Justworks makes it easy and affordable for businesses to hire and take care of people – freeing them to invest their time in what matters: Building their company

Justworks takes the busyness out of growing a business and alleviates the unknown. We’ve combined a simple platform and exceptional 24/7 customer service with the power of a PEO, so all teams have more time to focus on what matters. Get access to corporate-level benefits, seamless payroll, HR tools, and compliance support—all in one place.

Justworks

Effective Leadership Series Isaac Oates is the Founder and CEO of Justworks, the fastest growing HR technology company that helps entrepreneurs and businesses grow with confidence by giving them access to big-company benefits, automated payroll, HR tools, and compliance support — all in one place. FirstMark is a proud investor in Justworks. Early in his career, Isaac worked concurrently at Amazon and in the United States Army as an intelligence officer—in both roles honing various aspects of his leadership approach. After Etsy acquired his first startup Adtuitive, Isaac led Etsy’s HR and payments group. He founded Justworks in 2012. We recently caught up with him to hear more about his growth as a leader, how he handles delegation as CEO, and much more. What was your first management role? What did you learn from it? I started my career as a software engineer at Amazon, where I worked on “third party payments” (3PP), the system that moved money between buyers and sellers on their marketplace. About three years in, I took on a project management role within the team. Even though no one reported to me on paper, I was in a position to lead the broader team to a successful outcome. That was the first time it really clicked that leadership isn’t about the boxes and lines on an org chart, but about following people that you trust and respect. Early in your career, before you assumed leadership roles, what was one quality you appreciated in a great manager? My first manager at Amazon, Phil Wilson, really cared about me as a person. I was 22, fresh out of school and had just started as an engineer on the payments team. Phil would talk with me about his own career experiences and help me think through the challenges I was facing. I think the big lesson was that he could lead by asking questions rather than telling you what to do. He was really good at letting you draw your own conclusions but also getting you where he wanted. This is something I wish I was better at. It requires a lot of patience. He was much more like a coach or older brother in the support he gave and we’re still in touch to this day. The big lesson was that he could lead by asking questions rather than telling you what to do. What are the most important daily or weekly habits that you’ve developed as a leader? Whether it’s on paper, on a spreadsheet, or in my inbox, sorting tasks into different groups and then attacking them together head-on has helped me be more productive. Recently, for example, I set up some filters in my email account that separate messages that demand a response from everything else. That might seem small, but it’s changes in habit like this that have helped me be much more responsive to the people I work with. It’s made a surprisingly large difference in our operating tempo. I also take time on Sundays to draft emails to send out on Monday morning. It helps me catch up on my inbox without also dumping work on my team over the weekend. What framework do you use for your one-on-one meetings? I like to review the goals that we’ve set together, discuss if any changes are appropriate, and then exchange feedback. I have 30 minutes per month with each of my direct reports, so most of our substantive discussion happens in group meetings rather than 1:1. That’s intentional — I think group meetings are helpful in building shared consciousness and minimizing politics. How do you handle delegation? What and when do you choose to delegate and how’d you become comfortable with it? I’ve been fortunate to hire and work with some extremely talented people at Justworks, who are much better at most things than I am. That makes it easy to delegate. That said, if I’m still getting comfortable with their work style or it’s a high-risk project then I ask to stay involved as it progresses. Some things I’ll always stay closely involved in, for example, activities that impact or send messages about our culture like promotions to leadership roles and company-wide events. If I’m still getting comfortable with their work style or it’s a high-risk project then I ask to stay involved as it progresses. What advice would you give to a first-time manager about giving effective feedback? Giving effective feedback is difficult but it gets easier with time. I don’t have a specific framework, but I do acknowledge the person’s accomplishments and the effort they have put in. I also make it clear that my goal is to help them and the entire company perform better and that they should take the feedback in that vein, rather than criticism just for the sake of it.Giving feedback is probably the #1 management challenge for many people, including very senior and experienced leaders. Just keep working on it. What’s one unique hiring tip you’d share with a first-time manager? Start with the basics. Figure out where the person is from, what they’re about, what they value. Then ask yourself the right questions. Will this person strengthen your team? Do you think they have the potential to be promoted a few times? Do they have the curiosity to keep growing? Sometimes you get lucky and the right person falls in your lap, but usually, it takes a lot of nos to get to a yes. It’s worth taking the time. Want more? Check out our other Effective Leadership interviews with seasoned leaders from , , , and . Box Slack Oscar Trello Is there someone who you really admire as a leader (not at your current company) and would like to see us interview? Send their name and short description to jack@firstmarkcap.com.

