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Catching signals from others is how we started communicating as human beings. It all started, of course, with our vocal cords. Then we moved to smoke signals for long-distance communication. At some point, we discovered radio waves and are still using them for contact. This article will describe how you can tune in using and an SDR dongle. Fedora Linux My journey I got interested in radio communication as a hobby when I was a kid, while my local club, LZ2KRS, was still a thing. I was so excited to be able to listen and communicate with people worldwide. It opened a whole new world for me. I was living in a communist country back then and this was a way to escape just for a bit. It also taught me about ethics and technology. Year after year my hobby grew and now, in the Internet era with all the cool devices you can use, it’s getting even more exciting. So I want to show you how to do it with Fedora Linux and a hardware dongle. What is Ham Radio Amateur Radio (ham radio) is a popular hobby and service that brings people, electronics, and communication together. People use ham radio to talk across town, worldwide, or even into space, without the Internet or cell phones. What’s SWLing? To broadcast with your ham radio or SDR system, you need to obtain a license from a governmental body. But to intercept signals and listen to the open communication between two amateur radio stations, you don’t need one. The term SWLing comes from the abbreviation of Short Wave Listener, where you listen to stations communicating in the shortwave bands between 3 and 30 MHz. This can be used for long-distance communication using the , a layer of the Earth’s atmosphere. ionosphere To get started, you don’t need a license. Still, I recommend getting yourself an SWL sign to identify yourself in a listening contest. These are competitions for categories like who will discover the most connections in a month or who can listen to contacts from each country in the world. How to get an SWL Sign? There are two options: Contact your national radio club and ask them to issue one for you. I got my Czech one, OK1-36568, after a few weeks. Join the community and request a sign there. Short Wave Amateur Radio Listening You will get more information and help from either of these locations if you get stuck in some fashion! QSL Cards You can also use your sign to send QSL cards via post or electronically. This is a great way to communicate with people worldwide and make friends. Per Wikipedia, A QSL card is a written confirmation of either a two-way radio communication between two amateur radio or citizens band stations; a one-way reception of a signal from an AM radio, FM radio, television, or shortwave broadcasting station; or the reception of a two-way radio communication by a third party listener (in our case). A typical QSL card is the same size and made from the same material as a regular postcard; most are sent through snail mail. Replace the radio receiver with your Fedora Linux The focal point of the ham radio hobby is the radio transmitter/receiver. Most of the time, enthusiasts build their radio from scratch, but this differs from what I will write about here. SDR A software-defined radio (SDR) system is a radio communication system that uses software for the modulation and demodulation of radio signals. In other words, a piece of hardware and software replaces a radio transmitter/receiver. This helps you discover more in a way you are familiar with – a User Interface with built-in functions instead of the limited interface of a radio receiver. My explanation oversimplifies things, so if you want to go deep and read more about SDR, here is an excellent start. SDR Set Up under Fedora Linux Choosing the proper hardware If you search the Internet for an SDR dongle, you’ll find many ideas depending on your budget. In this tutorial, I’ll work with the one I have, which works well under Fedora 37. A note: The dongle covers frequencies from 25MHz to 1750MHz, which doesn’t cover the Short Wave bands. You would need an additional device to listen to them. This is included in the package I linked above. Some other hardware providers offer all-in-one products. Check if the dongle is visible Before installing anything, detect whether Fedora Linux recognizes your USB dongle. I hope you didn’t buy a fake one :-). Use the following command to list the USB devices on your system. lsusb One of the output lines (in the case of Nooelec) should be Realtek Semiconductor Corp. RTL2838 DVB-T Now proceed by installing the software you need Fedora offers a set of tools and drivers packaged as a group. Even though you would not use all the components in this package from the beginning, I recommend installing it. You’ll have more software to play with. sudo dnf group install 'Electronic Lab' I advise you to explore what’s in the group by running this command: sudo dnf group info 'Electronic Lab' Now check if you have everything set up correctly by running: rtl_test You should see something like this: Do not forget to kill this process because the device will be busy and cannot be used in the next step. A simple Ctrl + c works. Gqrx You have the dongle already in your device’s USB port and all the software you need to get started. Now it’s time to intercept your first signal. Start the program called . Don’t be alarmed by the strange interface. You’ll get used to it. Gqrx Configure the I/O Device Screen From the “Device” Dropdown, select the ‘ .’ RealtekRTL2838.. Leave the rest untouched for the moment. If you don’t see your device there, click the “ ” button at the bottom of the screen. Device Scan When your device is selected, click “OK,” and the dialogue will close. Configure the frequency screen Before you start intercepting signals, ensure there is something out there that proves everything works correctly. Since the dongle covers the FM radio band as well, do this: Locate your favorite radio station’s frequency. Mine is 105MHZ Set it in the Frequency field Select WFM (stereo) in the “Mode” dropdown. If you don’t do this, you will hear a sound. not Play And now, you need to start the reception by clicking the “play button” in your main menu. You will see the frequency visualized like this: If you hear a sound, everything will move to the next step. Check if everything is set up correctly if you don't hear anything. You may ask a question in the comments for this article; I can direct you to the proper forum to solve this. Feel free to play with some more FM broadcasts. You have the antenna for it in your pack. Let’s go Short Wave In the case of the Nooelec, you need to add one more device to the USB dongle and turn it on. Instructions on how to do that are included in the package you receive. In short, you plug the “Up Converter” into your USB dongle and make sure the switch is in the “convert” position. Some videos are available on how to do it if you get stuck. You will need an antenna and a good location Now things get trickier. If you live in an area where you don’t see an open space out your window or other buildings surrounding your building, you might have trouble catching a Short Wave radio amateur signal. Let’s try this to see if it works Try to be in the open. I usually listen from my terrace, which could be better but works under particular conditions. You would need a long wire to act as your antenna apart from the hardware. Try the antenna with the hardware initially – the telescoping one from , but it will catch only powerful signals. Nooelec Let’s go back to Gqrx Now with the converter, you need to make some changes to your device screen: Please note the – for the . This is required for the Up Converter to work. 125Mhz LNB LO field Tune your frequency to 14.100 Mhz and make sure your Mode is (standing for ) because this is this band’s main demodulation option. USB Upper sideband Then go to your screen, use the zoom slider, and set it to see about . In our case, you should have between 14.05 to 14.15 Mhz on your screen. FFT Settings 100 kHz Also, click the “ ” to see the information about the SW bands you are exploring. Enable Band Plan Then hit the play button and explore the space between 14.0 and 14.3 Mhz to get any amateur radio transmission. When intercepting a transmission, adjust your settings to improve your listening experience. It’s a journey that you have already started. Most probably, you will hear something like this: “CQ CQ CQ this is ..(followed by the radio license number spelled with the ). ham radio phonetic alphabet Listen very carefully, and by the call sign, you can determine the location of the radio amateurs’ country. You can visit the to learn more about them and even send them a QSL card confirming their connection. QRZCQ website . Keep the momentum going Now you have some tools and ideas for starting Short Wave Listening. This is the first step of an incredible and exciting journey you can have together with your Fedora Linux OS. You will discover the pleasure of , reading more about , how to be a part of a listening competition, and what mean. building your antenna for the specific band how the ionosphere helps those Q-codes This article was initially published in Fedora Magazine

Mastering Shortwave Listening (SWL) with Fedora Linux and Software Defined Radio

In this article, we will look at how to schedule tasks using the . Quartz is the de facto standard of scheduling libraries for Java applications. Quartz supports running jobs at a particular time, repeating job executions, storing jobs in a database, and Spring integration. Quartz framework Spring-annotations for scheduling The easiest way to use Quartz in Spring applications is to use the annotation. Next, we will consider an example of a Spring Boot application. Let's add the necessary dependency in @Scheduled build.gradle implementation 'org.springframework.boot:spring-boot-starter-quartz' and consider an example package quartzdemo.tasks;

import org.springframework.scheduling.annotation.Scheduled;
import org.springframework.stereotype.Component;

import java.util.Date;

@Component
public class PeriodicTask {

    @Scheduled(cron = "0/5 * * * * ?")
    public void everyFiveSeconds() {
        System.out.println("Periodic task: " + new Date());
    }

} Also, for the annotation to work, you need to add a configuration with the annotation. @Scheduled @EnableScheduling package quartzdemo;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.scheduling.annotation.EnableScheduling;

@SpringBootApplication
@EnableScheduling
public class QuartzDemoApplication {

    public static void main(String[] args) {
        SpringApplication.run(QuartzDemoApplication.class, args);
    }

} The result will be a text output in the console every five seconds. Periodic task: Thu Jul 07 18:24:50 EDT 2022
Periodic task: Thu Jul 07 18:24:55 EDT 2022
Periodic task: Thu Jul 07 18:25:00 EDT 2022
... The annotation supports the following parameters: @Scheduled - Allows you to run a task at a specified fixed interval. fixedRate - Execute a task with a fixed delay between the completion of the last invocation and the start of the next. fixedDelay - The parameter is used with and to wait before the first execution of the task with the specified delay. initialDelay fixedRate fixedDelay - Set the task execution schedule using the cron-string. Also supports macros (or ), , , (or ), and . cron @yearly @annually @monthly @weekly @daily @midnight @hourly By default, , and are set in milliseconds. This can be changed using the parameter, setting the value from to . fixedRate fixedDelay initialDelay timeUnit NANOSECONDS DAYS Furthermore, you can use properties in @Scheduled annotation: application.properties cron-string=0/5 * * * * ? PeriodicTask.java @Component
public class PeriodicTask {

    @Scheduled(cron = "${cron-string}")
    public void everyFiveSeconds() {
        System.out.println("Periodic task: " + new Date());
    }

} To use properties, you can utilize , , and parameters instead of , and accordingly. fixedRateString fixedDelayString initialDelayString fixedRate fixedDelay initialDelay Directly use Quartz In the previous example, we executed scheduled tasks, but at the same time, we could not dynamically set the start time of the job, or pass parameters to it. To solve these problems, you can directly use Quartz. The main Quartz interfaces are listed below: is an interface to be implemented by the classes that contain the business logic that we wish to have executed Job defines instances and data that are related to it JobDetails Job describes the schedule of job execution Trigger is the main Quartz interface that provides all manipulation and searching operations for jobs and triggers Scheduler To work with Quartz directly, it is not necessary to define a configuration with the annotation, and instead of the dependency, you can use . @EnableScheduling org.springframework.boot:spring-boot-starter-quartz org.quartz-scheduler:quartz Let's define SimpleJob class: package quartzdemo.jobs;

import org.quartz.Job;
import org.quartz.JobExecutionContext;

import java.text.MessageFormat;

public class SimpleJob implements Job {

    @Override
    public void execute(JobExecutionContext context) {
        System.out.println(MessageFormat.format("Job: {0}", getClass()));
    }

} To implement interface, you need to implement only one method that accepts a parameter of type. contains information about the job instance, trigger, scheduler, and other information about the job execution. Job execute JobExecutionContext JobExecutionContext Now let's define an instance of the job: JobDetail job = JobBuilder.newJob(SimpleJob.class).build(); And create a trigger that will trigger after five seconds: Date afterFiveSeconds = Date.from(LocalDateTime.now().plusSeconds(5)
        .atZone(ZoneId.systemDefault()).toInstant());
Trigger trigger = TriggerBuilder.newTrigger()
        .startAt(afterFiveSeconds)
        .build(); Also, create a scheduler: SchedulerFactory schedulerFactory = new StdSchedulerFactory();
Scheduler scheduler = schedulerFactory.getScheduler(); The is initialized in “stand-by” mode, so we have to invoke method: Scheduler start scheduler.start(); Now we can schedule the execution of the job: scheduler.scheduleJob(job, trigger); Farther, when creating , let's add additional data and use it when executing a Job: JobDetails QuartzDemoApplication.java @SpringBootApplication
public class QuartzDemoApplication {

    public static void main(String[] args) {
        SpringApplication.run(QuartzDemoApplication.class, args);
        onStartup();
    }

    private static void onStartup() throws SchedulerException {
        JobDetail job = JobBuilder.newJob(SimpleJob.class)
                .usingJobData("param", "value") // add a parameter
                .build();

        Date afterFiveSeconds = Date.from(LocalDateTime.now().plusSeconds(5)
                .atZone(ZoneId.systemDefault()).toInstant());
        Trigger trigger = TriggerBuilder.newTrigger()
                .startAt(afterFiveSeconds)
                .build();

        SchedulerFactory schedulerFactory = new StdSchedulerFactory();
        Scheduler scheduler = schedulerFactory.getScheduler();
        scheduler.start();
        scheduler.scheduleJob(job, trigger);
    }
} SimpleJob.java public class SimpleJob implements Job {

    @Override
    public void execute(JobExecutionContext context) {
        JobDataMap dataMap = context.getJobDetail().getJobDataMap();
        String param = dataMap.getString("param");
        System.out.println(MessageFormat.format("Job: {0}; Param: {1}",
                getClass(), param));
    }

