works without any delay.
  • It is best suited for companies and businesses that have Compute Intensive Workloads.
  • It is best for those who want to be in sync with the dynamic trends in the world of technology as it provides very easy upgrades to its users.
  • The server security is of high priority and it comes up with DDOS protection at the network level. There are multiple tools for users to enhance the security of the server like Bitninja.
  • Smart dedicated Compute (SDC) will provide its user with resilience, scalability, self-service, security, and amazing performance.

When, How, and Why to Use SDC

SDC is a modern technology and there are many people wish to learn more about its usage and requirements. Some people are confused about whether they need an SDC or not. These are some factors that require an SDC.

When There is a Need for High Security

Data is precious and is an uncompromisable asset for many companies. Cyber-attacks and phishing attacks are becoming common these days. Those companies that have highly sensitive data and cannot risk losing it must opt for Smart Dedicated Compute (SDC)

Dynamic IT Infrastructure

If IT infrastructure is a priority for your company, then know that building an IT infrastructure that’s dynamic and user-oriented can be a tough job. SDC can help your company in developing and maintaining a high-end dynamic IT infrastructure with its high accessibility, customer-oriented modifications with high security and privacy. SDC, being advanced, keeps your infrastructure dynamic, and provides a user experience like that of a public server.

Time of Deployment

A company that wants quick results and a fast interface can switch to a Smart Dedicated Compute (SDC) for quicker results. Since SDC is a dedicated service and caters to your needs personally, the problem of heavy traffic mishandling fades away, and hence, you deliver quicker services. Most of the SDC has a deployment time under 1 minute specifically about 50 to 55 seconds.

Data Security

If data is a priority for your company, then Smart Dedicated Compute is the ultimate solution for your company. Smart Dedicated Compute comes up with the option of saving machine images. One single click can do wonders by saving the image of your machine and running multiple replicas of the machine. So, SDC is perfect for those companies that are secure about their data.

Features of Smart Dedicated Compute (SDC)

Easily Scalable and Highly Reliable

One of the top features of SDC is that it is very easy to scale up in terms of resources and storage. A user can easily upgrade resources whenever more compute, RAM or diskspace is required.. Dedicated pinned cores make them highly reliable.

API Service

More and more companies are switching towards automation to save a lot of time and reduce the cost spent in hiring human force to conduct different work of management. Automation is the ultimate solution to these problems. Smart Dedicated Compute provides amazing API services for automating launching, managing, and terminating machines on demand for 24*7 hours.

Indian Datacenters

Smart dedicated compute offered by E2E Cloud comes with data centres built in India. India data centres have high technology, come up with Solid Disc Drive (SSD) storage, and are more trustworthy.

Monthly/Hourly Billing

The best thing about Smart Dedicated computing is that it is a temporary service and comes with different periodical subscriptions. There is no load of its long-time usage and maintenance. You can at any time unsubscribe to the services. It comes with hourly and monthly billing that can save you a lot of money by unsubscribing during the times when there is no requirement for the services.

Superfast Deployment

One of the amazing advantages of SDC is that there is no lag in performing different types of work. SDC provides superfast deployment speeds that make the process of execution fast.

Conclusion

In old times, large physical storage devices and CPUs were used that cost a lot and their maintenance was costly. Those devices also take up large space and give slower results. As technology changes with time, cloud computing came into place.

The advent of cloud computing changed the whole scenario of the IT sector over the globe. It came as a more fast, dependent, and secure option. It provides the right amount of facilities, higher task management, and an easy and secure option for data storage. More and more companies started shifting to cloud computing over the years.

SDC is the new age technology in the field of cloud computing and is preferable for those who need personal attention. It is a dedicated computing service that caters to the needs of the user and works according to those needs. It is a safe, reliable, and fast option for anyone concerned with security, high speed, and rich user experience. If those needs sound like your needs, opt for Smart Dedicated Compute (SDC) today!

 For free trial please click here :- http://bit.ly/3hhaiJm

Latest Blogs
This is a decorative image for: A Complete Guide To Customer Acquisition For Startups
October 18, 2022

A Complete Guide To Customer Acquisition For Startups

Any business is enlivened by its customers. Therefore, a strategy to constantly bring in new clients is an ongoing requirement. In this regard, having a proper customer acquisition strategy can be of great importance.

