Check the carefully before using this in production. This is an experimental technology Browser compatibility table The are a handy way to know when a user is close to a device. These events make it possible to react to such a change, for example by shutting down the screen of a smartphone when the user is having a phone call with the device close to their ear. proximity events Obviously, the API requires the device to have a proximity sensor, which are mostly available only on mobile devices. Devices without such a sensor may support those events but will never fire them. Note: Proximity Events When the device proximity sensor detects a change between the device and an object, it notifies the browser of that change. When the browser gets such a notification, it fires a for any change, and a event in the case of a more rough change. DeviceProximityEvent UserProximityEvent This event can be captured at the object level by using the method (using the or event name) or by attaching an event handler to the or properties. window addEventListener deviceproximity userproximity window.ondeviceproximity window.onuserproximity Once captured, the event object gives access to different kinds of information: The event provides an exact match for the distance between the device and the object through its property. It also provides the closest and farthest distance the device is able to detect something through its and properties. DeviceProximityEvent value min max The event provides a rough approximation of the distance, expressed through a boolean. The property is if the object is close or if the object is far. UserProximityEvent UserProximityEvent.near true false Example .addEventListener( , { (event.near) { navigator.mozPower.screenEnabled = ;
  } { navigator.mozPower.screenEnabled = ;
  }
}); window 'userproximity' ( ) function event if // let's power off the screen false else // Otherwise, let's power on the screen true Specifications Browser compatibility DeviceProximityEvent UserProximityEvent See also DeviceProximityEvent UserProximityEvent deviceproximity userproximity Credits Source: https://developer.mozilla.org/en-US/docs/Web/API/Proximity_Events Published under licence Open CC Attribution ShareAlike 3.0

Mozilla

Read My Stories

Proximity Events Specification: How To Receive Events From Device Proximity Sensors

Surgically implanting a 3D-Touch Capacitive Trackpad in place of the original Analog Joystick. PREFACE It’s 2020 and in the pandemic boredom it’s to survive from creativity suppression. But… when you realize that you own a toolbox with a plenty of electronics inside, it’s not so hard to see the same old things lying on the desk, in a different way. It’s the case of my Nintendo Switch: I never had the occasion to disassemble the Joy-Con controller before. What a wonderful occasion to put hands on its inside and start a new journey. no easy job “Well, let me look at the internet if someone crazy like a horse had the insane idea to replace the good old Analog Joystick with a Capacitive Trackpad” — No results found. MacGyver approves. PHASE 0 I am used to start sketching ideas on a notepad and here is my first drawing about how I imagined the Joy-Con with a Capacitive Trackpad in place of the original Analog Joystick. The best among the “Pros” bullet-points is the NO-DRIFT statement. If you are here, probably you already know that some Joy-Con controllers suffer from . Think about that for a second: no Joystick = no drift. Joystick Drift PHASE 1 First of all, you’re not a real nerd if you aren’t fascinated by transparent acid green stuff. So… a couple of keystrokes on Bezos’s website have been typed in order to achieve a new dress for the Joy-Con. Dismounting the shells , the only difficult part here is actually gently handling a pair of tweezers if you have a big hand. isn’t complicated The Analog Joystick is not a complex entity — actually, it’s a 2-CH potentiometer plus a push-button — and it’s attached to the main board by a . I ordered a with the same specs in order to bring the signals out of the circuit. 5-positions FPC connector with 0.5mm pitch flat and flexible ribbon cable Then, I re-assembled the Joy-Con and tested it directly with the Switch in order to check that everything worked fine. Alright, I have to replace an analog potentiometer with a digital one. PHASE 2 To do things in cleaner and more peaceful way, I draw in the schematics for a couple of components, I and designed some break-out boards for them. KiCad imported their footprints I chose to test alongside with connectors for flat cables (one for the input, one for the output). I ordered them online spending few bucks. different kinds of digital potentiometers with different ranges of price and performance Analog Joystick Capacitive Trackpad Within a week, I received the package from . With a solder paste spread and a hot-air gun job, the break-out boards were ready. my favorite PCB dealer Now it’s time to perform some tests. PHASE 3 Inevitable to say that an , a breadboard and a bunch of jumper wires come in help in order to coordinate the ensemble. Arduino The whole testing setup involved: [0] 1 x Micro-controller [1] 2 x 12-bit, voltage output Digital-to-Analog Converter (connected via I2C) [2] 1 x 5-Positions 0.5mm Pitch FPC connector for the Analog Joystick [3] 1 x 5-Positions 0.5mm Pitch FPC flexible flat ribbon cable [4] 1 x 12-Positions 0.5 mm Pitch FPC connector the Capacitive Trackpad [5] 1 x 12-Positions 0.5mm Pitch FPC flexible flat ribbon cable [6] 1 x Digital 3D-Touch Capacitive Trackpad (connected via I2C) Among all the digital potentiometers I broke-out and tested, I chose . The first step was to check if all the components were correctly wired, alimented and responding. I flashed the standard example into the board and the result was a success. the one that suited most, costed less and that, inevitably, got the job done i2c_scanner With few lines of code it was possible to initialize both the and the on the I2C bus, then I focused on implementing an efficient strategy in order to explore how the digital potentiometers could emulate both the X and the Y axis of the original Analog Joystick. DACs Capacitive Trackpad Since the DACs have a resolution of 12 bits, they accept a value range that goes from 0 to 4095, so I passed it through a loop by steps of 10. On the Switch console side, I fired up the the utility from the main settings, in order to see if something was gonna happen. Control Stick Calibration The Capacitive Trackpad is an interesting piece of electronics hosted in a very small and versatile form factor. Surprisingly, it also offers an amazing resolution of 2048 x 1535 x 63 (X x Y x Z) — and yes it has 63 levels of pressure sensitivity (I’ll exploit this feature later in order to digitally emulate the Stick-Button press of the Analog Joystick). It’s implicit to say that the second step was to implement a decent mapping in order to match the resolution of the potentiometers. Fortunately, the Arduino comes in help with the method so it was quite immediate to achieve decent results in almost no-time. map About the method call instruction, since the corresponding pin on the Joy-Con side handles a simple close-circuit logic, I could emulate the button press via code. pushStick(); Cool. The final result of the first prototype looked to me very promising. PHASE 4 Alright. We have a plane here, now we’d let it fly. The following step I had in mind, was to create an embedded and more portable solution of the first prototype. I decided to switch from UNO to a PRO MINI with its smaller package and to build a circuit board that could host it alongside with all the connectors and the digital potentiometers. In order to keep the optimization level high, I found that I could substitute the two single-channel DACs with a of the same family, saving some space on the PCB. double-channel one I fired up my faithful KiCad, I drew the schematics and then placed all the components at their place in a quite obsessive-compulsive (dis)order. PHASE 5 Punctual as usual, the courier brought the green gold alongside with the other components. Same ritual. Solder party. Testing with the digital multimeter. PHASE 6 The PRO MINI needed to be alimented: I stole all the milliamps needed directly from the main board, siphoning them from an uncovered solder pad. The main idea was to stick the board directly to the Joy-Con’s back with a professional double-sided tape, make a hole in the plastic shell and then pass all the cables through it. PHASE 7 The Capacitive Trackpad came out naked from its original package, so I had to design and develop a 3D enclosure by myself. is very handy in this kind of situations: by adding and subtracting a couple of primitives shapes, the job is well done without complications. Tinkercad After a quick slicing with , a few minutes of waiting time later and the 3D printer gave birth to the new born. Cura Super. It suited in perfectly at the first shot. I must say that the filament used preserved the mechanical properties very well. Nice job . FILOALFA PHASE 8 Since the power implied in alimenting the PRO MINI relies directly on the Joy-Con’s battery, I decided to add a small switch in order to turn off the implant while not in use, avoiding extra drains. Safety first: I covered all the exposed electronics with a good piece of Kapton tape, in order to don’t short-circuit anything while your hand’s sweating. FINAL RESULT And here we go. That’s how it looks in the end. It’s still portable, so it is possible to use it attached or in wireless mode. Let’s see it in action. Enjoy the world’s first Nintendo Switch Joy-Con controller with a 3D Capacitive Trackpad. NEXT STEPS Doing things more seriously: in my plans there’s the idea to miniaturize the whole circuitry in order to create a smaller PCB that could suit directly inside the Joy-Con controller in place of the Analog Joystick small box that’s approximately 19 x 16 x 4 mm in size. As you can see, the job is already ongoing. I am aware that this could arouse interest in a small niche of fanatics, modders and gamers but its HARDWARE stuff, and it costs. This project implies a good amount of work that I’ll be happy to do with your support. If it’s something that market asks, I would be happy to co-finance the development of the first small batch that you could potentially buy on in the incoming future. Tindie This is explicitly a call to action. If you want to make this Joy-Con Touch Mod-Kit real, . donate Previously published at https://medium.com/@matteo.pisani.91/how-i-hacked-nintendo-joy-con-controller-8ac22d75b0b8

