by Teknita Team | Jan 25, 2023 | Artificial Intelligence - Machine Learning
DALL-E (stylized as DALL·E) and DALL-E 2 are deep learning models developed by OpenAI to generate digital images from natural language descriptions.
Like GPT-3, DALL·E is a transformer language model. It receives both the text and the image as a single stream of data containing up to 1280 tokens, and is trained using maximum likelihood to generate all of the tokens, one after another.This training procedure allows DALL·E to not only generate an image from scratch, but also to regenerate any rectangular region of an existing image that extends to the bottom-right corner, in a way that is consistent with the text prompt.
DALL-E can generate imagery in multiple styles, including photorealistic imagery, paintings, and emoji. It can “manipulate and rearrange” objects in its images, and can correctly place design elements in novel compositions without explicit instruction. DALL·E excels at following natural language descriptions so users can plainly describe what they want to see.
Developers can now integrate DALL·E directly into their apps and products through Open AI API. More than 3 million people are already using DALL·E to extend their creativity and speed up their workflows, generating over 4 million images a day. Developers can start building with this same technology in a matter of minutes.
Microsoft is bringing DALL·E to a new graphic design app called Designer, which helps users create professional quality social media posts, invitations, digital postcards, graphics, and more.
Company is also integrating DALL·E in Bing and Microsoft Edge with Image Creator, allowing users to create images if web results don’t return what they’re looking for.
You can read more about DALL-E here.
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by Teknita Team | Jan 23, 2023 | Uncategorized
Big Query is a advanced and multi-cloud data warehouse designed by Google, created with the aim of business flexibility.
What do you need to know about Big Query?
Big Query is a scalable data warehouse (cloud data warehouse) designed by Google, a global giant known by almost every internet user. What are the areas of application for this solution? It must be admitted that Big Query offers many possibilities.
Big Query allows for handling millions of queries and conducting advanced analysis of significant amounts of data in SQL language. Knowledge of this language is quite important here. At the same time, entities that use this solution do not have to worry about high costs associated with maintaining advanced technological infrastructure or scaling or balancing traffic. Google offers all new customers $300 of free funds that can be spent on Big Query. Additionally, all customers receive completely free 10 GB of storage space and even 1 TB of queries per month.
Data can be quickly uploaded or downloaded from Big Query and then analyzed in detail. We only pay for the data that we analyze, and only after exceeding the aforementioned 1 TB limit. To use Big Query, we do not have to invest in expensive equipment and tools and technologies, while the configuration is exceptionally simple.
What are the main advantages of Big Query data warehouse?
Big Query is one of the most popular data warehouses. This is mainly due to the fact that it offers a wide range of features, which are appreciated by thousands of data processing and analysis entities worldwide.
The most important advantages of the Big Query data warehouse are as follows:
- No need to invest in your own server – all data is stored in cloud technology.
- Data analysis using Big Query is fast and efficient. Big Query data warehouse stands out for its ability to analyze large amounts of data significantly faster than traditional databases. One petabyte is processed in about 3 minutes, and one terabyte in just a few seconds. This fast operation time ensures that, regardless of how much data we have to analyze, we will get results at a rapid pace. Data analysis is performed in real-time, and all changes can be observed in real-time.
- Full control over costs. In Big Query, we only pay when the number of analyzed data exceeds 1 TB per month. This billing model gives us full control over the expenses. If we do not use the tool at all or do not exceed the specified limit, we will not pay a penny.
- BigQuery offers a machine learning feature. Big Query ML feature enables creation and development of machine learning capabilities using classic SQL queries. This tool allows you to check trends, which helps to design a long-term strategy for the company in specific areas.
- The Big Query data warehouse can be invaluable in any industry. The need for fast and efficient information analysis is visible in many industries – finance, industry, marketing, logistics, etc. Therefore, any company that wants to gain significant competitive advantages should consider using it.
Why choose Big Query data warehouse?
Year after year, more and more entities analyzing significant amounts of data are choosing Google Big Query. This is because with this solution, we do not have to invest in modern equipment, manage infrastructure, perform configuration or software updates. Google engineers are responsible for ensuring proper tool operation. We can then focus on proper analysis and data collection.
To be able to use the possibilities offered by Big Query, we do not have to make major changes or rewrite the source code. This is because Big Query supports the ANSI SQL:2011 standard and also offers ODBC and JDBC programming interfaces for free.
In Big Query, we also do not have to worry about creating backups – the program performs backups on its own, which are later stored for 7 days. During this time, we can familiarize ourselves with the entire history of changes and, if necessary, restore one of the previous versions.
Big Query also has a very high level of security – the tool is known for its reliable security, management, and reliability mechanisms. All data stored in the program is encrypted by default. Google states on its website that it guarantees 99.99% uptime.