So, if you are just starting your business, or planning to expand it, read on to learn more about this concept.

The problem with customer acquisition

As an organization, when working in a diverse and competitive market like India, you need to have a well-defined customer acquisition strategy to attain success. However, this is where most startups struggle. Now, you may have a great product or service, but if you are not in the right place targeting the right demographic, you are not likely to get the results you want.

To resolve this, typically, companies invest, but if that is not channelized properly, it will be futile.

So, the best way out of this dilemma is to have a clear customer acquisition strategy in place.

How can you create the ideal customer acquisition strategy for your business?

  • Define what your goals are

You need to define your goals so that you can meet the revenue expectations you have for the current fiscal year. You need to find a value for the metrics –

  • MRR – Monthly recurring revenue, which tells you all the income that can be generated from all your income channels.
  • CLV – Customer lifetime value tells you how much a customer is willing to spend on your business during your mutual relationship duration.  
  • CAC – Customer acquisition costs, which tells how much your organization needs to spend to acquire customers constantly.
  • Churn rate – It tells you the rate at which customers stop doing business.

All these metrics tell you how well you will be able to grow your business and revenue.

  • Identify your ideal customers

You need to understand who your current customers are and who your target customers are. Once you are aware of your customer base, you can focus your energies in that direction and get the maximum sale of your products or services. You can also understand what your customers require through various analytics and markers and address them to leverage your products/services towards them.

  • Choose your channels for customer acquisition

How will you acquire customers who will eventually tell at what scale and at what rate you need to expand your business? You could market and sell your products on social media channels like Instagram, Facebook and YouTube, or invest in paid marketing like Google Ads. You need to develop a unique strategy for each of these channels. 

  • Communicate with your customers

If you know exactly what your customers have in mind, then you will be able to develop your customer strategy with a clear perspective in mind. You can do it through surveys or customer opinion forms, email contact forms, blog posts and social media posts. After that, you just need to measure the analytics, clearly understand the insights, and improve your strategy accordingly.

Combining these strategies with your long-term business plan will bring results. However, there will be challenges on the way, where you need to adapt as per the requirements to make the most of it. At the same time, introducing new technologies like AI and ML can also solve such issues easily. To learn more about the use of AI and ML and how they are transforming businesses, keep referring to the blog section of E2E Networks.

Reference Links

https://www.helpscout.com/customer-acquisition/

https://www.cloudways.com/blog/customer-acquisition-strategy-for-startups/

https://blog.hubspot.com/service/customer-acquisition

This is a decorative image for: Constructing 3D objects through Deep Learning
October 18, 2022

Image-based 3D Object Reconstruction State-of-the-Art and trends in the Deep Learning Era

3D reconstruction is one of the most complex issues of deep learning systems. There have been multiple types of research in this field, and almost everything has been tried on it — computer vision, computer graphics and machine learning, but to no avail. However, that has resulted in CNN or convolutional neural networks foraying into this field, which has yielded some success.

The Main Objective of the 3D Object Reconstruction

Developing this deep learning technology aims to infer the shape of 3D objects from 2D images. So, to conduct the experiment, you need the following:

  • Highly calibrated cameras that take a photograph of the image from various angles.
  • Large training datasets can predict the geometry of the object whose 3D image reconstruction needs to be done. These datasets can be collected from a database of images, or they can be collected and sampled from a video.

By using the apparatus and datasets, you will be able to proceed with the 3D reconstruction from 2D datasets.

State-of-the-art Technology Used by the Datasets for the Reconstruction of 3D Objects

The technology used for this purpose needs to stick to the following parameters:

  • Input

Training with the help of one or multiple RGB images, where the segmentation of the 3D ground truth needs to be done. It could be one image, multiple images or even a video stream.

The testing will also be done on the same parameters, which will also help to create a uniform, cluttered background, or both.

  • Output

The volumetric output will be done in both high and low resolution, and the surface output will be generated through parameterisation, template deformation and point cloud. Moreover, the direct and intermediate outputs will be calculated this way.