Justworks’ Isaac Oates on How To Delegate as CEO + More

When Apple piggybacks on Google, it ‘just works’ better (Image from ) Flickr The other day, my iMac crashed. As it was a 2011 model, I was prepared. Well, sort of. I had been regularly backing up my stuff via Time Machine but had stopped doing this 24/7 a couple of years ago so as to extend my Time Machine’s life. It’s a venerable 2008 model. Also, a lot has changed since 2008 as most of my files are saved online and I don’t need regular backups any more. However when I ran the ‘restore utility’ on my Mac, I realised that I had lost track of time. My Time Machine informed me that my last backup was over four months ago. I mulled it over as my mouse hovered over the ‘restore’ button. By my reckoning, the only new files of any value on my Mac that I added in that period were a few photos and songs. So I gave Time Machine the go ahead with the ‘restore.’ Once the restore was done, the Mac seemed fine. But I could not say the same of apps like Photos, iTunes, Contacts and more. Besides the last four months’ missing files, Photos had also converted many earlier videos to thumbnails. These wouldn’t play when I clicked on them as the original files were missing. iTunes too had randomly made quite a few of my song collections disappear. The Bermuda Triangle To be honest, I wasn’t surprised as it’s not the first time Apple apps have played this trick on me, and it’s not just me. Here another victim the same tune on the Apple Support forum for iTunes. And here’s a about disappearing pictures from the Photos app. The latter seems to have had a happy ending for a few individuals who recovered their photos by tweaking some settings. I’m sure expert users will be able to relocate the missing photos but my heart goes out to the ordinary folks who have lost their precious memories forever. singing thread This sort of thing should not happen, but unfortunately it does with Apple. After several unsuccessful attempts to figure out why, I gave up and concluded there’s a sort of Bermuda Triangle in Appleland where songs and photos and the rest mysteriously disappear. But unlike the Bermuda Triangle, you can’t avoid using apps like Photos and iTunes if you are in the Apple ecosystem. There were two solutions. The first was to make a clean break an emigrate out of the Apple ecosystem. The second was to find a backup system where I am not expected to expect the unexpected, so to say. When Apple just works I had tried the ‘migration’ solution by moving to an Android for a while. But it didn’t work out. I don’t know if this was because I was just more comfortable with Apple, having been on the platform for ages. Or because there were situations when my Android let me down, while Apple actually ‘just worked.’ Let me illustrate with an example. I once had to make a screen recording as a demo of how to use a certain app on Android, and send it to a WhatsApp Group. After making the demo, I sent it from my Android phone to my iPhone via WhatsApp to test if it was working. It wasn’t. Whatever compression WhatsApp had used on the one minute long video had caused the audio and video to go off sync. Now I could troubleshoot and try to figure out what when wrong. But sometimes you just want to get things done instead of spending time figuring out why it doesn’t work. So I followed my gut feeling that the video might work if I sent it from my iPhone. Accordingly, I bluetoothed the video from my Android to my iPhone, and then Whatsapped it again. This time, the video worked perfectly. I don’t know why the problem happened. It could have been an issue with the WhatsApp on Android compressing videos using a method that’s different from WhatsApp on iOS. Or it could have been a hardware issue with my Android phone, a Redmi Note 4 with 4GB RAM and 64GB storage (which are pretty good specs). Or it could have been a problem with Android itself. What I do know was Apple just worked. In that sense, Apple is perfect for people who would rather spend time ‘doing things’ rather than ‘fixing things.’ I guess that’s why the Apple will always have a strong base of loyal users. However my problem is the situation when Apple ‘just works’ is no longer true. When Apple just doesn’t work Since the migrating to Android route wasn’t working for me, I had to check the reliable online backup route. Only one entity fit the bill. Google. One thing I can vouch for after ten years of using Google apps is that there are no Bermuda Triangles. Google is almost a synonym for reliable. Google’s biggest shortcoming is a loss of privacy. Not to mention all those persevering ads trying to sell me a plethora of hair loss remedies, completely oblivious of the fact that I have a full head of hair. A lot of people I know absolutely refuse to have anything to do with Google for this reason. However having , I figured it was worthwhile for me to to share my data with Google in return for free use of their services. This is probably because I don’t have much to hide. Which means I have more to gain and less to lose in sharing my data with Google. To illustrate, Google’s bots once helped me avoid missing a flight by warning me it was due to leave at 5 am while I was under the impression it was leaving at 5 pm. Google was able to do this because I let them read my mails, and signed in to Google’s notifications. But like I said, sharing data with Google is not for everyone. weighed the pros and cons Photos In fact, Google had already solved my photo backup issue a couple of years ago when it offered unlimited online backup of all my photos in the ‘Google Photos’ app. It’s not in full resolution admittedly, but it’s good enough for me. In fact, it even backs up ‘live’ photos as tiny videos. The problem is the ISPs in India used to have strict restrictions on internet bandwidth and download limits (wifi), and speeds were very slow. But things have improved in recent times. My connection has gone from a miserly 30GB/month @4Mbps two years ago, to an acceptable 300GB @60Mbps now. Cost too has gone down to ₹1250 per month ($20). What clinched the deal is Google offers ‘image’ search. Like I can search for ‘elephant,’ and ‘Google Photos’ will visually identify all the elephants in my photo collection. I found this fascinating enough to merit its . In fact, nowadays if I need to find a photo in a hurry, my go-to app on my iPhone is not Apple’s ‘Photos’ but ‘Google Photos.’ Yup, it just works. own post Setting up automatic photo backup in Google is easy. You first install the ‘Google Photos’ app, and give the app permission to access your ‘Photos’ app. Once the app is up and running, click on the icon with 3- horizontal lines on the app’s top left. This will reveal the settings gear icon. Click on that, then tap on ‘backup and sync,’ and toggle on the switch in the next screen. That’s it. Backing up all my photos on Google Photos Music My Music backup experience on Google was a bit odd. Apple Music and Google Play Music had launched in India with free trial offers, with Google also offering a free backup of all my music (probably to compete with Apple Match). I tried out both the services, and also backed up all my music on Google using the Chrome browser on my Mac (see below). As more free music streaming services came out in India, I discontinued my Apple music subscription, and switched to the free service of Google Play Music. Not surprisingly, it’s supported by ads, which isn’t really a deal breaker as there’s an option to skip the longer video ads similar to the YouTube thingy. Uploading my music to Google Play Music via Chrome Some time later, my favorite Nobel Prize winning singer disappeared from my iTunes. Maddening, no doubt, but I sort of expected it by now from the whimsical iTunes. Out of habit, I checked my Google Play Music library, and was surprised to find my entire uploaded music collection including the missing Dylan album, still available online. I do occasionally buy music from Google so my guess is they see me as a paying customer and let me keep my stuff for free in return. Anyway, as I started downloading my lost music, Bob started singing, “If not for you, My sky would fall.” That captured exactly what I felt for Google at that instant. Contacts Apple’s mysterious disappearing tricks also happens with people in my Contacts app. My plumber once vanished into thin air, a disappearing act that drove me nuts enough to spew out an about it. Again, it was Google to the rescue as I had backed up my contacts. entire post Apple actually makes it easy to back up your contacts with Google on your iPhone. Basically you sync your phone’s contacts with your Gmail contact list. This way, you can always retrieve a contact from your ‘google contacts’ if it goes missing from your iPhone. It’s again simple to set up. First, add your Gmail account to your phone’s Mail app. Then go to Settings and enable contacts syncing. As you can see below, my personal gmail account is set to have contacts to be synced