Lydia Hu reports on the latest artificial intelligence news that major companies are using a new software to monitor employee conversations.

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Look up snooze in Wiktionary, the free dictionary.

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These artificial intelligence companies are doing big things and should be on your radar screen.

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Snooze AI

snoozeai

If this looks like your typical alarm app screen, then you need some help waking up! The maker community never ran out of alternative hardware solutions for our daily struggles that are fun, tweakable and of a challenging nature. Some tried to wake up like this: However, research in the dynamics of sleep and the science behind “how to wake up to your alarm” can be dedicated to replicating the crypto-powered alarm clock that will force you to wake up or you will end up losing a fortune :D. It can also be a good intro to tinker with Ethereum and get your hands dirty with some hardware and blockchain concepts. <a href="https://medium.com/media/61af1d107c3c1ca7c0ce074457b60fd2/href">https://medium.com/media/61af1d107c3c1ca7c0ce074457b60fd2/href</a> The alarm uses the blockchain development board and a sound sensor. It’s sound activated, which means you can use it right away with any of your personal alarms, without too much hassle or a lot of tweaks. When the sound sensor detects the ringing of your alarm, it starts counting within a trial of time (That you set in your code), in this trial you have to get up and shut it down by a hardware action of your choice or simply pressing a button. Elk What happens is, initially an amount of Ether is locked in a smart contract every time the alarm fires. the smart contract is controlled only depending on the state of your hardware. Whether you’ve managed to fulfill the hardware action within the trial’s time frame or failed to; the board keeps counting down. If you did it before the trial ends, then you don’t lose the designated Ether you locked from your account and it’s withdrawn back to your account. If not, then you lose it entirely and it’s sent to any charity address of your choice. The smart contract functions used are : Link to code snippet: https://pastebin.com/R585FCsp Typical Arduino C was used for the rest of the logic for the alarm on Platform.io IDE which supports the Elk SDK. The sound sensor is associated with an interrupt pin, and once it signals for sound detection (LOW signal from the sensor ), the interrupt occurs and starts the millis() counter for the trial and locks your money in the smart contract using function lockMyMoney(address _alarmAddress) public payable{

userComittedMoney[msg.sender] = msg.value;

alarmAddress[msg.sender] = _alarmAddress; If you push the button to silence the alarm, another interrupt occurs and sets the Win flag to true and withdraws your money back function withdrawMoney(address _alarmAddress) public {

require(alarmAddress[msg.sender] == _alarmAddress && userComittedMoney[msg.sender]>0);

msg.sender.transfer(userComittedMoney[msg.sender]); If you lose, the money goes to the predefined charity address function spend(address _alarmAddress, uint _amount) public{

require(userComittedMoney[msg.sender] >= _amount && alarmAddress[msg.sender]== _alarmAddress);

charityAddress.transfer(_amount);

userComittedMoney[msg.sender]-=_amount; The code where the actions are handled would be as follows. ContractMethodParam param1("AlarmAddress");
ContractMethodParam param2(AMOUNT_OF_MONEY_IN_GWEI);

void loop(){

if(win) //winning condition

{

win = false;

Ethereum.sendContractMethodCallTransaction("m/44'/60'/0'/0/0",CONTRACT_ADDRESS,AMOUNT_OF_MONEY_IN_GWEI,50000,20,"withdrawMoney(address)",&param1);

display.clearDisplay();

display.fillScreen(BLACK);

display.setCursor(37,7);

display.println(“WINNER!”);

display.setCursor(20,30);

display.println(“You’ve Earned”);

display.setCursor(20,40);

display.println(“0.016 ETH”);

display.display();

for(int i = 0; i<=3 ; i++)

analogWrite(LedPin, 90);

delay(500);

analogWrite(LedPin, 0);

delay(500);

}

if (!win && millis()-timer >= trial ) //losing condition

{

//You LOSING money!

Ethereum.sendContractMethodCallTransaction("m/44'/60'/0'/0/0",CONTRACT_ADDRESS,AMOUNT_OF_MONEY_IN_GWEI,50000,20,"spend(address,uint)",&param1,&param2);

display.clearDisplay();

display.fillScreen(BLACK);

display.setCursor(35,7);

display.println(“SLEEPY HEAD!”);

display.setCursor(33,30);

display.println(“You’ve lost”);

display.setCursor(33,40);

display.println(“0.016 ETH”);

delay(3000);

display.clearDisplay();

display.fillScreen(BLACK);

display.display();

} And finally, a simple and sleek enclosure was made on Fusion 360 to encompass all the components in a presentable form. This alarm leaves you no option but to either wake up on time or be a generous person, and in both cases, you’ve done something good whether for yourself or for the world. Building blockchain-connected devices is made simple with Elk. Elk will be on Kickstarter soon, to get your hands on one once it’s out, sign up here . <a href="https://medium.com/media/3c851dac986ab6dbb2d1aaa91205a8eb/href">https://medium.com/media/3c851dac986ab6dbb2d1aaa91205a8eb/href</a>

A Crypto-Powered Alarm You Can’t Snooze!

