PopSci

I explain experimental results of Bell’s Theorem by superdeterminism. I follow with insights into how such a universe may arise and be compatible with the subjective experience of free will.

Push notifications are similar to promoters. You're peacefully walking down the street, and suddenly promoters approach you, urging you to take their flyers. You take them, but you don't read them and throw them into the nearest trash can.

The same goes for push notifications. You're reading an article, and suddenly a notification pops up with a promo code for free delivery of products. Then another one arrives, informing you about a giveaway. And then another one, offering a discount on all fruits. Notifications can appear on your screen at any time. If there are too many of them, your reaction is either to ignore them or disable them.

In this article, we will talk about how to write push notifications that people will click on and show you how to build a push notification strategy. At the end, we will provide a template for a push notification strategy.

Push Notifications - What is it?

A push notification is a pop-up message on a smartphone screen. To send one, you need to use a delivery service. You can send a notification instantly, schedule it for a specific time, or set up a trigger-based delivery - a chain of notifications that will be triggered by specific user actions.

Triggered push notifications are sent after a specific action is taken. For example, if a person starts adding items to their cart but doesn't complete the purchase, you can send them a notification urging them to complete the transaction after a certain period of time.

Notifications are sent to users who fall into specific segments for targeting. Segments are formed based on specific events. For example, the event "6 hours ago, a product was added to the cart but no purchase was made" will divide users into two segments: those who made a purchase and those who didn't.

Let's talk about concept art, one of the main pillars in the digital art world. Concept art is the foundational and fundamental stage of any media industry project, where bold design choices are made and the best one is selected, shaping the overall style of the product. "Concept" refers to abstract ideas and fresh designs, while "art" entails the intentional use of imagination to create objects for immediate contemplation, which can be assessed for their aesthetic appeal in terms of appearance, sound, or even words. The exact origin of the term is not entirely clear, but some attribute its first mention to Walt Disney Feature Animation during the creation of characters for the first feature-length animated film, Snow White and the Seven Dwarfs, in the 1930s. It was during this time that an entirely new profession, later known as "concept artist," began to take form and became highly sought after in the media industry.

As a product owner, it is common to face the question of whether to proceed with option A or option B. Or, which version of the screen should be implemented to achieve better results? Making such decisions can be challenging, especially when you are under tight deadlines with limited resources. Furthermore, such decisions are made based on personal judgment or copying the approach of a competitor, which can lead to suboptimal results.

The good news is that one can avoid such pitfalls by setting up a simple experiment environment that requires relatively low effort. In this article, we will describe how you can achieve this.

Every day a new neural network appears and every day more opportunities are opened to designers to simplify their workflow. Someone fundamentally refuses to use them, because “there is no life in machinex and technologies”, and someone is only happy to find a way to reduce the amount of work. Personally, I belong to the second type and want to share the most detailed gait on neurons I have acquired lately. 

The life of Langton's Ant seems sad and lonely, but, as we'll soon discover, he is not ready to put up with such an outrageous situation and is trying his best to escape. American scientist Christopher Langton invented his ant back in 1986. Since then, no one has been able to explain the strange behavior of this mysterious model...

On the Internet and in non-fiction literature you can often find various mathematical tricks. The Collatz conjecture leaves all such tricks behind. At first glance, it may seem like some kind of a trick with a catch. However, there is no catch. You think of a number and repeat one of two arithmetic operations for it several times. Surprisingly, the result of these actions will always be the same. Or, may be not always?

Last week, I introduced you to the world of onchain analysis and explored some of the ways it can be used to gain insights into the cryptocurrency market.

Today, we're taking things up a notch with a tutorial that will guide you through running your own onchain analysis. By the end of this tutorial, you'll have the skills and knowledge you need to start analyzing blockchain data and making informed decisions about your cryptocurrency investments. So let's dive right in and see what insights we can uncover!

This tutorial is built around the Bitcoin blockchain, but many of the techniques are applicable to any other blockchains as long as they have wallets, balances, and transactions.

TL;DR: All AI-based noise cancellations suck, only the physical cancellation technique works! And physical cancellation is implemented well only in Jabra devices yet, but other features suck them! All Bluetooth headsets suck too! So, no solution yet, just complaints!

The environment: I work in a pretty talky office room, where sit around 10 people, and all of them have many online conferences every day, including me. So, silence in the room is a rare situation.

The problem: The main problem is that most of the microphones pick up all side talk pretty loud, which makes it very unpleasant for other people to listen to my voice in meetings!