} It is important to note that all values that are added to must be serializable. JobDataMap JobStore Quartz stores data about , , and other information in . By default, the in-memory is used. This means that if we have scheduled tasks and shut down the application (for example, when restarting or crashing) before they are fired, then they will never be executed again. Quartz also supports JDBC-JobStore for storing information in a database. JobDetail Trigger JobStore JobStore Before using JDBC-JobStore, it is necessary to create tables in the database that Quartz will use. By default, these tables are prefixed with . QRTZ_ The Quartz source code contains for creating tables for various databases, such as Oracle, Postgres, MS SQL Server, MySQL, and others, and also has a ready-made XML file for Liquibase. SQL scripts Also, QRTZ tables can be automatically created when launching the application by specifying the property. spring.quartz.jdbc.initialize-schema=always For simplicity, we will use the second method and the H2 database. Let's configure a data source, use JDBCJobStore and create QRTZ tables in application.properties: spring.datasource.url=jdbc:h2:mem:testdb
spring.datasource.driverClassName=org.h2.Driver
spring.datasource.username=sa
spring.datasource.password=

spring.quartz.job-store-type=jdbc
spring.quartz.jdbc.initialize-schema=always For these settings to be taken into account, the Scheduler must be created as a Spring bean: package quartzdemo;

import org.quartz.*;
import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.scheduling.annotation.EnableScheduling;
import org.springframework.scheduling.quartz.SchedulerFactoryBean;
import quartzdemo.jobs.SimpleJob;

import java.time.LocalDateTime;
import java.time.ZoneId;
import java.util.Date;

@SpringBootApplication
@EnableScheduling
public class QuartzDemoApplication {

    public static void main(String[] args) {
        SpringApplication.run(QuartzDemoApplication.class, args);
    }

    @Bean()
    public Scheduler scheduler(SchedulerFactoryBean factory) throws SchedulerException {
        Scheduler scheduler = factory.getScheduler();
        scheduler.start();
        return scheduler;
    }

    @Bean
    public CommandLineRunner run(Scheduler scheduler) {
        return (String[] args) -> {
            JobDetail job = JobBuilder.newJob(SimpleJob.class)
                    .usingJobData("param", "value") // add a parameter
                    .build();

            Date afterFiveSeconds = Date.from(LocalDateTime.now().plusSeconds(5)
                    .atZone(ZoneId.systemDefault()).toInstant());
            Trigger trigger = TriggerBuilder.newTrigger()
                    .startAt(afterFiveSeconds)
                    .build();

            scheduler.scheduleJob(job, trigger);
        };
    }

} Thread pool configuration Quartz runs each task in a separate thread, and you can configure a thread pool for schedulers. It should also be noted that by default, tasks launched via the annotation and directly via Quartz are launched in different thread pools. We can make sure of this: @Scheduled PeriodicTask.java @Component
public class PeriodicTask {

    @Scheduled(cron = "${cron-string}")
    public void everyFiveSeconds() {
        System.out.println(MessageFormat.format("Periodic task: {0}; Thread: {1}",
                new Date().toString(), Thread.currentThread().getName()));
    }

} SimpleJob.java public class SimpleJob implements Job {

    @Override
    public void execute(JobExecutionContext context) {
        JobDataMap dataMap = context.getJobDetail().getJobDataMap();
        String param = dataMap.getString("param");
        System.out.println(MessageFormat.format("Job: {0}; Param: {1}; Thread: {2}",
                getClass(), param, Thread.currentThread().getName()));
    }

} the output will be: Periodic task: Thu Jul 07 19:22:45 EDT 2022; Thread: scheduling-1
Job: class quartzdemo.jobs.SimpleJob; Param: value; Thread: quartzScheduler_Worker-1
Periodic task: Thu Jul 07 19:22:50 EDT 2022; Thread: scheduling-1
Periodic task: Thu Jul 07 19:22:55 EDT 2022; Thread: scheduling-1
Periodic task: Thu Jul 07 19:23:00 EDT 2022; Thread: scheduling-1 The thread pool for tasks contain only one thread. @Scheduled Let's change the scheduler settings for @Scheduled tasks: package quartzdemo;

import org.springframework.context.annotation.Configuration;
import org.springframework.scheduling.annotation.SchedulingConfigurer;
import org.springframework.scheduling.concurrent.ThreadPoolTaskScheduler;
import org.springframework.scheduling.config.ScheduledTaskRegistrar;

@Configuration
public class SchedulingConfiguration implements SchedulingConfigurer {

    @Override
    public void configureTasks(ScheduledTaskRegistrar taskRegistrar) {
        ThreadPoolTaskScheduler threadPoolTaskScheduler = new ThreadPoolTaskScheduler();

        threadPoolTaskScheduler.setPoolSize(10);
        threadPoolTaskScheduler.setThreadNamePrefix("my-scheduled-task-pool-");
        threadPoolTaskScheduler.initialize();

        taskRegistrar.setTaskScheduler(threadPoolTaskScheduler);
    }

} the output will now be like this: Periodic task: Thu Jul 07 19:44:10 EDT 2022; Thread: my-scheduled-task-pool-1
Job: class quartzdemo.jobs.SimpleJob; Param: value; Thread: quartzScheduler_Worker-1
Periodic task: Thu Jul 07 19:44:15 EDT 2022; Thread: my-scheduled-task-pool-1
Periodic task: Thu Jul 07 19:44:20 EDT 2022; Thread: my-scheduled-task-pool-2 As you can see, these settings affected only the tasks set using annotations. Now let's change the settings of the scheduler that we work with Quartz directly. This can be done in two ways: through the properties file or by creating a bean . SchedulerFactoryBeanCustomizer Let's use the first method. If we hadn't initialized Quartz via Spring, we would have to register properties in the quartz.properties file. In our case, we need to register properties in application.properties, adding the prefix to them. spring.quartz.properties. application.properties spring.quartz.properties.org.quartz.threadPool.threadNamePrefix=my-scheduler_Worker
spring.quartz.properties.org.quartz.threadPool.threadCount=25 Let's launch the application. Now the output will be like this: Periodic task: Sat Jul 23 10:45:55 MSK 2022; Thread: my-scheduled-task-pool-1
Job: class quartzdemo.jobs.SimpleJob; Param: value; Thread: my-scheduler_Worker-1 Now the thread in which the task is started is called . my-scheduler_Worker-1 Multiple schedulers If you need to create several schedulers with different parameters, you must define several . Let's look at an example. SchedulerFactoryBeans package quartzdemo;

import quartzdemo.jobs.SimpleJob;
import org.quartz.*;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.scheduling.annotation.EnableScheduling;
import org.springframework.scheduling.quartz.SchedulerFactoryBean;

import javax.sql.DataSource;
import java.time.LocalDateTime;
import java.time.ZoneId;
import java.util.Date;
import java.util.Properties;

@SpringBootApplication
@EnableScheduling
public class QuartzDemoApplication {

    public static void main(String[] args) {
        SpringApplication.run(QuartzDemoApplication.class, args);
    }

    @Bean("customSchedulerFactoryBean1")
    public SchedulerFactoryBean customSchedulerFactoryBean1(DataSource dataSource) {
        SchedulerFactoryBean factory = new SchedulerFactoryBean();
        Properties properties = new Properties();
        properties.setProperty("org.quartz.threadPool.threadNamePrefix", "my-custom-scheduler1_Worker");
        factory.setQuartzProperties(properties);
        factory.setDataSource(dataSource);
        return factory;
    }

    @Bean("customSchedulerFactoryBean2")
    public SchedulerFactoryBean customSchedulerFactoryBean2(DataSource dataSource) {
        SchedulerFactoryBean factory = new SchedulerFactoryBean();
        Properties properties = new Properties();
        properties.setProperty("org.quartz.threadPool.threadNamePrefix", "my-custom-scheduler2_Worker");
        factory.setQuartzProperties(properties);
        factory.setDataSource(dataSource);
        return factory;
    }

    @Bean("customScheduler1")
    public Scheduler customScheduler1(@Qualifier("customSchedulerFactoryBean1") SchedulerFactoryBean factory) throws SchedulerException {
        Scheduler scheduler = factory.getScheduler();
        scheduler.start();
        return scheduler;
    }

    @Bean("customScheduler2")
    public Scheduler customScheduler2(@Qualifier("customSchedulerFactoryBean2") SchedulerFactoryBean factory) throws SchedulerException {
        Scheduler scheduler = factory.getScheduler();
        scheduler.start();
        return scheduler;
    }

    @Bean
    public CommandLineRunner run(@Qualifier("customScheduler1") Scheduler customScheduler1,
                                 @Qualifier("customScheduler2") Scheduler customScheduler2) {
        return (String[] args) -> {
            Date afterFiveSeconds = Date.from(LocalDateTime.now().plusSeconds(5).atZone(ZoneId.systemDefault()).toInstant());

            JobDetail jobDetail1 = JobBuilder.newJob(SimpleJob.class).usingJobData("param", "value1").build();
            Trigger trigger1 = TriggerBuilder.newTrigger().startAt(afterFiveSeconds).build();
            customScheduler1.scheduleJob(jobDetail1, trigger1);

            JobDetail jobDetail2 = JobBuilder.newJob(SimpleJob.class).usingJobData("param", "value2").build();
            Trigger trigger2 = TriggerBuilder.newTrigger().startAt(afterFiveSeconds).build();
            customScheduler2.scheduleJob(jobDetail2, trigger2);
        };
    }

} Output: Job: class quartzdemo.jobs.SimpleJob; Param: value2; Thread: my-custom-scheduler2_Worker-1
Job: class quartzdemo.jobs.SimpleJob; Param: value1; Thread: my-custom-scheduler1_Worker-1 The full source code is available over on . GitHub Conclusion Quartz is a powerful framework for automating scheduled tasks. It can be used both with the help of simple and intuitive Spring annotations and with fine customization and tuning, which provides a solution to complex problems.

How to Schedule Jobs With Quartz in Spring Boot

Cómo programar trabajos con cuarzo en Spring Boot

Many companies, as they grow, figure out the need to change their brand identities. But we should not assume that they evolved their brands because their original one was simply poor. Have you ever considered that an inferior brand that a start-up uses makes a lot of sense to their initial user? In this essay, I want to focus on the importance of having a brand that speaks the language of your early-stage customers. To get started, let's look at the story of Stripe: Stripe(.com) is a growing payments service. Now, a nice name that is easy to type and speak over the phone. It could be more beautiful and it suits well to the stage that they are at - an at-scale stage. But it wasn't always like that when they started, as revealed by the company's co-founder Patrick Collison: Stripe wasn't called Stripe back then… It was called /dev/payments because we, you can tell, we were great branding experts. (Greylock, 2015, 0h4m30s) Calling a company "/dev/payments" would not indeed make much sense - using the general branding hat as we know it. But luckily they were not branding experts at the time, as they were appealing their initial service to high-tech start-ups that needed an easy payments solution for their Linux systems. For that community, "/dev/payments" was an expression that made a lot of sense with their crowd; it fit with the domain's language. Perhaps they didn't notice what they did, fine. But maybe also the very fact that they were not branding experts, as pointed out by Patrick, perfectly helped them at that moment. They did not have the time (or branding expertise) to screw things up. Taking inspiration from Stripe's case, the following are a few points for entrepreneurs looking at how to better position their brand at the early stage: Don't spend time seeking a romantic "at-scale" brand Trying to look for your future brand, such as a lasting brand, would be a waste of time and it could even take focus away. Instead, come up with a culture-fit brand or, at least, try not to find a brand name that is too neutral or distant. If you have both, of course, go for it. But also remember to try out the different brand directions as you are running your many MVP experiments. You should think of your initial brand name as a test: if you have one that is meaningful and ridiculously nice for a niche of people, then you may be using your time correctly. Your brand may not be perfect, it’s necessary When looking at a brand that helps connect with a niche of users, and their culture, we create an initial story, a discussion. More importantly, it reminds us that everything is yet dynamic in the early stage, that much more will come as we learn with the initial customers, when we find them, the real or right ones. A name, a prototype, an early product - these things not perfect - exist to let us open the discussion with customers. Customers are the ones that can help us to understand the language. And that language is key to the development of the ultimate brand. When started, it wasn't . Instead, and as part of many experiments, they launched their initial service as tailored to a neighborhood at Menlo Park, California - a network called Lorelei neighborhood: Nextdoor.com Nextdoor.com And, we were very lucky, we found a community down in Menlo Park, willing to be her guinea pig. It's the Lorelei neighborhood, this is a photograph that I took one afternoon when I was down in Menlo Park one of the four times that I had to go down and pitch the idea of next door to a group of 10 folks that represented the homeowners association in Lorelei. (Sarah Leary, ProductSF 2016, 0h10m14s) The future brand name will naturally come "The name resulted in misspellings and confusion to those outside the company, so the company renamed itself Stripe" says Wikipedia. If you have a good reason to change your name, you are doing things correctly. Therefore, seek an initial culture-fit representation and drive it to the next stage! In the end, changing it or not won't be up to you - your audience will make that call. References Greylock. (2015, November 4th). Blitzscaling 11: Patrick Collison on Hiring at Stripe and the Role of a Product-Focused CEO [video]. Retrieved https://www.youtube.com/watch?v=qrDZhAxpKrQ Paul Graham. (2013, July). Do Things That Don't Scale. Retrieved from http://paulgraham.com/ds.html ProductSF 2016 (2016, November 10) Nextdoor Co-Founder Sarah Leary on The Journey of the Pivot. Retrieved from https://youtu.be/tvHAcc2UOl https://en.wikipedia.org/wiki/Stripe_(company)