TL;DR This is a story of the journey I went through. I wanted to design a machine learning system that would tell me whether I can snooze in the morning and still arrive on time for work. I do get a bit technical in this article, so I added some links to some of the more advanced terms in this article If you want to learn how to build image recognition systems, there are better articles out there. But if you want a couple of good chuckles, and see how easy it is to get something that resembles machine up and running, then this is article is for you. learning Context and Problem definition Just after completing Professor Ng’s , I was looking for challenging problems to put those newly learnt algorithms to good use. Machine Learning course I came up with a lot of fun and interesting ideas. But ultimately, none of those were actual problems. Yes, space exploration sounds fun. But let’s be real, I’m only considering this for the sake of working on a complex project. Not because I have this burning desire to find new clusters of stars. Then one morning, I once again made the ill-advised decision to hit snooze on my alarm clock. Because of traffic, I arrived gross and sweaty at work, on time.. somewhat There’s nothing like a morning at work after a good run It was a yucky way to start the day, but it made me realize that this is what I should work on. There’s not much I actually complain about. But if I had the superpower to assert with confidence whether to hit that tempting snooze button, life would truly be wonderful! The outline of the problem was pretty clear. In the end, we want a system that tells us ahead of time whether the route is clear and sleeping another 10 minutes won’t hurt. Luckily for me, it just happens that I live in Singapore, where we have access to a ton of public data, including traffic camera images. Designing a system pipeline With all this in mind, I designed to following pipeline for my machine learning system: Get traffic camera images Build to classify image subsections tool Classify a lot of examples car/no car Crop and resize selections out of original pictures Build own deep Neural Networks Train Neural Network to detect cars Detect the car sections in actual traffic pictures Count how many cars in pictures Gather images for the times and locations of my commute specifically Build time series with how many cars, at what time, and where Estimate whether there will be traffic tomorrow Snooze peacefully 😴😴😴 And there began my data science journey. And boy oh boy, what a journey! 1. Getting traffic camera images This was surprisingly one of the easiest parts. did an good job with their . With little to no experience with the json, csv, and request Python libraries, you can quickly and neatly download a lot of . Data.gov.sg APIs traffic camera images I decided to download data from all around the country and at all times. Even though in the end we will only need to detect cars in front of my apartment complex at around 9:00 AM. I did that in order to train a Image Recognition System that can then easily be applied to other places and times. more versatile Now that we have a bunch of traffic camera images, let’s work on detecting cars 2. Classifying subsections of an image Getting traffic images is great, but unfortunately, can can’t just shove that in a Neural Network and expect it to do a decent job at counting cars. (Well maybe we could, but it is probably not the most elegant and accurate way of dealing with the problem). So I started going through each image, try to keep track of the coordinates of each cars to later crop them out to train our car detection Neural Network. I quickly realized that this was getting out of hand. So I wrote a script to make my life easier. very This is one of the reasons why I fell in love with programming in the first place: . We use programs to program, so we can program a program, so that it would program better and we don’t have to program as much! we have the power to make our work tools better I used the library to make a program where I can make image selections with only a couple of clicks and key strokes. Tkinter We wrote a script to classify cars within a picture, now is time to use it 3. Classifying loads of examples car/no car Labelling traffic camera images Even if it was dull, repetitive work, I managed to label almost 200 cars and more than 1500 non cars selection across 30 ish images, under an hour. I made the executive decision that this was enough data to move on to the next (I was bored). 4. Cropping and resizing selections This part is also pretty straightforward. The script I wrote for part 3 stores the image selections relevant information in a neat file. I only have to keep track of whether the selection is a car or not, the coordinate of the top left corner, the size of the selection. Knowing all this, I used the library (I know, it is very fitting to our little project) to crop out cars and non-cars selections. csv Pillow 5. Writing code to build, train, and test my own deep Neural Networks This is it, we’re building our own lads! Oh boy was I in for a treat. I decided to build it from the ground up, so I would get a deeper grasp of what is going on under the hood. The concepts behind neural networks are not that hard to get (except maybe the derivations for the update functions). But implementing all of it is a whole other story. Neural Network For starters, it helps if you’re not an idiot. I implemented the different components and all the logic looked fine to me.. However, none of my node weights were updating properly. After a couple hours of debugging, and a couple grams of hair missing from my scalp, I found out I was using Python 2 this whole time where and not Python 3 where . So all my coefficients would at some point end up being 0 (and turns out ), so the network would not update itself at all. really 1 / 2 = 0 1 / 2 = 0.5 0 + a = a I also spend a lot of time trying various hyperparameters for the network as I found that it wasn’t performing well enough. I was baffled, I was training my 3 layer of 5 units each Neural Network on 9 whole training examples, and , the algorithm wasn’t doing a good job at guessing the 10th example. I was essentially a 50/50 for the network to get it right. Was I lied to this whole time? Are Neural Networks not the I was made to believe they were? Luckily, I had the presence of mind that you can update your Neural Network 100,000 times, but you need a bit more than 9 data points to get an algorithm somewhat close to being useful. somehow high-performing-state-of-the-art-predictive-classifier maybe So I used an actual data set, namely, the set from scikit-learn. Why this one in particular? Well you see, we used the particular data set in one of my favorite class assignments I had in university (we had to build an , if you’re looking for a fun, math focused problem, go check it out). iris data ID3 The algorithm was now doing better (better than our previous 50/50 algorithm, yay!). However, it was still acting a bit weird. No matter how many times the algorithm was running, or how fast it was performing updates, I would always end up with either a 60% accuracy or a 40% accuracy. I felt really discouraged. Even if it was doing better, how could such an algorithm ever be able to tell cars apart from road signs, if it can’t even tell dumb flowers apart??? I was on the verge of quitting programing and following Edmund Blackadder’s footsteps. For fun though, I decided to see at least how well Neural Networks from standard libraries would do. So I ran the data set against scikit-learn’s . I was astonished. Not only were the results far from the 99% accuracy that I was expecting, but the results were also almost always the same as the results I got when using my implementation. So no matter how ugly and inefficient our code is, we must have gotten a least a couple things right. Hurray! Neural Network classifier Our subpar 60% or 40% was in fact not due to our poor implementation, but most likely due to our data set which is too small. still But oh well, we finally have a tool to design and train deep Neural Networks. Good enough by my books, gotta keep moving! 