on my iPhone. Backing up my contacts on Google The other advantage of this system is you can keep your work contacts out of your phone to prevent excess clutter in your phone book. If you look at the middle image above, you can see my Work email account doesn’t have contacts synced. I save work contacts directly in my work email phonebook, and leave them there. If I need to have a work contact on my phone, I temporarily put him in my phone book. This does make him to appear in my personal Gmail contacts. But once I’m done with the job, I remove the contact from my phone, and it automatically diasappears from my personal Gmail. Should I ever need his number, I can always locate his details from my work email account. There is a better way to prevent clutter in your phonebook. Group all your work contacts in a group called Work, and then hide the group from within the Contacts app. Anytime you wish to see your work contacts, just tap on the groups link on the top left of your Contact app, and toggle the tick mark back on. This is far more convenient method except for one little issue. You can see groups in the Contacts app but you can’t create Groups in it. You have to go to your browser, sign in to your iCloud, and create the Group there. That’s just a bit too much for me. Why not in the app? Apple may have its reasons but they aren’t saying. However my issues with Apple are not just limited to backup. Image Editing Apple’s Photos offers a lot of options in editing images. But Google’s Snapseed is at altogether another level. Let me explain with one feature. Lots of times, when you shoot someone, you get a good mood shot but the details of the face can’t be seen. Now in Photos, you can brighten the whole image and see details. But doing that causes the rest of the picture to get washed out and you lose the mood. With Snapseed, you can easily brighten one particular area, say the face without brightening the rest of the image and washing out the picture. Saving the Mood: My original image VS whole picture brightened (Photos); and just the face brightened (Snapseed) See above the difference between how Photos and Snapseed fixed the image. What I want to do is see the Buddha’s smile so as to create a contrast with the mysterious jungle with menacing creepers circling around his head. With Photos, you can now see the smile on the Buddha’s face after tweaking the image but there is no more mystery as the dark, creepy jungle effect is gone. On the other hand, Snapseed lets me brighten just the Buddha’s face without losing the mood of the rest of the shot. Of course, this is no big deal for those who use editing software like Photoshop. (In fact, it may be possible to do this within Photos for all I know.) But for layman like me to whom Photoshop is a puzzle, this is a picture saver. In case, you want to know how I did it, here’s a screen recording on my iPhone. Using Snapseed to selectively brighten a small part of an image Basically you open the image from within Snapseed, tap on tools, then tap on ‘Selective’ in the second row, then tap the Buddha’s face, and you will see a ‘B’ appear on his face. Now tap the screen with two fingers apart, and a circle will appear. Slowly pinch your two fingers together till the circle only covers the Buddha’s face (the brightening effect only appears inside the circle). Then touch the screen outside and above the image, and slowly swipe right till the brightness count reads 100. To confirm, tap on the window like icon on the top left which gives me a before-after look. Finally, tap the tick mark at the right bottom corner, and then on ‘export’ which send the reworked image back to my Photos app. Image Scanning Another little gem of an app from Google is for which the closest equivalent on iOS is the scanning feature within the iOS Notes app. But unlike that, it’s perfect for scanning old paper photo albums and uploading it to Google Photos. Photos are usually reflective and it’s hard to scan them with a phone camera. PhotoScan gets around this by ingeniously shooting four shots from four corners of your image, and then combining the four shots to give a perfect scan without any reflections. In effect you are digitising your real Photo albums without having to go through the tedious process of using an actual scanner to scan each image. PhotoScan Maps Apple Maps just doesn’t work in India. It’s literally crippled and can’t give directions to any location, and instead says, ‘Directions are not available between these locations.’ I think Google Maps has too much of a headstart that Apple just stopped trying to catch up. In fact, Google is so clued into India that it offers offline maps. This is ideal for a country where the mobile network is non-existent in lots of places, and mobile data is limited. Apple Maps doesn’t work in India, while Google Maps does As for the real-time location sharing on Google Maps with one touch, I think it’s originally an Apple Maps feature. Since Apple Maps is semi-dysfunctional in India, Google gratefully appropriated this unique iPhone 3D Touch feature for Google Maps. Just hard press on the Google Maps icon, and a ‘Send My Location’ option pops up. It’s perfect for when you are driving, and have only a moment to tell someone where you are. YouTube If I wish to share large videos shot on my iPhone, Apple suggests we use the ‘Shared Albums’ feature of Photos. Unfortunately, this uses iCloud whose free version only offers 5GB of space. This 5GB has to be shared for all photos, documents and all my iDevice backups, which means it usually has very little free space. Apple would like me to buy extra space on iCloud. But that’s not going to happen when Google offers me unlimited space for free on YouTube, the world’s favorite video platform. Sharing videos using YouTube That’s why I upload videos shot on my iPhone to YouTube by default. It’s almost as easy to do as iCloud. Basically you go to Photos where your video is saved, select it, tap the share button at the bottom, and then choose YouTube from the share options. You can even ensure your video’s privacy by choosing ‘Private,’ which means only those you share its link with can view it. Mail Apple does give me a free iCloud email, but it’s not half as good as Gmail. So like almost everyone else on Planet Earth, I rely on a Gmail account. For everyday use, I operate my Gmail via the stock Mail app as it’s simple to set up. But Mail is limited in its capabilities, especially search. If the Mail app can’t find something, I usually fire up Google’s Gmail app which easily finds what I am looking for. I know there are many other good email apps. But sometimes having too many email apps to choose from is more stressful than whatever email issues I have. So I stick with combination of Mail and Gmail apps. Apple’s Mail app search feature falls short when compared to the Gmail app Google Drive and Docs Unlike the previous apps, I use these in tandem with Apple’s apps. iCloud is perfect for backing up my phone, and works seamlessly with online docs like Pages and Numbers. But I also use Google Docs as it’s easier to share across platforms. Space on iCloud is also an issue as I mentioned earlier. Google Drive is that way a far more convenient online vault as it allows me to share large files without having to worry about running out of space. Of course, there are other custom apps for large file transfers like Dropbox and WeTransfer. But that often leads to “Now where on earth did I put that file?” situations, which I would rather avoid. iCloud works seamlessly with Apple but limited space makes Google Drive a dependable standby News Google is not always the best alternative when an Apple app falls short. News is one instance where neither Apple nor Google really stand out from the other news apps. Others apps like Flipboard are more popular, at least here in India. Apple News vs Google Feed vs Flipkart — there’s no clear winner There are many more ways in which Google is deeply woven into Apple and improves my whole iPhone experience . Like every time I type something on my iPhone, I do it via , Google’s amazingly accurate swipe-to-type keyboard (it’s also a mini Google, a GIF maker and much more). To get something translated into another languages, I use . To know how to pronounce a word, I type define: xyz in my Safari browser. To play videos from my phone on my TV, I use the app (you need Google’s Chromecast device). To transfer money, I go to . To know if a flight is on time, I just feed in the Flight Number in Google… Gboard Google Translate Google Home Tez One last question. Why don’t I just get the Pixel 2XL, Google’s challenger to the iPhone? Maybe I should. Or maybe I’m just plain greedy and want the best of the two worlds of Apple and Google. That may explain things as I belong to the ‘mixed breeds are healthier than purebreds’ school of thought. iPhoogle - arguably the world’s best phone In short, I love my iPhone, but I love it better when it’s running on Google.

