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Artificial Intelligence

AI, ANN and other forms of an artificial Intelligence

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How Will Artificial Intelligence Influence Online Sports Betting?

Reading time 4 min
Views 148
Artificial Intelligence AR and VR
Opinion

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. 

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Data Phoenix Digest — ISSUE 2.2023

Reading time 2 min
Views 364
Python *Big Data *Machine learning *DevOps *Artificial Intelligence
Digest

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.

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Total votes 1: ↑1 and ↓0 +1
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Building a GPT-like Model from Scratch with Detailed Theory and Code Implementation

Reading time 14 min
Views 2.5K
Open Data Science corporate blog Python *Machine learning *Artificial Intelligence Natural Language Processing *
Tutorial

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.

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Total votes 25: ↑25 and ↓0 +25
Comments 0

Important Role of Cryptocurrency in NFT Game Development

Reading time 5 min
Views 371
Artificial Intelligence
Opinion

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.

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Total votes 2: ↑0 and ↓2 -2
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Exploring the Capabilities and Implications of ChatGPT 3 in the Educational Technology Field

Reading time 24 min
Views 957
Artificial Intelligence
Sandbox

From language translation and virtual assistants to self-driving cars and personalized recommendations, AI has been a buzzword for a while now, but it seems that it is only now with the new ChatGPT 3 being released to the public that it is so close to revolutionizing the educational technology field as well. In this article, I would like to give my first impressions, test results, and insights on the new technology.

ChatGPT is a chatbot by OpenAI that can write texts, code, answer questions, and solve various problems. It can even write college essays that, although lacking heart and personal touch, are still pretty good.

It somehow reminds me of the times when distance learning started captivating different fields and what started as a tool for kids with special needs (about 15 years ago, it was a major theme in pedagogical universities, at least) turned into massive online open courses from top universities available to anyone with access to the internet. In corporate learning culture, it went from "e-learning is a cheap and less effective replacement for offline trainings" to being a part of a complicated educational system where we can have the best qualities of offline and online learning for employees.

Right away, serious discussions emerged on the threats to the usage of ChatGPT. Since the beginning of December, many educators have been giving their opinion on its ability to write essays, code, and find correct answers for tests and on the studying culture that will probably need to change.

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Comments 5

InvokeAI 2.2: UI Outpainting, Embedding Management and more

Reading time 2 min
Views 3.2K
Python *Image processing *Machine learning *Graphic design *Artificial Intelligence

InvokeAI 2.2 is now available to everyone. This update brings in exciting features, like UI Outpainting, Embedding Management and more. See highlighted updates below, or the full release notes for everything included in the release.

What’s new?
Total votes 5: ↑5 and ↓0 +5
Comments 2

I trained a neural network on my drawings and give the model for free (and teach you to create your own)

Reading time 2 min
Views 1.7K
Python *Image processing *Machine learning *Graphic design *Artificial Intelligence
Tutorial

Great for seamless patterns, abstract drawings, and watercolor-styled images. How to use it and train a neural network on your own pictures?

Download the model here: https://huggingface.co/netsvetaev/netsvetaev-free

I wanna know!
Total votes 6: ↑6 and ↓0 +6
Comments 0

How Yandex Made Their Biggest Improvement in the Search Engine with the Help of Toloka

Reading time 5 min
Views 1.2K
Search engines *Data Mining *Machine learning *Artificial Intelligence Data Engineering *
Tutorial

Toloka is a crowdsourcing platform and microtasking project launched by Yandex to quickly markup large amounts of data. But how can such a simple concept play a crucial role in improving the work of neural networks?

Learn how
Total votes 1: ↑1 and ↓0 +1
Comments 0

FL_PyTorch is publicly available on GitHub

Reading time 2 min
Views 898
Mathematics *Machine learning *Artificial Intelligence

FL_PyTorch: Optimization Research Simulator for Federated Learning is publicly available on GitHub.

FL_PyTorch is a suite of open-source software written in python that builds on top of one of the most popular research Deep Learning (DL) frameworks PyTorch. We built FL_PyTorch as a research simulator for FL to enable fast development, prototyping, and experimenting with new and existing FL optimization algorithms. Our system supports abstractions that provide researchers with sufficient flexibility to experiment with existing and novel approaches to advance the state-of-the-art. The work is in proceedings of the 2nd International Workshop on Distributed Machine Learning DistributedML 2021. The paper, presentation, and appendix are available in DistributedML’21 Proceedings (https://dl.acm.org/doi/abs/10.1145/3488659.3493775).

The project is distributed in open source form under Apache License Version 2.0. Code Repository: https://github.com/burlachenkok/flpytorch.

To become familiar with that tool, I recommend the following sequence of steps:

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Total votes 1: ↑0 and ↓1 -1
Comments 0

Metaverses: hype or the future to come?

