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Today we’re diving into an exciting feature within ChatGPT that has the potential to enhance your productivity by 10, 20, 30, or even 40%. If you’re keen on learning how to leverage this feature to your advantage, make sure to read this article until the end. This feature stands out because it allows you to analyze almost anything by uploading your data and posing various questions to ChatGPT. Whether it's business data, your resume, or any other information you wish to explore, ChatGPT is here to deliver answers based on your specific dataset.

The world of education is constantly evolving, and one of the most significant recent advancements is the integration of 3D printing. This revolutionary technology, which allows for the creation of three-dimensional objects from digital models, is changing the way educators teach and students learn. At its core, 3D printing involves layer-by-layer construction of objects, enabling the production of complex designs that were previously impossible or too expensive to build.

In the past 5 years, I moved across 3 countries and 2 continents. It was not a short tourist travel or vacation, but a full immigrant experience with 1+ year experience minimum. I had to adapt to new cultures, new languages, new people, new food, new weather, new everything. One of the pains was to adopt new online services and information sources.

The problems I have faced were not obvious and interesting at the same time. I tried to analyze what was missing and required to make life easier.

Need to start your career or hobby in digital design and verification of silicon chips or reconfigurable hardware? Explore multiple FPGA toolchains and open-source ASIC tools? Design your own RISC-V CPU or ML accelerator? Prepare for an interview in SystemVerilog? Come to our first Silicon Valley meetup on portable SystemVerilog examples for ASIC and FPGA.

In Part 1, we became familiar with the concept of entropy.

In this part, we will delve into the concept of Mutual Information, which opens doors to error-resistant coding, compression algorithms, and offers a fresh perspective on regression and Machine Learning tasks.

It is an essential component that will pave the way, in the next section, for tackling Machine Learning problems as tasks of extracting mutual information between features and the predicted variable.

Here, there will be three interesting and crucial visualizations.

The first one will visualize entropy for two random variables and their mutual information.
The second one will shed light on the very concept of dependency between two random variables, emphasizing that zero correlation does not imply independence.
The third one will demonstrate that the bandwidth of an information channel has a straightforward geometric interpretation through the convexity measure of the entropy function.

In the meantime, we will prove a simplified version of the Shannon-Hartley theorem regarding the maximum bandwidth of a noisy channel. Let's dive in!

I develop robots, and I'm often asked, "How to make a robot?" and "Where do you find information and what resources do you use?"

If you don't know where to start and want to create your own robot, this article is for you. In it, I will try to explain the process and also share the first steps you should take.

3.What's an ugly smiling face?

It's the cat from curved space.

V. Komen, I. Tikhonenkov

Here we are discussing in general the majority of metrics for a stationary gravitation fields in one dimension. The only accepted approach so far to apply the equations of field (A. Einstein):

Today I would like to discuss the games Chess and Go, the world's champions, algorithms and Al.

In 1997, a computer program developed by IBM Deep Blue defeated the world Chess champion Garry Kasparov. Go remained the last board game in which humans were still better than machines.

Why is that?

Chess is primarily distinguished from Go by the number of variations for each move. Chess, the game is more predictable with more structured rules: we have value for each figure (e.g bishop = 3 pawns, rook = 5 pawns -> rook > bishop), some kind of openings and strategies. Go, in turn, has incredibly simple rules, which creates the complexity of the game for the machine. Go is one of the oldest board games. Until recently, it was assumed that a machine was not capable of playing on an equal footing with a professional player due to the high level of abstraction and the inability to sort through all possible scenarios - exactly as many valid combinations in a game on a standard 19×19 go-ban are 10¹⁸⁰ (greater than the number of atoms in the visible universe).

However, almost 20 years later, in 2015, there was a breakthrough. Google's Deep Mind company enhanced AlphaGo, which was the last step for the computer to defeat the world champions in board games. The AlphaGo program defeated the European champion and then, in March 2016 demonstrated a high level of play by defeating Lee Sedol, one of the strongest go players in the world, with a score of 4:1 in favour of the machine. A year later, Google introduced to the world a new version of AlphaGo - AlphaGoZero.

V. Komen, I. Tikhonenkov

In the previous post we've considered a model example of a motion of a free particle within a uniform gravitation field where a coupling to the field is defined by an observed inertion mass (see eq. (2) in https://habr.com/en/articles/739714/). The equation of motion was:

1 Playing Diplomacy

1.1 What this work is about

1.2 A puzzle for the talented and brave (Eccentrics are welcome: ?)

Uniform gravity, can it exist?