Alongside

BUNCH

JUMPER

Naked

Nintendo

Super

Hardware Upgrades At Home: Hacking Nintendo Joy-Con Controller 

Ask anyone in the crypto space about the major barriers to adoption and nine times out of 10, education comes up. Understanding this industry, its importance, and the potential it holds for all our lives is vital to growing the space. We need better education not just at a developer level through programming courses or Masters' degrees at universities, but for the general public, and at a grassroots level, as well. Education to Grow Our Numbers Many companies throughout the blockchain space have invested significant time and resources to onboarding people more easily, making their products more user-friendly, and trying to demystify aspects of the blockchain. Yet, it still isn't enough. The number of blockchain wallets is steadily on the rise to Statistica. Yet, it still resides at less than 50 million as per Q1, 2020. With a global population approaching 8 billion, it's pretty clear, there's still a very, very long way to go. according We hear a lot of news in the crypto media about how Bitcoin is saving Venezuela and that other countries with high or hyperinflation are continuously using cryptocurrencies as a store of value to shield their wealth. Having this option is a powerful thing. Yet, not being aware of this option is the reality for the resounding majority. Many people in developing countries have never even heard the word cryptocurrency let alone how it might be useful to them. In the developed world, there may be greater awareness especially when it comes to Bitcoin. According to , for example, over 90% of Britons have heard of Bitcoin, yet, understanding is significantly lower with ownership at less than 4% of the population. some surveys Crypto is still dealing with very small numbers largely because it is perceived as being too complicated or because it's still struggling to shake off its criminal association. Bitcoin and the Silk Road, child porn, ransomware hackers, crypto scams, money laundering… mainstream media never misses an opportunity to tarnish cryptos as being bad; despite the world's largest banks being among the of money laundering and price-fixing. greatest perpetrators Now Is the Time to Get the Message Across So, while educating about the space is growing modestly, global macro factors have now presented Crypto with an opportunity like never before. Worldwide unemployment caused by the lockdowns, a precarious economy, and a pandemic far from under control are all fueling the fire. Add to that the bewilderment of people trying to grasp at how governments have no money to fund a better health service one day--yet can print unprecedented amounts of it the next. They are also starting to wonder how the stock market can be positively ballooning in the middle of a pandemic when many don't have enough money to buy food and basic supplies. Where is all the stimulus money going? What will be left when the virus is over and the economy is in tatters? Inflation? Rising prices of basic goods? A devaluation of their currencies? Or an even greater divide between the 1% and everybody else? At a time when QE is on steroids and many people are still forced at home due to lockdowns or unemployment, now, more than ever, is the time for crypto to stand up and do a better job. This is probably the first time in history we've had such a captive audience willing to listen about the benefits of cryptocurrency, cutting through the hype. Cryptocurrency Companies Taking the Lead We're already starting to see the winds of change blowing in as major macro investors like Paul Tudor Jones publicly back Bitcoin in their portfolios. But then we have Goldman Sachs telling investors to stay away from Bitcoin, and the messaging is still mixed. In this confusing panorama, some of the best examples I have seen recently of furthering education in this space have come from the following sources: David Johnston, Yeoman's Capital At a panel for the first Blockdown online conference in April this year, I had the pleasure of speaking with participants about DeFi for the 21st century. One of the panelists that impressed me the most was David Johnston, Ceo of Yeoman's Capital and Chairman of the Board at Factom. Despite having been immersed in the space since the very early days and leaving the fiat system entirely in 2012, he's a no-nonsense speaker who understands the need to onboard the next wave to crypto. When discussing DeFi and how to reach more and more people, he explained that he was hosting a series of 100 days of Crypto to educate people "sitting around at home during lockdown". His aim is not just to reach out to those in developing countries or in financial strife but for those investors who simply don't want to leave their money in a bank with a negative yield. “People are getting a great rate of return on their assets at 7-10% percent in DeFi… In the current environment, that’s extremely attractive. So I expect to see more and more billions coming into the DeFi platforms.” You can check out his . series here OKEx Beacon Program Another interesting initiative that I have come across recently is being led by OKEx. Rather than a series of videos or articles about crypto, this global exchange is taking a different approach. The company is selecting people to participate in a hands-on series of Masterclasses along with a month-long mentorship program. This kick-off series, according to the exchange, is aimed especially at the European region, being among the hardest-hit areas, and will give participants access to industry professionals and one-on-one mentoring with OKEx chief executives. This program may not be about onboarding the masses, but it could be a way to for promising participants to kick start their careers working for a large exchange in an industry that's shown good resilience to the pandemic so far. You can find out more about the . Beacon Program here SIMBA Chain Training for New Developers is taking a strong initiative for people affected by COVID-19 lockdowns as well. The blockchain company has created a new training website for new developers or developer-curious to learn to build their own dApp using the company's "freemium low-code blockchain platform." SIMBA Chain Joel Neidig, CEO and co-founder of SIMBA Chain, commented: "America's economy has been broadsided by the COVID-19 pandemic, with a quarter of our workforce sitting on the sidelines wondering what their next move should be. It's not just service industry workers who are without work; freelance developers and consultants have also been displaced. Once we get through this temporary economic lockdown, the demand for skills in technology like blockchain will be greater than before. So we're making training available to all." Your skill level doesn't matter as long as you have an interest in learning and courses start with building your first dApp up to coding an Ethereum smart contract. Online Conferences As mass gatherings (and certainly international ones) have been canceled around the world, the cryptocurrency conference industry has had no choice to move online. To be fair, online events may not be the same nor give you the chance to network and kickstart new opportunities in your life. But, as with all areas ,the conference industry has had to adapt. And in its pivot, many great benefits have come. By making them free for people to attend, they are accessible to anyone, not just companies with deep coffers, investors or media, but to anyone interested in hearing about this space. From the which takes place online this week to the epic making a second appearance later this month, and even Consensus, the industry's largest (and most expensive event); the decision to open up the doors to all deserves some applause. AIBC Manila Blockchain Summit Blockdown As the frustration rises with traditional finance, the necessary aid fails to arrive, and people are staying at home, now, more than ever is blockchain's time to thrive. I hope that initiatives like these will begin to spread throughout the space and that the conversation will start to shift from "what is Bitcoin?" to "Have you bought Bitcoin yet?"

Chain

Dapp

Education Has Never Been More Important in the Blockchain Space

Since Wikipedia was founded in 2001, people worldwide rely on the online encyclopedia to expand their horizons and read information on just about anything. As true as that is today, however, the site’s traffic trends tell a very different story. Over the years, its traffic has been decreasing, a pattern that swiftly accelerated in 2019. We'll look into how, and why, Wikipedia is experiencing such a decline. The Numbers Behind the Traffic Loss: Wikipedia Desktop Traffic Explored Over the past 24 months, Wikipedia has lost billions of monthly organic visitors to . What are zero-click results? It's when a user searched in Google, and found a direct answer to his or her search (often at the top of the first search results page) without needing to visit any actual site. zero-click results When looking at its desktop traffic alone we see that in January 2019, the site won 2.2 billion visits, a number that dropped dramatically to 1.9 billion by January 2020 (a decrease of -14%). While the site still has billions of monthly visitors, those visits are becoming increasingly more difficult to win as evidenced by the decline. While zero-click search results are primarily responsible for this trend, they aren’t completely to blame for the site’s traffic drop. YouTube videos rank at the top of Google’s knowledge graph, and are often also among the top organic search results, making it Wikipedia’s fiercest competitor. The Zero-Click Effect Google introduced and in 2015, which is when the decline in was first noticed. This change took away any need to click on a specific link to see the desired results; therefore, . Knowledge Graphs Direct Answers organic traffic to Wikipedia search queries began ending with “zero-click” results While this has been very convenient for searchers, as traffic to Wikipedia shows, it has been less than ideal for businesses. Out of nearly 890,000 monthly searches worldwide, only 30,000 actually become search visits to a website. Here's a quick look at a basic search of the weather forecast in Los Angeles. After Googling "weather in Los Angeles", the data above was provided by weather.com. However, it's obvious that any searcher is able to get the answer to the question without clicking through to the actual site. The impact on traffic is staggering – only 15% of weather in Los Angeles searches actually result in a click and a consequent visit to weather.com. This means that 85% of people see this weather forecast display at the top of the page, and never follow through to click on any search results. Freddie Mercury: Wikipedia’s Best Keyword Analyzed “I won’t be a rockstar. I will be a legend.” To better understand this declining trend, let's look at Wikipedia’s top 20 organic keywords. Wikipedia’s most valuable search keywords are for celebrities, movies, and TV series. The natural next step is to dive into its top-performing keyword, "Freddie Mercury", to see what traffic patterns show. Although Freddie Mercury died in 1991, long before Wikipedia was founded, his name has become the site’s top-performing keyword in 2020. A quick Google query of his name pulls up a plethora of information about him, including his Wiki page, YouTube videos, and loads of news articles. But, 71% of those searches end there, without a click to a specific site. Looking at the organic mobile traffic for the search reveals zero-click results have cost Wikipedia’s English language subdomain tens of millions of organic visits. This whopping decline has been more apparent on mobile devices when Google shows an answer. This is because on mobile the search results don't often show any other results, whereas on desktop, other results are displayed below. So, Where Has Wikipedia’s Traffic Gone? In Google was able to steal over 550 million clicks from Wikipedia in six months, and here we are five years later watching that trend accelerate at breakneck speed. 2015, While many factors are contributing to that decrease, the vast majority of Wikipedia’s traffic has been lost to Google’s zero click results, emphasizing just how much power Google has over search traffic.

Google

YouTube

Digital Data for a Digital World

How Wikipedia Lost 3 Billion Organic Search Visits To Google in 2019

Public Policy is quite an obscure profession. It hides in plain sight. Most people don’t realize that there’s a piece of sophisticated machinery that constantly shapes the world they live in — a system under but also beyond politics. So let’s define it first. Public policy is any state-initiated and state-executed intervention to get a certain outcome. This outcome could be a lot of things — increase in literacy, reduced corruption, increase in exports, people using products made within the country, and so on. All of them, in theory, have the long term good of the citizens as an ever-present overarch. Policy is an application of Economics. It’s about changing few variables in a system to get a certain outcome. But most of the times, such a single voluntary change causes a hundred unwanted changes in effect. That definitely sounds like software engineering. Both policymakers and software engineers deal with systems that tend to do more than what’s asked. Unintended consequences tie these fields together. But policy is more complicated than software engineering, because it has to work on human beings. Programming a computer whose whole purpose is to obey you and do what’s asked is hard enough. Imagine programming thousands of computers at once, but this time the computers don’t even listen to you, they think they know what they need and are least bothered by your instructions. Software engineers work with deterministic systems but policy professionals do not and that makes their job much more challenging. (Assuming free will, and that humans aren’t systems which are extremely complex, but deterministic nonetheless.) This essay is an attempt to look at processes and tricks public policy professionals employ to deal with such challenges and see if we, software engineers, could borrow them. Public policy is governed by powerful forces of politics and public perception. So it’s likely that a policy implementation is dictated less by what right and more by what right. So, the processes we’ll look at will be more of how things work and less of how they work. The book ‘ ’, authored by Vijay Kelkar and Ajay Shah, veterans of public policy, has been a major reference for this piece. Let’s begin. is looks should do In Service of the Republic - The Art and Science of Economic Policy Play the long game Economic reforms take time. Even a small economic reform takes sustained time and effort. Its effects roll out in phases and need to be constantly monitored. Something that seems to be working out in the short-term could backfire in the long-term. A policy that’s not beneficial in the long-term is a failure. As Kelkar and Shah put it, “it’s a test match, not IPL.” In software engineering, when you get your code working, it’s tempting to consider the work done and move on. But it’s important to understand that the code doing what it was supposed to do, is not a sufficient condition for completion, it is only a short-term result. The long-term results, in this context, would take in to account how the code responds to modifications, is it understandable, extendable and maintainable. When you think of getting long-term results, you will think of including the so-called boring things in your day-to-day work: structuring the code well, leaving useful comments and writing documentation. As it is for the policy professionals, so it is for software engineers — a short term solution is no solution. Do the boring things. Test your solutions Policymaking isn’t considered a hard science mainly because of the difficulty in reproducing results. Due to the large number of variables in human societies, what works in a certain locality won’t work in its neighborhood. So, no matter how good a policy sounds in theory, it needs to be tested. Policy people do this with Randomized Control Trials (RCT). In these trials, policy is implemented on a small group of people, the impact is measured and compared with another group on which the policy was not implemented. This helps in determining the effectiveness of an intervention. These tests are necessary because it’s impossible to accurately predict how a policy might turn out. The 2019 Nobel Prize in Economics awarded to Abhijit Banerjee and team was considered to be a validation of the use of RCTs in policy. In the software context, such trials become a key process in assessing UX. What we, as engineers of the user experience consider optimal, might be far from the truth. Evidence is better than intuition, do A/B testing, let your users tell you what they prefer. To quote Edward Deming, “In God we trust, all others must bring data”. Treat the disease, not the symptom This again is a manifestation of the complexity of the world. A seen effect could be a result of unseen causes. The black smoke in the sky could be from burning of tires by vandals who have nothing else to do because they’re unemployed because new jobs aren’t coming in because the industries are steering clear of your state because the government has mandated a high reservation for locals. The disease here happens to be a botched policy itself and treating the disease means its reversal. Everything else is just treating the symptom. Curbing the sale of tires will not bring clear skies. Likewise, bugs in software are mostly symptoms and not diseases. Taking care of the symptom is primary, yes, but the underlying cause shouldn’t be avoided. In an application, frequently reappearing class of bugs indicate a lack of structure or guidelines for the development to adhere to. Unless that foundation is built, just fixing the bugs only delays the inevitable. Murphy’s law The bureaucracy that implements policy is a complex web. Lot of hands get involved in bringing out a policy. The intentions of the policy designers sometimes cannot be communicated to the ones implementing it. This gap demands directives to make sure that the details of implementation are airtight and nothing is left to interpretation. And this extra work starts with realizing that what can go wrong, will go wrong. In the context of software engineering, this is the aspect of security. Security features of a software should assume that the worst hackers are out to get them and should be designed as such. But security doesn’t just cover external factors. The software should be safe even from fellow collaborators. A developer having a bad day and making poor choices that they generally would not, is a very real possibility. These mistakes would ideally be spotted in peer code reviews. Even if they escape reviews, bad decisions shouldn’t domino through the system. Contagious modules should get auto quarantined. This requires preemptive identification of fragile or vulnerable portions of the code-base and having tightly regulated access to them. If a system expects the participants to be vigilant and have an impeccable foresight all the time, it’s fragile. Build robust software resistant to bad actors — internal and external. Have skin in the game The lessons till now were based on what makes policy work effectively. But we can learn more from its points of failure. It’s difficult to devise policies which change people’s lives for good while being insulated from their impact. Most policymakers are subject to a very real disconnection from the people they target. Neither success nor failure of a policy generally make its way back to them. This is an avenue where software engineers can radically better the policy professionals. In software engineering, this problem of connection boils down to the user feedback loop — how close are the builders of a system with its users. Engineers are generally well placed in the loop but the one practice which would seal the loop in all the right places would be Support Driven Development. Kevin Hale, who coined the term, describes it like this — “what we’re trying to figure out is how to inject values like responsibility, accountability, humility, and modesty into software development. It’s a way of creating high-quality software. All you have to do is make everyone do customer support. What you end up having is, you fix the feedback. The people who built the software are the ones supporting it”. With this, you introduce the thought — “ in the developer, and with that, some skin is pulled into the game. NN Taleb would approve. If I’m going to build this, how does it affect me later when I have to support the user?” Economics is a treasure trove of insights on human behavior. For the amount of time we spend with other humans, we spend a disproportionate amount understanding them. Hopefully, this essay has provided — to software engineers in particular — good reasons to explore Economics so that you do what you do, just a little bit better. References ‘ ’, authored by Vijay Kelkar and Ajay Shah In Service of the Republic — The Art and Science of Economic Policy on the science of policymaking. Freakonomics episode An on how radically different social groups tend to be. article A on support driven development. primer