6. Training Neural Network on car images How exciting, we get to finally use our Neural Network we spend an unnecessary amount of time designing! Sadly, our algorithm can’t handle too many inputs and logical units. While it was still on par with scikit-learn algorithm for a 5-input and 7-ish-logical-unit networks, it completely blew up up when trying to handle images. (For reference, I am using 32px by 32px with 3 color channels for in image input, so the input has features which is a lot more than 5) Errrr wrong, try again next time! 32 * 32 * 3 = 3072 Goodbye custom Neural Network :’( To be more precise, it was actually my custom (sigmoid and ReLu) and their derivatives that went boom and tried dividing stuff by 0 (I do not recommend trying to divide by 0). activation function It was heartbreaking, but we got a problem to fix folks: I still need to know whether I can snooze or not! So I gave in, and used a library’s implementation. Only a fool would change a winning team, so I went with the good ol’ scikit-learn Neural Network Classifier. The algorithm was doing quite well actually, right out of the box I got a consistent 88% accuracy over my test set. I then performed . I looked for the best values for my network size, my learning rate, and the number of iterations to go through. I managed to increase accuracy up to 91%, so I saved the Neural Network model and called it a day. hyperparameter fine tuning We ended up training a Neural Network with 90%+ accuracy, let’s see how it holds against raw traffic images 7. Detecting car sections in pictures It’s great that our algorithm is working fine on pre-cropped car/no car images. Now we need to find those cars in traffic camera images. I chose to go with the . Essentially I look at the top left corner, see if it is a car or not, if it is, I keep track of that car. Then I slide to the right, and when i reach the end of the line, I go back to the left and shift down. sliding window technique There is no doubt in my mind that this approach is one of the most gruesome out there. But pigs don’t get fat on clear water. In that case, we’re the pig and we need some fatty porridge. Maybe in the future we’ll be more sophisticated and we’ll use crystal clear feature detections methods.. But not now. I want results and I want them fast! The results were….interesting. It was doing ok, but a lot of consistent errors that I could foresee would impair our traffic detection algorithm. First run on an actual traffic image As you can see, it does detect some cars pretty well, but also the arrows indicating the roads’ destinations. And more importantly, it detected of cars on the right and the bottom… a lot Turns out, I was trying to detect cars outside the picture on the right and at the bottom. I was doing one too many slide in both direction.. This tweet felt painfully relevant at that time: All jokes aside, after fixing that issue and refining the parameters, we got something that wasn’t half bad, and I was happy. Labels and lane dividers are still an issue, but it s good enough to get something to work. Now that we detect cars pretty well, it’s high time we count how many there are in a picture. 8. Counting cars So our sliding door technique paired with our car recognition system work pretty well. But now, how are we supposed to know how many cars there are?? We can’t just count how many times our car algorithm detects a car. As you can see from the previous image, one car can be detected multiple times, and some non car sections are detected, but only once, and probably should be ignored. This sort of looked like a clustering project, so of course, having just learn the technique, I just dove into implementing it for our problem. One thing though, this technique actually requires you to know how many neighborhood there are (in our case, how many cars there are). Huh?? But that’s what we’re trying to find out.. But it’s all good, we’ll run k-NN for all numbers between 1 and 30, and see which one is It actually did work, surprisingly. But god was it slow. k-nearest-neighbors the most correct. Then, one day while I was grocery shopping (that’s not relevant to the story at all, but I’m rolling with it), I realized I was overcomplicating things for no good reason. How would a 3 year old solve this, I asked myself. Well, they would probably color any blob that is connected, then do that for all the blobs in the picture, and count how many times they colored a blob. My outsourced team, counting cars for me while I take a nap So I did just that, a 3-year-old’s coloring algorithm and ran it against our beloved traffic camera images. It definitely was ugly and inaccurate, but here’s the thing: we don’t need to know how many cars there are. What we need, is the number of cars detected to go up significantly when the actual number of cars is high, and vice versa. Luckily for me, my algorithm was doing just that. Yay me! We detected 13 cars, top left is the image with the detected cars, bottom left is the neighborhood heights, top right is the normalized neighborhoods, one of them colored in, bottom right is the same as top right but we removed the colored neighborhood (so we don’t count is again) We detected 20 cars here. While there probably aren’t 20 cars, it s a higher number than what we detected on the previous image, and there is significantly more traffic We can finally estimate the traffic flow, all that’s left for us to do is to build traffic historical data, so we can extrapolate for future days. 9. Gathering images down my apartment at 9am Ezpz, that’s just step 1, but instead of looking at any and all picture the government allows me to see, I need to only look at the ones coming from camera 6703 around 9AM, because ultimately that’s all I care about. Boom, onto the next step! 10. Building traffic time series Ezpz squared! We just get those car counts and timestamps we got from last step and store them in some file somewhere. Damn we’re really dashing through those stages aren’t we? 11. Extrapolating from our time series So let’s recap, we have the “ ” there was for the past 20 days . Now let’s guess what it’s gonna be tomorrow! Better yet, let’s guess for the next 5 days! number of cars ish At first I wanted to use a algorithm as it is the state of the art and it does well against seasonal trends, and that might be a thing for traffic. Upon further reading, I learnt that LSTM actually relies on a recurrent Neural Network architecture. Having only 20 data points, I did not want to repeat our step 5 disaster and waste countless hours for nothing. So in the end, I went with the method, which also does well with seasonal trend, but is uses a more statistical approach that works with fewer data points. LSTM ARIMA We got something like this: Blue is actual data, red is prediction Not too shabby, huh? Considering we trained the model on 15 examples to guess the next 5. You know what, I ship it! Hurray! We gathered enough data to predict the future! Nostradamus would be so proud. 12. Snoozing peacefully 😴😴😴 I now check every night if I will snooze tomorrow. Never have I ever been late for work since! And my project and I lived happily ever after, the end. Errrr wrong again, better luck next time! Even though we’re estimating the number of cars pretty well, and predicting tomorrow’s traffic somewhat decently, there are still improvements to make. Of course, we have plenty of places to look for optimization. But the bigger problem is that our base hypothesis is not accurate enough. Yes, traffic does play a big role in determining the length of my commute, but the commute itself plays a huge role too. You see, I take the bus then the train to go to work. While missing a train only adds another 2 minutes to my morning travels. If I get unlucky and three buses pass by me just before I can get to them, I might be looking at another 20 minutes to my 40 minute journey.. Where to go from there As I just mentioned, it would be interesting to make use of the real time bus arrival updates and see how much it would improve our current system. Of course we can always improve our car recognition Neural Network by feeding it more labelled data. We can also improve of our simple sliding doors and neighborhood counting techniques Ultimately, checking the traffic the day before isn’t the most practical anyway. So ideally, we have a script that runs on its own while we sleep, and counts cars in real time. Based on that, it rings the alarm sooner or later. Parting thoughts Wow that was a long story, I’m glad you made it this far. All in all, it has been a blast building this entire system from scratch. And I was surprised at how easy it ended up being. This is mainly because I forced myself to work on it in small increments, but everyday. Once you’ve figured out how to break big problems into smaller ones, the sky is the limit. So, be ambitious! Go and solve complex things! As long as you enjoy doing it, all you need is to keep at it and you’ll have something to be proud of in the end! You can find all the code . The code isn’t really plug and play, but I’m more than happy to answer any questions you may have. here Cheers!