1. The motion of a free particle-like cat

V. Komen, I. Tikhonenkov

Good morning! You've woke up. Having prepared coffee and toasts of bread you are drifting from a kitchen to a table before a large wall TV. The left hand keeps a small plate with toasts and the right one controls coffee level within your beloved mug. The life is plotted out for ten seconds to come. But Ervin is already worried that you, as usual, made conspiracy and decided not to share your breakfast with him. So the damned cat thrusts himself across you pass, hits your legs. By the next moment the plate, toasts and the mug are falling. And – yes! All those precious things reached a floor level by the same time. Physics...It's how it shows up, unexpected. And we used to identify ourselves as physicists. The unexpected thing is that we still do. It's whence our motivation originates. We cannot pass by any falling objects quietly.

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.

This is the complete crash course on the Elliptic Curves Cryptography used in Bitcoin and other blockchains. With code samples and a live demo from scratch.

Konstantin Kotelnik, an analyst at Innotech, ponders over making technical documentation easier to understand for developers and helping the clip-thought generation work effectively with large quantities of data. Read the article to find out about the potential emergence of a graphical IT-Esperanto and the standardisation of technical language.

The first text-based CAPTCHA ( we’ll call it just CAPTCHA for the sake of brevity ) was used in 1997 by AltaVista search engine. It prevented bots from adding Uniform Resource Locator (URLs) to their web search engine.

Back then it was a decent defense measure. However the progress can't be stopped, and this defense was bypassed using OCR available at those times (for example FineReader).

CAPTCHA became more complex, noise was added to it, along with distortions, so the popular OCRs couldn’t recognize this text. And then OCRs custom made for this task appeared. It costed extra money and knowledge for the attacking side. The CAPTCHA developers were required to understand the challenges the attackers met, what distortions to add, in order to make the automation of the CAPTCHA recognition more complex.

The misunderstanding of the principles the OCRs were based on, some CAPTCHAs were given such distortions, that they were more of a hassle for regular users than for a machine.

OCRs for different types of CAPTCHAs were made using heuristics, and the most complicated part of it was the CAPTCHA segmentation for the stand along symbols, that subsequently could be easily recognized by the CNN (for example LeNet-5), also SVM showed a good result even on the raw pixels.

In this article I’ll try to grasp the whole history of CAPTCHA recognition, from heuristics to the contemporary automated recognition systems. We’ll figure out, if a CAPTCHA is still alive.

I’ll review the yandex.com CAPTCHA. The Russian version of the same CAPTCHA is more complex.

Hello, I am Aleksandr Ivanov, CTO at Quadcode. We came to Habr to show the Fintech “kitchen”; we’ve been at it for 8 years, so we can already share our experience. In our blog we will talk about architectures, technologies, tools and life hacks.

Overview

Sometimes all of us need to make a graphical installer for one's own linux distro. It goes without saying that you are able to use a distro-specific installer like Anaconda for RedHat-based or DebianInstaller for debian-based. On the other hand Calamares is a graphical installer which is not aligned with only one package manager.

I want to share my experience how to make a universal install solution with GUI. I did not find any complete article about it, hence, I reinvented the wheel.

When you have an IT, which supports all aspects of your organization automated performance and you have a firm confidence that IT executes well, there is always a chance that something could go wrong in technology or in related IT processes. Depending on complexity of IT environment varieties of risks scenarios could arise. This article as a summary of different faithworthy sources aims to help you in getting high level understanding on what could go wrong and how you can predict it in a more conscious way.

My name is Maxim Tornov and I have been working in various IT areas for a long period of time. Since then, for over 14 years I am working in the area of IT/IS risk management with focus on in IT/IS audits, internal control implementation and assessment.

I am sure that at the present the topic of Information Technologies risk management became more vital. Organization’s efficiency in IT risk management directly affects the achievement of various organization’s goals, goals which have dependency on IT, those goals may include reliability and efficiency of business processes, the organization's compliance with regulatory requirements, the integrity of financial reporting, and many others.

I sincerely hope that this material will be useful to you and may give you some new ideas that you can contribute to the benefit of your personal development and the development of your organization's risk management culture.

The All-Russian Institute of Aviation Materials (VIAM) showed its own developments in the field of additive technologies, including a series of small-sized gas-turbine engines MGTD-10, MGTD-20 and MGTD-150. 

Reverse engineering of such parts can be done using 3D scanners. You can see some examples and sample deviations here.

We have previously written about how the Raise3D Pro2 is used for printing surgical guides. In this article, we will talk about intervertebral cages developed and patented by the Pozvonoq startup of the North-West Technology Transfer Center and the Russian manufacturing company Ortoinvest, which specializes in the development and production of power equipment and implants for traumatology and orthopedics.