Target

What Can Software Engineers Learn from Public Policy Professionals?

Beginning. I'm a coder by trade. A few weeks ago I was setting up and needed to read its source to troubleshoot an error. Turns out it was written in go, perfect opportunity to start learning a new language! This is the story of building , an SBE framework written in golang. Vault conthego I find it's more fun and effective to learn something by actually using it in a project. I've been using for a while now and really like the idea of free-form executable specifications (spec). A spec is a collection of example scenarios (ex. given/when/then structure) written in plain language, usually in Markdown. Concordion The spec is backed by fixture code which, when executed, will mark assertions in the spec as either passed or failed (html reporting showing green or red respectively). A quick search tells me nothing like this has been done in go yet so project candidate sorted. To start, I worked my way through the golang to learn the basics. Googling for existing tooling  that helps in language conversion from Java to Go gave me nothing but did lead to an excellent article - " ". tour Lessons learned porting 50k loc from Java to Go My main takeaway was the idea of iterative testing and validation after every little step. I entertained the thought (and did some reading) of AST transforms using antlr but that got me nowhere. Ideation and initial reading was from Saturday-Monday, May 9-11, around 12 hours effort. Iterations. Setup and preparation. Before I can get started on the first test there was the usual required project bootstrapping. I've got Intellij Idea for an IDE, decided on github as repo, and elected to just manage tasks in-project as a list of things to do in markdown. One of the main pre-requisites was to be able to parse markdown and convert it to xhtml. is the best library for that. However I realised during my initial stab that it wasn't able to render link titles with parentheses (which, like Concordion, was to be my mechanism for adding commands in markdown). The library being opensource though, a couple of nights and rounds of PR reviews later, it was ready for prime time (kudos to its maintainers). Go markdown This was over Tuesday-Wednesday, May 12-13, around 8 hours effort. First test, running a fixture method that spits out "Hello World!". Talk about biting off more than you can chew. First up was xml parsing the spec (now in the form of xhtml) into generic nodes, not standard but still pretty straightforward. What I didn't foresee was that I'd need to be diving into Go reflection this early (specs contain only strings, the call to something like "HelloWorld()" needs to be deconstructed and resolved to the relevant fixture function via reflection). Aside from the official docs, was my friend. Given a standard library function, it searches Go projects in github and shows you how the function is used. This proved to be an invaluable resource. With the large kubernetes codebase written in Go, there's a lot of examples to learn from. Also I've had to cast my mind back over a couple of decades during my C programming days to get the brain comfortable with pointers again. All up it was 3 days before first commit late on Saturday the 16th, with that first test working, around 16 hours effort. gowalker With the first test under my belt it's time to put the design hat on and think carefully about the commands that conthego will be supporting. These commands are the main interface for consumers using the tool so it pays to put enough upfront investment into them to make them simple and elegant to use. I was under no illusion I'll get everything perfectly right but I was conscious that I needed to start with a 'good set'. An hour of writing and rewriting got me the command set below. Apart from the one using literal parameters, the rest have stood the test of time (a couple of weeks!). Early on I decided to stick close to what Concordion already offers. Deviations were mostly for ease of parsing. Command prefixes were a single special character and (if required) appear only at the start of the command instruction string. set
[World](- "var1")

echo
[](- "$var1")
[](- "$var1.prop2")

exec
[](- "Hello()")
[](- "var1=Hello(TEXT)")
[](- "var2=Hello(var1)")
[](- "var1=Hello('literal')")

assert equals or isTrue
[World](- "?Hello()")
[World](- "?var1") Next lot of functions was to implement variable setting, function parameter passing, echoing of results, inline TEXT processing, and rudimentary dot navigation for struct properties. Of these, dot navigation proved to be a quite tricky as there was no implementation yet in Go. I rejected the notion of writing one, even the most basic, until my google foo led to the wonderful . OGNL go-dotnotation The trick was to marshal my structs into json then unmarshal them back into a generic tree of json nodes, which go-dotnotation can navigate. Simple and sufficient for my usecase.  At this point, passing structs and slices around, it took a fair bit of pointer wrangling to fix some gnarly bugs (I understood the issues then but am sure I'd need to keep re-learning pointer semantics). This lot was part Saturday and most of Sunday, the 17th, at least 8 hours effort. Next up was execute-rows - executing a set of commands (specified on table headers) over each row of a table. Turning things around my head on how to make it work, I've come to appreciate the beauty of sequential processing of commands: top to bottom, left to right; a perfect match for depth-first traversal of the xhtml node tree. This meant binning some future (complex) usecases that don't fit the model but I was quite happy in exchange to keep functionality limited and simple. I introduced pre-processing which can transform commands in the xhtml nodes prior to the command collector collecting them for execution. In this case 'transform' means removing the command instructions from the table headers and distributing them to the actual data rows. This was Monday night, the 18th, 4 hours effort. Verify-rows - there are two variants: first is verifying a simple list of strings, the second verifying a list of structs. This got me back to the drawing board (to be honest, I'm still not fully sold on the solution I came up with thus these commands are currently experimental). In the end I decided to constrain the implementation to support only unstructured lists for the first case, and a table for the second. I needed to disambiguate the intent for list-processing from the regular commands. The top options were to introduce a new type of token in the command instruction string to signal list processing (ex. square brackets in "?listOfNames[]")  or to introduce a new command that would impact processing of the succeeding commands. directive I opted for the latter for the reasons stated below. Implementation of verification for a list of strings was Tuesday night, 19th, 4 hours effort. to keep command instruction strings simple because there already was prior art - a directive command '!ExpectedToFail' which impacted succeeding assertions I considered list-processing to be 'advanced' commands and merited 'signaling' via use of a directive Verification for a list of structs is next, with support limited to being applied on a table. A major design decision here is to be able to choose for each column a specific struct property to assert on or echo. You can use echo exclusively (without asserts) for usecases like displaying a table of reference/config items. This was Wednesday night, 20th, 4 hours effort. I wanted to encourage easy usage, in case anyone would be keen to try, Tidying up of the basic command examples and the README file was Thursday night 21st, 4 hours effort. I've counted 60 hours above. I'm writing this on Sunday night, 24th, 4 hours effort. I'm a programmer, a serial optimist when it comes to estimates; and 64 is a nice round power of 2. Ending. The decision to store the task backlog as a TODO list in Markdown has proven to be handy. It felt natural to keep maintaining it whilst implementing code, all in the IDE. This worked as it was only me working on the codebase. Add another person and I'd probably look for a lightweight board like Trello. Being able to tick off items (or multiple) on something like a nightly basis builds up confidence and a sense of satisfaction. I've found that living documentation in the form of executable specifications are extremely useful in understanding how a system works. I always make it a point to refer to these artifacts primarily as specs rather than tests. Specs should be able to stand on their own even without having been executed. Crafting useful specs takes effort and time from the whole team with the main rewards being shared understanding, increased confidence that the system behaves as expected, and having something like a jumpstart tool for new team members. The Concordion documentation is the best resource describing how to write good specs. It's been fun learning and creating something new, and there's still a lot of TODOs to slowly nibble at. But now I feel I've been neglecting my books :) Enjoy! https://github.com/fanovilla/conthego Commit timeline: b0 Thu May : : + fix README.md b491b Thu May : : + Merge pull request # fanovilla/feature/tidy-examples a09c7 Thu May : : + better echo tests Thu May : : + better assert- test
cadc82e Thu May : : + better assert-equals test af7442 Wed May : : + reorder backlog
c2a03d6 Wed May : : + actor spec pre-processing routines a3622a Wed May : : + use concordion css dc272a Wed May : : + implement verify table rows d58b7 Wed May : : + implement verify rows list of s
ea5cf4d Tue May : : + add reporting of date time generated directives
c6fa62e Mon May : : + implement execute rows
df56ffd Sun May : : + simplify run spec hook
d3de448 Sun May : : + update todos cc Sun May : : + fail on panic c83b22 Sun May : : + implement slice eee8 Sun May : : + implement assert ea8d27 Sun May : : + Create LICENSE.txt f8c59 Sun May : : + implement map values; failed assert fails test; ExpectedToFail directive
fbf8cca Sun May : : + implement struct values; dot.navigation b76e Sun May : : + implement TEXT substitution; assign execute result to var de4 Sun May : : + implement echo
a953e87 Sun May : : + rename ReflectUtils to MethodCaller d3a5f Sun May : : + implement variable setting parameter passing d22215 Sat May : : + Initial commit 09874 21 23 14 22 2020 1200 77 21 22 57 56 2020 1200 1 from 78 21 22 53 24 2020 1200 set and 290460f 21 22 31 13 2020 1200 true 21 21 51 21 2020 1200 5 20 22 28 45 2020 1200 20 22 16 01 2020 1200 ref out 1 20 22 13 04 2020 1200 3 20 22 00 47 2020 1200 83 20 00 33 50 2020 1200 for string 19 18 38 59 2020 1200 and 18 23 50 44 2020 1200 17 23 17 14 2020 1200 17 23 03 18 2020 1200 12425 17 22 53 17 2020 1200 0 17 22 34 09 2020 1200 return 620 17 22 08 05 2020 1200 true 5 17 21 30 29 2020 1200 2f 17 20 40 03 2020 1200 return 17 19 45 15 2020 1200 return 613 17 16 51 12 2020 1200 8961 17 14 47 20 2020 1200 17 01 09 23 2020 1200 06 17 01 03 33 2020 1200 and 5 16 23 13 56 2020 1200