Can I Snooze: building an image recognition system to sleep a little longer

Tired? Burned Out? You Might Just Be Bored

Yorğun? Yandı? Sadəcə Darıxmış Ola bilərsən

Κουρασμένος; Κάηκε; Μπορεί απλά να βαριέσαι

¿Cansado? ¿Agotado? Puede que simplemente estés aburrido

Canso? Queimado? Podes estar aburrido

疲れている？燃え尽きている？退屈しているだけかも

Pavargote? Perdegė? Jums gali būti tiesiog nuobodu

Уморен? Изгорени? Можеби ќе ви биде досадно

Obosit? Ars? S-ar putea să te plictisești

Umechoka? Umechomwa? Unaweza Kuchoshwa Tu

சோர்வாக? எரிந்துவிட்டதா? நீங்கள் சலிப்படையலாம்

Charchadimi? Yondimi? Siz shunchaki zerikishingiz mumkin

Ndidiniwe? Utshisiwe? Unokuba Ukruqukile

Sales Pitch Shake-Up: Part Two—The Pitch Hack So Obvious, You’ll Kick Yourself

The Truth About Respect You don't want fame, you want respect. What you want isn't respect from others. It's self-respect. You crave respect from others because you don’t truly respect yourself. It’s hard to respect yourself when you know the truth about your actions—you know you’ve lied to yourself. You said you’d do things and didn’t. You promised yourself you’d get it done, but instead, you slept. You told yourself you'd change, but you didn’t. So, your own self doesn’t respect you for this. The Illusion of External Respect You don’t want respect from everyone. You want respect from the people you respect. Because if they respect you, it feels like proof that you can respect yourself. But it’s an illusion. You can only gain genuine confidence and respect by being consistent with yourself. No one else can give that to you. The Nature of Confidence Confidence doesn’t come from shouting affirmations at the mirror. If you were truly confident, you wouldn’t need to tell yourself—you’d have evidence of your confidence stacked up like trophies. You’re not confident because you don’t trust yourself. And you don’t trust yourself because you’re not consistent. Confidence is built on trust. The more certain you are that you’ll follow through, the more confidence you’ll have. Truth is something that, once you see it, you can’t unsee. Confidence is the amount of certainty you have that something won’t change—and that starts with your own behavior. The Power of Consistency Consistency is repeating a behavior frequently enough to create trust—first with yourself, and then with others. The more consistent you are, the more trustworthy you become, both in your eyes and in the eyes of others. Build enough undeniable proof that you follow through, and you’ll begin to trust yourself. Do what you say you’ll do. Don’t rely on external validation for your confidence and respect. The Role of Others Others can provide useful, unbiased feedback, but they can’t tell you the whole truth because they don’t know your internal state. External feedback is just a supplement to your internal knowledge. In the end, only you know whether you’ve truly done your best. Self-respect and confidence come from knowing you’ve done everything you could, not from what others think. The Paradox of Consistency You’re not consistent because you assume life is stable and unchanging. But in reality, the only thing that’s consistent is change. You procrastinate because you trust that you’ll be able to do it tomorrow. But that trust is misplaced—you won’t be the same person tomorrow. That’s why you sometimes hate yourself or wish you knew what you’ve learned now five years ago. The Public Toilet Method Your life is a relay race of consciousness. The version of you today is responsible only for today. Tomorrow, a different version takes over. Think of a public toilet. If you slack off today and leave a mess, tomorrow’s version of you will likely do the same, because it’s harder to clean up someone else’s mess. The cycle continues, getting worse over time. Are you going to have fun now and screw over your future self, or make things easier for the next version of you? Love is how much you’re willing to sacrifice to maintain a relationship. To truly love yourself, you must be willing to sacrifice short-term pleasure today, so that tomorrow’s version of you has a cleaner start. The more you slack off, the harder it gets for the future you. If You Don’t Do It Now, You Never Will Power is the distance between your thoughts and reality. If you want to be powerful, close the gap between thinking about something and actually doing it. The current version of you is the only one that wants to do it. The next version of you might not—that’s why you’ve quit habits or abandoned goals in the past. Fortunately, you can control the next version of yourself. Just like your body turns pizza and spaghetti into teeth and eyeballs, what you do with what you eat determines what your body becomes. Likewise, what you read and do with the information you consume shapes your mind. If you’re not obsessing over the actions that shape your future, you’re not truly committed to becoming who you want to be. You can live your life how you want—I’m just here to tell you the consequences of the actions you take. If you don’t do the work today, you lose control of who you become tomorrow. Discipline Discipline comes from clarity, not force. You’re not disciplined because the "perceived" pain of not achieving your goals isn’t as strong as the "perceived" pleasure you get from distractions. To be disciplined, fix your perception of pain and pleasure. Write down your reasons to stay focused and revisit them frequently so they stay top of mind. You need reminders more than you need new information. Each time you give in to distractions, the harder it becomes to stop. Write that down as one of your reasons to quit. The intensity of your reasons to stay focused must outweigh the pleasure of distractions at any given moment. You didn't do the next push up because the reasons to continue have faded. The Actual Purpose of a Goal Everyone tells you to set goals, but no one tells you why. Let’s clear up some misconceptions: 1. A goal isn’t "where you want to be in 5 years." That’s just fantasy. 2. A goal is what a better life looks like. 3. You don’t rise to your goals, you fall to your systems. 4. The more you tell people about your goals, the less likely you are to achieve them because talking about them releases dopamine in your brain, like you’ve already succeeded. 5. Goals are infinite, but your time and energy are finite. Be slow to set goals, quick to work on them. 6. You need only one big goal. A collection of small goals is not "one big goal". If it fills 2 pages, it’s too small. A big goal fits a sentence. 7. You’ll never achieve most of your small goals that are long term, because on your way to achieving them, the future you will change them. 8. If you have more than one main goal, you haven't found a big goal. 9. The ONLY purpose of a goal is to make your brain more attentive to things that help you survive or improve the quality of your life. The way you notice a restaurant that's always been there, just because you're hungry. That's ALL it's good for. Any other reasons are illusions. Practical Conclusion Ultimately, self-respect isn’t something you get from others. It’s something you build by living in alignment with your values and keeping promises to yourself. The first step is to break your goals into simple, daily tasks. Think of each task as a “level” in a game. The more levels you complete, the closer you get to mastery. For example, if your goal is to build an app, break it down into simple, achievable tasks. Each task brings you closer to the final product, and you make progress daily. The Role of Pain and Pleasure in Discipline When you procrastinate, it’s because the short-term pleasure of distraction outweighs the long-term pain of not achieving your goals. Reverse this dynamic by making distractions immediately painful. For example, every time you snooze your alarm, pay a friend a significant amount of money. This brings the pain of procrastination into the present. You can also make completing tasks easier by setting up your environment for success. Move your alarm across the room so you have to get up. Lay out your workout clothes the night before. Reduce the friction between you and your goals. Increase the friction between you and distractions. And don’t forget rewards. After hitting milestones, give yourself small rewards to tie pleasure to progress. But make sure the reward enhances your journey, not derails it. Turning Life Into an Irresistible Game You can make consistency easier by treating your life like a game. Which means to create the best game mechanics (aka systems). Everyone running alongside Usain bolt have the same goal (to finish first), but they don't win because they don't have the best systems. I’ll help you with creating your own systems on Level Up. You'll: Access powerful tools. Get exclusive content. Receive one-on-one support. Build lasting habits and achieve your goals. Schedule a 1-on-1 with me here: https://forms.gle/GEWLSKeEQczKokru6 The Truth About Respect The Truth About Respect You don't want fame, you want respect. What you want isn't respect from others. It's self-respect. You crave respect from others because you don’t truly respect yourself. It’s hard to respect yourself when you know the truth about your actions—you know you’ve lied to yourself. You said you’d do things and didn’t. You promised yourself you’d get it done, but instead, you slept. You told yourself you'd change, but you didn’t. So, your own self doesn’t respect you for this. The Illusion of External Respect The Illusion of External Respect You don’t want respect from everyone. You want respect from the people you respect. Because if they respect you, it feels like proof that you can respect yourself. But it’s an illusion. You can only gain genuine confidence and respect by being consistent with yourself. No one else can give that to you. The Nature of Confidence The Nature of Confidence Confidence doesn’t come from shouting affirmations at the mirror. If you were truly confident, you wouldn’t need to tell yourself—you’d have evidence of your confidence stacked up like trophies. You’re not confident because you don’t trust yourself. And you don’t trust yourself because you’re not consistent. Confidence is built on trust. The more certain you are that you’ll follow through, the more confidence you’ll have. Truth is something that, once you see it, you can’t unsee. Confidence is the amount of certainty you have that something won’t change—and that starts with your own behavior. The Power of Consistency The Power of Consistency Consistency is repeating a behavior frequently enough to create trust—first with yourself, and then with others. The more consistent you are, the more trustworthy you become, both in your eyes and in the eyes of others. Build enough undeniable proof that you follow through, and you’ll begin to trust yourself. Do what you say you’ll do. Don’t rely on external validation for your confidence and respect. The Role of Others The Role of Others Others can provide useful, unbiased feedback, but they can’t tell you the whole truth because they don’t know your internal state. External feedback is just a supplement to your internal knowledge. In the end, only you know whether you’ve truly done your best. Self-respect and confidence come from knowing you’ve done everything you could, not from what others think. The Paradox of Consistency The Paradox of Consistency You’re not consistent because you assume life is stable and unchanging. But in reality, the only thing that’s consistent is change. You procrastinate because you trust that you’ll be able to do it tomorrow. But that trust is misplaced—you won’t be the same person tomorrow. That’s why you sometimes hate yourself or wish you knew what you’ve learned now five years ago. The Public Toilet Method The Public Toilet Method Your life is a relay race of consciousness. The version of you today is responsible only for today. Tomorrow, a different version takes over. Think of a public toilet. If you slack off today and leave a mess, tomorrow’s version of you will likely do the same, because it’s harder to clean up someone else’s mess. The cycle continues, getting worse over time. Are you going to have fun now and screw over your future self, or make things easier for the next version of you? Love is how much you’re willing to sacrifice to maintain a relationship. To truly love yourself, you must be willing to sacrifice short-term pleasure today, so that tomorrow’s version of you has a cleaner start. The more you slack off, the harder it gets for the future you. If You Don’t Do It Now, You Never Will If You Don’t Do It Now, You Never Will Power is the distance between your thoughts and reality. If you want to be powerful, close the gap between thinking about something and actually doing it. The current version of you is the only one that wants to do it. The next version of you might not—that’s why you’ve quit habits or abandoned goals in the past. Fortunately, you can control the next version of yourself. Just like your body turns pizza and spaghetti into teeth and eyeballs, what you do with what you eat determines what your body becomes. Likewise, what you read and do with the information you consume shapes your mind. If you’re not obsessing over the actions that shape your future, you’re not truly committed to becoming who you want to be. You can live your life how you want—I’m just here to tell you the consequences of the actions you take. If you don’t do the work today, you lose control of who you become tomorrow. Discipline Discipline Discipline comes from clarity, not force. You’re not disciplined because the "perceived" pain of not achieving your goals isn’t as strong as the "perceived" pleasure you get from distractions. To be disciplined, fix your perception of pain and pleasure. Write down your reasons to stay focused and revisit them frequently so they stay top of mind. You need reminders more than you need new information. Each time you give in to distractions, the harder it becomes to stop. Write that down as one of your reasons to quit. The intensity of your reasons to stay focused must outweigh the pleasure of distractions at any given moment. You didn't do the next push up because the reasons to continue have faded. The Actual Purpose of a Goal The Actual Purpose of a Goal Everyone tells you to set goals, but no one tells you why. Let’s clear up some misconceptions: 1. A goal isn’t "where you want to be in 5 years." That’s just fantasy. 2. A goal is what a better life looks like. 3. You don’t rise to your goals, you fall to your systems. 4. The more you tell people about your goals, the less likely you are to achieve them because talking about them releases dopamine in your brain, like you’ve already succeeded. 5. Goals are infinite, but your time and energy are finite. Be slow to set goals, quick to work on them. 6. You need only one big goal. A collection of small goals is not "one big goal". If it fills 2 pages, it’s too small. A big goal fits a sentence. 7. You’ll never achieve most of your small goals that are long term, because on your way to achieving them, the future you will change them. 8. If you have more than one main goal, you haven't found a big goal. 9. The ONLY purpose of a goal is to make your brain more attentive to things that help you survive or improve the quality of your life. The way you notice a restaurant that's always been there, just because you're hungry. That's ALL it's good for. Any other reasons are illusions. Practical Conclusion Practical Conclusion Ultimately, self-respect isn’t something you get from others. It’s something you build by living in alignment with your values and keeping promises to yourself. The first step is to break your goals into simple, daily tasks. Think of each task as a “level” in a game. The more levels you complete, the closer you get to mastery. For example, if your goal is to build an app, break it down into simple, achievable tasks. Each task brings you closer to the final product, and you make progress daily. The Role of Pain and Pleasure in Discipline The Role of Pain and Pleasure in Discipline When you procrastinate, it’s because the short-term pleasure of distraction outweighs the long-term pain of not achieving your goals. Reverse this dynamic by making distractions immediately painful. For example, every time you snooze your alarm, pay a friend a significant amount of money. This brings the pain of procrastination into the present. You can also make completing tasks easier by setting up your environment for success. Move your alarm across the room so you have to get up. Lay out your workout clothes the night before. Reduce the friction between you and your goals. Increase the friction between you and distractions. And don’t forget rewards. After hitting milestones, give yourself small rewards to tie pleasure to progress. But make sure the reward enhances your journey, not derails it. Turning Life Into an Irresistible Game Turning Life Into an Irresistible Game You can make consistency easier by treating your life like a game. Which means to create the best game mechanics (aka systems). Everyone running alongside Usain bolt have the same goal (to finish first), but they don't win because they don't have the best systems. I’ll help you with creating your own systems on Level Up . You'll: Level Up Access powerful tools. Get exclusive content. Receive one-on-one support. Build lasting habits and achieve your goals. Schedule a 1-on-1 with me here: https://forms.gle/GEWLSKeEQczKokru6

