Melick's Blog

  What is Deepfake Deepfake is a technical way of generating not genuine videos, audio and visual images based on real data inputs. This is commonly archived using deep learning and machine learning technologies. Deep learning technology uses high-power computers to correct their self by its own without any human intervention. There is quite several deepfake software available in the market. Some of them are FaceApp [https://www.faceapp.com/] DeepFace Lab [https://github.com/iperov/DeepFaceLab] below shows some popular deepfake creations that we have seen in the past. The video was first shared by the Dutch deepfake YouTube Channel. How this is been created An ordinary way of archiving this is to use deep learning AI programs to identify patterns and similarities of real video, audio and images and change the reality to map the target outcome. These programs use quite several genuine inputs and manipulate the real data to match the target output. Generative Adversarial Networks (GAN) A

 Front-End technologies and frameworks rapidly come and go from the market. It is very challenging to select the correct front-end technology for a new enterprise application. Many people only consider the technological capabilities of the technology. Though it is important to consider technology aspects, it is also important to consider the sustainability of the enterprise applications. Human talents are a crucial component for the sustainability of the application. This is very important to consider developer adaption and industry trends while you are choosing your front-end technology. Why it is important to consider human talents? Human Talent Availability - Employees move all the time. This technology which we are choosing should be popular or in demand in the market, so this organization can acquire resources easily. Human Talent Cost - When a new technology introduces it will be hard to find talent with the skill. This demand for talent will be high. so the cost is. Community Su

Before jumping to Blockchain word let's have a look at simple enterprise applications and their underline technologies. Voting Solution The above illustrates a real Business use case. Let's see the challenges of the current usual technical architecture and mitigations. User should be able to Vote  - This is not a complex requirement. unless the service is down, service SLA can be improved using proper DR techniques and using correct cloud infrastructure set-up. Votes should not be able to change after the vote  - This can be mitigated using proper crypto graphical controls. However, central control of the solution data is held by one party this can not be avoided. Storage of the votes  - This is quite challenging with the existing technology as storage of the votes data will be owned by one single entity. Regardless of security controls and processes implement in an organization to restrict access to data, there is always a risk of getting expose, manipulated, and availability

It is crucial to understand the project deployment and the landscape of any technical project. This will help to assess the complexity and dependencies to plan across. Information Technology terminology landscape refers to related infrastructure and application components/systems around. Knowing your field helps you to plan for execution and deployment strategies effectively. Greenfield  Deployment Greenfield is an empty landscape where nothing is decided or confirmed. The technical team can decide on the technology and how it can be utilized. There are no dependencies on existing applications and thus can be easily rolled out. A fresh start and nothing exist at the moment Can introduce best practices, new flows Moderate risk presents as there is no proof of a working landscape Adding a new landscape to existing Brownfield Deployment Brownfield can be considered as extending the landscape base on existing technology. this can be thought as upgrading or adding new components based on th