Trello

Learning Go by Building a Specification-by-Example Framework

Micro Optimization: Don't Get Lost In The Rabbit Hole

Go is a programming language that was designed in 2007, and this fact directly puts it into the young budding category. Even it is fairly young, as compared to others, it has a lot to offer. No, don't get confused with its adorable and goofy Gopher mascot. This language is more like a dominant alien trying to rule the universe of development! So if something would eventually be ruling the entire universe, shouldn't we know about it in detail? It is better to use it like armor, rather than taking a hit. Wonder, if this is the reason why web app development companies are using Go as a core language for creation? On that note, let us get to know the Gopher a little better to choose the best for ourselves. What Is Go Language? Go was publically announced in 2009 by its creator Google. It is an open-source programming language, statically typed, and produces compiled machine code binaries. This language includes build-in types like arrays of varying lengths, key-value map and it also supports the standard library. According to some developers this Google language is just like C for the 21st century with syntax. Because just like C it has an easy-to-learn and simple syntax. It allows the users to manage objects, safely use memory, deliver static/ strict typing with concurrency, and collect garbage. It is hands down, one of the fastest-growing programming languages. As per Rob Pike, Robert Griesemer, and Ken Thompson the aim to develop Go was to combine the immaculate features of the rest of the languages. Therefore, they were able to create GoLang with following properties: Highly efficient language with static typing Advance networking performance Full use of multi-core power Easy and simple to use State-of-the-art productivity Default concurrency support Quick compilation It has successfully replaced the traditional features of class inheritance with interfaces and type embedding. With Go compiler and a Text editor, one can easily set up an environment to implement the language. Why Was It Launched? At this point you might be wondering, why Google specialists even thought about launching the personal programming-language? If yes, then take a look at a couple of reasons: Networked hardware Enhance productivity while working with multicore processors Gargantuan codebase As the development was going on, there were only two things on their mind: Get rid of the persisting weakness of languages Keep their fortes Hence, the development took place with a motive to eradicate all the drawbacks present in C/C++. At the same time, they also focused on integrating advantages from all the other languages. Python and Javascript it has to take readability and usability From C/C++ it has to take runtime efficiency and static typing High performance with multiprocessing machines and networking According to its founder the following line explains its complete philosophy- “One problem should have one solution”. And because of this it is a comprehensive and intuitive language, displaying high performance while data processing. How To Implement This Programming Language? Since it is an open-source language, anyone can use it for specific needs. It is easy to contribute to it and tune Go to work as per one's requirement. But the list of its natural habitat for creation of the distributed web application includes: Server-side programming Backend Orchestrating complex networks Web development With its leading feature like concurrency, taking care of several requests and interaction with users is executed much faster with minimal CPU overhead. Top six areas in which Go is used include: Web development Databases Network programming System programming DevOps Security Why You Should Use GoLang? 1. A smart standard library It is easy for GoLang users to accomplish a lot without learning or importing complicated secondaries libraries. Its own standard library is sophisticated and does not overwhelm the user. Reducing the risk of errors from conflicting functions names is easy. Slice is one of the Go's smallest additions that provides a simpler way to incorporate data structures into code blocks. Hence, a single line of code is enough for multiple tasks with complicated workarounds. 2. Very simple to use Being a budding programming language, it is not as popular as Python, JavaScript, or any other languages. But it is very easy to understand. With clean syntax and lesser complicated functions, newcomers can easily understand it. The slick syntax makes it easy to read, making it an ideal choice for a complicated development. 3. Effective documentation Even tough GoLang is simple to read and write, it does require to document programs. Hence, there is smart documentation with standard policies in place including libraries and functions. In case one forgets to put the document in place, Google sends out an alert. 4. Safer The simpler code of Go allows it to be a lot safer. It is easy to find errors, and with garbage collector it is easy to prevent memory from bleeding off in the code. The increase in simplicity boosts security. 5. Access to cloud services With GoLang one can use all features, capabilities that cloud services providers deliver. For example, EC2, AWS S3, SQS, DynamoDB, SNS, etc. One can connect the GoLang SDK to take it from the official source of the service provider. 6. Compiler GoLang has achieved high compiling speed by converting the code directly to machine level commands. With a different operational system, the compiler can run programs on machines with simple commands. What Is Its Perfect Fit? Well, with all its advantages listed, it is important to know about the places where it can be used. So take a look: API's Notification services Streaming systems Mailing platforms Serverless web services XML, Jason Media platforms News outlets On-demand services Does Anyone Actually Use Go? It might be a new language, but it is gaining momentum as businesses are picking up their interests in this language. Despite varying opinions about Go's feasibility and characteristics, this adorable Gopher has already been turning a lot of heads in the market. Some of the world-known enterprises that use GoLang are: Google BBC Uber Docker Intel Medium Baidu Alibaba These are just a few, there are a lot more present in different industries from education to finance, who think using GoLang is beneficial for their business. Interesting Stuff About Go That You Must Know! Here is what most people like about GoLang In GoLang there is no need to put a comma at the statement's end. But it does require proper syntax to correctly translate the code. No comma: It is a special function to create maps, slices, and channels so that they can return the initialized value of type T. Make: The compiler will complain because of unused import or variable. Strict unused import & variable: It is simple to implement one interface in another with 'embedding'. And to put the cherry on top, it is simple to one struct in another. Embed interface & struct: There is no doubt that GoLang is simple, but it is powerful to do many things. It always delivers top-notch performance. Simple with quality performance: Wrapping It Up! But now you must be having a precise idea about GoLang. So what do you think, will it work for you or will you give it a pass? Whatever the choice is, this language has a lot in store for your growth. So don't let it GO, as it is one of the most in-demand . programming languages Until the next update, stay tuned.

Initialized

Intel

Uber

Why Should You Go With GoLang [Newbie's Guide]

In software development, testing ideas, doing trials and continuously learning is the approach that leads to success. That’s why creating a minimum viable product (MVP) can be so beneficial for every business that wants to have their IT product done the right way. The concept of minimum viable product was popularized by Eric Ries, a business owner and the author of The Lean Startup. In the book, Ries analyzes the mistakes that were made by startup owners and employees, as he had lots of experience with startup culture in the USA. He was confident about his conclusion - to build a successful enterprise, the idea needs to be researched, discussed with people and tested beforehand. What is a minimum viable product? Simply put, MVP is a basic version of the product we want to develop. It has a set of features that are the most important ones for the potential user. The team of software designers and developers prepare a mobile app, or a web app that can be used and tested but doesn’t have all the functionalities assumed for the project. MVP is an integral part of the software development process. It doesn’t require that much effort to be built, but at the same time, the outcome is so insightful and helpful. Making IT products without it would be much less efficient and the final result could be much more defective. What is the purpose of a minimum viable product? The main goal of MVP is to learn. Crafting a new product, even if it’s similar to the ones that are already there, is always a challenge. Collecting required information can be hard if we can’t present any sample to the customers. And this data is crucial to achieving results in the future. The essential characteristic of a minimum viable product is the first word of the whole definition, which is “minimum”. That means we need to deliver the most basic app or website that is possible to get the desired feedback. The principle here is to share a small product with one, two, or three features instead of assumed ten. Start with the vision of functionalities that will be most useful for the customers. If you own a business, you probably know them best. Building MVP based on your vision will make the whole development process more efficient. Another purpose of MVP is to save the time and cost of the whole project. Testing the new product early in the process is the best way to avoid failures that can prolong it. Also, being able to eliminate a problem at this point is often protecting us from losing money and time. Then we can invest it in building a product that will really be appreciated by the customers - instead of wandering in the dark, trying to guess what they will like. What is the role of a minimum viable product in Agile? Agile is a work methodology that likes to iterate and validate. It considers MVP as one of the crucial stages in software development. Before we even begin the first stage of production, we should determine if your idea is profitable to our business but also if the customer can appreciate it. Agile will search for the answer. Its goal is to achieve the best result using available resources effectively. So wasting time is not an option when working this way. MVP may be one of the most successful tools to get people to talk about our product before it hits the market in its final form. How do you create a minimum viable product? At first, we need an idea. After initial discussions, workshops and arrangements with the software house of our choice, the process begins. Target group We need to remember that our MVP is dedicated to a specific group of people - our potential customers. So determining this group, its needs and desires would definitely help to find out which features should be included in the MVP. At this point, it is worth remembering that people like products and services that solve their problems in a comfortable and positive way. Think about that when you evaluate your target audience. What do they want to do in their spare time? What are their main difficulties in life? What kind of service are they looking for? Be aware of your potential clients’ desires, not just your business goals. Data analysis After running the minimum viable product for the first time, we get tons of data we need to process, analyze and draw conclusions from. At this point, it’s only the factors we can measure with internal tools that we implemented into the product. This data will help us to find out if the target group we aimed for is actually the right one. Also, we can study the consumer paths and see if the usage of our product is compatible with our predictions. Feedback from customers Now we can read the reports on bugs, missing features, as well as unnecessary features and all the other insights from the people that used our MVP. Including the information from the previous step, we can learn what was done right and what needs improvements to reach the final stage. Carefully familiarize yourself with the opinions, because they are the most critical information about our idea and the product itself. Maybe this research will determine that our initial concept isn’t as good as we thought. That’s not a reason to give up! MVP is great for situations like that because it gives us a chance to change the strategy and pursue some other project idea. Product update Based on all the collected feedback and conclusions we got from all the previous steps, we can now build another version of our product. If there’s a need for that - it can be another improved MVP to run even more tests. If not - an MVP becomes the actual product. After being updated with more functionalities and proper design, of course. Should I invest in a minimum viable product? Working on any type of business solution should be sufficient. Software development is not an exception here. Investing in MVP can bring so many benefits to the whole process. Investing in it is money well spent. Be sure to find out a reliable business partner - a company that will provide you with robust IT solutions tailor-made with your requirements in mind. At itCraft, we always propose to build a minimum viable product before the actual production stage begins. We can use it to collect feedback, test each functionality and find out what else needs to be fixed. Our company wants to provide high-quality software that delivers business value to our clients’ end-customers. Building MVPs with React Native and other technologies we specialize in is the way to understand how our products might be perceived and what we can do better. We also recommend downloading our ebook on Cross-Platform and Native development . MVP can be helpful when determining which technology to use when building an app. With this ebook, you will get a lot of insightful knowledge and business case studies that justify the choice of one or another method. Hope it will help!