Limitations of Big Query data warehouse
Big Query data warehouse has certain limitations and limits in terms of information processing. The most important of these are as follows:
- Maximum number of exported bytes per day. The limit is 50 terabytes per day.
- Maximum number of exports per day. The limit is 100,000 exports per day.
- Number of daily queries. There are no limits on the number of bytes that can be processed in queries within a given project.
- Number of daily queries per user. There are no limits on the number of bytes that users can process in queries per day.
- Number of bytes of processed query data per hour. The limit is 1 terabyte per hour.
- Maximum size of a single table. The limit is 10 terabytes.
- Maximum size of a single partition. The limit is 4 terabytes.
- Maximum number of columns in a table. The limit is 10,000 columns.
- Maximum number of rows in a table. The limit is 1 trillion rows.
- Maximum number of partitions in a table. The limit is 10,000 partitions.
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by Teknita Team | Jan 20, 2023 | Uncategorized
The Java Virtual Machine (JVM) is an abstract computing machine that enables a computer to run Java programs. It is a virtual machine that provides a runtime environment for executing Java bytecode, which is a program compiled from Java source code. The JVM acts as a “layer” between the Java code and the underlying hardware and operating system, allowing Java programs to be run on any platform that has a JVM implementation. This makes Java a “platform-independent” programming language.
To use the Java Virtual Machine (JVM), you first need to have the Java Development Kit (JDK) installed on your computer. The JDK includes the JVM, as well as other tools necessary for developing and running Java programs.
Once you have the JDK installed, you can use the JVM by doing the following:
- Write your Java code using a text editor or an Integrated Development Environment (IDE) such as Eclipse or IntelliJ IDEA.
- Compile your Java code using the Java compiler (javac) that comes with the JDK. This will convert your source code into bytecode, which can be executed by the JVM.
- Run your bytecode using the Java interpreter (java) that comes with the JDK. This will start the JVM and execute your bytecode on the machine.
It’s important to note that the JVM is not just for running Java code, it is also used for running other JVM-based languages like Kotlin, Scala, and Groovy.
You should use the Java Virtual Machine (JVM) when you want to run Java or other JVM-based programming languages, such as Kotlin, Scala, or Groovy, on your computer. JVM provides a runtime environment for executing Java bytecode, which is a program compiled from Java source code.
Here are some specific scenarios where you might use the JVM:
- When you want to write cross-platform software that can run on any operating system, such as Windows, macOS, or Linux, that has a JVM implementation.
- When you want to write server-side applications, such as web servers or backend services, that need to handle multiple concurrent connections and perform complex computations.
- When you want to use the vast ecosystem of Java libraries and frameworks, such as Spring, Hibernate, or Apache Tomcat, that are available for various application domains.
- When you want to write code that can leverage the security, performance, and scalability features provided by the JVM, such as automatic memory management, built-in support for multithreading, and JIT compilation.
- When you want to use JVM based languages, such as Kotlin, Scala, or Groovy, that are built on top of JVM but offer features like functional programming, concise syntax, and improved type inference.
In summary, JVM is a powerful and versatile platform that allows you to develop and run a wide variety of software applications, from small scripts to enterprise-grade systems, on any platform that supports the JVM.
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by Teknita Team | Jan 19, 2023 | Project Management
Power BI is a business intelligence and data visualization tool developed by Microsoft. It allows users to connect to various data sources, perform data transformations, and create interactive and visually appealing reports.
Power BI offers a wide range of features for creating interactive and visually appealing reports. Some of the key features of Power BI include:
- Data Connectivity: Power BI allows users to connect to various data sources, including Excel, SQL Server, and cloud-based services such as Azure, Salesforce, and Google Analytics.
- Data Transformation: Power BI allows users to perform data transformations, such as filtering, grouping, and summarizing, to prepare the data for analysis.
- Data Visualization: Power BI offers a wide range of visualization options, including charts, tables, and maps, to help users make sense of the data.
- Natural Language Querying: Power BI allows users to ask questions in natural language and receive instant answers in the form of visualizations.
- Real-time Data Streaming: Power BI allows users to stream real-time data and create visualizations that update in real-time.
- Collaboration and Sharing: Power BI allows users to share and collaborate on reports and dashboards with other users.
- Customizable: Power BI allows users to customize their reports and dashboards with various themes and custom visuals.
- Mobile App: Power BI has a mobile app version for iOS, Android and Windows.
- Power Automate integration: Power BI allows you to connect with power automate for automation of some of the data preparation tasks.
- Power Query and M language: It allows you to access and manipulate data from various sources, including web pages and databases, using Power Query and the M language.
Power BI allows you to connect to various data sources, create and publish interactive reports, and share them with others. The software provides a variety of visualizations, such as charts, tables, and maps, as well as features for data modeling, filtering, and analysis. With Power BI, you can easily create professional-looking reports that provide insights into your data.