Apple ‘just works’ better when it piggybacks on Google

Finance has come a long way from the days when people joked about hiding money under their mattresses or in their couch cushions. The crypto industry is responsible for a large portion of this innovation, but the irony is that many individuals are now hiding their crypto wallets' seed phrases (which they use to access their money) in places not much more secure than under their beds! Janine Grainger, Founder and CEO of Easy Crypto, looks at whether seed phrases and their associated vulnerabilities are an inevitable part of the crypto journey, or whether continued innovation in the industry has more to offer… First Things First - What’s Wrong With Seed Phrases? Seed phrases are effectively the master key to your cryptocurrency. They offer you full control over your digital assets without reliance on any other party (such as a bank, a credit company, or an exchange). However, with that freedom comes responsibility, and “being your own bank” means that there’s no call center there for you if you forget your password. Seed phrases need to be kept safe from attackers whilst always being accessible to the owner. This is not an insignificant challenge, and for this reason, ‘Lost Bitcoin’ is an official term! It refers to Bitcoin that the current owner can't locate either because they forgot their private key or have lost their hardware wallet device. Estimates suggest that around 6 million Bitcoin, or 30% of Bitcoin's supply, have been irretrievably lost, amounting to $554 billion in value. Having phrases on a piece of easy-to-lose paper or on a USB device (or pic on your phone or laptop) really is akin to stepping back in time; when the goal of crypto has always been to move us towards the future of money - where control over your assets shouldn’t come at the expense of peace of mind... Just Keep These 12 Words Somewhere You Can Find Them, but No One Else Can… If someone else gets hold of your seed phrase (e.g., by stealing your backup or hacking into your phone), they can access and take all your crypto. Even the ‘gold standard’ of security - hardware wallets - need to have the seed phrase backed up somewhere, leaving your crypto only as secure as your backup location (which hopefully is not under your mattress!)… A lot of wallets look largely the same as they did a decade ago, and wallet help desks are still fielding calls from panicked users whose wallets have been emptied using stolen seed phrases. Malware and viruses have been developed to search files for lists of seed phrase words, and one enterprising scammer even developed a photo editing app that would search people’s albums to search for screenshots of seed phrases. As crypto has become more common, so have these hacks that target seed phrases, leading many in the industry to ask whether there is a way that we can minimize the risk of accidental loss or theft. Could a post-seed phrase world offer much better protection and control? Wallet Innovators Have Moved On… In pursuit of both simplicity and security, today’s wallet innovators believe that self-custody doesn't mean using a seed phrase. You can own your own funds while taking advantage of the backup and protection of third-party software that not only enables you to sign transactions but, importantly, gives you options around how you secure and protect your funds. have to This innovation taps into the use of technologies like Multi-Party Computation (MPC). This approach involves the use of key 'shards' rather than entire seed phrases to authorize transactions, together with secure software. This still provides a user effective control over their assets with the ability to integrate safeguards such as Two-Factor Authentication (2FA). (You have no option for 2FA with a seed phrase - pretty terrifying when you think about it!) ‘But hang on, isn't reliance on third parties what we are trying to avoid?’ you might say. With seedless wallets, reliance shifts to software that approves transactions based on predetermined conditions, such as 2FA. In the future, it’s likely that this software itself could be a self-governing entity operating on blockchain technology (called a Decentralised Autonomous Organisation) using smart (or automated) contracts that eliminate the need for a centralized authority. This would ensure wallets are censorship-resistant and less dependent on a single entity. Ok, but How Would Recovery Work With No Seed Phrase? This, too, is becoming a lot simpler… Social recovery The introduction of novel social recovery options is making wallet recovery more accessible. Social recovery involves designating trusted individuals (friends, family, your lawyer, or even automated systems) to help you in the recovery process. If you lose access to your wallet, they would simply be sent a link to verify your identity. Cloud backup The use of encrypted cloud backup for password recovery adds an additional layer of convenience. Unlike downloadable files containing your entire seed phrase, cloud backups allow wallet apps to automatically verify the existence of the (password-protected) backup file, prompting users to create a new one if necessary (for example, accidental deletion). One prominent wallet recently announced a staggering 55% surge in active users within a span of four months, reaching over 30 million users by January. As wallet adoption and the crypto space continue to evolve, so too will the tools and methods that empower individuals to navigate it. While some people will always want to use a seed phrase, most users (particularly beginners) want something that is easy, safe, and just works ‘out of the box.’ This is what MPC enables and will hopefully see the term ‘Lost Bitcoin’ become a thing of the past.

The Future of Crypto Wallets - Do We Really Need Seed Phrases?