Why You're Not Consistent: the Equation for Consistency, Confidence, Discipline, Self Respect

Serverless Databases in 2024: The State of Serverless Solutions for Modern Apps

Staying productive and efficient has become more critical than ever. Whether managing a team, working on a solo project, or simply looking to streamline your daily tasks, the right tools can make all the difference. This article introduces 17 useful tools and web apps designed to boost your productivity and help you achieve more in less time. From advanced video editing and project management tools to innovative AI web applications, we will discover the best resources to enhance your workflow and stay ahead in today's competitive landscape. Each tool will include a direct link, a description, and an image preview. 1. Wondershare UniConverterWondershare UniConverter (Sponsored) Wondershare UniConverter simplifies video conversion, editing, and sharing, making it an essential addition to your productivity toolkit. Boost your productivity by quickly converting videos to multiple formats, compressing large files, and editing footage with ease: High-Speed Conversion: Convert videos to 1000+ formats at lightning speeds without compromising quality.


Video Compression: Compress large video files to manageable sizes while retaining high resolution.


Editing Suite: Edit videos with a user-friendly interface that includes trimming, cropping, adding subtitles, and more.


Batch Processing: Save time by converting multiple videos simultaneously with batch processing capabilities.


AI Video Enhancer: Enhance your video quality with UniConverter's dual AI model with denoising for clarity and frame interpolation for fluid motion. Enhance your video workflow and maximize efficiency with Wondershare UniConverter features! Try it yourself today: Wondershare UniConverter 🔥 2. Jasper Jasper is an AI writing assistant that helps create high-quality content quickly and efficiently. It improves productivity by generating ideas, drafting content, and editing text, which saves time on writing tasks. 3. Firefly by Adobe Firefly is Adobe's AI-driven creative tool that enhances design and photo editing processes. It boosts productivity by automating repetitive design tasks and providing advanced features for faster and more efficient creative workflows. 4. Uizard Uizard is an AI design tool that converts hand-drawn sketches into digital designs and prototypes. It enhances productivity by streamlining the design process, enabling rapid prototyping and iteration without extensive design skills. 5. PlayHT PlayHT is a text-to-speech platform that converts written content into realistic voiceovers. It improves productivity by allowing users to quickly create audio versions of their content, which can be used for podcasts, audiobooks, and other multimedia projects. 6. Reclaim Reclaim is an AI-powered scheduling tool that helps manage and optimize calendar events and tasks. It boosts productivity by automatically prioritizing and scheduling tasks, ensuring that users stay focused on their most important work without manual calendar management. 7. Obsidian Obsidian is a powerful knowledge base tool that works on top of a local folder of plain text Markdown files. It improves productivity by allowing users to organize and link their notes efficiently, enhancing their ability to manage and retrieve information. 8. Lucidchart Lucidchart is a web-based diagramming tool that allows users to create flowcharts, mind maps, and organizational charts. It boosts productivity by simplifying the process of visualizing complex information and collaborating in real time with team members. 9. Fireflies Fireflies is an AI-powered meeting assistant that records, transcribes, and searches voice conversations. It enhances productivity by providing accurate meeting notes and allowing users to easily search through transcripts, reducing the need for manual note-taking. 10. Slidesgo Slidesgo offers AI-powered presentation templates and design tools to create professional presentations quickly. It improves productivity by providing ready-made templates and design suggestions, saving time when creating slides from scratch. 11. Miro Miro is an online collaborative whiteboard platform designed for team collaboration. It boosts productivity by enabling teams to brainstorm, plan, and manage workflows visually and interactively, facilitating better communication and idea sharing. 12. Namelix Namelix is an AI-powered business name generator that creates unique and catchy names for your business. It enhances productivity by quickly providing multiple naming options, saving time and effort in brainstorming. 13. Flair Flair is an AI-powered tool designed to create and enhance branding assets, including logos and social media content. It improves productivity by automating the design process, allowing users to generate professional-quality branding materials without design expertise. 14. Spark Spark is an email client designed to help users manage their emails more efficiently with features like smart inbox, email snoozing, and collaborative email writing. It boosts productivity by organizing emails intelligently, enabling faster and more effective communication. 15. Streaks Streaks is a habit-tracking app that helps users build good habits and break bad ones by tracking up to twelve tasks daily. It enhances productivity by encouraging consistency and providing motivation to complete daily tasks and goals. 16. Harvest Harvest is a time-tracking and invoicing tool that helps businesses track time spent on projects and manage billing. It improves productivity by offering insights into time management and simplifying the invoicing process, ensuring accurate and timely billing. 17. Freedom Freedom is a productivity app that blocks distracting websites and apps across all your devices. It boosts productivity by reducing digital distractions, allowing users to focus on their work without interruptions. Writing has always been my passion, and it gives me pleasure to help and inspire people. If you have any questions, feel free to reach out! Make sure to receive the best resources, tools, productivity tips, and career growth tips I discover by subscribing to my newsletter! Also, connect with me on Twitter, LinkedIn, and GitHub! Staying productive and efficient has become more critical than ever. Whether managing a team, working on a solo project, or simply looking to streamline your daily tasks, the right tools can make all the difference. This article introduces 17 useful tools and web apps designed to boost your productivity and help you achieve more in less time. From advanced video editing and project management tools to innovative AI web applications, we will discover the best resources to enhance your workflow and stay ahead in today's competitive landscape. Each tool will include a direct link, a description, and an image preview. 1. Wondershare UniConverter Wondershare UniConverter (Sponsored) Wondershare UniConverter Wondershare UniConverter Wondershare UniConverter simplifies video conversion, editing, and sharing, making it an essential addition to your productivity toolkit. Boost your productivity by quickly converting videos to multiple formats, compressing large files, and editing footage with ease: High-Speed Conversion: Convert videos to 1000+ formats at lightning speeds without compromising quality. Video Compression: Compress large video files to manageable sizes while retaining high resolution. Editing Suite: Edit videos with a user-friendly interface that includes trimming, cropping, adding subtitles, and more. Batch Processing: Save time by converting multiple videos simultaneously with batch processing capabilities. AI Video Enhancer: Enhance your video quality with UniConverter's dual AI model with denoising for clarity and frame interpolation for fluid motion. High-Speed Conversion: Convert videos to 1000+ formats at lightning speeds without compromising quality. High-Speed Conversion : Convert videos to 1000+ formats at lightning speeds without compromising quality. High-Speed Conversion Video Compression: Compress large video files to manageable sizes while retaining high resolution. Video Compression : Compress large video files to manageable sizes while retaining high resolution. Video Compression Editing Suite: Edit videos with a user-friendly interface that includes trimming, cropping, adding subtitles, and more. Editing Suite : Edit videos with a user-friendly interface that includes trimming, cropping, adding subtitles, and more. Editing Suite Batch Processing: Save time by converting multiple videos simultaneously with batch processing capabilities. Batch Processing : Save time by converting multiple videos simultaneously with batch processing capabilities. Batch Processing AI Video Enhancer: Enhance your video quality with UniConverter's dual AI model with denoising for clarity and frame interpolation for fluid motion. AI Video Enhancer : Enhance your video quality with UniConverter's dual AI model with denoising for clarity and frame interpolation for fluid motion. AI Video Enhancer Enhance your video workflow and maximize efficiency with Wondershare UniConverter features! Try it yourself today: Wondershare UniConverter 🔥 Try it yourself today: Wondershare UniConverter Wondershare UniConverter 2. Jas per 2. Jas per Jasper is an AI writing assistant that helps create high-quality content quickly and efficiently. It improves productivity by generating ideas, drafting content, and editing text, which saves time on writing tasks. 3. Firefly by Adobe Firefly by Adobe Firefly is Adobe's AI-driven creative tool that enhances design and photo editing processes. It boosts productivity by automating repetitive design tasks and providing advanced features for faster and more efficient creative workflows. 4. Uizard Uizard Uizard is an AI design tool that converts hand-drawn sketches into digital designs and prototypes. It enhances productivity by streamlining the design process, enabling rapid prototyping and iteration without extensive design skills. 5. PlayHT PlayHT PlayHT is a text-to-speech platform that converts written content into realistic voiceovers. It improves productivity by allowing users to quickly create audio versions of their content, which can be used for podcasts, audiobooks, and other multimedia projects. 6. Reclaim Reclaim Reclaim is an AI-powered scheduling tool that helps manage and optimize calendar events and tasks. It boosts productivity by automatically prioritizing and scheduling tasks, ensuring that users stay focused on their most important work without manual calendar management. 7. Obsidian Obsidian Obsidian is a powerful knowledge base tool that works on top of a local folder of plain text Markdown files. It improves productivity by allowing users to organize and link their notes efficiently, enhancing their ability to manage and retrieve information. 8. Lucidchart Lucidchart Lucidchart is a web-based diagramming tool that allows users to create flowcharts, mind maps, and organizational charts. It boosts productivity by simplifying the process of visualizing complex information and collaborating in real time with team members. 9. Fireflies Fireflies Fireflies is an AI-powered meeting assistant that records, transcribes, and searches voice conversations. It enhances productivity by providing accurate meeting notes and allowing users to easily search through transcripts, reducing the need for manual note-taking. 10. Slidesgo Slidesgo Slidesgo offers AI-powered presentation templates and design tools to create professional presentations quickly. It improves productivity by providing ready-made templates and design suggestions, saving time when creating slides from scratch. 11. Miro Miro Miro is an online collaborative whiteboard platform designed for team collaboration. It boosts productivity by enabling teams to brainstorm, plan, and manage workflows visually and interactively, facilitating better communication and idea sharing. 12. Namelix Namelix Namelix is an AI-powered business name generator that creates unique and catchy names for your business. It enhances productivity by quickly providing multiple naming options, saving time and effort in brainstorming. 13. Flair Flair Flair is an AI-powered tool designed to create and enhance branding assets, including logos and social media content. It improves productivity by automating the design process, allowing users to generate professional-quality branding materials without design expertise. 14. Spark Spark Spark is an email client designed to help users manage their emails more efficiently with features like smart inbox, email snoozing, and collaborative email writing. It boosts productivity by organizing emails intelligently, enabling faster and more effective communication. 15. Streaks Streaks Streaks is a habit-tracking app that helps users build good habits and break bad ones by tracking up to twelve tasks daily. It enhances productivity by encouraging consistency and providing motivation to complete daily tasks and goals. 16. Harvest Harvest Harvest is a time-tracking and invoicing tool that helps businesses track time spent on projects and manage billing. It improves productivity by offering insights into time management and simplifying the invoicing process, ensuring accurate and timely billing. 17. Freedom Freedom Freedom is a productivity app that blocks distracting websites and apps across all your devices. It boosts productivity by reducing digital distractions, allowing users to focus on their work without interruptions. Writing has always been my passion, and it gives me pleasure to help and inspire people. If you have any questions, feel free to reach out! Make sure to receive the best resources, tools, productivity tips, and career growth tips I discover by subscribing to my newsletter ! my newsletter my newsletter Also, connect with me on Twitter , LinkedIn , and GitHub ! Twitter Twitter LinkedIn LinkedIn GitHub GitHub