Startups: Stop Romanticizing Your Brand and Tailor it for Early Adopters

A QR Code (Quick Response Code) is a two-dimensional barcode that was introduced in 1994. It is a machine-readable optical label that stores the information about the product to which it is attached. A single QR code can hold up to 4,000 characters. It consists of patterns of black squares which can be scanned and translated into human readable information using an imaging device. Not long ago, QR codes were limited to redirect users to certain web pages or URLs. Today, QR codes aren’t limited to sharing information, but they can do much more. From promoting business products to mobile contactless payments, QR codes are making our life easier in a lot of ways. Excessive use of mobile phones, internet, and remote devices has changed the way consumers and businesses interact. It has given rise to digital marketing where almost every organization is trying to engage clients available on the internet. QR codes can help marketers track performance of the products. Here are some of the applications of QR codes: QR Codes On Packaging According to a , 52 percent of consumers would purchase a product again if they receive premium packaging the first time. Therefore, it is important to create beautiful and appealing packaging on the products. Millennials want aesthetically pleasing packaging with minimal design. QR codes can help you achieve that. Also, GMO products in the US requires to have QR codes on the products so that customers can learn more about the product and its ingredients. So, it is a common practice to include QR codes on product packaging. research QR Codes For Cashless Payments Retail stores can use QR codes to facilitate quick cashless payment systems. Walmart was amongst the first to use QR code for cashless payments. These can be very helpful in attracting millenials who like the idea of cashless ecosystem. No need to carry cash with you when you can make payment with your smartphones. Now, we can see QR codes at almost all the retail stores, and consumers can make payments easily with the help of their smartphone. Social Media Social media is also using QR codes. Giants like Facebook, Twitter, Snapchat allow users to follow accounts by scanning QR codes. WhatApp allows you to open your messages on your computer by scanning a code. All you have to do is scan a code with your phone, and you’re good to go. Brands can use QR codes to build presence on social media by driving more and more users on their accounts. It saves you the hassle of looking up for those accounts by easily redirecting you to the page that you’re looking for. Tracking Performance Metrics For marketers, it is very important to keep track of performance metrics. It is usually not easy to see how well a marketing campaign is performing. But QR codes can help with the problem. Based on the number of scans, marketers can understand if the marketing campaign or the product itself is performing well or not. It will help them create better marketing strategies. Multi URL QR Codes — How Do They Help? Whether you own a restaurant, retail store, or a travel agency, multi URL QR codes can help you customize your deals according to the time of the day. In simple words, a multi URL QR code is a single code to redirect to multiple online resources. Key features of multi URL QR codes are: · System-based redirection · Time-based redirection · Location-based redirection · Real-time statistics · Print-ready reports · Custom designed QR codes · High-grade flexibility Let’s learn more about multi URL QR code’s time-based redirection. Set Different URLs per Time Time-based redirection is the best way to promote limited offers using the same QR codes you’ll be using after the offer ends. Some cases of using time-based redirection in multi URL QR codes are listed below: 1. For instance, you can let users avail breakfast, lunch, dinner, and midnight deals at your website or local store using the same QR code. When the time duration for breakfast ends, the users will be automatically redirected to the lunch offer page and so on. Sounds fair enough? 2. Another use-case of time-based redirection is offering discounts on your restraint menu or store products during the Christmas holidays. All users need to do is scan the QR code, avail the discounted coupons or offers, and make the purchase. 3. Moreover, you can use to do A/B testing of your campaigns to see what converts best from the same QR code at different times. A dynamic multi URL QR code allows you to change the saved information anytime. Thereby, when the offer ends, you can simply replace the offer landing page with a new one. And anyone can create QR codes. Using a like QRzebra, you can create QR codes, customize them per your brand, and track real-time data including time, date, location, device type, and the total number of scans. QR codes make our life faster and easier. From faster checkouts to increased number of sales, there are a lot of reasons we cannot overlook the importance of QR codes. Also, if you’re a business, it is important that you seek out each and every tool to maximize ROI. QR code generator with logo

Real-World Applications Of QR Codes Today

I read the whitepaper so you don’t have to. What is Tor? The Onion Routing Protocol (TOR) was designed by the US Navy in the mid 1990s at the U.S Naval Research Labatory[0]. The pre-alpha version of Tor was released to the public in September of 2002 [1] and the Tor project, the company that maintains Tor, was started in 2006. Here is a quote from the paper titled “Tor: The Second-Generation Onion Router” on what Tor is in a nutshell: Tor is a circuit based low-latency anonymous communication service [2] The core principle of Tor is “onion routing” which is a technique for anonymous communication over a public network. In onion routing messages are encapsulated in several layers of encryption, analogous to encapsulation in the OSI 7 layer model [3]. It is called onion routing because onions have layers and this networking protocol also has layers. The resulting ‘onion’ (fully encapsulated message) is then transmitted through a series of nodes in a network (called onion routers) with each node peeling away a layer of the ‘onion’ and therefore uncovering the data’s next destination. When the final layer is decrypted you get the plaintext of the original message. The original author remains anonymous because each node in the network is only aware of the preceding and following nodes in the path (except the first node that does know who the sender is, but doesn’t know the final destination). This has led to ‘attacks’ on which the NSA runs servers in order to attempt to be the first and last nodes in the network. If the NSA server is the first node, it knows where the message is from. If the NSA server is the last node, it knows the final destination and what the message says. [4] Overview Onion Routing is a distributed overlay network designed to anonymise TCP-based applications like web browsing, secure shell and instant messaging. Clients a path through the network and build a where each onion router in the paths knows the predecessor and the successor, but no other nodes in the circuit. choose circuit Packets flows down the network in fixed-size cells which are unwrapped by a symmetric key at each node and relayed downstream. The notion of a symmetric key comes from Symmetric-Key Encryption Algorithms. Symmetric-Key Encryption Algorithms, a detour In Symmetric Key Encryption the same key is used for both Alice (sender) and Bob (receiver) as opposed to public key encryption where these keys differ. This makes it faster and easier to use than Public Key encryption, but this also causes two problems: The key needs to be stored securely Transfer of key may not be secured. If a third party figures out the key, either by attacking the transfer of the key or some other method they will be able to decrypt all communications encrypted with this key. Symmetric Key encryption is also much less computationally expensive than public key encryption, which is useful in a network like this. is a set of cryptographic protocols based on algorithms that require two separate keys: Public Key Cryptography Public-key — Which is public and visible by others Private-key — Which is private and meant to be kept secret. These two keys are mathematically linked. In public key cryptography the use of the public key is to encrypt plaintext and the use of the private key is to decrypt encrypted text. This means that anyone can encrypt plaintext for a specific person but only that person can decrypt it. The two keys are very large prime numbers. Assume q and p are two separate and equally large prime numbers and then n = pq. n is used to encrypt the message and p and q are used to decrypt the message. This works because factorisation is hard to compute. Given a very (very) large number, find the factors of that number which are prime numbers. Often times the numbers are in hexadecimal. Digital Signatures Another useful tool of cryptography to know is digital signatures. Digital Signatures use public-key cryptography. A digital signature is a digital version of a physical signature. Often times you can say you have cryptographically / digitally signed a document. Only the person with the private key can produce valid digital signatures which allow them to sign a document alot more securely than a physical written signature. Alice wants to digitally sign a message, m. In order to do that Alice must have: Alice then uses a signing function to produce a digital signature: The internals of the signing function isn’t necessary to know. The function takes a message, a private key and it will produce a digital signature. exact Anyone can use the public key to verify a digital signature: If anyone knows how to put spaces in trueorfalse (in mathjax) I will greatly appreciate the help! I say that a signing function isn’t necessary to know however if you want to learn a few go ahead. The reason I haven’t added them to this document is because someone from 2–3 years time might read this and signing functions could be completely different. Tor itself Tor requires alot of users to create anonmity and thus if Tor was hard to use users wouldn’t adopt it so easily making it less anonymous. Because of this, the usabillity isn’t just a design choice of Tor but a . If Tor isn’t usable or designed nicely, it won’t be used and thus it won’t be secured. security requirement Tor has therefore had to make some design decisions that may not improve security but improve usabillity. Disadvantages Tor is not a completely decentralised peer-to-peer system like many people believe it to be. If it was completely peer to peer it wouldn’t be very usable. Tor requires a set of directory servers that manage and keep the state of the network at any given time. Tor is not secure against end to end attacks. An end to end attack is where an entity has control of both the first and last node in a path, as stated earlier. This is a problem that cyber security experts have yet to solve, so Tor does not have a solution to this problem. Tor does not provide protocol-normalisation like Privoxy or the Anonymizer, meaning that If senders want anonymity from responders while using complex and variable protocols like HTTP, Tor must be layered with a ﬁltering proxy such as Privoxy to hide differences between clients, and expunge protocol features that leak identity. [2] Tor does not hide the identity of the sender. In 2013 during the Final Exams period at Harvard a student tried to delay the exam by sending in a fake bomb threat. The student used Tor and Guerillar Mail (a service which allows people to make disposable email addresses) to send the bomb threat to school officials. [5] The student was caught, even though he took precautions to make sure he wasn’t caught. Gurillar mail sends an originating IP address header along with the email that’s sent so the receiver knows where the original email came from. With Tor, the student expected the IP address to be scrambled but the authorities knew it came from a Tor exit node (Tor keeps a list of all nodes in the directory service) so the authoriies simply looked for people who were accessing Tor at the time the email was sent. Onion Routing So given the network above we are going to simulate a very basic onion routing protocol. The laptop on the left is the sender and the server rack on the right is the receiver. So we start off by encrypting a message with 3 layers of encryption (Tor typically uses 3 nodes, so therefore 3 layers of encryption are needed) The first layer is stripped off on the first machine. Something important to note here is that every machine only knows what the predecessor is or what the sucessor is, it does not know what the final goal is unless it is the last node in the path. As it travels down the path, more and more layers are stripped away. The second (middle) node does not know where the message originated or where the final destination is. The final node knows what the message is and where it’s going, but it doesn’t know who sent it. The computer then reads the content of the message which might be “connect me to Facebook” and it then connects to Facebook and receives a message back as a response. Because the node doesn’t know where the original message came from, it sends it back through the network to the predecessor and says “pass this back through the network”. But before doing this, it adds it’s own level of encryption back. Eventually the original node receives a fully encrypted packet containing the response from Facebook. Because the original node has both private and public keys it can fully decrypt the message. One of the key properties here is that once a node decrypts a layer, it cannot tell how many more layers there are to decrypt. It could be as small as 1 or 2 or as large as 200 layers of encryption. The first node knows who sent the message but it doesn’t know what the message says because it is encrypted. The last node knows what the message says but it can’t tell where it came from. How is a circuit created? Each machine, when it wants to create a circuit, chooses the exit node first, followed by the other nodes in the circuit. All paths in the circuit obey these rules: We do not choose the same router twice for the same path. We do not choose any router in the same family as another in the same path. (Two routers are in the same family if each one lists the other in the “family” entries of its descriptor.) We do not choose more than one router in a given /16 subnet. We don’t choose any non-running or non-valid router unless we have been configured to do so. By default, we are configured to allow non-valid routers in “middle” and “rendezvous” positions. The first node must be a Guard node. A guard node is a privileged node because it sees the real IP of the user. It’s ‘expensive’ to become a guard node (maintain a high uptime for weeks and have good bandwidth) Something important to note here is that Tor uses the Diffie-Hellman algorithm to set up session keys between the user and onion routers. Diffie-Hellman Diffie-Hellman is a way of a shared secret between two people in such a way that the secret can’t be seen by observing the communication. You’re not sharing information during the key exchange, you’re creating a key together. generating Now for some basic knowledge on Diffie-Hellman, taken from here I come up with two prime numbers, and and tell you what they are x y You then pick a secret number ( ) but don’t tell anyone. Instead you compute and send that result back to me (we’ll call it ) a A I do the same thing, but we’ll call my secret number and the computed number . So I compute and send you the result. b B Now you take the number I sent you and do the exact same operation with it. So that’s . I do the same operation with the result you sent me, The cool part here is that the answer I get at step 5 is the same answer you get at step 4. It comes down to a cool property of modulo components: Tor Hidden Services In a traditional network you have a definite input and a definite output. You know where your data is going. In a Tor Hidden Service you input some data but no outside force can see where it’s going. It is possible to communicate with a server without the user or the server knowing who eachother are. When a server is set up on Tor to act as a hidden service, the server sends a message to some selected Onion Routers asking if they want to be an introduction point to the server. It is entirely up to the server as to who gets chosen as an introduction point and it doesn’t matter who is chosen. The introduction points know that they are going to be introducing people to the server. The server will then create something called a hidden service descriptor which has a public key and the IP address of each introduction point. It will then send this hidden service descriptor to a distributed hash table which means that every onion router will hold some part of the information of the hidden service descriptor. If you try to look up a hidden service the introduction point responsible for it will give you the full hidden service descriptor. The key for this hash table is the onion address and the onion address is derived from the server. The idea is that the onion address isn’t publicised over the whole Tor network but instead you find it another way like from a friend telling you or on the internet (addresses ending in .onion). So almost every single onion router will have minimal knowledge about the hidden service unless they explicitly want to find it. If you want to access an onion address you would first request the descriptor off of the hash table and the descriptor has, let’s say 4 or 5 IP addresses of introductory nodes. You pick one at random and you’re going to ask the introduction point to introduce you to the server and instead of making a connection directly to the server you make a rendezvous point at random in the network from a given set of Onion Routers. You then make a circuit to that rendezvous point and you send a message to the rendezvous point asking if it can introduce you to the server using the introduction point you just used and then it says “I want you to send a message, X, to the server”. The rendezvous point makes a circuit to the introduction point and sends it the word X and its IP address. The introduction point sends the message to the server and the server can choose to accept it or do nothing. If the server accepts the message it will then create a circuit to the rendezvous point. The server sends the rendezvous point to the server and the rendezvous point looks at both messages and if they’re the same then it will then act as another hop on the circuit and connect them directly. Another important thing to note is that every single Tor packet (called a cell) is exactly 512kb and they are all encrypted. Tor does this so people cannot guess that larger cells are images / media. In short, a hidden service works like this, taken from : here A hidden service calculates its key pair (private and public key, asymmetric encryption). Then the hidden service picks some relays as its . introduction points It tells its public key to those over Tor circuits. introduction points After that the hidden-service creates a , containing its public key and what its are. hidden service descriptor introduction points The hidden service signs the with its private key. hidden service descriptor It then uploads the to a (DHT). hidden service descriptor distributed hash table Clients learn the .onion address from a hidden service out-of-band. (e.g. public website) (A $hash.onion is a 16 character name derived from the service’s public key.) After retrieving the .onion address the client connects to the DHT and asks for that $hash. If it exists the client learns about the hidden service’s public key and its . introduction points The client picks a relay at random to build a circuit to it, to tell it a . The picked relay acts as . one-time secret rendezvous point The client creates a , containing the address of the and the , before encrypting the message with the hidden service’s public key. introduce message rendezvous point one-time secret The client sends its message over a Tor circuit to one of the , demanding it to be forwarded to the hidden service. introduction points The hidden service decrypts the with its private key to learn about the and the . introduce message rendezvous point one-time secret The hidden service creates a , containing the and sends it over a circuit to the . rendezvous message one-time secret rendezvous point The tells the client that a connection was established. rendezvous point Client and hidden service talk to each other over this . All traffic is end-to-end encrypted and the just relays it back and forth. Note that each of them, client and hidden service, build a circuit to the ; at three hops per circuit this makes six hops in total. rendezvous point rendezvous point rendezvous point _Support the content you love. Buy a Coffee for Brandon Skerritt with Ko-fi.com_ko-fi.com Buy Brandon Skerritt a Coffee. ko-fi.com/hacker _Go to paypal.me/BrandonSkerritt and type in the amount. Since it's PayPal, it's easy and secure. Don't have a PayPal…_www.paypal.me Pay Brandon Skerritt using PayPal.Me References [0] — [1] — [2] — [3] — [4] — [5] — [6] — http://www.onion-router.net/Publications/JSAC-1998.pdf http://archives.seul.org/or/dev/Sep-2002/msg00019.html http://fermatslibrary.com/s/tor-the-second-generation-onion-router http://ieeexplore.ieee.org/abstract/document/1094702/ https://cyber-peace.org/wp-content/uploads/2013/06/Attacking-Tor_-how-the-NSA-targets-users-online-anonymity-_-World-news-_-theguardian.pdf http://www.thecrimson.com/article/2013/12/17/student-charged-bomb-threat/ https://www.youtube.com/watch?v=QRYzre4bf7I