The Software House

Minimum Viable Product: a Crucial Stage of Development Process

Google and Amazon! These tech titans are a dream come true for every budding AI engineer. Every fresh engineering graduate who has walked out of college dreams about working at Google or Amazon — “the perfect work environment.” But have you ever wondered how everybody got there? When , the current CEO of Alphabet was called for an interview for the VP of a product management role at a company, the interviewers asked him what he thought of Gmail. It was on the very same day Google announced the , 1st April 2004. For which he responded saying he can’t answer the question because he could not use the product. In the fourth round of the interview, someone asked him a question, have you seen Gmail? To which his answer was, no. Sundar Pichai email service The interviewer showed it to him. Further on, when the fifth interviewer asked what he thought about Gmail. Pichai could answer all the questions. In such situations, most people try to cook up stories just to get to the next question. Sundar did the exact opposite and ended up making an impression. “He demonstrated intellectual humility.” Now you might be wondering why all the big talks, right? Well, you see, at times telling the employer or the hiring manager you have no clue about the question might dock off certain points, but it is still better than coming up with uncertain facts or answers that might be entirely false. “Successful, bright people rarely experience failure, and so they don’t learn how to learn from that failure.” - Laszlo Bock , Former Senior VP of People Operations at Google Laszlo also says it is one of the top qualities he expects to find in a candidate. If you’re wondering how to crack an interview at Google or Amazon, you might need to show intellectual humility just like Pichai. Do you have what it takes to get into these tech giants? The next time you find yourself sitting for an interview at any one of these companies, make sure to find your . inner Pichai How Amazon recruits an AI engineer: The process Let’s break down the primary components of what an AI engineer interview consists of: Initial Screening Phone screening is ideally processed by the hiring manager or the recruiter. This is the first and foremost step a recruiter takes to have a better understanding about the candidate. This call is to brief you about the job role and to talk about the interview process. A run-through is made about your past work experiences and your responsibilities in the previous organizations. They also need to have a clear understanding of your interests in working for the company and whether you have the grit and competency for the given job role. Technical Screening The second round comes to the technical screening, this generally takes place with an AI engineering management or a machine learning engineering management. Technical questions are asked just to check whether you’re competent enough and whether you fit well with the company’s culture. You’ll be asked questions on machine learning concepts and AI concepts, etc. You need to keep your head straight and answer with confidence to all the questions asked. Whether you’re a novice or an experienced AI professional you need to be ready to answer every question that the interviewer asks you. After parsing into many questions, here is the list of the most common technical questions an might need to answer: AI engineer What is AI? What is the difference between AI, machine learning, and deep learning Name the ? different types of AI What are intelligent agents? What is the most popular ? Or name five of the best languages used in AI? programming language used in AI Can you define what are neural networks and how they function? What’s the difference between strong AI and weak AI? What is machine learning, explain the difference between AI and machine learning? How would you explain machine learning to a non-technical person? Can you give us certain ? examples of AI in use Define the Turing Test? What is TensorFlow? Is there a connection between if yes, explain? Game Theory and AI , Can you tell me what are the different types of keys in a relational database? Will AI impact application development? How? What are the good properties of a knowledge representation game? Explain the hype behind AI?What is the tower of Hanoi? What is a breadth-first search algorithm? What is an A* Algorithm search method? This is just the first part of the technical round. The second technical screening round will be the coding round. In this, you may use whatever programming language you prefer. Onsite Interview The onsite interview generally goes on about five to six rounds of interviews. This round of interviews comprises a mixture of behavioral and technical interview questions. The behavioral question you can expect: behavioral questions often cover up your past job roles and your past work experience and why you’re leaving your current job. Remember this may be a tricky question, so you need to answer it using your intellectual humility. They might even ask leadership principle questions, make sure you know both Google’s and Amazon’s leadership principles or the leadership principles of the company you’re giving your interview for. Technical questions you can expect: although you’ve been through with the technical round, you might still need to answer technical questions that cover both machine learning and AI concepts. Most of the past interviewees were asked questions related to object-oriented design. Ensure you cover every aspect of the AI and machine learning field. Reality Check On average, most people get rejected on their first round of interviews. Rejections can be due to multiple reasons — either the candidate does not possess the required skill-set or perhaps due to a lack of knowledge in the given job role. You need to possess strong technical knowledge with the latest AI tools and technologies to succeed in today’s job market. Impressing the hiring manager might be the only factor that’s standing between you and the job. You can always opt for an AI certification program to help eliminate such roadblocks. Taking up a professional certification keeps you in-sync with the latest industry trends. Are you set to find your ? inner Pichai Don’t do another interview until you’ve mastered these questions! Previously published at https://medium.com/datadriveninvestor/how-do-you-crack-an-ai-engineers-interview-at-companies-like-google-and-amazon-56c6e5d1b513

Alphabet

Amazon

Preparing to AI Engineer’s Interview at Companies Like Google and Amazon

The Introduction The goal of this blog post is to introduce you to some of the most common pitfalls that make state management unnecessarily difficult and to outline 3 simple strategies that will help you avoid them. Managing the state of an application if extremely hard and I think is the main reason why applications tend to become so complex. For some reason, we try to manage the complexity by over-engineering our solution to the problem. There are so many ways of managing the state of your application ( , , ) and countless abstraction libraries on top of these. redux flux finite state machines But first, let's quickly define what I call the state of an application so we are on the same page. The Definition Of State The state of an application is a representation of a system at a given time. The UI of a front-end application is a representation of the state. If a user changes the state by interacting with your application, the UI may look completely different afterward because it is represented by this new state. The state is able to keep the data of different components in sync (or not) because each update will re-render all relevant components. Moreover, you can use the state to communicate between different components. I would suggest that there are the following types of state: - this one lives on the server and it is accessible, for example, via a REST endpoint Persistent State - where is the user in the application? Is he on the sign-in page, the sign-up page or the profile page? Navigation State - what is the colour of the button? Is the panel expanded or not? Is the modal open Local UI State - you can think of the filters selected by the user when dealing with a large list of items, the current page in the list of items Client State As you can see, there are many aspects to be taken into consideration when thinking about the state of our application. The in state management arises when we try to (server data, web workers, UI components, navigation etc) all of which biggest problem coordinate all these state sources update the state concurrently. How we decide to sync all this data is one of the most important decision when designing the state management of our application. The 3 Simple Strategies That Will Simplify Your Application State Management 1. Identify the type of state you are dealing with Make this your first step in your state management decision tree. Developers seriously underestimate the value of doing this (including myself) but it is extremely important in order to keep it simple. To help you identify it, you should think if this particular state of the application should be saved for later use or if you want the user to share the exact same state of the application with another user. If this is the case you should consider to reflect the state of the application in the URL. Except for the persistent state, the rest of the state is not stored on the server which means that there is no way of saving it for later use or for sharing it with other users. Also, if the user refreshes the page he will land on the same state of the application. Why is important? Think about when you want to share a Youtube video with a friend from a specific moment. The link you are going to share will have all the information needed to play the exact same video from that exact specific moment. Example. 2. Keep your state data as close as possible The next step in simplifying the state of your application is to keep your state data as close as possible to where it is needed. This comes with the following two benefits: and . maintainability performance Performance Imagine you have a hierarchy of components and you keep your state in the root component. Each time the state changes the entire tree is re-rendered and that is perfectly fine if all the components in the tree depend on that state. But what if that change only affects a component somewhere at the bottom of the hierarchy? You want to keep that part of the state as close as possible to the component that needs it. This way the component tree will re-render a lot fewer components than a state change at the top of the tree. Maintainability From the maintainability point of view always start a new component by managing it’s internal state inside of that component and if a sibling or the parents need access to that state just lift that part of the state up to the parent. This goes both ways. If you have a piece of state in a parent component that only one child needs, then move that piece to the child level. 3. Don't keep your entire state globally I've notice this pattern especially in applications that use redux. There are developers that like to keep their entire state into redux. If you are using redux you should aim on keeping only global state into redux and the local state as close as possible to the components that need that data. The problem with using redux for every piece of state is . Redux adds a lot of complexity to your application because maintaining the state involves working with reducers, actions, dispatching calls which results in having your state management all over the place. It get really Ben Lesh puts it really well in one of his tweets: increased complexity hard to maintain. Conclusions As you can see, as soon as the application is starting to grow, so does the complexity of managing the state. This is why the state management strategy is not something that you want to add late in your project, you should plan for it because it can be the decisive factor for the success or failure of your application. “If you fail to plan, you are planning to fail!” - Benjamin Franklin Previously published at https://codemachine.dev/3-tips-that-will-simplify-your-application-state-management