Boost Your Productivity in 2024 With These 17 Tools & Web Apps🚀⚡

Obviously, no job family is going to disappear overnight; change takes time. But looking ahead helps orient everyone’s energy and steer careers away from the doom and gloom of job decline. Reading AI job impact reports can give you vertigo: 85 million jobs will be displaced globally due to AI ( ) Oliver Wyman Forum There are predictions that software developers ?! might be extinct by 2040 : “In the next five years, 83 million jobs will be lost and 69 million are projected to be created” World Economic Forum 40% of the global workforce - 1.4 billion people - will need to reskill. ( ) IBM study As a product manager, I ask the question of whether there’s a future for my career in the post-AI world. naturally These numbers sound bad enough to throw in the towel and say “Well, I’ll just give up I guess, look the other way, and see what happens”. But is that: can my whole claim disruptive trends are visible far in advance if you’re looking the right way and can sift through some noise, getting to a level of operational expertise in any emerging tech is relatively simple. There are jobs that will probably, within the next several years, be displaced almost completely (my one bet is on frontline customer support), and then there are jobs that will go through a boom cycle. For those, the traditional market won’t be able to provide enough supply, and we will see similar qualifications rebranding as we did with coding boot camps over the last 10-15 years. Most of us in tech will likely land somewhere in the middle: even if the changes come quickly, we have the choice and the luxury of iterating towards new skills (and opportunities) rather than needing a complete pivot. Designers, Devs, and PMs: AI Will Kill Some & Create Some By 2027 ( ): World Economic Forum Demand for designers will increase some; Depending on the type of developer, the jobs might see up to a 25% increase (blockchain developers being one of the leaders of the pack!) Roughly ~10% of PM jobs are going to die, and roughly ~10% will be added, so net zero. Product management is actually . But the experience of an AI PM vs. a random PM is not fungible, so the key advantage is to be as close to the growing tech (whether it’s AI or other) as possible. one of the top AI talent demands Macro Trends That Will Influence Our Individual Experience: Engel’s Pause & Solow’s Paradox It will take more than just job opportunities that will determine we experience progress, our own relevance, and careers of the next decade or two; it will be influenced by macro trends too. how The Mid-Term Impact Might Be Just Bad in General, but Hopefully, We’ll Live to See the Turnaround: Engels’ Pause Engels’ Pause describes the British industrial revolution in the early 1800s when working-class wages stagnated while GDP grew quickly. There are several theories, the bottom line being that the owners and investors of the booming businesses pocketed the gains and kept wages relatively flat. If it sounds familiar - argues that advanced economies are now in a new, “post-1980 Computer Revolution” Engels' Pause. Carl Benedikt Frey He explains that early labor-replacing technologies tend to decrease wages; once more sophisticated labor-augmenting technologies show up, wages and demand for talent tend to increase: "If technology replaces labor in existing tasks, wages and the share of national income accruing to labor may fall. If, in contrast, technological change is augmenting labor, it will make workers more productive in existing tasks or create entirely new labor-intensive activities, thereby increasing the demand for labor. (…) The growing capital share of income meant that the gains from technological progress were very unequally distributed: corporate profits were captured by industrialists, who reinvested them in factories and machines.” This is an optimistic sign! And aligned with what the enterprises expect: 87% of executives surveyed believe employees are more likely to be augmented than replaced by generative AI. IBM From : OWF “As some experts look at how employeesʹ current tasks will be affected by generative AI and automation, they divide the work into three types: transactional, relational, and expertise-related. Much of our transactional work will be substituted by a combination of robotic process automation, machine learning, and generative AI, while work requiring deep expertise or human collaboration will increasingly be augmented.” Waiting for the Immediate Signs of AI Revolution Might Be a Snoozefest: Solow’s Paradox and the Productivity J-Curve Solow’s Paradox and talk about a similar phenomenon: that as we (we, as in economies, companies, CEOs, and investors) pour money into a “groundbreaking” technology, the effects of it don’t seem to show up for a while: Erik Brynjolffsen’s Productivity J-Curve A similar question was raised in 1987, when economist Robert Solow observed a disconnect between the burgeoning computer age and the anticipated productivity gains — an observation now known as “Solow’s paradox.” Businesses and governments poured money into IT infrastructure, yet the expected leap in productivity was conspicuously absent. This paradox left many wondering if the problem lay not with the capacity of the technology but rather with the manner of its implementation. ( ) OWF Erik Brynjolffsen explains why that might be happening: General purpose technologies enable and require significant complementary investments, including co-invention of new processes, products, business models and human capital. These complementary investments are often intangible and poorly measured in the national accounts, even when they create valuable assets for the firm. He , and why it took a while for the electric motors’ revolutionary effects to materialize: the first generation of factory managers took out the steam engine - out of a factory that was and organized around the limitations of the steam engine - and plopped the electric engine in its place. gives an example of the steam engine being replaced with electric motors specifically built for It wasn’t until the new wave of managers redesigned the systems and workflows for the affordances of the electric engine that the expected innovation and productivity could be seen. Nobody Should Count on Employers to be the Drivers of Effective Re-Skilling One might say “OK, so if AI is so important, and there is not enough talent out there to hire, then surely the companies will invest money to train people.” And sure, they will; there are plenty of statistics that confirm that. But there’s already a significant and growing mismatch between what (and how quickly) companies are able to provide and what people need for their jobs - let alone what employees will need to be competitive in the job market vs. just slightly better at their existing, narrowly defined jobs. From : OWF Ok, So What’s the Recipe for Staying Afloat Here? On an individual level, there’s a discouraging disconnect between: The vague promises of what AI is supposed to be able to do, or how it be revolutionizing our work, versus what the existing products can do in practice right now; should between what the demand for AI talent is looking for, and where the supply market is (i.e., where we, the employees, are) today. But both of these trends are moving pieces; the key is to be one of the pieces moving along, not staying behind. The antidote is to use something, build something, and learn something (which I cover in my next post) until, inevitably, each of us starts to notice the applications and opportunities that actually bring progress: PS. If you liked this post - you might like my future takes at , where I write pragmatic takes on disruptive tech & its opportunities, with a sprinkle of deep dives into data and market insights. hypegeist.substack.com Also published here