You know what’s cooler than using an image when building a website? How about making something with HTML and CSS that looks and acts like an image? And you know what, this is super easy now with container queries. In this post, we’re going to make an ad, that looks like an image, with HTML and CSS. Then we’re going to make it act like an image as it gets squished, expanded, and moved to other locations within the document. Ok, let’s check it out! https://youtu.be/5ugwp7HlpGs?embedable=true Ok, so we have this Vans ad in the sidebar of the site that we are building, and it’s currently an image. This makes it difficult to edit; a designer would need to update it and provide us with a new image if something needed to change. Also, we’d probably need multiple versions to use with the source set so that it will look crisp on both high-density and low-resolution displays. So, we’re tasked with converting it to HTML; how can we do this? Some Downsides to Using Images and Viewport Units Well, we could probably use viewport units, but we’d need to add extra code if we were to put the ad in different locations where its dimensions would be different since everything would be based off the viewport and not the container dimensions. So, we could pull it off, but it could get a little messy. Instead, we could use container queries and container query units. Container queries are a little like media queries but based off the dimensions of any given container in the page instead of the overall viewport. Setting up a Container With the CSS Property container-type Ok, let’s check out what we’re starting with. So, it looks pretty good right here but, how does it do as it responds? Uh, the text and borders don’t change size, so it needs some love cause it’s pretty broken as it stands. Now, one thing we’re already doing here is, we’re using an which allows the container to respond as an image would so, that’s all good. aspect-ratio figure {
    aspect-ratio: 1 / 1.5;
} We just need to change all the dimensions for the content to make it respond correctly too. The first step here is to provide a container to monitor our dimensions. This will be our figure element. To use container queries here, we need to define what is known as a containment context. We can do this with the property. For this example, we can use a value of inline size. container-type figure {
    ...
    container-type: inline-size;
} This is going to set up a container that will size things based off its inline size which, in this case, will be the width of the figure. Alright, so now we have a container to monitor, so we’re now free to use container query units. And, there’s lots to choose from. We can use any of these unit values: cqw cqh cqi cqb cqmin cqmax Here, we’re going to use which, I believe, stands for container query inline. One unit is equal to one percent of the width of the container. Ok, that’s all we need; from here, we’re just setting units as needed. cqi cqi Here, we have a couple of custom properties that are used on several elements within this ad. figure {
    ...
    --frameInset: 0.5rem;
    --frameStyle: solid 0.25rem currentColor;
} Let’s start with the amount this frame is inset from the outer edge of the container. Let’s make it three . cqi figure {
    ...
    --frameInset: 3cqi;
} Next, let’s set the thickness of the borders here. In this case, I’m going to use the function to prevent the borders from ever-shrinking under one pixel, but I want them to be dynamic as long as they are larger than that one-pixel value. max So, the first value is one pixel, then the second is the dynamic value. Let’s make it one . cqi figure {
    ...
    --frameStyle: solid max(1px, 1cqi) currentColor;
} Now, for the element, which is the main title, the "Vans" text, let’s make it twenty-five . And, for the space underneath the title, let’s make it three . strong cqi cqi strong {
    font-size: 25cqi;
    padding-bottom: 3cqi;
} Now, let’s move to the "Off the Wall" subtitle. It should be about half the size of the main title, so let’s try twelve . And, for the space above the text, let’s go with three again. cqi cqi em {
    font-size: 12cqi;
    padding-top: 3cqi;
} Alright, for the last piece, the "Since 1966" label, let’s go with a font size of six . And, for the space above and below, we’re using the logical property for which takes up to two values. The first value is the value above the text, and the second value is for the space below. cqi padding-block So, let’s go with two above. And, in our calculation, we’ll leave the as is, but we’ll go with five of additional space. cqi --frameInset cqi time {
    font-size: 6cqi;
    padding-block: 2cqi calc(5cqi + var(--frameInset));
} Ok cool, this looks good. Let’s take a look at how it responds. As we squeeze it, everything is properly responding uniformly like we wanted. It looks a lot like an image. It looks pretty good even when it’s small, and you can see that the borders never shrink below one pixel. Then, when we get into really narrow widths it gets wider, and everything still looks great. How cool is this? One set of styles, and it just works all the way through. As we scale it back and forth, it looks great. Now, what’s even more cool is that we can take our ad mark-up, move it to or main column region here, and everything continues to work just like it would if it were an image. <header><h1>A Brief History of Vans</h1></header>
<div class="content">
    <main>
        <figure>
            <svg viewBox="0 0 256 256">
                <path d="M90.4,67.9C88,69,87.1,70.6,83,80c-4.4,10.2-4.8,12.3-3.1,15"/>
                <path d="M97.4,95.2c-0.6,0.6-1.2,1.7-1.2,2.3s0"/>
            </svg>
            <figcaption>
                <strong>Vans</strong>
                <em>Off the Wall</em>
                <time>Since 1966</time>
            </figcaption>
        </figure>
        ...
    </main>
</div> This is just so nice and so cool. Remember, there’s only one set of styles to pull all of this off. And, zero media queries were involved. There’s quite a bit more to container queries as a whole, so be on the lookout for future posts where I cover different aspects. Want to See It in Action? Check out the demo code and examples of these techniques in the Codepen example below. If you have any questions or thoughts, don’t hesitate to leave a comment. https://codepen.io/brianmtreese/pen/poGegXB?embedable=true

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**PANAMA, February 5th, 2024/Chainwire/--**The Protocol Foundation has launched a to drive growth in Taraxa’s unique EVM-compatible blockDAG Layer-1 ecosystem, after an overwhelmingly successful on-chain governance approval. Taraxa $10 million Grant Program The Taraxa Grant Program is open to any individual, team, and organizations of any type. Funds will be granted specifically for technical development with an emphasis on driving usage and growth within the Taraxa ecosystem, and are disbursed according to quantifiable milestones. Building on Taraxa presents a unique opportunity for developers to experience the benefits of the world’s first and only native EVM-compatible decentralized network built with the blockDAG architecture. Here are just a few of the reasons why builders should consider building the next big idea on Taraxa. An unique opportunity to Build on blockDAG: blockDAG is the next evolutionary step up from block-chain, able to achieve stunning throughput and low latency without sacrificing security and decentralization by enabling parallel block processing on the network instead of just one block at a time. True EVM Compatibility: any dApp that works on Ethereum just works on Taraxa, no need to learn new languages, frameworks, or tooling. Fast & Low-Cost: with peak throughput of 5k TPS, sub-second block times, instant block inclusion, and under 4-second finalization, working on Taraxa is fast & smooth, with each transaction costing next to nothing. True Finality: zero risk of transactions being reversed, Taraxa’s True Finality guarantees that when a transaction is finalized (under 4 seconds), it is finalized forever. Front-Running Prevention: Taraxa’s architecture and speed minimize and fragment the network’s mem pool, making it almost impossible and definitively unprofitable for DeFi transactions to be targeted for front-running. Supportive Community: Taraxa’s community is highly engaged and the development team is helpful to a fault. Not only will the user be building on a network backed by the best technology in the world, but he will also receive the full support, attention, and participation from Taraxa’s community! The upcoming Ficus Root Bridge in mid-2024 further strengthens the Taraxa ecosystem’s utility, asset diversity, and cross-chain liquidity. DeFi builders don’t have to worry about fragmented assets or liquidity, since they flow seamlessly between Ethereum and Taraxa. The bridge, coupled with Taraxa’s fast, low-cost and natively EVM-compatibility, make Taraxa a natural Layer-2 solution for dApps or consensus layer for rollups. Developers can today and pitch their ideas on how to creatively leverage decentralization to solve problems! apply to the Taraxa Grant Program About Taraxa Founded by two Stanford engineers in 2018, Taraxa is an EVM-compatible smart contract platform based on t-Graph consensus utilizing blockDAG, with many world-first technical innovations on top of the blockDAG architecture. After launching its mainnet in 2023, Taraxa represents the next evolutionary step in decentralized networks. Contact Taraxa Protocol Foundation foundation@taraxa.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program . here