How To Simplify Your Application State Management

When I was in the process of learning web development, I was always thinking to myself: “Am I ready to start applying for jobs”, “How many things do I need to know before I start applying for jobs”, “When should I start applying for jobs”. These are probably one of the most important questions in your web development career and ones most people struggle with. These questions mainly focus on the people who are self-taught web developers but also can help people who’ve learned programming in college or in some different way. Why Should You Ask Yourself If You Are Ready to Apply For Jobs If you are not thinking about applying for jobs, you won’t get a job, it’s that simple but a lot of people get that wrong. They think that they need to just keep learning and jobs will come or something like that and that’s not how things work. You need to always ask yourself if you are ready or you’ll never be ready. Starting applying for jobs is one very brave decision and not all people are brave enough to do it, but they need to or they will be stuck in learning new things and newer getting anything out of that. There is one exception and that’s when you’re building your own product like a website or app or something else, then you can get away without actually applying for jobs because you’ve just created a job for yourself. Front-end Developer Jobs Not all jobs take equal time to learn them. For the front-end development jobs, you should start applying as soon as you learn HTML, CSS, and JavaScript and have a few real websites built with them. You probably know that a lot of companies use JavaScript frameworks, which may keep you away from applying if you don’t know them, and what will you do, you will start learning that framework, once you finish that, that job may not be open anymore. My recommendation would be to apply to jobs that you don’t feel 100% qualified, because there is no job that you are 100% qualified for, no one is. Let’s say that the job requires the knowledge of JavaScript, HTML, CSS and React and 2 years of experience in that fields, but you only know HTML, CSS, and JavaScript and have only 1 year of experience. In my opinion, you should apply, because you can learn React while you are working there or when they see that you are not that familiar with react, they may give you some other position or you won’t use React at all. Come on, the worst thing that can happen is that they reject you. Back-end Developer Jobs In terms of back-end development jobs, things are a little different in my opinion. If you are applying for development jobs, which only require back-end technologies like Python, Django, PHP, Laravel or something else, you should probably know those technologies. But, there are a lot of situations where the job requires a back-end technology like Django, Python’s framework for web development, and also some front-end technologies like HTML and CSS. If you have a job offer like that and you only know Python you should apply because HTML and CSS are very easy to learn, but if you don’t know Python and only know HTML and CSS then you maybe not apply and rather look for some front developer jobs, where you’ll have much bigger chances. Full-Stack Developer Jobs Full-stack development jobs are probably the most intimidating ones because they require you to have the most amount of knowledge, but in the truth, it’s not like that. A lot of people apply for the full-stack development job and end up doing only the back-end or the front-end for the most time. The point is that there are rare cases where you will be only doing the jobs that you’ve applied for, in most of the cases you will be doing a little bit of front-end and a little bit of back-end, and that’s also true for front-end and back-end only jobs. So let’s say that a job requires the knowledge of HTML, CSS, JavaScript, Python, Django and React and you only know HTML, CSS, JavaScript, and Python. If the situation is like that you should apply, you will have time to learn Django and React on that job and also what I’ve said before, you probably won’t do those exact things on that job. If you aren’t familiar with the thing above and you want to learn to code, here are some courses which you can use: For learning Web Development: The Web Developer Bootcamp For Learning to create mobile apps: The Complete Android N Developer Course For learning to create desktop games: The Ultimate Guide to Game Development with Unity 2019 Quick pause, if you like to get information through articles, but you sometimes just don’t have time to sit down and read them or you just don’t like reading, there is a solution to your problem. WhistleX is a free browser extension that reads articles for you. You just need to press the play button and that’s it. It can be used on any news website, blog, or any similar website. It can be also used on a phone, check instructions here . Let’s get back to the article. Conclusion For the end, you need to know that there are rare cases where you will be working the job that is the exact same as the one you’ve applied for, you will be probably working a little bit of everything. And in terms of applying, you should apply for jobs that you feel half qualified at least. 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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Machine learning (ML) is the process which enables a computer to perform something that it has not been explicitly told to do. Hence, ML assumes the central role in making sentient machines a reality. With the launch of Sophia, an AI robot developed by Hanson robotics, we wonder how close we are to be outclassed by these smart fellows. If you are speculating about the future of machine learning in the next ten years, you are at the right place! Let’s get going. Status Quo ML has made it less complex for prospective systems by bringing in a way that enables them to enrich their knowledge base from large data sets, keeping programming errors at bay and avoiding logic issues. With the of use of BigData framework in the mainstream applications, smart algorithms can now crunch this colossal repository of both static and dynamic data and continuously learn and improve its efficiency. This year, ML experts moved away from abstractions and theorizing, focussing on business applications of AI powered by machine learning and the . In the practical arena, ML has been extensively applied in preventive healthcare, medicine, banking, finance, marketing, and media. concept of Deep Learning Considering the unscathed continuance of previous five years, ML isn’t slowing down anytime soon. The ML Hype Among significant breakthroughs in ML, Google recently open sourced its machine learning project , which is already a very active project being used for drug discovery to generating music. Microsoft open sourced CNTK, Baidu announced the release of PaddlePaddle, and Amazon announced to back MXNet in their new AWS ML platform. Facebook, on the other hand, is mainly supporting the development of not one, but two Deep Learning frameworks: Torch and Caffe. Google is also supporting the highly successful Keras. Tensorflow This hype is centered on the idea that algorithms and machine learning are going to take center stage in the tech world, for a long time. Demands supply gaps in machine learning have become steeper and platform wars have become fiercer. Upgrade In the coming few years, AI applications will become more commonplace than ever, and people will be more accepting towards machines among them. Therefore all service providers will need to seriously upgrade both their hardware (storage, backup, computation power, etc.) and software (servers, networks, ad-hoc networks, etc.) capabilities. Just like the parallel processing capacity provided by GNUs have made the current AI possible and viable, the computation power would need serious amp up to accommodate what’s coming. All sections of the technological workforce will come under immense pressure to enhance and invent. We have seen a boom in the use of in mobile applications, image recognition systems, pattern recognition applications, filtering tools, robotics, etc. Scientists are currently trying to develop a working machine that follows the exact processing that human brain does. If we mapped every node and neural network of our brain and fed data to it, the system should be able to process data like a human brain. machine learning This concept is called cognitive computing. Cognitive computing systems will hence use pattern recognition, natural language processing, data mining to teach itself the thought process of a human being. With their end goal being a sentient AI machine, these systems should garner a lot of attention in the coming years. Cognitive Learning vs. Deep Learning: Where does the future lie? Deep learning is a process employed to help the system learn from unstructured or unlabeled data, all the while being unsupervised. Whereas, will use well-structured and segmented data to train and test the model sentient machine, deep learning employs data mining and data processing techniques to scale according to the data, model the data better and make it useful to other machines. cognitive computing It also uses neural networks but in combination with the enormous IoT data repositories, the scale, and type of processing differentiates it from cognitive learning. Its major application will be in the systems at the back end, systems that will contribute more towards marketing, branding, creating a database for other machines to learn from. With IoT, deep learning systems will create a data mine that will be the spine of most intelligent systems. While cognitive computing systems will work in collaboration with deep learning trained systems and IoT to perform the mainstream tasks in fields like Healthcare, medicine, scientific research and hypothesis testing, self-driving cars (automation), lip reading from video input and ultimately the sentient computing machine. These two fields, ML and AI, will grab much of the focus. Now, a sentient machine might be far-fetched but the importance of machine learning in healthcare, cloud systems and marketing cannot be overestimated. Stronger efforts to automate all routine parts of healthcare like testing for contaminants (viruses, bacteria, other foreign particles) in samples, detecting cancerous growths, examining x-rays and scans for the exact issues (which might escape the attention of the doctor or practitioner) will be made. Even as of now, some hospitals in developed countries like the USA, the UK, European nations are adopting AI options. More institutions and universities will invest in this field, and the demand will up-shoot manifold. Wrap up In the coming ten years, AI applications will become more commonplace than ever, and therefore all service providers will need to seriously upgrade both their hardware (storage, backup, computation power, etc.) and software (servers, networks, ad-hoc networks, etc.) capabilities. Just like the parallel processing capacity provided by GNUs have made the current AI possible and viable, the computation power would need a serious boost to accommodate what’s coming. All sections of the technological workforce will come under immense pressure to upgrade and invent.

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Code generators do our hard work. But we don’t need them anymore. Free lines of code A few years ago working in the industry I took part on the demo of a programming product in which a or was used. The presenter boasted of writing less code, leaving the machine to write the text for her. Based on the templates that she was declaring. The seduction argument consisted of writing less code. Today we know that this approach is completely wrong. wizard code generator If we have to tell the machine what the meta code is, it is because we are not being declarative enough. Photo by Phil Desforges on Unsplash There are several reasons: a) We have not yet reached the level of abstraction and we have to teach the interpreter to make syntactic manipulations on our models. If there is a certain redundancy, the usual approach would be to model that redundancy by searching in real world against the abstract concept we should match. b) Some code generators are based on the (almost always incorrect) excuse that generated code is faster than the more declarative one used when including an indirection or abstraction. The performance argument almost always loses its support against a real benchmark. As a counterpart we can argue that to read or debug a function in general, the bunch of computer generated code confuses the novice programmer (and the experienced one wastes lots of time). What is (wrong with) software? Currently, human time is more valuable and scarce than machine time. c) Some programming languages ​​impose arbitrary type restrictions that are only saved with intermediate code generation such as Java generics or templates in c++. These are language limitations and not model restrictions. Non-declarative languages ​​like C++ or Java offer us with tools like or that Templates Generics look different but are similar. < :isEmpty() {
 }
}; Linked_List<T>::append(T value) {
 generic_node<T> *new_node = generic_node<T>;
} template > <T>: class T bool Linked_List void new Photo by Shahadat Rahman on Unsplash d) The interpreter uses meta-programming to resolve these hints, although this is discouraged, among other reasons, for leaving obscure references, almost impossible to refactor and easily erasable by mistake. Laziness Chapter I: Meta-Programming e) The code generated with Wizards or with meta-programming is much darker, much more difficult to follow and violates the principle of failing fast because it does not usually know how to defend itself against possible invalid constructions. We have the choice not to use it if we want to build good software models. f) The code generated by the wizards, templates and is of very low quality. It is not usually documented and generates coupling as it is a repetitive . In case of finding an error in one of the generated fragments and, due to said coupling, we will have to correct it in multiple places violating the Fail Fast Philosophy, Explained automatic code generation tools cut&paste DRY principle. Coupling: The One and Only Software Designing Problem g) The generated code has little added value, and often encourages bad design practices like automatic generation. setters and getters Nude Models - Part I : Setters h) Finally, if computers can make inferences about the repetition of our design patterns, it is because we are not contributing the creative part (and for now not replicable) and we will be out of work in the short-term. (Most) Programmers are losing our jobs very soon The solution is on the usual shelf Given the symptom of finding a pattern that is repeated in our code, the diagnosis is almost always the same: There is an abstraction or generalization in the domain of the problem that we have not yet discovered. The trivial solution is to go, with the help of our favorite domain expert, to discover what that encompasses repetition or pattern that the wizard or template did not allow us to discover. is the real-world concept Photo by Volodymyr Hryshchenko on Unsplash Conclusions Dynamic code generators were a fad at a time when productivity was measured based on the lines of code generated. To avoid them, we must stay true to the rule of bijection and look for abstractions within the real world in the problem domain. Part of the objective of this series of articles is to generate spaces for debate and discussion on software design. We look forward to comments and suggestions on this article.