  • Network architecture used

The architecture used in training is 3D-VAE-GAN, which has an encoder and a decoder, with TL-Net and conditional GAN. At the same time, the testing architecture is 3D-VAE, which has an encoder and a decoder.

  • Training used

The degree of supervision used in 2D vs 3D supervision, weak supervision along with loss functions have to be included in this system. The training procedure is adversarial training with joint 2D and 3D embeddings. Also, the network architecture is extremely important for the speed and processing quality of the output images.

  • Practical applications and use cases

Volumetric representations and surface representations can do the reconstruction. Powerful computer systems need to be used for reconstruction.

Given below are some of the places where 3D Object Reconstruction Deep Learning Systems are used:

  • 3D reconstruction technology can be used in the Police Department for drawing the faces of criminals whose images have been procured from a crime site where their faces are not completely revealed.
  • It can be used for re-modelling ruins at ancient architectural sites. The rubble or the debris stubs of structures can be used to recreate the entire building structure and get an idea of how it looked in the past.
  • They can be used in plastic surgery where the organs, face, limbs or any other portion of the body has been damaged and needs to be rebuilt.
  • It can be used in airport security, where concealed shapes can be used for guessing whether a person is armed or is carrying explosives or not.
  • It can also help in completing DNA sequences.

So, if you are planning to implement this technology, then you can rent the required infrastructure from E2E Networks and avoid investing in it. And if you plan to learn more about such topics, then keep a tab on the blog section of the website

Reference Links

https://tongtianta.site/paper/68922

https://github.com/natowi/3D-Reconstruction-with-Deep-Learning-Methods

This is a decorative image for: Comprehensive Guide to Deep Q-Learning for Data Science Enthusiasts
October 18, 2022

A Comprehensive Guide To Deep Q-Learning For Data Science Enthusiasts

For all data science enthusiasts who would love to dig deep, we have composed a write-up about Q-Learning specifically for you all. Deep Q-Learning and Reinforcement learning (RL) are extremely popular these days. These two data science methodologies use Python libraries like TensorFlow 2 and openAI’s Gym environment.

So, read on to know more.

What is Deep Q-Learning?

Deep Q-Learning utilizes the principles of Q-learning, but instead of using the Q-table, it uses the neural network. The algorithm of deep Q-Learning uses the states as input and the optimal Q-value of every action possible as the output. The agent gathers and stores all the previous experiences in the memory of the trained tuple in the following order:

State> Next state> Action> Reward

The neural network training stability increases using a random batch of previous data by using the experience replay. Experience replay also means the previous experiences stocking, and the target network uses it for training and calculation of the Q-network and the predicted Q-Value. This neural network uses openAI Gym, which is provided by taxi-v3 environments.

Now, any understanding of Deep Q-Learning   is incomplete without talking about Reinforcement Learning.

What is Reinforcement Learning?

Reinforcement is a subsection of ML. This part of ML is related to the action in which an environmental agent participates in a reward-based system and uses Reinforcement Learning to maximize the rewards. Reinforcement Learning is a different technique from unsupervised learning or supervised learning because it does not require a supervised input/output pair. The number of corrections is also less, so it is a highly efficient technique.

Now, the understanding of reinforcement learning is incomplete without knowing about Markov Decision Process (MDP). MDP is involved with each state that has been presented in the results of the environment, derived from the state previously there. The information which composes both states is gathered and transferred to the decision process. The task of the chosen agent is to maximize the awards. The MDP optimizes the actions and helps construct the optimal policy.

For developing the MDP, you need to follow the Q-Learning Algorithm, which is an extremely important part of data science and machine learning.

What is Q-Learning Algorithm?

The process of Q-Learning is important for understanding the data from scratch. It involves defining the parameters, choosing the actions from the current state and also choosing the actions from the previous state and then developing a Q-table for maximizing the results or output rewards.

The 4 steps that are involved in Q-Learning:

  1. Initializing parameters – The RL (reinforcement learning) model learns the set of actions that the agent requires in the state, environment and time.
  2. Identifying current state – The model stores the prior records for optimal action definition for maximizing the results. For acting in the present state, the state needs to be identified and perform an action combination for it.
  3. Choosing the optimal action set and gaining the relevant experience – A Q-table is generated from the data with a set of specific states and actions, and the weight of this data is calculated for updating the Q-Table to the following step.
  4. Updating Q-table rewards and next state determination – After the relevant experience is gained and agents start getting environmental records. The reward amplitude helps to present the subsequent step.  