DIFFERENCE BETWEEN POWER BI REPORTS AND DASHBOARDS
Power BI Reports and Power BI Dashboards are both components of the Power BI platform, but they serve different purposes.
Power BI Reports are interactive and visually appealing documents that allow users to analyze and explore data. Reports can contain multiple pages, and each page can have a different layout and visualization. Power BI Desktop is primarily used to create Reports.
Power BI Dashboards, on the other hand, are a collection of visualizations, such as charts and tables, that are displayed on a single page. They provide a high-level overview of the key metrics and insights from the data. Dashboards can be created and edited in the Power BI Service and can be shared with other users. The main purpose of Dashboards is to give an overview of important data and insights, so users can quickly understand the state of their business.
In short, Reports are more detail oriented and allows you to dive deep into the data, Dashboards are more high-level and focused on giving you a quick overview of the most important data and insights.
Power BI is considered one of the best report tools – it is easy to use and has a friendly user interface. It is also affordable and has a free version for small business.
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by Teknita Team | Jan 18, 2023 | Process Automation
Automation refers to the use of technology to control and operate equipment, machines, and processes without the need for human intervention. It involves the use of automated systems, such as robots, software, and artificial intelligence, to perform tasks that would otherwise be done manually. Automation can be applied to a wide range of industries, including manufacturing, transportation, healthcare, and finance.
AUTOMATION STARTS WITH ENTERPRISE RESOURCE PLANNING.
Automation can begin with the implementation of an Enterprise Resource Planning (ERP) system. An ERP system is a software solution that integrates and automates various business processes, such as accounting, inventory management, customer relationship management, and human resources. It helps to streamline these processes by centralizing data and automating tasks such as data entry, reporting, and analysis. This can improve the efficiency and accuracy of business operations, as well as provide real-time data and insights to support decision-making. By automating these processes, ERP systems can reduce the need for manual labor and increase productivity. An ERP system can also help businesses to better manage their resources, improve their ability to scale, and increase their competitiveness.
RPA CAN TRANSFORM YOUR BUSINESS
Robotic Process Automation (RPA) is a technology that allows businesses to automate repetitive and rule-based tasks, such as data entry, data processing, and data analysis. It can be used to automate tasks across a wide range of industries and business functions, such as finance, accounting, human resources, customer service, and IT.
RPA can revolutionize business by increasing efficiency, reducing labor costs, and improving accuracy and consistency. By automating repetitive and rule-based tasks, businesses can free up human resources to focus on more complex and value-added tasks. This can help businesses to improve productivity and reduce the risk of human error.
RPA can also help businesses to improve decision-making by providing them with more accurate and up-to-date data. This can help businesses to identify new opportunities and respond more quickly to changes in the market. Additionally, RPA can also help businesses to improve customer service by providing faster and more accurate responses to customer inquiries.
RPA can also be integrated with other technologies such as Artificial Intelligence, Machine Learning and Natural Language Processing, this way it can go beyond simple automation and allow for more sophisticated tasks, such as chatbot interactions, sentiment analysis and natural language generation.
In summary, Robotic Process Automation (RPA) is a technology that allows businesses to automate repetitive and rule-based tasks, such as data entry, data processing, and data analysis, which can revolutionize business by increasing efficiency, reducing labor costs, improving accuracy and consistency, and improving decision-making capabilities, as well as improving customer service, and providing more accurate and up-to-date data.
COMPANIES ARE MOVING TOWARD HYPERAUTOMATION
Hyperautomation is a term used to describe the use of advanced technologies, such as artificial intelligence, machine learning, and robotics, to automate business processes. Many businesses are beginning to adopt hyperautomation to increase efficiency, reduce labor costs, and improve accuracy and consistency.
Hyperautomation can help businesses to automate repetitive and dangerous tasks, which can increase productivity and reduce the risk of workplace accidents. It can also help businesses to optimize their production processes and increase their output. Additionally, Hyperautomation can also help businesses to improve their decision-making by providing them with more accurate and up-to-date data.
In summary, Hyperautomation is a trend that is being adopted by many businesses to increase efficiency, reduce labor costs, and improve accuracy and consistency, but its adoption varies depending on the company’s capability and willingness to invest in the technology.
Automation has the potential to revolutionize business by increasing efficiency, reducing labor costs, improving accuracy and consistency, and increasing output. It can also help businesses improve customer service by providing faster and more accurate responses to customer inquiries. Automation can also help businesses to scale their operations, by allowing them to handle larger volumes of work with the same or fewer resources. Additionally, automation can also help businesses to improve their decision making, by providing them with more accurate and up-to-date data. This can help businesses to identify new opportunities and respond more quickly to changes in the market. Automation is also a key enabler for digital transformation, which allows businesses to optimize their processes, improve collaboration and communication, and increase agility.
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