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If you told me two months ago that today would be the first day of quarantine that I would digitally get pen to paper, two-months-ago-me would have been outraged at quarantine-me. With no competition for my attention, I assumed that every creative pursuit that I’d put off for lack of time would come bursting out of me in a personal Renaissance like Bob Dylan producing . If Shakespeare wrote during plague quarantine, surely I could do something during my quarantine. The Basement Tapes King Lear But my time so far has been a lot less and and a lot more eating mac and cheese, wearing sweatpants and reading 2000 pages of . My unstated assumption before quarantine was that I have this bright star of imaginative creativity burning white hot within me, waiting for everything else in my life to get out of the way so that it could have an unimpeded outlet into the world. King Lear The Basement Tapes Game of Thrones But this muse, so independent in concept, has shrunk in proportion with my smaller social life, smaller set of experiences, and generally smaller world. I’ve felt increasingly lethargic and drained as my star of creativity has proven to be more like a generator, where the fuel is relationships and experiences, and the output is activities of greater societal value than eating mac and cheese. I admire the Henry David Thoreaus of the world who can use extended solitude to produce works of brilliance, but despite our , I don’t think I’ll ever follow in his footsteps. Just sitting down to write this required drinking an inhuman amount of coffee and listening to super loud indie rock to trick myself into thinking that I have energy. similarly terrible facial hair But, if we’re honest, everyone is tricking themselves a great deal during this season. As shelter-in-place rules keep us trapped at home, we’ve taken as many of our beloved relationships and activities as possible online. Happy hours that used to be in bars are now on Facetime; musical performances have moved from concert halls to Instagram; churches meet via Zoom; friends watch movies together at a distance via Netflix. I’ve slotted tons of these digital activities into my calendar in place of their physical, pre-COVID equivalents, and sometimes I spend more time digitally with others than I did physically before quarantine began. So, why am I so drained? Why am I cancelling video calls with people I miss desperately out of pure exhaustion? Because, despite the fact that we can still connect with others digitally, there’s something fundamentally missing. We desire to actually be together, and technology like video chat promises to give us the togetherness that we so desperately crave. But no matter how connected you feel on that call, sooner or later it ends and you snap back to into your surroundings, realizing that you’re not in a room full of people, but instead at home alone staring at a blank laptop screen. In the end, the togetherness you felt was an illusion. But it’s a — one we desperately need. Similarly to how we suspend our disbelief in magic while watching Harry Potter to allow us to engage with the story, we suspend our disbelief that we’re not actually in the same place as our friends when we call them to allow us to feel the connection we crave. And similarly to how great special effects can make fantastical elements of a movie easier to believe, the radical improvements in digital communications technology over the last few decades has made it much easier to believe that we’re with the people we love as we see their faces streamed to us in glorious, real time 1080p. sacred illusion As quarantine carves a massive hole in the lives of all but the staunchest hermit, the illusion becomes necessary and almost impossible to live without — something , at least in our strange times sacred . But as we demand more and more of the illusion by moving all of our social events and relationships online, we stretch it to its breaking point. When our deep human need for connection can only be met via Facetime and Zoom, at some point the gap between the promise of physical togetherness and the reality of simulated togetherness grows too large — we’re unable to suspend disbelief anymore and the communication that once gave us energy now saps it. The Illusion of Digitization Just like video calling, much of our Internet technology exists to allow us to digitize social activities so that we can conduct these activities in ways we couldn’t before. We’ve digitized going to the store (Amazon), playing games with friends (Xbox Live), attending a performance (Instagram Live), and many forms of work (every knowledge worker working from home right now). All of these digitized experiences require the same illusion as the video call, as our imagination fills the space left by the imperfections that are inherent in taking a physical experience and putting it online. Reddit, for example, is the digitization of local meetup groups. Taking these communities online is incredibly powerful, as it allows people to connect over niche interests with no regard for physical distance. If I’m a part of a group of ping pong enthusiasts on Reddit, I can discuss ping pong, watch videos of matches, or learn about technique seamlessly. But the illusion breaks down when I finally want to find someone to play against. That physical need can’t be met digitally. Digitizing a physical activity has benefits and drawbacks, but it is always a limited version of the real thing, stripped of some amount of depth and richness. This limitation is inherent in digitizing an activity. As a software engineer, one of the first decisions you make when creating a new software product is the decision of how to model your data. This requires deciding exactly what information is going to be stored, how it will be structured and how it will be presented to the user. As a result, when creating a software product to bring a social activity online, certain pieces of information that are present in the physical activity will be left out of your data model by necessity, creating a gap between the real activity and the digitized version. As a result, no matter how hard we try, our digital approximations are always of their physical counterparts, resulting in the illusion discussed earlier. But, as the famous quote by statistician George Box goes: incomplete models “All models are wrong, but some are useful. Since we’re not going into the office right now, my team at work meets via Zoom. There are aspects I miss about meeting in person that simply are not supported by Zoom’s technology — seeing people’s body language clearly, having side conversations to catch up on the weekend, or eating cookies that someone made over said weekend and brought in to share. In those moments, the illusion is made obvious, and I remember that we’re not together in a conference room in the office. But that’s ok. The most important thing of those meetings is not sharing cookies (sadly), but being able to discuss ideas and make decisions, and Zoom allows us to do that really well. We can share screens, present slides, and discuss freely in a group. The model of a physical meeting is , but incredibly . wrong useful When we use digitized activities to replace the parts of their physical counterparts that they model well, the illusion holds up. Sure, sometimes screen share freezes at a crucial moment, but generally the Zoom model of collaborative work together is good enough to allow me to suspend disbelief and fully engage in work with my team. The trouble comes when we use the digitized activities to replace things they were never meant to. The Failed Digitization of Social Life The weird thing about Zoom fatigue is that, at first glance, it seems like video calls should be a decent approximation of most of my social activities. Social life consists mostly of talking to different people in different places — happy hours, meals and parties are largely just vehicles for conversation. It seems like talking to these same groups of people via video chat should be able to keep me socially afloat for a couple months. But instead, each video call leaves me more burned out. There have been tons of articles about the phenomenon of Zoom fatigue, all by people that did far more research than yours truly. But I think two interesting threads can be drawn from our discussion of the illusion of digitization that are helpful for understanding our current moment and thinking about what it means for the post-quarantine future. Digitizing anxiety First, part of our Zoom fatigue problem is that video calls digitize the wrong part of social interactions. In every conversation of significance, there’s both joy and anxiety to be experienced. We feel joy when we connect with someone else and are able to meaningfully share life with one another. This might look like making a clever joke that only that group understands, being listened to and accepted when sharing about your problems or fears, or expressing feelings about a common experience. We makes us anxious when we feel judged, self-conscious, or not accepted in a conversation. To share life in the ways listed above, we risk exposing our emotions and who we truly are to someone else, which always brings the threat of rejection. If the conversation makes us aware of this threat, we feel anxiety. Video calls take all the anxiety-provoking parts of conversation and amplify them, while dulling the joyful parts. Spotty connections and other distractions on the other person’s screen can make us feel unheard and uncared for. You can’t make eye contact, a crucial part of building trust. Seeing a video of yourself during the call stokes self-consciousness — I find that I am much more self-conscious of the way I’m being perceived when I can see a video of myself speaking in real time. Latency makes it harder to have flowing, natural conversation that leads to deeper connection. And, most crucially, no matter how connected you feel to the other person, at some point the screen goes black, and you’re snapped back to being alone. Every conversation ends with a sort of involuntary Irish goodbye, which feels deeply uncomfortable. Video calls promise the world and seem close to the real thing, but often leave us feeling empty. The illusion holds up — it just models the part of social life better than the part of it. As a result, we long to disconnect and hide from video calls with friends, even though we’re lonely and in need of connection. anxiety-provoking joy-giving A lot of life has this combination of joy and anxiety, which makes me wonder: what if there was technology that amplified the joy part of an experience while dulling the anxiety part? Would it be like the opposite of video calls, where instead of hiding from it, we instinctively gravitate towards it? This sounds great (free joy!), but when you think more about it, the result is chillingly similar to the fate of the fat humans from WALL-E. These people get all pleasure and no risk — what could be better? And yet, there’s something about responsibility, risk and sacrifice that makes the pleasure of a deep relationship or climbing a mountain or learning a skill much richer and more lastingly meaningful. The apps we use want to draw us in, so they (indirectly) optimize for a high ratio of dopamine hits to negative feelings, resulting in the sort of gravitational pull that services like Instagram have. It’s the opposite of Zoom, offering the positives of the experience of “social life” with none of the negatives. But in reality, this optimized experience of social life also fails to give us lasting joy or fulfillment. Video games and virtual reality in particular escalate these questions even more. Imagine a VR game that is perfectly optimized to digitize the pleasure of social life with none of the anxiety. Is playing a game like that good for us? Considering our addiction to normal games and apps, a game like that could have the gravitational pull of a black hole, where anything that enters never comes out. In some sense, it’s a blessing that our technology is still flawed at modeling the activities in the real world that make us joyful. If the illusion was perfect, we might not return to the real life equivalent at all. Our inescapable physicality Second, even if Zoom perfectly modeled conversation, creating the perfect illusion for every non-physical aspect of talking to a friend, our social interactions would still be deeply impoverished. No matter how well we digitize experiences, the physical nature of our humanness is essential. We are inescapably physical. We often think of ourselves as having a body, but we are our body — there’s no without your physical body. And as physical beings, our needs for friendship, community and love are physical needs as much they are emotional needs. you Jesus, my role model, understood this. When you read about the way he cares for people in the Bible, it’s usually in a deeply physical way, which can be counterintuitive for a guy who is supposed to be super spiritual. When Jesus heals sick or disabled people, he always reaches out and touches them — even the contagious lepers who are shunned physically by their community. He shares meals with all kinds of people, he lets kids climb all over him, he makes food for hungry people to meet their physical needs. He gets down on his knees and washes the dirty feet of his followers the night before his (very physical) death. Unlike our common perception of a spiritual teacher considering himself above the physical, Jesus enters into the physical reality of life, meeting people’s needs physically as well as spiritually and emotionally. Furthermore, demonstrates the necessity of the physical for deep connection and relationship. If we were primarily minds with a body, there’s no reason God could not have just beamed information or experiences to people’s brains instead of becoming a physical person. the belief that Jesus was the human embodiment of God But to truly connect with physical people, he needed to enter the physical world and care for people physically. The incarnation of Jesus shows the fundamental importance of the physical in relationships. We all deeply miss the physicality of our relationships in this moment. We spend a lot of time talking, but the ways that we care for each other physically matter just as much — a hug, sharing food, eye contact, singing together, throwing a frisbee. It might be obvious, but there’s something to physical presence that is not and cannot be captured by a video camera and a screen. Our digital substitutes for physical presence are good, and despite burnout, I’m thankful for the ability to see the faces of my friends and family to help ease the social pain of quarantine. But we need the physical, with all of its messiness and danger and inconvenience, and I’m hopeful that when we get it back soon enough, it will taste a little bit sweeter having known its absence. This article was originally published (with irreverent and fun footnotes not found here) on my personal blog, Digital Inklings . You can also find other articles I've written about technology and sign up to receive emails when a new ones come out at Digital Inklings, if that's the sort of thing you're into.