In case the Q-table size is huge, then the generation of the model is a time-consuming process. This situation requires Deep Q-learning.

Hopefully, this write-up has provided an outline of Deep Q-Learning and its related concepts. If you wish to learn more about such topics, then keep a tab on the blog section of the E2E Networks website.

Reference Links

https://analyticsindiamag.com/comprehensive-guide-to-deep-q-learning-for-data-science-enthusiasts/

https://medium.com/@jereminuerofficial/a-comprehensive-guide-to-deep-q-learning-8aeed632f52f

This is a decorative image for: GAUDI: A Neural Architect for Immersive 3D Scene Generation
October 13, 2022

GAUDI: A Neural Architect for Immersive 3D Scene Generation

The evolution of artificial intelligence in the past decade has been staggering, and now the focus is shifting towards AI and ML systems to understand and generate 3D spaces. As a result, there has been extensive research on manipulating 3D generative models. In this regard, Apple’s AI and ML scientists have developed GAUDI, a method specifically for this job.

An introduction to GAUDI

The GAUDI 3D immersive technique founders named it after the famous architect Antoni Gaudi. This AI model takes the help of a camera pose decoder, which enables it to guess the possible camera angles of a scene. Hence, the decoder then makes it possible to predict the 3D canvas from almost every angle.

What does GAUDI do?

GAUDI can perform multiple functions –

  • The extensions of these generative models have a tremendous effect on ML and computer vision. Pragmatically, such models are highly useful. They are applied in model-based reinforcement learning and planning world models, SLAM is s, or 3D content creation.
  • Generative modelling for 3D objects has been used for generating scenes using graf, pigan, and gsn, which incorporate a GAN (Generative Adversarial Network). The generator codes radiance fields exclusively. Using the 3D space in the scene along with the camera pose generates the 3D image from that point. This point has a density scalar and RGB value for that specific point in 3D space. This can be done from a 2D camera view. It does this by imposing 3D datasets on those 2D shots. It isolates various objects and scenes and combines them to render a new scene altogether.
  • GAUDI also removes GANs pathologies like mode collapse and improved GAN.
  • GAUDI also uses this to train data on a canonical coordinate system. You can compare it by looking at the trajectory of the scenes.

How is GAUDI applied to the content?

The steps of application for GAUDI have been given below:

  • Each trajectory is created, which consists of a sequence of posed images (These images are from a 3D scene) encoded into a latent representation. This representation which has a radiance field or what we refer to as the 3D scene and the camera path is created in a disentangled way. The results are interpreted as free parameters. The problem is optimized by and formulation of a reconstruction objective.
  • This simple training process is then scaled to trajectories, thousands of them creating a large number of views. The model samples the radiance fields totally from the previous distribution that the model has learned.
  • The scenes are thus synthesized by interpolation within the hidden space.
  • The scaling of 3D scenes generates many scenes that contain thousands of images. During training, there is no issue related to canonical orientation or mode collapse.
  • A novel de-noising optimization technique is used to find hidden representations that collaborate in modelling the camera poses and the radiance field to create multiple datasets with state-of-the-art performance in generating 3D scenes by building a setup that uses images and text.

To conclude, GAUDI has more capabilities and can also be used for sampling various images and video datasets. Furthermore, this will make a foray into AR (augmented reality) and VR (virtual reality). With GAUDI in hand, the sky is only the limit in the field of media creation. So, if you enjoy reading about the latest development in the field of AI and ML, then keep a tab on the blog section of the E2E Networks website.

Reference Links

https://www.researchgate.net/publication/362323995_GAUDI_A_Neural_Architect_for_Immersive_3D_Scene_Generation

https://www.technology.org/2022/07/31/gaudi-a-neural-architect-for-immersive-3d-scene-generation/ 

https://www.patentlyapple.com/2022/08/apple-has-unveiled-gaudi-a-neural-architect-for-immersive-3d-scene-generation.html

Build on the most powerful infrastructure cloud

A vector illustration of a tech city using latest cloud technologies & infrastructure