Taraxa Launches $10 Million Grant Program For Its BlockDAG Ecosystem

Designing a serverless system can be complex, and without knowing the internal workings of the services, you could easily lose the data. A steep learning curve is the main drawback of building serverless applications on . AWS could do a better job of making an ideal developer experience. We’ve seen some small improvements, but the ideal platform is still far away. Not only that, the development experience could be better. There are many cases where the actual behavior goes against the initial developer expectation, and you can easily lose data or get unexpected results without a deep understanding of . A good platform should abstract the details from the developer. But that is not the case with AWS. AWS AWS services Let’s start with common ground. In more traditional, non-event-driven systems, you write data directly to the database, and losing data means that there is an issue with the database. But serverless systems are, in a large portion, event-driven systems, and data is eventually consistent. Putting data/events into such a system does not necessarily mean that it is immediately written to the database. It can be passed between several event busses, pub-sub, and event streaming systems … and, in most cases, ends up in a database, like DynamoDB, which is by its nature eventually consistent. If you put data/event into such a system and it does not eventually end up at the destination or you do not get it when retrieving from the database, you have a problem. The data could also be lost, duplicated, you get older records than expected, etc. NoSQL This article’s title mentions losing data, but we will actually cover all these cases. Content Overview - Nine Ways to Lose Data Using Serverless without Even Knowing It Duplicate and Unordered Events Bulk Operations Eventually Consistent DynamoDB Filter Dead Letter Queue Messages are Lost After the Retention Period A Poison Pill Message Can Also Cause the Following Messages to be Lost Lagging Behind When Processing Data Throttling Missing/Misconfigured DLQ and Maximum Retry Exceeded 1. Duplicate and Unordered Events This is the most common way for your data to be deformed. Most services do not guarantee order and exactly-once delivery. SQS FIFO and SNS FIFO provide that, and stream-based systems like DynamoDB Streams and Kinesis Streams provide order guarantees. SQS FIFO and SNS FIFO are less scalable and more expensive than their regular counterparts, and you should only use them if you have solid reasons to. In most cases, you should expect the events to be triggered unordered, and they can be duplicated. Handling unordered messages means that you should not override the new record with the older record received afterward. Handling duplicated events means that the system should be . For example, if you receive a charge on your bank account, you should check that the same transaction was not already processed. idempotent Most AWS services do not guarantee order and exactly once delivery. You should ensure your system is idempotent. Although most developers know this, it goes against basic intuition, and we quite easily forget that Lambda subscribed to SQS, SNS, and EventBridge can be triggered multiple times with the same payload. But there is the same case with other, less-used services. If you save data to , the same problem can occur. Kinesis Firehose can duplicate records. Athena behaves like an SQL database, but that does not mean that it has all the constraints that SQL databases have. Records with the same ID can quite easily be duplicated, and queries that do not anticipate that would return wrong results. S3 via Kinesis Firehose and queried by Athena Athena behaves like an SQL database but does not have constraints. Records with the same ID can be duplicated. 2. Bulk Operations This is probably the most dangerous thing that developers often forget because it goes against basic intuition. What would you expect if one or more records failed when bulk inserting into SQS, SNS, EventBridge, DynamoDB, or Kinesis? Well, if you expected the SDK to throw an error, so the problem is logged, and maybe the whole process can be retried or dropped to some Deal Letter Queue (DLQ) ... you would be wrong. You will not know if you have lost the data if you do not check that list. The problems go further with read operations. If you do a bulk get operation on DynamoDB and do not receive some records, you would expect that the records do not exist. Wrong again. The SDK returns records that it managed to get and also the records that it failed to process (field ), SDK does not throw an error. It just returns the list of failed records. UnprocessedKeys but that does not mean that the records are not in the database. Failed bulk operations using AWS SDK do not throw an error. You might been losing data. The funny thing is that SDK for EventBridge does not even have a non-bulk operation. So even if you put one record in, you still use a bulk approach and may lose the data if you do not check the result ( field). FailedEntryCount Failure with bulk operations may happen more frequently than with regular operations because sending a lot of data could overload the system, which could fail/throttle on more records. You should customize the settings on how the SDK communicates with the service and how the retry and backoff mechanism works. where default settings are not optimal, especially when using Lambda. You can read more about that . You should do that for DynamoDB, here 3. Eventually Consistent As mentioned, with event-driven architecture and especially a NoSQL database (e.g., DynamoDB), which are, in essence, eventually consistent, you will, in most cases, not know if the database will return the latest data. That is by design in most distributed systems. But it goes against our intuition, especially when using the database. DynamoDB is eventually consistent, so you might not get the data you just saved. For the operations on the Primary Index or Local Second Index, you can force DynamoDB to provide consistent data, which is twice as expensive. But you cannot do that when you query the Global Second Index, which is more often used. The delay until the index is synchronized could be substantial if you insert a lot of data. The easiest solution is not to retrieve data immediately after inserting, but it might not be feasible. For example, in a synchronous process, the user expects the response immediately. If you decide to wait a while, you will not know how long the delay should be. You could insert and retrieve a record and get a previous record back. 4. DynamoDB Filter DynamoDB is one of the more dangerous services that can cause loss of data or receive unexpected results if you do not know how the database works in detail. I already mentioned the bulk operations and eventual consistency. Those are more generic problems. Issues regarding the DynamoDB filter are unique. DynamoDB has a filter operation, which, as the name implies, removes undesired items from the resultset. When you use the DynamoDB Filter, you might not get any data, although there are matching records in the database. 😱😱😱 Let's first refresh how DynamoDB works. DynamoDB returns 1MB of data or up to the number of records defined by the limit parameter. Then the filter is applied. Data is then sent to the consumer. If you set the limit to 10 records and set a filter, DynamoDB would retrieve 10 records and then apply the filter. If some or all of those records do not meet the filter criteria, they will not be returned. This means that you will receive less than 10 records or . You could check the to see if there are more records, but why would you if your intuition tells you that you received less than the requested 10 records? The same goes even if you do not use the limit. DynamoDB retrieves 1MB of data from the storage, applies the filter, and returns results that could again be empty, although there are matching records in the database. That is clearly stated in the , but if you are new to DynamoDB, that is quite unexpected. possibly zero, although there could be millions of matching records in the database LastEvaluatedKey documentation 5. Dead Letter Queue Messages are Lost After the Retention Period A Dead Letter Queue (DLQ) pattern in event-driven/asynchronous systems is used to drop messages that failed to process so they are not lost. Those messages should be either inspected manually or by an automatic system and returned ("redrived") to the system when the problem is resolved. But if you are building the automatic system, do not just retry all failed messages because you could cause an endless loop, which would be very expensive. If the SQS queue is used for DLQ, If you do not process them until the retention period is over, they are lost. the records in DLQ are not stored forever. Saving data to the Dead Letter Queue might not prevent data loss if you forget to act upon the alarm 🚨 message. The first thing that you should do when configuring a DLQ is to set it to a maximum retention period and configure an alarm so that you are notified if some messages are dropped there. You should also not forget to configure a subscription to the alarm, which can quite easily be overlooked. Finally, you should also respond to the alarm message, which could be the most problematic part because it involves human intervention. Failing to process the message should occur quite rarely, and once the issue occurs, the person notified may not respond because they may not know or remember what the message is about. There is also a common problem with alert fatigue because of too many messages, and people start ignoring them. This could also happen to experienced teams. 6. A Poison Pill Message Can Also Cause the Following Messages to be Lost This problem occurs when using FIFO SQS, FIFO SNS, DynamoDB Streams, and Kinesis Streams without configuring DLQ. What happens if you encounter a record, commonly known as a poison pill message, that you cannot process? If the default configuration is used, the record keeps on retrying indefinitely. Those services guarantee the order, so no other record in that FIFO group or Kinesis/DynamoDB Streams shard/partition will be processed. But all those services do not store the data indefinitely. SQS stores it by default for 4 days, extendable to 14 days, DynamoDB Streams for 1 day, extendable to 7 days, and Kinesis Streams for 1 day, extendable to 1 year. So, if the issue with the problematic message is not resolved by then, you will lose all the data older than that, not just that poison pill message. A Poison Pill Message 💊 can cause the loss of all old data in FIFO SQS, FIFO SNS, DynamoDB Streams, and Kinesis Streams. Knowing that, you should configure a DLQ where messages will go after several failed retries. But here is a second problem. Those services guarantee order, which is, of course, lost if some messages are skipped. 7. Lagging Behind When Processing Data Lambda attached to SQS, Kinesis Streams, and DynamoDB Streams is processing the data. What happens when the Lambda cannot keep up because: processing is too time-consuming downstream service cannot handle the load low reserved concurrency low maximum concurrency (SQS only) small batches the data is not sufficiently parallel processed due to hotkeys in DynamoDB not enough or unbalanced shards in Kinesis Streams? In that case, the data is coming faster than it is processing. (see the part about the Poison Pill). Then you start losing messages. Records in the system are becoming old and could be older than the retention period If you are slow with processing ⌛, you can lose the data in SQS, Kinesis Streams, and DynamoDB Streams if data exceeds the retention period. You should configure an alarm for metrics that indicate unprocessed messages are becoming old: for Lambda attaches to Kinesis Streams and DynamoDB Streams IteratorAge for Lambda attached to SQS ApproximateAgeOfOldestMessage for Lambdas executed asynchronously AsyncEventAge 8. Throttling When the load hits the predefined quotes/limits, the system starts to reject requests. All AWS services have a lot of predefined quotes. Some are soft, meaning that you can increase them by sending a request to AWS. In the asynchronous process, if you configure DLQ, Lambda Destination, or a similar mechanism that the system can use to store rejected messages, later, . But in the synchronous process, like HTTP requests hitting API Gateway and then directly database, those requests are lost because the client/user expects the response right away. First, for all the quotes that you are likely to hit. It is impossible to list them all, but the first one in your mind should be . In most accounts, the default limit is 1,000. This is easily hit with a high load. You should do load testing if you intend to build a service that expects a high load. you can still process them when you resolve the issue, or the load is lower you should configure alarms Lambda account concurrency limit You should do load testing if you intend to build a service that expects a high load. 9. Missing/Misconfigured DLQ and Maximum Retry Exceeded Without DLQ, when retries are exhausted, you will lose the message. Each service has different ways and different options to configure retries. Another story is configuring DLQ correctly, which is a challenge on its own, and it would be hard to find a better example of a bad developer experience. Let's go step by step. Mostly, it depends on the . invocation mode The challenge of the day. Try to correctly configure the Dead Letter Queue in AWS. 🫣 Asynchronous invocation: SNS, EventBridge, S3, and many other services invoke Lambda asynchronously. In that case, you need to configure two DLQs: For SNS and EventBridge, only the SQS queue can be configured as DLQ. In DLQ, messages are dropped if the service fails to send them to the target and not if the target fails to process them. If the target is Lambda, it tries to deliver to the internal asynchronous Lambda queue. They go here only if the target service is unable to process or permissions are insufficient. Apart from configuring DLQ, you also must pay attention to how the retry mechanism works. This is not the retry mechanism for how many times the target Lambda is retried! It is a configuration of how many times it retries to put a message to the internal Lambda queue, which succeeds almost every time. DLQ on the service side (SNS, EventBridge, …) You will not see many messages in this DLQ. In this DLQ, messages go when invoking a Lambda fails. This does not need to be the SQS queue. It can also be an SNS topic. Or it can be replaced or supplemented by newer Lambda Destination, which is a better solution, but the principle is the same. Lambda Destination can also send messages when Lambda succeeds, not just when it fails. Lambda Destination, in addition to SQS, supports sending messages to other destinations like Lambda function, SNS, or EventBridge. Additionally, it provides previously unavailable error details. DLQ on the Lambda side Lambda invoked asynchronously: Lambda Destination: When you execute Lambda functions asynchronously by yourself, you also need to configure DLQ/Lambda Destination, but only the one on the Lambda side because no service is invoking the Lambda. Lambda attached to SQS (Polling invocation): In this case, you should configure the DLQ on the SQS side only. DLQ or Lambda Destination on the Lambda side will not work because the Lambda is not executed asynchronously. Lambda synchronously polling batches of messages from SQS: Lambda attached to DynamoDB Streams or Kinesis Streams (Polling invocation): This configuration is, again, completely different. When configuring the trigger, you can configure DLQ, which can be an SQS queue or SNS topic. You must configure only one DLQ, not two, like on SNS or EventBridge. The DLQ does not receive a failed message nor any error details. You get a position of the message, which you can get from the stream (if it is not past the retention period). The configured DLQ in the AWS console is also visible as Lambda Destination, although this is not an asynchronous Lambda Destination mentioned above, but a stream Lambda Destination. The destination can only be SQS or SNS, but not Lambda or EventBridge. Talk about total confusion! Synchronous invocation No DLQ here because it is not an asynchronous operation. Read more about Implementing , , and . AWS Lambda error handling patterns retry mechanisms configuring DLQ Also published here.