Hey there, my fellow crypto enthusiast! Are you looking to take your trading game to the next level and gain a deeper understanding of the market trends and behavior? If so, then onchain analytics is the perfect tool for you.

People-professionals are working in IT, not robots

In fact the average competition for one workplace in IT is about 500 people – the market lacks specialists! You can find and read more. It's not hard to find on the internet

Need specialists who know their business!
For this reason, I wrote about how to become one and what you should pay attention to at the beginning of your journey. Even have my presentation with IT-directions! Also I understand something in Game Development..

Flew!🐌

I believe listicles have a huge potential for testing demand hypotheses. Have you tried using listicles for your demand validation? If so - let us know in the comments how this worked for you.

Do you know these "Top N something something" kind of articles? Like:
- 5 best GPS vehicle trackers
- The 14 hair growth products that actually work
- Top 10 Best CRM Software Tools in 2023
They are often referred to as "listicles" - articles presented in the form of a list.

I love them - they make picking a new phone, a movie to watch, an app to install much easier. I also use them at work all the time while looking for solutions to everyday challenges.

So what if we use one of them to benchmark our product against the best available alternatives?

Everything that follows from this point forward input prompts, followed by ChatCGP’s responses, complete with sample code in Swift.

> Hey ChatGPT, can you make a SwiftUI registration form with name, address and city fields?

Do you need to produce satellite interferometry results for your work or study? Or should you find the way to process terabytes of radar data on your common laptop? Maybe you aren't confident about the installation and usage of the required software. Fortunately, there is the next generation of satellite interferometry products available for you. Beginners can build the results easily and advanced users might work on huge datasets. Open Source software PyGMTSAR is available on GitHub for developers and on DockerHub for advanced users and on Google Colab for everyone. This is the cloud-ready product, and it works the same as do you run it locally on your old laptop as on powerful cloud servers.

Search your own data like in google search engine.

In this article I will talk about my attempt to create flexible, compact and beautiful modular prototyping framework

Online sports betting is a vertical of the gambling industry that has witnessed a massive surge in recent years. It is a great source of entertainment and thrill for online punters and bettors. Moreover, it also provides monetary benefits that are enough to entice the average layman. This is one of the most prominent reasons why people are gravitating towards these online sports betting platforms.

Additionally, the growing popularity of these platforms is urging sports betting software development companies to innovate and upgrade their platforms to cater to the growing needs of the user base. This is where Artificial Intelligence comes into the equation, AI has been at the forefront of innovations and development and has been offering users an enhanced user experience across multiple platforms. 

Artificial Intelligence technology has allowed Sports betting platforms to evolve with time and streamline their operations for better efficiency and enhanced productivity. This is why sports betting platforms all over the world are adopting this technology to offer better features and functionality to users and also increase their productivity and revenue. 

In this article, we will highlight how Artificial Intelligence has influenced the sports betting industry. So without further delay, let’s get started. 

Video recording of our webinar about dstack and reproducible ML workflows, AVL binary tree operations, Ultralytics YOLOv8, training XGBoost, productionize ML models, introduction to forecasting ensembles, domain expansion of image generators, Muse, X-Decoder, Box2Mask, RoDynRF, AgileAvatar and more.

Unlock the power of Transformer Neural Networks and learn how to build your own GPT-like model from scratch. In this in-depth guide, we will delve into the theory and provide a step-by-step code implementation to help you create your own miniGPT model. The final code is only 400 lines and works on both CPUs as well as on the GPUs. If you want to jump straight to the implementation here is the GitHub repo.

Transformers are revolutionizing the world of artificial intelligence. This simple, but very powerful neural network architecture, introduced in 2017, has quickly become the go-to choice for natural language processing, generative AI, and more. With the help of transformers, we've seen the creation of cutting-edge AI products like BERT, GPT-x, DALL-E, and AlphaFold, which are changing the way we interact with language and solve complex problems like protein folding. And the exciting possibilities don't stop there - transformers are also making waves in the field of computer vision with the advent of Vision Transformers.

Most people assume crypto and NFT are the same but both are different. NFTs are based on blockchain platforms that allow the minting and exchange of cryptocurrencies of a specific type. The basic difference between crypto and NFTs is that two NFTs can not have equal value. Meanwhile one 1 crypto coin will be equal to one coin.

In this article, we will discuss NFT games, like why they are trending and what features and functions are making them more advanced than traditional games. As the demand for NFT based is increasing day by day, then you can also churn this opportunity by developing your own game with the help of a crypto app development company. 

Before diving in, let’s know about the blockchain and NFTs.