How does Tor *really* work?

SEO is arguably the fastest-changing industry of all, and it only seems to be growing. There are a variety of reasons for this, but one main factor that has changed SEO as we know it today from what was possible 8-10 years ago is how Google ranks webpages in their search engine results page (SERP). Nowadays there aren't any shortcuts or simple ways to rank your website higher on SERPs - you either need good content + user engagement/interaction or else nothing will happen at all. SEO may have been easy 10+ years ago when keyword stuffing could get websites into the top ten slots; however, now such tactics no longer work, they can actually do more harm than help with rankings. Modern Google search algorithms take into account many little things: from the quality and uniqueness of content to adaptation for mobile versions and voice search. In this article, we'll discuss the top 7 SEO trends of 2021. Trend # 1: Google's Page Experience Update 2021 saw the emergence of a new ranking algorithm from Google. The main idea behind the Page Experience Update focuses on evaluating websites based on user experience. In simple terms, if a resource is safe, convenient, and attractive to people, it gets high positions in the search results. User experience will be measured using Core Web Vitals metrics. These indicators include: LCP (Largest Contentful Paint) - analyzes the loading speed of a web resource, that is, the time it takes for the main block of content (text, images, and videos) to be displayed. This is an important indicator. If the site takes a long time to load, this negatively affects the visitor's reaction. The optimal value is loading the main content in 2.5 seconds. FID (First Input Delay) - an assessment of the site's interactivity. Determines the time between the time visitor entered the web resource and began to interact with the content, and how the website reacted to the action. The optimal FID is up to 100 ms. CLS (Cumulative Layout Shift) - visual stability analysis. The indicator calculates unexpected "jumps" of the content block during the display of a web page. The optimal CLS is less than 0.1 (i.e., 0 to 1 hop). Trend # 2: Mobile Friendly In early 2021, Google began to use another important indicator for ranking web resources - Mobile Friendly. This is due to the fact that a significant part of search queries is done using smartphones. Therefore, all website owners should prepare their high-quality mobile versions. It is important that they not only exist but also have a stylish design, load quickly and work stably. You can evaluate the mobile version of the site in by assessing the quality of resource optimization. Google Search Console After the test, you can view the report and recommendations for improving the mobile version of your website. Trend # 3: Safety To get into the TOP ranking of search engines, a resource must be not only beautiful, convenient, and interesting. It is important to take care of its safety. Web developers and SEOs should pay attention to: the presence of a secure HTTPS protocol. Every day we read the news about the leakage of personal data of Internet users. For this, it is important to correctly configure the HTTPS protocol; lack of malware and unsafe content. The presence of viruses is often evidenced by the pessimization of the web resource, warnings from hosting providers, and user complaints. You should regularly use from Yandex and from Google; Site status check Safe Browsing banners and pop-ups. Such elements not only annoy visitors but also slow down the page loading speed. Trend # 4: EAT EAT is an acronym that has been one of the most important ranking factors since 2018. It stands for: Е (expertise) А (authoritativeness) T (trustworthiness) This metric is not important for all sites. For example, if the resource is dedicated to the most beautiful representatives of K-POP, then E-AT will not be important, since the likability of a particular singer is a subjective indicator. But if the site is devoted to medical or financial topics, the E-A-T factor will play one of the determining roles in the ranking. How is EAT assessed? For YMYL (Your money or Your Life) topics (finance, health, jurisprudence), the author's expertise is important. That is, an article on the selection of contraceptives will clearly be more useful for an Internet user if it is written by a certified gynecologist. 1. Expertise: Nevertheless, expertise can also be referred to in everyday topics. To confirm the author's expertise, the page must contain information about him. Just a photo and a surname are not enough. It is important to make markup that confirms the identity of the author. On his page should be placed information that will prove the expertise: diplomas of higher education, certificates, etc. In this case, the author's regalia must correspond to the subject in which he works. If he writes about medicines, a pharmacist or medical diploma does not hurt. The company or person who runs the page must be respected by industry experts or opinion leaders. This factor is assessed by Google assessors. They look for information about authority on the Internet. 2. Authority: It is understood that the texts on the pages will be truthful and accurate. Assessors check this factor by paying attention to the authors of the content, the credibility, and the authority of the sources. 3. Credibility: To improve performance for EAT, the analyst Search Quality Manager Gary Ils advises that it is worth using references to authoritative sources. It's important to keep track of the relevance of the data and check the facts. It will also be useful to provide more information about the authors, which will confirm their expertise. Trend # 5: Long Tailed Key Phrases Long-tail search terms are key phrases of 5 or more words. They are not high-frequency, but they are capable of generating about 50-70% of organic traffic. Longtails help users find information faster. Trend # 6: A large number of traffic sources Search engines respond well to resources that attract traffic from different places. This signals that the website is popular and interesting to different audiences. The SEO trend is certainly not new, but in 2021 it continues to gain momentum. Developers, optimizers, and business owners need to pay attention to the development of such areas to attract users: video hosting sites - YouTube, Daily Motion; social networks - Instagram, TikTok, Facebook, etc .; messengers - Telegram, WhatsApp, Viber. Don't forget about forums, directories, display and contextual advertising, blogs, and so on. Trend # 7: Local SEO There is a trend towards an increase in the number of search queries, which are accompanied by the phrases "close", "close", "near", etc. For example, people often search: "A pharmacy near me." Do not neglect the registration of the company on maps and directories. If a person is looking for a pharmacy, restaurant, or gym, the search engine will first show them the websites of places that are close to the user. If you don’t have expertise in local SEO, you can always look up . SEO Services in Toronto, Miami, Malaysia, Singapore, New York Summary Following the precepts of EAT, we dealt with the latest trends in search engine promotion. A lot has changed, but the basic things have remained unshakable: in order to be at the top of the rankings, it is important to work on the usability of the site, solve technical problems in a timely manner and generate quality content.

Top 7 SEO Trends in 2021 Every Marketer Should Follow

is one of the most rapidly growing exchanges, swiftly making a reputation for itself by rapidly adding new services. It pioneered new products such as . It is unfortunate Americans cannot take advantage of this exchange. FTX basket trades, prediction markets, and fractionalized stock trading has invested in FTX (both entities founded by ). Alameda is a quantitative crypto trading business with a that is a prominent market maker on FTX. Alameda Research Sam Bankman-Fried $100 million AUM Alameda was one of the major liquidity providers and market makers in the industry within a year of its start, trading up to $1 billion per day. TUSD and USDC were also early liquidity partners. Moreover, , a decentralised exchange that is independent of the FTX ecosystem. FTX created Serum (SRM) Disclaimer : Throughout this article I have used referral links. Most of these services gives you additional discounts if you use referral links. FTX Products & Features 1. NFT Marketplace The marketplace appears to run on both the Ethereum blockchain and a network named Solana, which employs a proof-of-stake consensus mechanism and consumes substantially less power than Ethereum. FTX are a sort of cryptocurrency that may provide verifiable ownership and scarcity of any sort of asset. NFTs have been widely utilised for Non-fungible tokens (NFTs) digital art, music, and memes, among other sorts of material, to date. Some of FTX’s NFTs are linked to physical objects and “redeemable” for their physical equivalents. An NFT linked to an image of should result in three genuine KAWS statuettes; the same is true for an NFT linked to an FTX-branded condom. FTX levies a on each transaction or trade on NFTs. three KAWS statuettes 5% fee to both the buyer and the seller 2. Futures offers over that may be traded using a stablecoin as collateral, such as USD or USDT. FTX 100 futures pairings Futures contracts are paid using stablecoins. That is, you will be putting up . You don’t need a bank account to pay the futures when they expire this way. Instead, use a stable coin to make it easy to enter and exit a position. When you deposit stablecoins, they are converted into USD to cover your margin needs. stablecoins as collateral FTX also includes a structure of backstop liquidity providers that will step in if is required. clawback Sign Up on FTX & get 5% Off on Your Trading Fees 3. Leveraged Tokens Leveraged Tokens are a unique asset for cryptocurrency traders developed by FTX. These are ERC20 tokens with leveraged exposure to the trading pair of up to 3x. To begin trading leveraged coins, there is from the user’s FTX account balance. There are also exchange-traded funds (ETFs) that have leveraged exposure to a variety of existing and popular cryptocurrency assets. no margin need Using FTX leveraged tokens can assist a trader control risk. Any transaction being traded by the derivatives exchange. gains are immediately reinvested back into the underlying asset This implies that if your leveraged token investment is profitable, the tokens will automatically add 3x leveraged holdings to it. Conversely, if the position is negative, leveraged tokens will immediately lower risk. 4. MOVE Contracts Move Contracts enable you to trade depending on the movement of the price of a certain cryptocurrency while only risking a small amount of money. Movement can occur in any direction. They are futures contracts that expire based on the total amount of Bitcoin. It can be done on a daily, weekly, monthly, or quarterly basis. Weekly contracts do not have to match to the calendar week. . This feature draws a large number of users to the exchange. The total volatility of the BTC during a certain time period is the major determinant 5. Options You may also trade Bitcoin options on FTX, which offer you the right but not the responsibility to purchase or sell the digital coin at a certain date and price. You can use leverage to go long or short on options, just like you can with futures. When it expires, . the contract will be settled for an amount equal to its expiry price in dollars 6. Prediction Markets They make it possible for users to trade in more conventional ways. It’s comparable to traditional betting. . You will either win and the contract will settle at 100%, or you will lose and it will settle at 0%. You may place a wager on any real-world occurrence One well-known example is betting on who will win the forthcoming elections. Each candidate will be given a contract. . They have the option to long or short each contract. The buy-in fee will be different for each contender and will be determined by their chances of winning Following the success of our presidential election prediction markets, we will strive to extend our prediction market service to . This process is already in motion, with Super Bowl prediction markets live on the platform and more intriguing markets on the way. include new events such as sports, e-sports, midterm elections, and more 7. Tokenized Stocks Tokenized stocks are the most exciting product from FTX. Giving qualified traders the opportunity to trade a tokenized stock is something that has never been done before in crypto. 24 hours a day, 7 days a week, 365 days a year These are backed up 1:1 with shares held at a registered brokerage, entitling the trader to all of the economic . benefits of owning the stock: dividends, stock splits, and so on In addition to stock spot trading, we have implemented futures trading capability for these products, enabling customers to trade with up to 101x leverage in the same manner they would with any other market on FTX; . same collateral pool, same margin requirements, same everything 8. Spot Trading Similarly to a spot trading exchange, traditional traders may acquire a variety of popular digital assets on the market. , including BTC, ETH, LINK, FTT, PAXG, ADA and XRP. FTX presently supports over 100 trading pairings that may be exchanged for USD or USDT 9. OTC Desk Assume you are purchasing a big number of assets. In such situation, you may be allowed to purchase ‘over the counter,’ or ‘OTC.’ Professional traders typically pick this option since the . Another argument may be that it will have an impact on the price of that coin. order book may be too thin to complete the deal Most exchanges provide this option, however other than the spread for it. You have the option of requesting OTC quotations. It offers discounted prices. You may learn more about it by visiting the . FTX charges no fees FTX OTC Quote webpage Sign Up on FTX & get 5% Off on Your Trading Fees How to get started with FTX To open an account in FTX, go to the top right corner and . In the profile settings, you may safeguard your account by using . click on the Register option two-factor authentication Following that, you must complete your KYC. 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In a recent blog post on , BioWare Austin and Anthem Executive Producer, Christian Dailey, announced that the game studio has opted to cease development on Anthem. This includes a previously announced fundamental restructure of the game that was being worked on under the name of Anthem NEXT, which will no longer see the light of day. BioWare’s official website This ends a tumultuous run for the online multiplayer game and so-called live service. The game launched in January 2019, where it received middling reviews and amassed disappointing sales, failing to hit publisher Electronic Arts’ expected six million copies sold by . March 2019 For the remaining players of the doomed title, Dailey did announce in his blog post that Anthem will continue running as a live service as it exists today. Whether BioWare will keep to that promise for the foreseeable future remains to be seen. Additionally, Dailey cited the COVID-19 pandemic and issues with “working from home during the pandemic” impacting productivity and development for what BioWare had planned for relaunching Anthem. Dailey added, “Not everything we had planned as a studio before COVID-19 can be accomplished without putting undue stress on our teams.” Ironically enough, it was reported by Jason Schreier in in April 2019 how much stress and pressure the development team for Anthem was put under so the game could make its launch date. Kotaku One anonymous former BioWare developer claimed, “I actually cannot count the amount of ‘stress casualties we had on Mass Effect: Andromeda or Anthem.” In terms of the future for BioWare, Daily noted that the team is looking to achieve “laser focus” in order to strengthen the next planned installment of Dragon Age and also Mass Effect, along with updates to Star Wars: The Old Republic. However, the sad end for Anthem definitely serves as a cautionary tale that should serve as an example to the entire video gaming industry. Otherwise, it will be a mistake that history is doomed to repeat. More Gaming News Pokémon Legends: Arceus Revealed Alongside Diamond and Pearl Remakes Ninja Gaiden: Master Collection Arrives for All Platforms on June 10 7 Nioh 2 Character Creation Codes on PC