Nine Data loss Pitfalls in Serverless Computing

The world of web applications is rapidly undergoing a fundamental shift from web2 to web3 technologies, with decentralization and composability at the heart of this transformation. For dApp developers, this shift is not just a trend but a necessity. Decentralized databases, exemplified by permanent storage solutions like are becoming the backbone of secure, scalable, and user-centric applications. Arweave What Actually Is a Database? Technically, just an “organized set of data held in a computer.” In theory, this means that anything more structured than a pile of files on a disk somewhere can be called a database. In practice, it’s more specific than that. a database is Databases of course provide a place to put files, but most importantly, they provide . A schema plus a query layer. In this sense, Arweave itself is a database -- one big pool of data, searchable with GraphQL. tools to find the exact data an application needs The catch is that in permissionless systems, it’s a matter of bottom-up standards, not top-down schemas. The Atomic Asset (SWS-1) and Asset Discoverability (ANS-110) standards both specify ways to make Arweave data easy to find and use in any application, promoting interoperability. The Rise of Decentralized Databases Censorship, rent-seeking, data availability problems. Decentralized databases have emerged as the antidote to these pitfalls of centralization. They offer unparalleled security, data immutability, and user sovereignty. , for instance, epitomizes this with its "pay once, store forever" model, making it a cost-effective and pro-user solution for permanent dApp state storage. Arweave In the Arweave ecosystem alone, teams at , , , , and more are working to provide developers with a way to easily use and query Arweave with familiar syntax. Kwil WeaveDB HollowDB Glacier Empowering dApp Developers Security and Immutability The decentralized nature of these databases ensures that once data is stored, it becomes immutable. This is ideal for applications requiring secure, tamper-proof systems. Scalability and Flexibility Decentralized databases scale effortlessly with your application. The architecture of decentralized databases ensures data availability even if some nodes go offline, offering a reliable and scalable solution. User-Centric Design Decentralized databases give users unprecedented control over their data. It’s being stored with whatever database layer you choose, but it’s also there forever on Arweave, and no one can take that away. A compelling feature for dApps aiming to be more user-centric via data portability. Cost Efficiency The absence of central servers means no regular maintenance or need to provision infrastructure, reducing operational costs. The Evolution From Centralization In the Web2 era, centralized databases were the go-to solution for data storage and management. While they offered a controlled environment, their limitations were glaring: susceptibility to hacks, high maintenance costs, and being a single point of failure. However, certain centralized elements, such as APIs and caching layers, still hold value and have been integrated into this new generation of databases. The Hybrid Future: Best of Both Worlds While decentralization offers numerous advantages, a balanced approach that incorporates elements of centralization can be incredibly powerful. After all, the blockchain trilemma states that a system weighted towards decentralization and security will sacrifice scalability. Base layer Arweave is both secure and decentralized, but without centralized helpers (caches, gateway magic, APIs, etc.) databases that leverage it can’t provide the experience users or developers have grown to demand -- we’re accustomed to web2. What was once considered blazingly fast now ™, and anything less capable isn’t an acceptable choice for most developers. just works This hybrid model -- a decentralized base with centralized, hot-swappable helper layers -- acts as a bridge between what web2 expects and what web3 enables. Real 🌏 Impact Decentralized databases are making significant inroads in various sectors, from supply chain management and healthcare to financial services. Arweave's permanence is particularly useful in applications requiring long-term data availability. “WeaveDB can replace centralized databases in all cases,” says founder LensPlay Sahil Kakwani. “It's a standout choice for applications requiring decentralization, resilience, and high performance.” In another WeaveDB user interview, founder Harang Ju noted that decentralized solutions “will easily replace traditional centralized databases in places where transparency and openness are key.” Tepe While building the MEM explorer, the Decent Land Labs team implemented Kwil as an alternative to directly querying MEM interactions from the Arweave L1 chain. Compared to the GraphQL option, which takes several seconds, Kwil is able to return data almost instantly. While mainstream adoption may be a little while down the road, essential components are being built and battle-tested in preparation. Where We Stand… At Decent Land Labs, we believe in user sovereignty, data composability, and the . The future is not just decentralized, it’s also hybrid, leveraging the strengths of both centralization to create highly capable, scalable, and interoperable systems with a strong foundation. storage-based computing paradigm By embracing this shift and leveraging hybrid solutions along with the data permanence decentralization offers, developers are not just following a trend; they are preparing themselves for the future. Check out for more insight on how to integrate your dApps today! docs.mem.tech If you enjoyed our content, please and feel free to comment below! SUBSCRIBE Our new protocol release Molecular Execution Machine is now live! - Beta Testing Sign Up mem.tech