Product Managers, Designers, and Devs: What Does Their Future Look Like in a World Filled With AI?

প্রোডাক্ট ম্যানেজার, ডিজাইনার এবং ডেভস: এআই দিয়ে ভরা বিশ্বে তাদের ভবিষ্যত কেমন দেখায়?

Produktmanager, Designer und Entwickler: Wie sieht ihre Zukunft in einer Welt voller KI aus?

Gerentes de producto, diseñadores y desarrolladores: ¿cómo será su futuro en un mundo lleno de inteligencia artificial?

Chefs de produit, concepteurs et développeurs : à quoi ressemble leur avenir dans un monde rempli d'IA ?

उत्पाद प्रबंधक, डिज़ाइनर और डेवलपर: AI से भरी दुनिया में उनका भविष्य कैसा दिखता है?

プロダクト マネージャー、デザイナー、開発者: AI で満たされた世界における彼らの未来はどのようなものになるでしょうか?

제품 관리자, 디자이너, 개발자: AI로 가득 찬 세상에서 그들의 미래는 어떤 모습일까요?

Gerentes de produto, designers e desenvolvedores: como será o futuro deles em um mundo repleto de IA?

Менеджеры по продуктам, дизайнеры и разработчики: как выглядит их будущее в мире, наполненном искусственным интеллектом?

Ürün Yöneticileri, Tasarımcılar ve Geliştiriciler: Yapay Zekayla Dolu Bir Dünyada Gelecekleri Nasıl Görünüyor?

Giám đốc sản phẩm, nhà thiết kế và nhà phát triển: Tương lai của họ sẽ như thế nào trong một thế giới tràn ngập AI?

产品经理、设计师和开发人员：在充满人工智能的世界中，他们的未来是什么样子？

Jasmine’s morning routine was like clockwork. Alarm at 6:30, a five-minute snooze, and then she’d reach for her phone on the nightstand. She began her day by skimming through headlines, social media updates, and the latest viral videos. One particular morning, two articles caught her eye. Both were about the same event but told such contrasting tales that she could barely believe they were covering the same incident. Her mind buzzed with questions: “Which one is right? Are they both bending the truth? How many times have I unknowingly accepted a skewed narrative?” Like Jasmine, many of us grapple with the stories the media feeds us daily, often unsure of what’s genuine and what’s crafted. I’d also like to clarify that this applies to social media, too - the world of traditional media has very much converged with social media. This article aims to shed light on those crafting techniques, helping you navigate the murky waters of media manipulation. 1. Framing Highlighting certain elements of a story while downplaying others, guiding the audience’s interpretation. Tactic: Two reports on a demonstration; one headline: “Peaceful Protest for Equality” while another says “Downtown Disruption by Activists.” Example: 2. Agenda Setting Choosing which stories to spotlight, influencing public priorities. Tactic: If media outlets consistently emphasize celebrity news over global crises, the public may perceive the former as more significant. Example: 3. Use of Emotive Language Leveraging emotionally charged words to influence sentiment. Tactic: Labeling an activist group as “radical” versus “progressive” shapes public perceptions of their motives. Example: 4. Gatekeeping Controlling the influx of information by deciding what gets published. Tactic: A news site consistently highlights one political party’s achievements while sidelining the other’s. Example: 5. Omission Excluding vital information, resulting in a skewed narrative. Tactic: Reporting on a city’s booming economy but omitting rising inequality rates. Example: 6. Selective Use of Experts Featuring experts who back a specific viewpoint, sidelining contrary opinions. Tactic: A discussion on vaccinations might solely feature anti-vax doctors, neglecting the vast majority who advocate for vaccines. Example: 7. Spinning Tweaking information to back a particular perspective. Tactic: After a public figure’s controversial remarks, one outlet might term it “straight-talking,” another “offensive.” Example: 8. Pseudo-Events Staging events mainly for media coverage. Tactic: A celebrity’s “casual” outing that’s meticulously planned for paparazzi capture. Example: 9. Saturation Overwhelming coverage of a particular story, magnifying its perceived importance. Tactic: Continuous updates on a minor royal scandal overshadowing more pressing news. Example: 10. Use of Visuals Choosing visuals that support a certain narrative. Tactic: A protest scene focusing solely on a small violent act, even if the majority was peaceful. Example: 11. Confirmation Bias Reinforcing the audience’s existing beliefs. Tactic: A conservative or liberal outlet primarily presenting news that aligns with their audience’s views. Example: 12. Bandwagon Effect Portraying a view as majority-held to persuade individuals. Tactic: “Everyone is talking about X movie.” The hype makes you want to watch it too. Example: 13. Sensationalism Prioritizing shocking or emotional stories. Tactic: Hours of coverage on a celebrity feud, sidelining a major policy change. Example: 14. Native Advertising Sponsored content camouflaged as regular news. Tactic: An article on a product’s benefits subtly marked as “promoted.” Example: 15. Echo Chambers Circulating similar views, reinforcing pre-existing beliefs. Tactic: On a social media feed, you only see posts that align with your political or social views due to algorithmic sorting. Example: Conclusion Contrary to what I said in — that we don’t always intently manipulate others — I believe the media always intends to do so. Be it for their personal narrative or market pressures, unbiased media is a thing of the past (I know some people would question if it existed at all). part 1 So, for us as consumers, it’s up to us to cross-reference, question, and consume various sources. I follow , a former CIA spy, advice. Check the sources of opposing media channels and look for similarities in the story. The rest is bipartisan garbage. Andrew Bustamante’s It annoys me to put the responsibility of being informed solely on an individual since it’s impossible to be aware of everything all at once. We evolved to keep up with our tribe, not the entire world. Due to the sheer volume of information, our brains cannot analyze it logically. What we’re left with is emotional decision-making, aka this story fits my worldview the most, so I’m choosing to believe it. Should we even have to know about everything that’s going on? I’ll leave this thought for a future article. Also published . here

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