Anthem: BioWare Ceasing Development on Game Restructuring aka Anthem NEXT

Authors:
(1) Omid Davoodi, Carleton University, School of Computer Science;
(2) Shayan Mohammadizadehsamakosh, Sharif University of Technology, Department of Computer Engineering;
(3) Majid Komeili, Carleton University, School of Computer Science. Table of Links Abstract and Intro Background Information Methodology Prototype Interpretability Prototype-query Similarity Interpretability of the Decision-Making Process The Effects of Low Prototype Counts Discussions Prototype-query Similarity Our second set of experiments has the goal of finding out whether the regions activated by a prototype contain the same concept as the prototype itself. Prototype classifiers, in general, use the closest prototype to a query in their operation. Part-prototype classifiers follow the same idea by finding the closest prototype patch to another patch in the input image. For this to be interpretable, the notion of closeness used by the method should match that of a human. Otherwise, the explanation itself will seem nonsensical. Figure 5 shows examples of both good and bad similarity between the query patch and the prototype. As before, the first experiment was purely comparative. Each fine-grained task consisted of two pairs of images. Each pair consisted of a prototype and its activation on a query image. The prototypes picked were the most important prototypes when trying to classify an image. The idea was to avoid prototypes that were not instrumental in the final decision as they were more likely to not be present in the query image itself. The annotators were then told to select the prototype/activation pair that were conceptually more similar to each other. Figure 6 shows examples of this task where annotators are expected to select pair-2 because the corresponding images are more similar than the pair-1 images. This works well for the part-prototype classification methods as they all have an explanation generation procedure that utilizes their prototypes. On the other hand, ACE is not a classifier. It is an unsupervised concept learning method. Nevertheless, we thought that ACE by itself also had a notion of similarity baked into the method. It picks multiple patches from potentially different images to represent a concept. The assumption is that these patches are similar because they share that concept. Here, we decided to simply include two patches from the same concept in the pairs that represented ACE. The annotators were presented with batches of 10 fine-grained tasks. Like before, 2 out of those 10 tasks contained validation data. Also similar to previous experiments, annotators had to obtain qualification by completing 7 tasks perfectly before being allowed to work on the main experiment. The experiment was repeated 3 times and the results were aggregated. The instructions shown to the annotators are shown in Figure 6. As with prototype interpretability experiments, we also devised a more absolute version of the similarity experiment by adding the options "Both" and "None" to the same experimental layout. The instructions for this other experiment were as follows: • Each set contains two pairs of images. In each one, select the pair of images where the marked regions in those images are conceptually closer to each other than the other pair. • For example if in pair 1, the marked regions are conceptually very different (for example, one is of a face and the other is of the paws of a cat), do not select that pair. On the other hand, if in pair 2, the marked regions are visually and conceptually very similar, select pair 2. • If both pairs have similar regions, select Both. If none of the pairs has similar regions, select None. In total, 1156 pairs were compared and annotated by humans for the comparative study of prototype-query similarity. Table 5 shows the percentage each method was chosen against others. As can be seen, TesNet were chosen 71.88% of times when compared to other methods. At the second place was ProtoPNet with 64.47% preference. This shows that apart from TesNet, the other methods show comparatively worse prototype-query similarity compared to ProtoPNet itself. This has an interesting implication for the interpretability of these methods compared to the baseline. Table 6 shows the results of the same experiments but on a method-by-method basis. Each element of the table shows the results of the pairwise comparison between the two methods, with the method shown in the first column being the one selected out of the two. For example, the intersection between the row "ACE" and the column "ProtoPool" shows the percentage of times (24.17%) ACE was chosen against ProtoPool in the experiments. While there is more variation when looked at with this much detail, the general trends hold true. For the absolute experiments, 1984 pairs were compared and annotated by humans in total. Table 7 shows the percentage of times each method’s prototypes and query sample activations were seen to be close conceptually. While the overall rankings seem to have mostly remained the same, the lower overall percentages show that none of these methods is doing well in this regard. The best results, TesNet at 42.98% and ProtoPNet at 40.41% are still quite low. This is in agreement with the results previously reported in[12], [14]. Finally, Table 8 shows the results of the same experiments but on a method-by-method basis. Each row shows the percentage of times a method (shown on the first column) was selected either solely or as part of the "Both" option when paired with another method shown on the top row. Note that the sum of mirrored cells does not necessarily add up to 100% due to the existence of "Both" and "None" options. The consistently low similarity rates across different methods point to a general failure of all models in achieving a good similarity between the activated regions of the query samples and the prototypes. This paper is available on arxiv under CC 4.0 license. Authors: (1) Omid Davoodi, Carleton University, School of Computer Science; (2) Shayan Mohammadizadehsamakosh, Sharif University of Technology, Department of Computer Engineering; (3) Majid Komeili, Carleton University, School of Computer Science. Authors: Authors: (1) Omid Davoodi, Carleton University, School of Computer Science; (2) Shayan Mohammadizadehsamakosh, Sharif University of Technology, Department of Computer Engineering; (3) Majid Komeili, Carleton University, School of Computer Science. Table of Links Abstract and Intro Abstract and Intro Background Information Background Information Methodology Methodology Prototype Interpretability Prototype Interpretability Prototype-query Similarity Prototype-query Similarity Interpretability of the Decision-Making Process Interpretability of the Decision-Making Process The Effects of Low Prototype Counts The Effects of Low Prototype Counts Discussions Discussions Prototype-query Similarity Our second set of experiments has the goal of finding out whether the regions activated by a prototype contain the same concept as the prototype itself. Prototype classifiers, in general, use the closest prototype to a query in their operation. Part-prototype classifiers follow the same idea by finding the closest prototype patch to another patch in the input image. For this to be interpretable, the notion of closeness used by the method should match that of a human. Otherwise, the explanation itself will seem nonsensical. Figure 5 shows examples of both good and bad similarity between the query patch and the prototype. As before, the first experiment was purely comparative. Each fine-grained task consisted of two pairs of images. Each pair consisted of a prototype and its activation on a query image. The prototypes picked were the most important prototypes when trying to classify an image. The idea was to avoid prototypes that were not instrumental in the final decision as they were more likely to not be present in the query image itself. The annotators were then told to select the prototype/activation pair that were conceptually more similar to each other. Figure 6 shows examples of this task where annotators are expected to select pair-2 because the corresponding images are more similar than the pair-1 images. This works well for the part-prototype classification methods as they all have an explanation generation procedure that utilizes their prototypes. On the other hand, ACE is not a classifier. It is an unsupervised concept learning method. Nevertheless, we thought that ACE by itself also had a notion of similarity baked into the method. It picks multiple patches from potentially different images to represent a concept. The assumption is that these patches are similar because they share that concept. Here, we decided to simply include two patches from the same concept in the pairs that represented ACE. The annotators were presented with batches of 10 fine-grained tasks. Like before, 2 out of those 10 tasks contained validation data. Also similar to previous experiments, annotators had to obtain qualification by completing 7 tasks perfectly before being allowed to work on the main experiment. The experiment was repeated 3 times and the results were aggregated. The instructions shown to the annotators are shown in Figure 6. As with prototype interpretability experiments, we also devised a more absolute version of the similarity experiment by adding the options "Both" and "None" to the same experimental layout. The instructions for this other experiment were as follows: • Each set contains two pairs of images. In each one, select the pair of images where the marked regions in those images are conceptually closer to each other than the other pair. • For example if in pair 1, the marked regions are conceptually very different (for example, one is of a face and the other is of the paws of a cat), do not select that pair. On the other hand, if in pair 2, the marked regions are visually and conceptually very similar, select pair 2. • If both pairs have similar regions, select Both. If none of the pairs has similar regions, select None. In total, 1156 pairs were compared and annotated by humans for the comparative study of prototype-query similarity. Table 5 shows the percentage each method was chosen against others. As can be seen, TesNet were chosen 71.88% of times when compared to other methods. At the second place was ProtoPNet with 64.47% preference. This shows that apart from TesNet, the other methods show comparatively worse prototype-query similarity compared to ProtoPNet itself. This has an interesting implication for the interpretability of these methods compared to the baseline. Table 6 shows the results of the same experiments but on a method-by-method basis. Each element of the table shows the results of the pairwise comparison between the two methods, with the method shown in the first column being the one selected out of the two. For example, the intersection between the row "ACE" and the column "ProtoPool" shows the percentage of times (24.17%) ACE was chosen against ProtoPool in the experiments. While there is more variation when looked at with this much detail, the general trends hold true. For the absolute experiments, 1984 pairs were compared and annotated by humans in total. Table 7 shows the percentage of times each method’s prototypes and query sample activations were seen to be close conceptually. While the overall rankings seem to have mostly remained the same, the lower overall percentages show that none of these methods is doing well in this regard. The best results, TesNet at 42.98% and ProtoPNet at 40.41% are still quite low. This is in agreement with the results previously reported in[12], [14]. Finally, Table 8 shows the results of the same experiments but on a method-by-method basis. Each row shows the percentage of times a method (shown on the first column) was selected either solely or as part of the "Both" option when paired with another method shown on the top row. Note that the sum of mirrored cells does not necessarily add up to 100% due to the existence of "Both" and "None" options. The consistently low similarity rates across different methods point to a general failure of all models in achieving a good similarity between the activated regions of the query samples and the prototypes. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Analysis of Prototype-Query Similarity Rankings