The Decentralized Database Revolution

La revolución de las bases de datos descentralizadas

La révolution des bases de données décentralisées

विकेंद्रीकृत डेटाबेस क्रांति

分散型データベース革命

A revolução do banco de dados descentralizado

Cuộc cách mạng cơ sở dữ liệu phi tập trung

去中心化数据库革命

In today's digital world, information has become the lifeblood of progress and empowerment. With unprecedented access to vast amounts of data, individuals and organisations can make informed decisions, innovate rapidly, and connect globally. However, the significance of information also underscores the need for responsible dissemination, critical evaluation, and safeguarding of data to ensure that the benefits of the digital age are harnessed effectively while minimising potential risks. But what exactly is information? Can we measure it? How do we actually communicate information over the internet or any other medium? What do social media apps and all electronic communications have in common? How did we get to today’s digital age? The answer to the questions above dates back to the 1940s. A story about a visionary endeavour that proved to be not just successful, but transformative, reshaping the course of history itself. An endeavour that seamlessly intertwined engineering, science, and mathematics. From the crucible of this endeavour arose a nascent discipline known as information theory, which would go on to serve as the bedrock for the communication infrastructure that underpins today’s digital world. While one might anticipate that a realm as expansive as information theory sprang forth from the collaborative synergy of numerous mathematicians, scientists, and engineers, history takes an intriguing twist. In a remarkable turn of events, it appears that this domain was the culmination of a solitary individual's decade-long endeavour. The genius behind this transformative feat was none other than Claude Elwood Shannon. Transforming Circuit Design From Art To Science In a convergence of diverse knowledge and unquenchable curiosity, Shannon's journey unfolded. Armed with dual bachelor's degrees in Mathematics and Electrical Engineering, he took an unexpected turn. A seemingly incidental philosophy course, undertaken to fulfill a university requirement, introduced him to the works of George Boole, the autodidact English logician of the 19th century. Shannon applied Boolean algebra in switching circuits in his master’s degree thesis. According to many people it was the most important master’s thesis of the twentieth century. The starting point of digital circuit design, a transformative work that turned circuit design from an art into a science. Because of this thesis, circuit design is no longer a trial and error process. Designs can be tested mathematically, before they are built. Nowadays, engineers routinely design computer hardware, software and complex systems with the aid of Boolean algebra. Before Shannon's master thesis, small devices that use magnetism to open and close electrical switches, called electromagnetic relays, were used to build circuits that routed telephone calls. However, there was no consistent theory on how to design or analyse such circuits. People thought about them in terms of the relay coils being energised or not. Shannon used Boolean algebra to make abstractions. He shifted the focus from the relays themselves to the function of a circuit. He used this algebra of logic to analyze, and then synthesise, switching circuits and to prove that the overall circuit worked as desired. This is when the AND, OR, and NOT logic gates were invented. Logic gates are the building blocks of all digital circuits, upon which computers and computer science is based. Connections to artificial intelligence But if there is a way to apply laws of thought in switching circuits, we can apply human thought in machines. Shannon’s master’s thesis also lays the foundation of the idea that machines could be made to think. The public response During the 1940’s, applying Boolean algebra in electronic circuits was shocking. It was completely unexpected and many thought that however interesting, it was purely theoretical. Life has proved them wrong, however! When looking under specialised glasses and when our background is not diverse enough, it's often difficult to see the magic that lies underneath. Science, Engineering and Mathematics: The Marriage Science seeks the basic laws of nature. Mathematics is the universal language of logic that searches for new theorems to build upon the old. Engineering builds systems to solve human needs. The three disciplines are distinct, yet interdependent. It is knowledge as diverse as it spans all three disciplines, that resulted in groundbreaking social and technological changes. Turning special cases into a unifying theory Up to the 1940’s, any attempt for electronic communications was considered as a special case that demanded special theories and implementation tools. The huge advance at that time was the discovery of how to use electricity to communicate. For example, remote communication was done using analogue signals. Sending a message involved turning it into varying pulses of voltage along a wire, which could be measured at the other end and interpreted back into words. This works quite well for short distances but for long distances it becomes unusable. Every meter that an analogue electrical signal travels along a wire, it gets weaker and suffers more from random fluctuations, known as noise. One option was to boost the signal but this would result in boosting noise too. Special cases were unified and problems were solved in light of Shannon’s monumental paper in 1948, titled: “A mathematical theory of communication”. A mathematical theory of communication Shannon thought about the problem of communication in a radically new way. The basic problem was how to get a message from one place to another, fast and reliably, even when the two places are very far apart. He asked questions that no one has asked. What exactly is information and is there a universal theory that could allow perfect communication? Here is a snapshot of his thoughts: “The fundamental problem of communication is that of reproducing at one point either exactly or approximately a message selected at another point. Frequently the messages have meaning; that is they refer to or are correlated according to some system with certain physical or conceptual entities. These semantic aspects of communication are irrelevant to the engineering problem. The significant aspect is that the actual message is one selected from a set of possible messages. The system must be designed to operate for each possible selection, not just the one which will actually be chosen since this is unknown at the time of design.” Information and meaning To make information measurable, Shannon disregarded semantic content. Information has nothing to do with what we understand or not. Let’s say that we’ve learned the news from the media and most of it did not make much sense. We did get information. What kind of information we’ve got was not considered to be a communications engineering problem. Although it may sound counterintuitive and maybe even restrictive that information has nothing to do with content and meaning, treating information as such was a radical idea that made possible what seemed to be impossible. Measuring information According to information theory, information is the amount of uncertainty and it’s measured in bits. Assume for example that we throw a fair dice once. Since a fair dice will give a number from 1 to 6 with equal probability, the information that we get by throwing the dice will be equal to the logarithm of base 2 of 6. This is approximately 2.58 bits of information. The invention of the “bit” catalysed the birth of information theory and ignited an explosion of innovation that continues to shape industries, economies, and societies. The bit's simplicity, in the form of binary code, belies its profound impact, underscoring the adage that sometimes the smallest units of thought hold the power to reshape the entire world. Communicating information If we communicate and say nothing new to each other, we exchange no information. After all, if you knew in advance what I would write in this article, what would be the point of writing it? Shifting the communication problem Traditionally, the problem of communications engineering was primarily viewed as a deterministic signal-reconstruction problem: Given that a transmitted signal is distorted by a physical medium, try to transform the received signal in order to reconstruct the original as accurately as possible. The observation that the key to communication is uncertainty, shifted the focus of the communication problem from the physical to the abstract. It was no longer a deterministic problem but a probabilistic one. This was also a huge shock to the engineering community at the time. Communications engineering Having defined what information is, Shannon found a way to make the communication problem a general problem. He used a diagram like this: The first major contribution from this diagram is that one of the transmitter’s jobs is to convert all information to bits. Having successfully applied Boolean logic (true or false, zero or one) to switching circuits, Shannon generalizes the idea. All information can be represented as zeros and ones. Pictures, movies, and sound, for example, can all be treated the same way. This was one of the most important unifications of the twentieth century. Communications engineering is no longer a set of special cases that demand special theories. The problem of communication now reduces to two questions: How do we convert information to zeros and ones and how can we make sure that the zeros and ones are received accurately. The second major contribution came from realising the important role of redundancy in information. Is there a minimum number of bits that we can shrink our information without losing anything important? Shannon discovered that minimum and showed how to calculate it. His formula was based on the probabilities in the message and it is almost identical to a fundamental quantity in Physics called entropy (which is related to randomness and disorder). Shannon calls his quantity entropy too, and he proves that it's the answer to his question. Entropy in information theory is the minimal size that we can compress our messages without any loss. The very idea that we can compress a large amount of data into something very small, is what makes the information age possible. Shannon’s idea that we should first change information to zeros and ones and then compress it is a huge first step towards a universal theory of communication. The third major contribution is that there is a speed limit in information transmission. Each channel has its own discrepancies and limitations like noise and interference. It could be a wire, air or water for example. Shannon calculated the speed limit beyond which we know that our communication will fall apart. This is known as the Shannon limit. The very idea that there is a speed limit for information communication was another radical idea at that time. The fourth major contribution is the answer to the question how do we eliminate channel noise. We can use mathematical codes, known as channel codes. Noise is eliminated by carefully introducing redundancy with such codes. Shannon proved that this can work at maximum speed, right at the Shannon limit. If we can find the right codes, we can have perfect communication, with as few errors as we want. He proved that there exist codes that can achieve the Shannon limit but he provided little insight on how to find them. This sparked scientific research for decades. Shannon showed that redundancy in communications is a two-sided coin. Depending on what we want to do we may remove redundancy or artificially introduce it or both. While compression requires removing redundancy, channel coding involves carefully adding redundancy in order to eliminate the effects of channel noise. The public response The publication of the mathematical theory of communication was like dropping a bomb. A new scientific field had been conceived, redefining basic ideas. Information existed before Shannon, just as objects had inertia before Newton. However, information used to be for example a telegram, a photograph, a conversation, a book, or a song. Now, information was bits. And as if that was not shocking enough, another series of shocks hit the public: the sender no longer mattered, the intent no longer mattered, the medium no longer mattered, the meaning no longer mattered. Electronically communicating information has limits. How much information, how quickly could it be transmitted? It was all calculated in this work. It used to be common engineering sense that noise was a problem in communication that had to be lived with. That common sense was drastically re-evaluated since channel coding was an option. It has taken decades to understand, extend and answer open questions from findings of the scientific bomb that was dropped in 1948. How Did All This Happen? So how did all that happen back in the 1940s? What made Claude Elwood Shannon one of the greatest electrical engineering heroes of all time? I think it was a mix of skills. When Shannon was asked about the success of his idea to apply Boolean algebra in switching circuits he replied: “It just happened that no one else was familiar with both those fields at the same time.” While people who knew him recognise his modesty and humility in this statement, it also explains a wider truth: Diversity of knowledge is key. After all, he was both a genius mathematician and a genius electrical engineer. The persistent generalist His genuine curiosity and his need to understand how things work gave him a large number of interests and activities. This made him the perfect generalist. From each and every part of his work he gained the satisfaction of fulfilling his curiosity. He asked questions from new perspectives and would never stop until he found the right answers. Experts say that he was working on the mathematical theory of communication for a decade. This work survived broken marriages and the second world war. A full cycle specialist He was a conceptual theorist that would redefine ideas if necessary. Whenever he focused on a problem he would become a specialist. His interest and ability in mathematics, his curiosity to explore, learn and discover, his passion for building things would make him work his way through all aspects of a problem. From understanding concepts and designing, to developing and implementing solutions on gadgets and finally testing them. A theorist and a practitioner that would redefine information and calculate its practical limits. Curiosity beyond conventional boundaries Shannon followed his curiosity, asking questions and looking for answers in multiple fields. He didn’t let conventional boundaries define what he could or could not be interested in. “I think the history of science has shown that valuable consequences often proliferate from simple curiosity,” he said. Conventionally, the founding fathers in a scientific field are usually the people who lead its developments for years to come. It's all about incentive, I think. Viewing a field as their child is usually the incentive to nurture and help their child grow. Shannon's incentive appears to be simply the joy of fulfilling his curiosity. After his publication of the mathematical theory of communication, people expected him to lead information theory research and practice to new dimensions. MIT hired him for exactly this reason. His curiosity, however, led him to study things like: Gambling games. He built a wearable computer that could improve the odds for Russian roulette. How the brain works. Can we simulate the brain using a machine? How does the brain transform information? This kind of discussions he had with Alan Turing in their quest to understand the brain. He proved that we can make a reliable circuit using faulty components, having enormous applications to brain modeling. The data in the brain is interrelated. There is a huge amount of redundancy. Rules can be developed that depict how neurons connect. The intelligent machine. This idea was also a byproduct of his interest in the brain. He built a chess playing machine. He observed that although there is an astronomical number of possible chess games, we don't have to look all the way to the end of the game to figure out what a good move is. We only have to look ahead a few moves and evaluate the possible moves that we could reach. It is all about finding the path that leads to the best one! This principle is the basis for every chess program that came after. How the stocks work. He did work on the theory of stocks, applying information theory to the stock market. He developed various mathematical models to predict stock performance and has tested them—successfully, he said—on his own portfolio. Biology and genetics. He actually did a PhD in genetics! He found that different genetic possibilities could be mathematically represented in matrices. Using matrix algebra he could predict how traits are passed on through generations. Juggling machines. Juggling relates to patterns according to Shannon. There is a topology and a combinatorial aspect. He wrote a paper on Scientific American and came up with a formula that relates the number of balls we are juggling to how long each is in the air versus in the hand. Claude Shannon was notoriously curious. At home, he had a basement full of gadgets and machines that he spent hours enjoying making. It was his personal workshop for all kinds of curiosities. His friends called it “a gadgeteer's paradise” and Shannon the “master gadgeteer”! Fields and disciplines influenced Shannon revolutionised electronic communications and made the internet, wireless and wireline communications possible, including audio, video and multimedia transmission. Computer programs and apps, gaming, barcodes, QR codes, biometrics, digital clocks, digital photography, streaming services and the like, became a reality. Anytime we store, process or transmit information in digital form, every time we save a file on a hard drive or in the cloud, send an email, load a web page, chat on any social media app, we’re relying on concepts based on Claude Elwood Shannon’s mathematical theory of communication. This publication is considered as the main reason why Shannon is known as the father of information theory. The fields that information theory influenced are vast, including applied mathematics, theoretical physics, data science, genomics, linguistics, neuroscience, probability and statistics and telecommunications. From classical complexity theory, stochastic thermodynamics, quantum information theory and processing, cryptography, data compression and storage, channel coding and information transmission, cybernetics and control, biochemical signaling, machine learning and neural networks. According to Eric Schmidt, former CEO of Google: “I often wonder if Shannon understood how much information there would be after his many discoveries. Did he understand that we would have this information explosion? In the last couple of years we’ve generated more information than in the sum of all human history. Literally, he not only won the lottery, he invented the lottery.”

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