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Remote work is on everyone’s minds right now. If you are fortunate enough to still have a job right now chances are you are doing it remotely. And you’ve probably learned that you can do your job pretty well from home - just as well as you did in the office if not better. And why is that? It’s certainly not because of the added stress of a pandemic. Could it be because your management team actually trusts you to get it done? We all thrive when we feel trusted. In fact, remote work has been shown to increase productivity by 15% and it also boosts overall morale within a company. That’s because remote workers feel trusted and that trust is empowering. Employees who work at organizations that value trust report 106% more energy at work and 76% more engagement in tasks. When adults are treated like adults and left to their own devices, more often than not they will derive their greatest satisfaction from setting and achieving goals. Those people who feel trusted at work are also at significantly lower risk of burning out on the job and have 74% lower stress levels and 29% higher life satisfaction. Most people will tell you that their best days at work are the days where they make progress toward their goals. People are typically inherently self-motivated, so trusting them to do their jobs no matter where they are working goes a long way toward keeping a company going. It’s possible that remote work is here to stay, too. Adoption was slow because people were unsure how remote work would actually work, but now that the transition has been made and people have proved their abilities, it’s unlikely that companies will need to continue to provide vast and expensive office spaces in which employees will work. Working from home allows for a better work/life balance, and it costs companies less. It’s a win-win situation. Remote work is here to stay. Learn more about the future of remote work and the from the infographic below. psychology of trust

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-- , the technology publishing platform serving 4M readers per month, today announced a $1M strategic investment from , the San Francisco-based startup designed to help creators monetize content and provide a premium experience to consumers. Additionally, the companies kicked off a three year partnership focused on for contributing writers. Web Monetization is an open specification that is freely available to any monetization service provider who wants to support sites like HackerNoon. EDWARDS CO June 10, 2020 HackerNoon Coil Web Monetization “We want to become the best place for tech professionals to read, write and publish,” said HackerNoon CEO David Smooke. “To date, we’ve provided editorial resources, validation, and distribution. Now with this strategic partnership, HackerNoon will experiment with streaming micropayments to writers based on how much time Coil users spend reading their stories.” "HackerNoon is home to an incredibly dedicated community of technologists and software developers,” said Jonathan Greenglass, Coil’s Chief Growth Officer.  “We’re thrilled to be working with HackerNoon to provide its community with a simple way for readers and writers to participate in the value exchange between one another." Starting today, HackerNoon Writers can now add their Web Monetization meta tag to their stories on HackerNoon. Once enabled, Coil automatically streams micropayments to the writer’s wallet based on the amount of time Coil Members spend reading. We will also offer a way for writers to that are dedicated to making the Internet a better place. donate their earnings via Coil to charities Last year, HackerNoon (dubbed HackerNoon 2.0) to serve readers, writers and sponsors on their own terms. The company pivoted from a publishing platform to a software company and a publication, creating 100+ years worth of reading time since July 2019. launched their own content management system “Props to HackerNoon's editorial teams for editing my piece. Truly amazed at the editing quality and the effort they pour into *every* article that goes through their hands. Excited to see them grow even bigger!” tweeted Human+Business Founder and HackerNoon contributor Andy Chan. “Congratulations to David Smooke, Linh Dao Smooke, Dane Lyons,  Austin Pocus, and everyone else on the HackerNoon team. The new platform is well-built and progressing fast. Thanks for everything you all are doing for the global developer community,” tweeted FreeCodeCamp Founder Quincy Larson. Coil paid $11.35 per share, valuing the company at $11.5M pre-money. In HackerNoon’s previous , the share price was $8.20. The company remains entirely common stock. As part of the partnership, , Coil’s Chief Growth Officer will be joining David Smooke and Linh Dao Smooke on HackerNoon Board. Previously, he was CFO of Imgur, one of the internet’s largest communities, and a top 30 website in the US. equity crowdfunding round Jonathan Greenglass “In addition to implementing the Web Monetization standard, we will use this investment to expand the editorial, sales, and most importantly, software teams,” said David Smooke. About HackerNoon How hackers start their afternoons. We are an open and international community of 12,000+ contributing writers publishing stories and expertise for 4,000,000+ curious and insightful monthly readers. Founded in 2016, HackerNoon is an independent technology publishing platform run by David Smooke and Linh Smooke. HackerNoon is built for technologists to read, write, and publish. About Coil Coil was founded in 2018 to build a better business model for the web. Coil makes it easy for creators to monetize their content across the internet, and provides an alternative to advertising and site-by-site subscription models. As members enjoy content, Coil uses a proposed open web standard called Web Monetization to stream micropayments to creators in real time. Coil is designed to support a variety of creators, developers and content platforms. In 2019, Coil, in collaboration with Mozilla and Creative Commons, launched the to boost open, fair and inclusive standards and innovation in Web Monetization. Coil also invested $20 million in Imgur, the community-powered entertainment platform reaching 300 million people each month. For more information about Coil, please visit coil.com and follow on Twitter (@Coil). $100 million Grant for the Web

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HackerNoon Raises $1M From Coil, Will Stream Micropayments from Readers to Writers via the Browser

So you want to earn a little spending crypto in exchange for your thoughtful Hackernoon content. You could try selling shady links on the black market...but you know that's not right. And getting a sponsorship deal isn't easy without risking life and limb... Good news! Now you can accept a stream of micro-tips from your loyal readers. No need to sellout while you work toward your dream influencer status and land a huge Red Bull or Red Hat deal. Todo list to monetize your content on Hackernoon 1) and get a payment pointer. 2) Add your payment pointer to your . Sign up for Coil as a Creator HN profile settings Adding a web monetization meta tag also works on your personal blog. Check out to learn more. Protip: webmonetization.org

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....is my answer to this question someone posted on Twitter the other day: "What is your best advice in 4 words or less". Let me tell you about the time I learn to connect all the seemingly isolated events in my career and came up with this advice in retrospect. 8 years ago, I founded with , another sophomore at , who reached out as he was going to Vietnam that summer and was also extremely passionate about education, like myself. I happened to be cooking the idea for the first ever summer camp for middle school kids in Hanoi then. Evan had experiences with and could raise some money for CKP, on top of the grant I already got from Brown. We recruited a few other founders and got to work. CKP is still going strong to this day. the Creative Kid Project Evan Schwartz Brown University Camp Rising Sun I didn't know Evan, nor did I think the project was gonna turn out or get any funding when we met. Yet, I went for it anyway. I had an unshakable feeling that this was the right thing to do. Fast forward to the fall of 2018, , the company I now ran with my husband , was raising funds for the first time and in the midst of our breakup with Medium. Having published a good bit about crypto and blockchain,  I reached out to Evan, who was then a software developer at (the 3rd largest cryptocurrency), about a potential partnership. That did not turn out. But later on, Ripple former CTO, Stefan Thomas, learned about our raise and . Little did I know, just a few months earlier, Stefan had left Ripple to found , the solution provider. Earlier in their Ripple days together, Evan and Stefan have co-papered , the foundation upon which Coil was built. Hacker Noon David Ripple helped close the last of our $1.07M equity crowdfunding round Coil Web Monetization the Interledger protocol I was stressed out about Hacker Noon's decision to not take the low-ball offer from Medium and . I felt a little embarrassed to admit all that to my friend Evan, who I haven't spoken to in a while. I just knew he was working with (and pivotal to) Ripple, a company that I do respect and like. So, I went for it anyway. go out of our way instead to finance on our own terms Today, I emailed the news to Evan, who learned about it only yesterday during a Coil Board meeting! we announced Coil's $1M strategic investment in Hacker Noon and the launch of our 3-year-long partnership to stream micropayments for our writers . Sometimes, the universe just finds funny ways to align the events in your life so they make sense in retrospect, doesn't it? And now is the part of the story where I make an important PSA to all the "young" people out there, particularly those still in school. Trust your instincts. Submit that internship application, found that club, volunteer at that organization. Everything in life happens for a reason, and trust your instincts might be scary. Yet, go for it anyway. Put your heart in the right place, things will turn out fine.

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The Pandemic of Childcare

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I believe the next era of marketplaces is going to look very different than the marketplaces we’ve seen so far. It used to be the case that marketplaces could add a ton of value just by aggregating any and all supply and demand. The onus was on the users to filter using the available information in the marketplace to choose what they wanted or needed. This model has worked well for a ton of product and service categories and marketplace companies. But now, there’s an increasing need for more “managed” marketplaces — platforms that take on more work, not less (e.g., interviewing and vetting suppliers, automatically setting prices, etc.) — to intermediate the delivery of the product or service. The managed marketplace model is critical to unlocking categories involving high-stakes or high price transactions (such as therapy, home buying, fine art, travel experiences), as well as those impacting users’ lives and health in other ways. In childcare, for instance, people don’t want to just see a list of all possible caregivers — they want to know with certainty that the providers they’re hiring are trustworthy and qualified. Last week’s WSJ piece on Care.com illustrated the tragic shortcomings of an unmanaged marketplace model: https://www.wsj.com/articles/care-com-puts-onus-on-families-to-check-caregivers-backgroundswith-sometimes-tragic-outcomes-11552088138 This week, the company announced it is overhauling its supplier onboarding process, including verifying licenses and credentials and checking criminal databases — adding a layer of management onto a previously open marketplace: Care.com Overhauls Vetting of Sitters, Listings Managed marketplaces are an important evolution in marketplaces. The low-hanging opportunities in marketplaces have been picked, and the next wave of startups are innovating on the underlying marketplace model to tackle more complex goods/services that have remained offline. . Because –people feel like they’re interacting with a high-quality, concierge-level service. In the future, marketplaces may not even feel like marketplaces to the end user they connect all the dots behind the scenes–and provide such a high level of standardization and quality Examples range from daycare (e.g. Wonderschool) to skincare (e.g. Heyday). On the surface, Heyday looks like a chain of facial shops — a physical retail and services business. But underneath, it’s building a personalized skincare platform, matching different women to the exact right products for their skin, driven by the company’s growing corpus of data on what ingredients have worked well for various skin types, sourced from their physical business. What are other interesting innovations in marketplaces? Interested in hearing more examples! Originally published as “ The next generation of marketplaces may not even look like marketplaces "

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What Will the Next Era of Marketplaces Look Like?

HackerNoon Tech Stories Archive June 10th, 2020

@mozillaMozilla Contributors

@matteo.pisani.91Matteo Pisani

@christina-combenChristina Comben

@SimilarWebSimilarWeb

@kuladeeparunKuladeep

@francisnFrancis Novilla

@raphael.moutardRaphael

@ankitsinghAnkit Singh

@Alexa & ChristophAlexa i Krzysztof

@albertchristopheralbertchristopher

@marinvirdolMarin Virdol

@jureJure Reljanović

@vincent-olagoVincent Olago

@mcseeMaximiliano Contieri

@owenauchOwen Auch

@brianwallaceBrian Wallace

@hackernoonHackerNoon

@DaneDane Lyons

@linhLinh Dao Smooke

@lijinLi Jin

@mozilla
Mozilla Contributors

@matteo.pisani.91
Matteo Pisani

@christina-comben
Christina Comben

@SimilarWeb
SimilarWeb

@kuladeeparun
Kuladeep

@francisn
Francis Novilla

@raphael.moutard
Raphael

@ankitsingh
Ankit Singh

@Alexa & Christoph
Alexa i Krzysztof

@albertchristopher
albertchristopher

@marinvirdol
Marin Virdol

@jure
Jure Reljanović

@vincent-olago
Vincent Olago

@mcsee
Maximiliano Contieri

@owenauch
Owen Auch

@brianwallace
Brian Wallace

@hackernoon
HackerNoon

@Dane
Dane Lyons

@linh
Linh Dao Smooke

@lijin
Li Jin