*Photo by Ben Sweet on Unsplash* What happens when a nerd reads psychology? He comes up with seven stages of identity development. The following is a summary of one of the many fascinating ideas Joscha Bach shared on . Although his theory is informed by psychologist Robert Keegan’s work, he draws on AI, consciousness and cognitive science background to create a theory of his own. this podcast A Quick Intro Into Kegan’s Work In the , distinguished six developmental stages. For Kegan, the development of the Self is a process of the mind gradually becoming aware of itself. You build a mental structure of who you are and how the world operates. Evolving Self Robert Kegan Although it’s considered a developmental model, it would make more sense to call it a framework because development doesn’t happen in distinct stages. You might go through stages in parallel or need to revisit the previous stage. How The Mind Generates Reality We don’t yet fully know how consciousness is generated. We just know we’re here, and we’re conscious. The brain sits in a dark box and never sees the light of day. Its idea of what’s going on is generated by the input from the sensory data. So the five senses (smell, touch, vision, hearing, taste) and the brain act as buffers between us and reality. This means that we have never experienced the reality, only our of the real world. real perception Our brain offers a view of the world based on our underlying assumptions (mostly developed in the early years or during times of (IDENTITY) crises). I wrote a longer piece on the topic of reality , and Joscha explains this much better in the podcast. here You’re interacting with a game engine unconsciously created by you, for you. Everyone is. The Seven Stages Bach views this as a framework that allows you to understand how the mind works. The stages are: Reactive survival (Infant) Personal self (Young child) Social self (Adolescence) Rational Agency (Self-direction) Self-authoring (Full adulthood) Enlightenment Transcendence Stage 1 (Infancy) In infancy, there’s no concept of self yet. Instead, you have an attentional self that builds the view of the world and the initial model of self. It’s a bit like building a game engine in the brain to track sensory data and interpret that data. Stage 2 (Young child) Once you finish building the model of the world (stage 1), the self starts to come together. It arises as an agent for you to be able to interact with the world. We think of the outside world as an objective reality, but it’s a model of the world that has been generated by our mind. So, as young children, we begin interacting with the “outside” world based on the model of the world we developed in stage 1 (I guess it would make sense to say the model of the world that was installed for us). Stage 3 (Adolescence) After this personal self and stage two are online, many people form a social self. That allows you to experience yourself as part of the group. You begin forming your opinions by assimilating them from your group. is the underlying worry. What my environment thinks about x At this stage, you also begin building empathy. Empathy should not be mistaken with compassion (feeling sympathy for others’ joy and pain). Empathy is building a mental architecture similar to your group. Akin to a hive mind. It becomes difficult to resonate with the group if you are wired differently. That’s why people we refer to as ‘nerds’ or neurotypical people sometimes struggle in this stage. Their question is, do you stay a little bit autistic, or do you catch up? And you can catch up, but that usually happens later in life when you can consciously build empathy. Stage 4 (Rational Agent) You begin to understand that stuff is true and false regardless of what other people believe, and you have agency over your own beliefs. In this stage, you discover epistemology, the rules about determining what’s true and false, and can determine for yourself, as opposed to looking for the hive mind for answers, what’s true. Stage 5 (Self-Authoring) At this stage, you discover how identity is constructed. You realize that your values are not terminal, but they’re instrumental to achieving a world that you like and aesthetics that you prefer. The more you understand this, the more you get agency over how your identity is constructed, and you realize that identity and interpersonal interaction are a costume, and you have agency over that costume. It’s useful to be a costume because it tells something to others, and it allows you to interface in different roles (partner, daughter, employee, boss, friend etc.). This stage is also considered to be full adulthood because you begin understanding that other people form their identities depending on past experiences. You realize that everybody could be you in a different timeline if you have had the experiences they had. their Stage 6 (Enlightenment) At this stage, you can collapse the division between a personal self and the ‘generator’ (the mind) of the world. A lot of people get there via meditation or psychedelics or by accident (like Ekhard Tolle). You suddenly notice that you are not actually a person, but you are a vessel (consciousness) that can create a person, and the person is still there. You observe that personal self, but from the outside, and you notice it’s a representation. You might also notice that the world that is being created is a representation of you. This creates the experience of I am the universe. The thing that’s creating everything. It’s not like you’re creating quantum mechanics and the physical universe. What you’re creating is this game engine that is updating the world, and you’re creating your valence, your feelings, and all the people inside of that world, including the person that you identify with. Stage 7 (Transcendence) This stage is more or less hypothetical, says Bach. It’s a trans-humanist stage in which you understand how you work, in which the mind fully realizes how it’s implemented, and can also, in principle, enter different modes in which it could be implemented. According to Bach, this stage is not open to people yet, but this could change if/when we merge with AI. To Close Most people get stuck around stage 3. If the online world is to be judged as the representation of the real world, the collective is definitely stuck in stage 3, aren’t we? Liberal, republican, cryptoboi, woke, pro-Peterson, anti-abortion, etc. Social media encourages us to pick a side, and that further cements our identity, even in the real world. But identity is not everything. There are other stages past stage 3. P.S. You can listen to a (23 mins) I recorded on this topic with more commentary about each stage. podcast

 7 Stages of Identity Development, According to a Cognitive Scientist

The French commander Nicole, surnamed the “Pilgrim,”

After the launch of Meta’s latest application “Threads” (as the full name, “Threads, an Instagram App”) there are mixed reviews and ones of confusion like: “ Do we need another Twitter? ” Under the Microscope: Dissecting the Surge of Twitter Alternatives Having 206 million daily active users today, is no doubt a true powerhouse. With its many features, such as trending topics, hashtags, and real-time updates, the platform has become an invaluable tool for businesses, politicians, and celebrities to share their messages. And with its ability to connect people worldwide, Twitter will remain a key application of interest in the social media landscape. Twitter What makes Twitter so appealing? Unlike other platforms, Twitter prioritizes concise text-based communication over photo sharing. By removing the pressure of visual representation, Twitter encourages users to focus on the power of words, ideas, and shared experiences. This approach allows for more meaningful conversations and connections through language. Also the 280-character limit, initially set at 140 characters, challenges users to express their thoughts briefly, resulting in sharper, more impactful communication. By embracing conciseness, Twitter promotes unique writing styles and the creative use of language, inspiring engaging interactions. Twitter has emerged as an influential platform for news and information dissemination. Its real-time updates and vast user base make it a primary source for breaking news, trending topics, and discussions. Users, including journalists, organizations, and public figures, actively share and discuss news, events, and social issues. Hashtags and trending topics enable users to explore specific subjects, staying informed about current events and societal movements. Why do investors keep investing in Twitter-like apps? Investors and entrepreneurs are often drawn to the idea of replicating the success of Twitter due to several compelling reasons. They may perceive the potential to achieve significant financial gains and influence online communication. Twitter's success, as evidenced by its large user base and cultural impact, has demonstrated the viability of a platform centered around concise, real-time communication. By emulating its core features and functionalities, investors and entrepreneurs aim to attract a similar user base and cultivate an engaged community. Financial gains are a primary motivation. Twitter's market capitalization and revenue streams indicate the immense value of a successful social media platform. Replicating Twitter's model, or even capturing a fraction of its success, presents a significant potential for generating revenue through advertising, data monetization, and other business models. Additionally, investors and entrepreneurs recognize the power of influence and the ability to shape online conversations. Twitter has become a major platform for public figures, organizations, and thought leaders to share their perspectives and engage with a wide audience. Replicating Twitter allows investors and entrepreneurs to position themselves at the forefront of digital communication. This enables them to shape narratives, promote their brands or products, and influence public discourse. Visual credit : Beeple; PULLING ZUCK'S THREADS How many “Twitter-like” apps are there? 1. Threads Threads is the latest Twitter clone that has hit the markets. However, it has an advantage over other Twitter alternatives- it is owned by the social media giant Meta. With quite a minimalist interface, Threads allows you to post text updates with a limit of up to 500 characters and post photos and videos up to 5 minutes long. The new social media app is tied in with Instagram. Threads fetch usernames and other user info from Instagram. Like Twitter, Threads also has a feed that contains posts from those you follow and recommendations. You can keep your profile public or private and choose restrictions for who can reply to your Threads. However, the Twitter alternative has a glaring identity issue that gets in the way of making a name for itself. If it tries to be too much like Twitter, possibly judged as a carbon copy that isn't offering anything new. If it tries to be too different from Twitter, you're not getting a full Twitter alternative. In either case, any Twitter alternative is starting on the back foot in terms of how users and other companies perceive it. Very few people will want to be on a "less popular Twitter," and even fewer companies would. 2. BlueSky BlueSky is one of the most popular Twitter alternatives that has made headlines for the past few months. Despite being in the beta stage as of writing, the platform has gained over 100,000 users and has been downloaded more than 375,000 times. It is a decentralized social network conceptualized by former Twitter CEO Jack Dorsey. With a Twitter-like user interface, BlueSky is built on AT Protocol, which is a federated protocol. It borrows a few features from Twitter, including its feed, posts, likes, block lists, a mute option, and more. All posts likes, and blocks are public on BlueSky as the platform aims to make social interactions available across platforms for everyone. Currently, it is impossible to access BlueSky unless you have an invite code. Alternatively, you can join the waitlist and wait for your turn. 3. Mastodon Unlike many of the other Twitter alternatives, was launched way back in 2016 and rose to popularity in 2022. For easy understanding, Mastodon is not a social media website. In fact, it is a decentralized, open-source platform that allows you to create and run your websites known as Instances. Mastodon What makes Mastodon favorable for users is several Twitter-like features: tweets (referred to as toots on Mastodon), replies, bookmarks, hashtags, retweets, and more. Users can make posts up to 500 characters, respond to threads, and share blogs from your selected communities. With more than 1.5 million active users and apps available for iOS and Android, Mastodon is a more based alternative for Twitter. 4. Spill Spill is another contender that can be rightly labeled as a Twitter alternative because it is created by none other than former Twitter employees. The social media app looks like Twitter but has many more references to “Tea”. For example, when a user publishes a post, the app says, “It’s brewing your tea,” instead of recommended content feed, it has a “spill board,” and the posts are called spills. This Twitter alternative focuses more on photos, videos, and GIFs than text-based posts. However, Spill is still in beta, and you will need an invite to join Spill. Alternatively, you can join the Spill waitlist and wait for your turn. 5. T2 Former Google and Twitter employees develop T2 and aim to reimagine the social media landscape as a “source for up-to-date, short-form information, and friendly conversations.” As it is today, the app looks like a stripped-down Twitter with a much-simplified interface. You must join a waitlist to start using T2; little is known about the platform's features yet. But, it could become a great Twitter alternative once it rolls out for everyone. Is this going to be the end of Twitter, as we know it? It is important to note that replicating Twitter's success is difficult. Twitter's longevity, dominance in the market, established user base and brand recognition pose significant challenges for newcomers. Building a successful social media platform requires a deep understanding of user needs, effective marketing strategies, robust infrastructure, and a commitment to maintaining a vibrant and engaged user community. , investors and entrepreneurs are attracted to replicating Twitter due to the potential for financial gains, the ability to shape online conversations, and the opportunity to innovate and improve existing social media models. They should also acknowledge the challenges while aiming for similar success as Twitter. They must bring more unique value propositions to compete in this dynamic social media landscape. In conclusion Lead image credit - Beeple: PULLING ZUCK'S THREADS

Why There Are So Many Twitter Alternatives

Technology is an essential part of life today. We use multiple, sometimes dozens, of gadgets daily, some for work and others for personal enjoyment, and new models for both are coming out seemingly every day. As more keep coming, it may leave you with the question: has the tech market become oversaturated? There are in the U.S. alone. Companies like these account for more than a third of the world’s overall market. With so many companies pushing out so many devices, is there any room left for innovation? Is it possible to really do anything new anymore in the industry? Here’s a closer look. more than 585,000 tech businesses What Does It Mean to Be Oversaturated? You can define oversaturation in a few different ways. One is to look at the market in terms of jobs. If there are more workers than available jobs, it’s safe to say that the tech industry is indeed oversaturated. Despite large, sweeping layoffs from some of the nation’s largest tech companies, technology job creation still outpaces people filling those roles. Available jobs in the industry and have increased every month for the past two years. In light of these trends, you can’t safely say the job market is saturated, at least on an overall scale. grew by 207,000 in 2022 Another way to define oversaturation is to see if there’s any room left for new businesses to carve out a segment of the market. That’s trickier to quantify. If you look at the startup failure rate, the picture is mixed. Information businesses, which many tech companies fall under, have within their first year, placing them above average and the third-highest industry for failure. Technical services, by contrast, fall comfortably below the average. a 20.8% failure rate A more helpful way to look at oversaturation in tech is to consider the rate of innovation. Many new products emerge each year, but do these represent any significant steps forward? Are new industry players coming out with game-changing innovations, or is everything consolidated in tech’s Big Five? The answers will offer a more practical look at the market for both businesses and consumers. Gaining Perspective From the Past When you take this definition of oversaturation, the picture may look bleak at first. If you compare the newest iPhone or TV to one a few generations ago, you’ll find some improvements but wouldn’t call the older one outdated by any stretch. However, looking at the pace of innovation in the past provides some needed context. New tech generations came out far more slowly in the past, but even then, not every new model represented a great leap forward. Consider how the World Wide Web , but the first website didn’t appear until two years later. came out in 1989 On a historical scale, the tech sector is just as, if not more, innovative than ever. Industry-changing technologies don’t emerge frequently, nor have they ever, and when they do, it often takes time to see how game-changing they are. Think of how artificial intelligence (AI) has been around for years but only recently started to disrupt things. An Oversaturation of Gadgets With Room for Innovation Of course, slow innovation in the past didn’t come with quite so many new releases, either. Big, overall steps forward may be keeping the same pace or going a little quicker, but companies are pushing out new devices faster than ever. That can make innovation feel slower. When you consider both these sides, you could say there’s an oversaturation of gadgets but not of technological innovation itself. There is still plenty of room for new, exciting technologies and upgrades, and these are still coming out. However, most releases hitting the market today don’t represent this innovation. Where Does the Market Go From Here? In light of this saturation, tech companies can look to areas that haven’t felt its full effects yet. While there’s an oversaturation of devices, many rural areas or other nations don’t have the internet accessibility or similar infrastructure to take advantage of these gadgets. Tech companies can use business mapping software , finding where there’s still room to grow. to highlight the most promising markets Smaller firms and startups can focus on the areas where devices are currently limited. Virtual reality (VR) is one of the most promising. The technology has only recently started catching on, and experts predict will use VR headsets monthly by the end of the year. Focusing on more niche AI and IoT applications may help, too. roughly 65.9 million people Consumers can react to this saturation by being patient. Consider that each new phone generation may not be a significant improvement over the other. By waiting and using your purchasing power to pay mostly for the biggest leaps forward in technology, you can encourage an emphasis on innovation over constant sales. Tech Is Oversaturated in Some Areas but Not Everywhere Overall, the tech market today is oversaturated in terms of the number of devices it puts out without substantial improvements. However, that doesn’t mean there isn’t room to grow. There is still plenty of innovation happening if you know where to look. If companies and consumers can hone in on these areas and move away from the rapid release cycle, the tech industry can feel fresh and innovative again.

Is the Tech Market Oversaturated?

In 2009, Bitcoin was launched making it the first-ever peer-to-peer digital money; the first financial application built on blockchain technology. One could argue that started with BTC in 2009. DeFi (Decentralized Finance) is a growing ecosystem of actual, working protocols and applications, which are delivering value to several thousands of users, and transacting the equivalent of hundreds of millions of dollars in digital assets, every day. DeFi The very foundations of a new global financial system are being laid with applications that enable everything from making simple money transfers and payments to lending, borrowing, trading, portfolio management, and even insurance contracts. With decentralized finance on the blockchain, you can do anything that you are currently doing with your traditional finance system, without giving a commission or the requirement to go through middlemen or brokers. But DeFi lacks one important feature which is often overlooked. Sounds exciting, doesn’t it? PRIVACY! But wait….. Why is privacy important? is necessary for ensuring freedom on the internet. When your transactions are being watched — or when your transaction history is available to be known — a person isn't totally free to make their own decisions. Privacy your account number or receiving address, one can check your entire history of transactions and even what crypto assets you hold. Just by knowing To save you from this tragedy, FinFarm brings you a detailed comparison between top privacy-focused cryptocurrencies. Bytecoin (BCN) Launched back in 2012, described itself as a private, decentralized cryptocurrency with an open-source code and was the first cryptocurrency designed to protect user privacy. It is a cryptocurrency that works on the blockchain operated by a multitude of nodes around the world and uses Ring signatures, which have since also been incorporated into other similar coins (see below), to mix different outputs of similar value into one transaction, making it almost impossible to deduce where the money came from. On the Bytecoin blockchain, all addresses are obscured. Bytecoin (BCN) Bytecoin allows users to generate numerous unlinkable one-time addresses from a single set of keys. This makes it nearly impossible to establish a connection between transactions or addresses. Bytecoin does not support smart contracts, and the high risk of user privacy being attacked is still prevalent, even though it adopts a decentralized mixed currency technology. Dash (DASH) Dash, whose name is derived from the term " was in January 2014 as a fork of Litecoin (LTC). Dash utilizes a centralized currency mixing scheme where users simply transfer sums of money to multiple addresses several times; to mix and obfuscate transactional history. digital cash," launched The centralized currency mixing scheme has high applicability in various cryptocurrency systems; however, the existing solution requires the sender and receiver to mix coins online. If the sender and receiver can't reach an agreement on the amount of mixed currency, the transaction must be postponed. There is a common delay problem with Dash and the currency mixer is centrally deployed. Dash does not support smart contracts, and the third-party mixed-currency provider mechanism relies on the credibility of the third party, which encounters unpredictable risks. In recent years, Dash's development has focused on attempting to make Dash a payment tool with strong circulation value instead of the emphasis on privacy protection. Verge (XVG) Verge was first in October 2014 as ‘ ’, a fork of (PPC). In February 2016, it was Verge in order to for easier mass-market adoption and to distinguish itself from (DOGE), with which it has no direct connection. Verge Currency uses the Proof of Work (POW) mining principle. It is also one of a few cryptocurrencies to have multi-algorithm support. Verge has 5 different hash functions: Scrypt, X17, Lyra2rev2, myr-groestl, and blake2s. Such design is intended to allow for more equal access to the mining ecosystem. launched DogeCoinDark Peercoin renamed rebrand Dogecoin Verge’s Dual-Key Stealth Addressing allows senders to create an unlimited number of one-time destination addresses on behalf of the recipient without any interaction between the parties. Stealth addresses are a method by which additional obfuscation can be implemented to further protect the receiving party when transacting with Verge. When multiple users send funds to a stealth address, rather than these transactions appearing on the blockchain as multiple payments to the same address, they instead appear as multiple payments going to different addresses. Smart Contracts on Verge are under development. Monero (XMR) Monero was launched in April 2014 and features the “proof of work” (POW) consensus mechanism to enable the creation or minting of the XMR asset. Proof of work is often also called ‘mining’ and Monero’s mining algorithm; , is an AES intensive and memory-consuming operation; which is designed to encourage mining with the central processing unit (CPU) of a computer. RandomX Monero uses the Ring Confidential Transactions algorithm for its privacy encryption method. The method mixes the signer's public key with another public key set and then signs the message, making it impossible for intruders to distinguish which public key corresponds to the actual signer; therefore, protecting the user's real identity. Monero's participating users do not need to communicate with other participating nodes, they can participate in mixed-currency by themselves, providing effective protection measures for commonly distributed denial-of-service (DDOS) attacks and information disclosure in the decentralized mixed-currency mechanism. mixed-currency Monero does not support smart contracts, and the high risk of a user’s privacy being attacked is still present, even though it adopts its decentralized mixed currency technology. Users need to rely on the public key of other users when using . If other users are malicious, the problem of users’ privacy disclosure may arise. There are a few cases that claim to trace transactions on the Monero network but we neither confirm nor contradict those claims. Ring Confidential Transactions technology Zcash (ZEC) was launched in October 2016 and was originally based on Bitcoin’s codebase. It is a cryptocurrency that uses encryption technology to provide users with optional privacy protection. Originally named , using the ZeroCash protocol in November 2013, this was forked into Zcash cryptocurrency in 2016 with the specific purpose to add a development fund that is taken from block rewards. Zcash ZeroCoin Zcash payments are published on the blockchain and users can utilize optional privacy functions to hide the sender, receiver, and amount of transactions on the blockchain. Only those who have the key can see the contents of the transaction. The user has full control and can choose to provide the key to others to prove payment for auditing purposes. Zcash now uses a called to encrypt user information. Zk-SNARKs is an encryption method based on pure mathematical theory. The encryption method is self-contained, it has the advantage of not depending on an external operating environment; therefore, has a wider range of application scenarios. ZeroKnowledge Proof technology zk-SNARKs Since Zcash uses the same underlying architecture as Bitcoin's network, it can only support simple transactions, similar to the Bitcoin network with a pre-set privacy protection mechanism. Beam (BEAM) Beam is a scalable, privacy-oriented cryptocurrency based on the elegant breakthroughs of the , which completely conceals the values and metadata of transactions in a printable way, which also reduces bloating on the blockchain. In addition to enhanced privacy and fungibility, this allows for much greater scalability. - Beam takes up far less disk space than other privacy-oriented cryptocurrencies. mimblewimble protocol In layman’s terms The cryptographic protocols used in Beam require no trusted setup and Beam uses the BeamHashIII Proof-of-Work algorithm; a memory-hard mathematical challenge that is designed to encourage GPU miners. Like Bitcoin, scarcity is ensured by periodic halving. Complex transactions are possible, such as escrows, time-locked transactions, atomic swaps, and much more. Beam has further evolved from the mimblewimble protocol to solidify best-in-class privacy-preserving mechanisms with dandelion++ and lelantus-MW. Beam supports in-wallet decentralized applications (DAPPS) and smart contract deployment, which are named ‘Shaders’. Anyone can create their on Beam, and even mint My Hackernoon profile image is an NFT that I bought on Beam and by this NFT you can own privacy tokens Confidential NFT’s. neither track my assets nor other NFTs in my portfolio. And one of the most of Beam is that you do not have to pay gas fees on failed transactions! YES, No gas fees for failed transactions. underrated features Recently, an NFT public sale on Ethereum went horribly wrong and users accumulated more than $145million in failed transaction fees. This would never happen on Beam as failed transactions do not incur gas fees. Here is a Detailed Comparision for you: Parameters ByteCoin Dash Zcash Monero Verge Beam Algorithm Cryptonight X11 Equihash RandomX Scrypt, X17, Lyra2rev2, MYR groestl, and Blake2S Beam Hash III Scalability Better in terms of Blockchain size May implement PoS to improve scalability Blockchain is heavier than Bitcoin Worst Scalability in terms of blockchain size Better than other privacy coins Excellent scalability, lighter than Bitcoin Auditability Can be done but with restrictions Can be done but with restrictions Can be done but with restrictions Not useful Can be done Can be done and optional for a user Smart Contracts Support No No No No Under Development Yes Dapps No No No No Upcoming Yes Gas Fees for failed transactions Yes Yes Yes Yes Yes No DeFi Ecosystem (DEX, Lending & Borrowing ,etc) No No No No Upcoming Upcoming Create your own privacy tokens No No No No Upcoming Yes NFTs No No No No No Yes

Choosing The Best Privacy Focused Crypto!

“Digital twin is a digital representation of a physical entity that helps in tracking and modifying the activities of the object real-time”. Concept of Digital Twin “Digital Twin is a virtual representation of a physical object, used to understand and predict the activity of its physical counterpart. Digital Twin technology is used throughout a product’s life cycle to track, predict, and optimize the product and the system before investing in the assets.” The term digital twin was first coined by Dr.Michael Grieves in the year 2002. However, this concept was anticipated by David Gelernter in 1991 in his book, Mirror Worlds. Digital twin consists of three distinct parts: Physical Product Virtual Product The connection between the physical and virtual products Types of Digital Twin There are three types in which we can segregate digital twins - Digital Twin Prototype (DTP) DTP consists of the analysis, design, and process to perceive the physical product. Digital Twin Instance (DTI) DTI is the digital twin of an individual instance of a product after it is manufactured. Digital Twin Aggregate (DTA) DTA is the aggregation of DTIs whose data and information can be used for interrogation about the physical product, prognostics, and learning. Introduction Digital twin technology is a concept where the physical and virtual world meet, where every industrial product is bound to get a complete digital impression of itself. These connected digital entities generate data in real-time and help organizations predict their problems and fix them in advance. This concept helps the organization plan and design their products better. Digital twins play a major role in delivering products for better customer experience. The data is analyzed using connected sensors, combined with other sources of information to make the predictions. How Digital Twin technology helps the industry: Digital Twin technology is a live model that is utilized to drive business results, and can be executed by manufacturing industries for numerous reasons: Visualizing products in use, by real users, in real-time Building a digital thread, connecting different systems, and promoting trace-ability Clarifying assumptions with predictive analytics Troubleshooting distant equipment Managing complexities and linkage within systems of systems. The idiosyncrasy of Digital Twin Connectivity The significant trait of Digital Twin is its connectivity. The digital twin associates the physical item and its virtual partner. The idea of IoT makes connectivity conceivable. The connectivity in digital twins is made by sensors on the physical items that get the information, coordinate and convey through different advances. This trademark enables the association to remain associated with the products and its clients. Homogenization The digital twin is an advanced innovation that goes about as both the circumstances and logical results of the homogenization of information. Because of the way that any kind of data or substance can be put away and transmitted in the equivalent computerized structure, it very well may be utilized to make a virtual portrayal of the item, accordingly decoupling the data from its physical structure. In this manner, the homogenization of information and the decoupling of the data from its physical antiquity, have permitted digital twins to appear. In any case, digital twins likewise empower progressively more data on physical items to be put away carefully and become decoupled from the item itself. As information is progressively digitized, it tends to be transmitted, put away and figured in quick and minimal effort ways. As indicated by Moore's law, registering force will keep on expanding exponentially over the coming years, while the expense of figuring diminishes altogether. This would, along these lines, lead to bring down minimal expenses of creating computerized twins and make it similarly a lot less expensive to test, foresee, and take care of issues on virtual portrayals as opposed to testing on physical models and trusting that physical items will break before mediating. Digital twin innovation permits itemized data about a physical article to be imparted to a bigger number of specialists, unconstrained by physical area or time. In his white paper on advanced twin innovation in the assembling business, Michael Grieves noticed the accompanying about the results of homogenization empowered by digital twins Re-programmable Digital twin innovation permits physical items to be re-programmable. Digital twins can be utilized to gather information about the presentation of the motor and if necessary modify the motor, making a more current form of the item. Additionally, servitization can be viewed as a result of the re-programmable nature too. Producers can be responsible for tracking the digital twin, making alterations, or reinventing the digital twin when required and they can offer this as an additional help. Digital Traces Another characteristic of digital twin technology is that it leaves digital traces. These traces can be used by engineers to improve their designs so that these same malfunctions will occur less often in the future. For example, when a machine malfunctions to go back and check the traces of the digital twin, to diagnose where the problem occurred. These diagnoses can in the future also be used by the manufacturer of these machines. Modularity In the perception of the manufacturing industry, modularity can be depicted as the structure and customization of items and create modules. By adding particularity to the manufacturing industry, makers gain the capacity to change models and machines. digital twin innovation empowers producers to follow the machines that are utilized and notice potential territories of progress in the machines. At the point when these machines are made particular, by utilizing digital twin innovation, producers can see which segments cause the machine to perform ineffectively and supplant these with better fitting segments to improve the manufacturing procedure. Gartner has estimated that the use of digital twins will triple by 2022, so where is the technology best suited in manufacturing? Companies use Digital Twin technology to improve ongoing operations, train employees and to test new products or procedures before launching them to the real world where it becomes more expensive and complicated to fix any issues. Applications of Digital Twin Technology The digital twin technology proved to produce a virtual replica of physical products with 99.98% accuracy that is applicable across different fields which helps the organizations enhance their customer experience. The design phase is used for simulation and visualization of a product to verify the 3D design and to ensure if all the parts fit together. Simulations include mechanical, thermal and electrical as well as interrelationships between these aspects. Design: Using 3 Dimension visualization at the system level the constraints such as spatial footprint and physical connection can be verified. The systems connect to the digital twin of the other component for simulation, data transfer, and other control functionalities. System Integration: In 3 Dimension visualization, digital twin helps in troubleshooting. Virtual reality glasses can furnish field specialists with an overlay over the genuine gear to envision parameters Diagnostics: The condition of the equipment can be tracked using the past and present data with predictive algorithms to provide insights about the equipment. This helps the organization plan its maintenance. Prediction: In the event that all the propelled administration parameters (IoT network, investigation calculations, and so on) are preconfigured in the advanced twin, they can be empowered when the hardware is introduced and the client buys into these administrations. In the ideal case, no further building is required. Advanced services: A Digital twin backings and expels vulnerability during structure and setup while supporting applications and guaranteeing accessibility and unwavering quality through condition observing and propelled administrations. The Digital twin technology was first adopted by NASA to monitor the activities of the machines in outer space as it is impossible to be physically present. It proved vital during the failure of the Apollo 13 mission. 7 classic applications of Digital Twin Technology ( Source: Forbes ) Forbes has classified 7 different field examples where the digital twin technology is up and running successfully: NASA used pairing technology, the precursor to digital twin technology, from the earliest days of space exploration to solve the issue of operating, maintaining and repairing systems when you aren’t near them physically. At the Spring Festival Gala aired on China Central Television, the four human hosts were joined by an AI copy of themselves—their very own digital twin created by ObEN. Digital twin technology has even been deployed to refine Formula 1 car racing. There is even a digital twin of Singapore! Imagine all the variables that go into the management of a city. Chevron expects to save millions of dollars in maintenance costs from the digital twin technology they will have deployed on equipment by 2024 in oil fields and refineries. Similar to the benefits of manufacturing, digital twins can revolutionize healthcare operations as well as patient care. A digital twin of a patient or organs allows surgeons and health professionals to practice procedures in a simulated environment rather than on a real patient. Digital twin technology can help personnel get comfortable with the Internet of Things implementation and automation because they have the opportunity to simulate the application prior to it going live. Benefits of Digital Twin Technology By being able to control any system of systems from a distance through sensors, real-time, digital twin technology holds a variety of benefits throughout the life of a product. —The digital twin helps the organization to identify the issue in the system before it occurs helping reduce the downtime. Downtime reduction —Identifying faults that develop in the system and get insights into what parts might need repair or replacement. Inventory management —Managing similar products produced by the same manufacturer at different operating conditions such as temperature, pressure and other climatic conditions. Fleet management —Monitoring the whole fleet and simulating the future scenario. What if simulation —Making comparisons with the aim to increase the overall efficiency. Operations planning —Increases the reliability of the product by reducing the risk of failure and lowering the maintenance cost. Increased reliability —Customers can remotely configure the product and increase production. Improved customer experience Conclusion Digital twin technology provides accurate results and its real-time monitoring makes it possible to be used in different fields to improve productivity, customer experience and enhance the business of any industry. This technology enables the physical component to be accessed remotely ahead of any failure that would occur in the system reducing the chances of failure. By 2022 digital twin technology is expected to be implemented in almost all the fields to improve quality. We at TVS Next have broadened our horizons and have expanded our business into offering multiple new tech-based solutions, apps, and services - Digital Twins being one of them.

All You Need to Know About the Life-Changing Digital Twin Technology

Source: Freepik.com Having the right cloud migration strategy can be a significant differentiating factor between a successful migration vs. failure of investments. It includes identifying the needs of specific applications, and then defining how to move them to the cloud. When migrating your applications to the cloud, you need to ensure the integrity of the system across the three layers: the application itself, underlying database, and the host operating system. Based on complexity and requirements, you will need to make necessary changes to the application and/or the database. Alternatively, you may even opt to adopt an entirely new platform. So essentially, you will have several possible combinations to choose from. To summarize these possible combinations, in Dec 2010, Gartner pointed out that you may choose from to move your applications to the cloud: five key migration strategies Rehost Rehosting is a kind of “lift and shift” strategy, that means migrating the application as-is, along with its environment (Database and OS), onto a new infrastructure platform (Hardware Infrastructure as a Service or HIaaS). This may require changes to be made in the infrastructure level configurations, for which several automated and manual tools can be used. Since there are no major changes required in the application architecture, it is often considered as a faster way of migration. Organizations often use this method with small and standalone applications. Refactor The application is re-architected using the cloud-native features. Developers may reuse the language, or use cloud-native features, frameworks, or containers (Platform-as-a-Service or PaaS). This is often expensive, but usually, it is chosen when you opt to address new business requirements by adding new features or want to enhance the scalability and performance of the application. Revise Revise, or re-platform is about modifications to the existing code, often done to uplift the legacy applications, as well as rehosting or refactoring the application to the cloud (HIaaS or PaaS). Examples may be moving monolithic Python-based application to Google App Engine or migrating the on-premise Oracle database to Amazon RDS. It may often require to break the business logic into smaller applications or modules. This “lift-thinker-and-shift” strategy is time-consuming and expensive as well. However, this reduces the overall management and operations costs (like licensing) moving forward. Rebuild You may completely rebuild the application on a PaaS infrastructure, by dropping the existing code and architecture. This provides opportunities to write applications by leveraging the native-cloud functionalities, or the other innovative features offered by the cloud service providers. For example, you can leverage the new technologies like DynamoDB and AWS Lambda to rebuild completely serverless applications, for which you need not manage the servers by yourself. But this leads to lock-in with the cloud vendor, as you will have minimal  options in case the cloud vendor chooses to change the pricing or the privacy policies. Replace You may also want to consider replacing an existing application and moving to a new cloud-based commercial solution. For example, dropping an in-house developed product and adopting a Software-as-a-Service (SaaS)-based solution may often seem to be the most viable option. This is often based on simple cost-based calculations, including licensing costs, operational costs, and cost for upgrades and maintenance. Key considerations Choosing the right for your organization requires a thorough analysis of the existing environment. Following the are essential factors you need to consider during planning for cloud migration: cloud migration strategy Identify and fill the skill gaps Many organizations have an established IT department, with excellent knowledge and know-how of their existing environment, but when it comes to cloud, those skills may often seem like a square peg in a round hole. Developing and running applications for the cloud requires a new set of fundamentals for performance optimization, scaling up (or rather scaling out), and managing security and compliance. For cloud environments, QA related methodologies are also completely revamped, with DevOps and DevOpsSec riding in the front seat. Your teams need to get past the initial learning curve to understand and adapt to the new world of design and operational principles. Source: Freepik.com Keep expenses under control The success or failure of cloud migration may have a direct impact on your Total Cost of Ownership (TCO) for cloud adoption. Besides the visible cost factors like processing power, data storage, additional tools, and security, you must also consider several additional factors. For instance, during the entire duration of migration, you will be paying for both your old infrastructure licenses, as well as the new one. Also, the productivity of the staff (IT as well as non-IT) is also impacted during the transition period (due to learning curves, system downtimes, etc.), and they might not perform their daily tasks efficiently. So if the transition period extends for a significant duration, overhead expenses may cancel out the entire value of the cloud. Analyze the security and performance risks Data hosted in the cloud is often considered at risk of exposure, leading to threats of data breaches, hijacking, or even data loss. With the cloud, you usually have limited options for customization (as compared to on-premise data). So you need to ensure that IT professionals and security auditors are involved in the decision making, and they are aware of all the possible security keyholes when selecting the cloud vendor and services. Besides the basic security layers (like data encryption, two-factor authentication, etc.), there must be deep scans of the chosen services to identify the kind of vulnerabilities and level of risk. While making a choice between open source software vs. commercial applications, all risks and rewards need to be considered. Monitor anything and everything about your cloud The monitoring of the cloud infrastructure can help in controlling resource utilization. According to a recent by Forbes, organizations may be wasting one-third of their cloud spending on unnecessary items, either due to redundancy of subscribed services or due to subscription of services which are not used optimally (sometimes not used at all). At the same time, you also need to monitor your cloud to ensure that all the public interfaces and network touchpoints are secured. Strict monitoring of all the apps, databases, and configurations is also required to avoid any non-compliance. survey Source: Freepik.com Best practices To summarize, here are some best practices that can help reduce the risks and improve efficiency during cloud migration: While choosing a cloud vendor, go with the one that optimally fits your budget, while meeting all the desired requirements. The optimal cloud platform and supporting services for your organization need not be the costliest one available in the market. Just make sure they offer or support the essential capabilities, like monitoring of resource usage, integration with third party security services, etc. Always go with a phased approach, and migrate the low-risk applications first (as a proof of concept) to test the waters before jumping in. Also, prioritize the important ones first, and the optional ones later. Start planning for security from the beginning, and include the DecSecOps in a loop right from the initial phases. Also, try to keep other employees in the loop, to avoid any shocks of a sudden overnight change. Learn from others’ mistakes. Explore not only good experiences but also the of cloud migration to know common points of failure. Mistakes also teach you a lot. failures When dealing with large-sized applications, try to go for a hybrid approach. Migrate some specific elements to the cloud, and keep the critical data and modules on-premise, to get better control and flexibility at the same time. Go with the old saying, “Hope for the best, but prepare for the worst”. Always have a backup plan. Expect that mistakes will happen, and have a plan B to keep moving with those mistakes.

Key Considerations for a Smart Cloud Migration Strategy

HackerNoon Reporter: Please tell us briefly about your background. I’ve had first-hand insight into how broken the global food supply chain is having left school and trained as a chef. After that, I spent close to a decade in the food and beverage industry - working in the Uk, Australia, Spain, and on cruise ships. What's your startup called? And in a sentence or two, what does it do? AGR1 (Agricultural Growing Revolutionised, farm to plate in 1 day) is a state of the art hydroponic farming company, that specialises in low land, natural light hydroponics, growing produce that’s Nakd of chemicals/pesticides then delivering to kitchens within hours of harvest, in reusable containers that are the same size as that which kitchens are already using making our brand ‘Nakd Produce’ the most sustainable and freshest there is in the market. What is the origin story? After years of being in F&B, a short time in finance in Moscow then Hong Kong, my son Henry Xander Harrison was born in 2014. That night when holding him, I realised I had to change who I was, my priorities, and what I did. A month later I was shown hydroponics, after a couple of years working for companies that claimed to be about making a better world, I realised that there aren’t any who I believe are doing it right. What do you love about your team, and why are you the ones to solve this problem? the diversity of experience, knowledge, and the commitment to making AGR1 and Nakd a success. If you weren’t building your startup, what would you be doing? Why talk about hypotheticals? At the moment, how do you measure success? What are your core metrics? Growing the best produce, having happy customers. What’s most exciting about your traction to date? We’re the first people to do hydroponics in Johor. Our produce is served daily to the royal family. Our customers love our produce and boxing system. What technologies are you currently most excited about, and most worried about? And why? Most excited about the development of the hydroponic and start ag industry. Most worried would have to be drone dogs…. Because Drone dogs!! Along with robot-controlled farms(we need jobs for people! Not robots. What drew you to get published on HackerNoon? What do you like most about our platform? We need to get attention for what we’re doing. You guys have a cool setup. What advice would you give to the 21-year-old version of yourself? I wouldn’t, I’ve lived, made mistakes, now I have a son and a mission. What is something surprising you've learned this year that your contemporaries would benefit from knowing? Not as many people genuinely care about food security as they should, especially the people in positions of power to make an impact now before it’s too late. Vote for AGR1 for Johor Bahru. Startup of the Year

Startup Interview: "Not as many people genuinely care about food security as they should"

Have you ever heard of “ ”? Dark Data It may sound like we are in movie, but it’s really a simple term. The Matrix Let’s say for example, that you work in a company. And one day you realized that there are a lot of data that can’t be used, analyzed, or even found because of certain reasons or circumstances. Well, all of that data is called “ ”. Dark Data Dark data is data that the organization is unaware of or unable to find or even fail to use. Well, I guess that wasn’t hard, right? What’s is that, despite the effort from companies on gathering data, it seems like most of the organizations still aren’t using data properly as soon as they get it. hard According to Splunk’s State of , a lot of organizations have a lot of dark data. The report was a joint effort between Splunk and TRUE Global Intelligence. The companies surveyed over 1,300 business managers and IT leaders. Dark Data Report Can you imagine that over 60% of companies believe that half of their data is dark?! Not only that, but a believe that over 75% of their data is dark. third of them 75%? That’s huge. I am wondering how we get all these are incredible and huge numbers. “Data is hard to work with because it’s growing at an alarming rate and is hard to structure and organize. So, it’s easy for organizations to feel helpless in this chaotic landscape,” (Tim Tully), chief technology officer at Splunk. I did some research and realized that there are high challenges which are faced by these organizations: 1. The huge data volume. 2. The lack of skills and resources. 3. Not having the right motivation from employees to gain more data skills. 4. Bad management & leadership. In the report, they mentioned that 69% of employees said that they want to continue doing what they’re already doing, regardless of the impact on the business or their own career. In simple words, all these employees will have a very hard time in structuring and organizing the data. Unless if they were working in a data-driven role. Personally, I believe that we live in a world with very huge and complicated data. And our world is getting more complex every single day. Different Regions, Different Attitudes About Dark Data There are huge differences between different countries and regions towards dark data. Whether they were opinions, actions, or even education. Let’s take for example. China Nowadays, you can see that people in China are so confident in their abilities about AI, even if their current adoption of AI isn’t that much higher than the global average. But they believe that they can handle their dark data in manageable and efficient ways more than the other countries or regions. Even for countries like , , and , respondents said positive answers about than respondents from other countries did. France Japan Germany 25 percent less Data is so valuable. I hope that companies will start to think about their . Dark data strategy Because by the end of the day, there's a huge power state of dark data and we must bring it into the light. Everyone should be part of the solution.

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