Reading time 5 min
Views 1K
Decentralized networks *Machine learning *Artificial Intelligence Social networks and communities AR and VR

Alexander Volchek, IT entrepreneur, CEO educational platform GeekBrains

Pretty much everyone in the IT community is talking metaverses, NFTs, blockchain and cryptocurrency. This time we will discuss metaverses, and come back to everything else in the letters to follow. Entrepreneurs and founders of tech giants are passionate about this idea, and investors are allocating millions of dollars for projects dealing with metaverses. Let's start with the basics.

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Total votes 2: ↑1 and ↓1 0
Comments 0

«If I had a heart...» Artificial Intelligence

Reading time 8 min
Views 2.9K
Reading room Artificial Intelligence Science fiction

Most people fear of artificial intelligence (AI) for the unpredictability of its possible actions and impact [1], [2]. In regard to this technology concerns are voiced also by AI experts themselves - scientists, engineers, among whom are the foremost faces of their professions [3], [4], [5]. And you possibly share these concerns because it's like leaving a child alone at home with a loaded gun on the table - in 2021, AI was first used on the battlefield in completely autonomous way: with an independent determination of a target and a decision to defeat it without operator participation [6]. But let’s be honest, since humanity has taken in the opportunities this new tool could give us, there is already no way back – this is how the law of gengle works [7].

Imagine the feeling of a caveman observing our modern routine world: electricity, Internet, smartphones, robots... etc. In the next two hundred years in large part thankfully to AI humankind will undergo the number of transformations it has since the moment we have learned to control the fire [8]. The effect of this technology will surpass all our previous changes as a civilization. And even as a species, because our destiny is not to create AI, but to literally become it.

... more, give me more, give me more ...
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Comments 0

Text-based CAPTCHA in 2022

Reading time 7 min
Views 1.9K
Information Security *Machine learning *Artificial Intelligence
Translation

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.

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Total votes 4: ↑3 and ↓1 +2
Comments 0

ruDALL-E: Generating Images from Text. Facing down the biggest computational challenge in Russia

Reading time 11 min
Views 7.6K
Сбер corporate blog SberDevices corporate blog Image processing *Machine learning *Artificial Intelligence

Multimodality has led the pack in machine learning in 2021. Neural networks are wolfing down images, text, speech and music all at the same time.  OpenAI is, as usual, top dog, but as if in defiance of their name, they are in no hurry to share their models openly.  At the beginning of the year, the company presented the DALL-E neural network, which generates 256x256 pixel images in answer to a written request.  Descriptions of it can be found as articles on arXiv and examples on their blog.  

As soon as DALL-E flushed out of the bushes, Chinese researchers got on its tail.  Their open-source CogView neural network does the same trick of generating images from text.  But what about here in Russia? One might say that “investigate, master, and train” is our engineering motto.  Well, we caught the scent, and today we can say that we created from scratch a complete pipeline for generating images from descriptive textual input written in Russian.

In this article we present the ruDALL-E XL model, an open-source text-to-image transformer with 1.3 billion parameters as well as ruDALL-E XXL model, an text-to-image transformer with 12.0 billion parameters which is available in DataHub SberCloud, and several other satellite models.

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Total votes 3: ↑3 and ↓0 +3
Comments 4

Data Phoenix Digest — 01.07.2021

Reading time 5 min
Views 1.5K
Python *Algorithms *Big Data *Machine learning *Artificial Intelligence

We at Data Science Digest have always strived to ignite the fire of knowledge in the AI community. We’re proud to have helped thousands of people to learn something new and give you the tools to push ahead. And we’ve not been standing still, either.

Please meet Data Phoenix, a Data Science Digest rebranded and risen anew from our own flame. Our mission is to help everyone interested in Data Science and AI/ML to expand the frontiers of knowledge. More news, more updates, and webinars(!) are coming. Stay tuned!

The new issue of the new Data Phoenix Digest is here! AI that helps write code, EU’s ban on biometric surveillance, genetic algorithms for NLP, multivariate probabilistic regression with NGBoosting, alias-free GAN, MLOps toys, and more…

If you’re more used to getting updates every day, subscribe to our Telegram channel or follow us on social media: TwitterFacebook.

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Total votes 1: ↑0 and ↓1 -1
Comments 1

DataScience Digest — 24.06.21

Reading time 5 min
Views 1.5K
Python *Algorithms *Big Data *Machine learning *Artificial Intelligence

The new issue of DataScienceDigest is here!

The impact of NLP and the growing budgets to drive AI transformations. How Airbnb standardized metric computation at scale. Cross-Validation, MASA-SR, AgileGAN, EfficientNetV2, and more.

If you’re more used to getting updates every day, subscribe to our Telegram channel or follow us on social media: Twitter, LinkedIn, Facebook.

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Total votes 2: ↑1 and ↓1 0
Comments 0

Flitter Your Business With AI Integrated Flutter App Development

Reading time 5 min
Views 2.3K
Development of mobile applications *Machine learning *Software Artificial Intelligence Flutter *
Sandbox

As we all are aware of the fact that the digital market is heavily leaning towards a reliable UX-driven process, app development has become quite complex, especially for targeting the industry for mobile platforms.

For every organization, creating a product that is beneficial for their customer needs always comes up with a plethora of challenges. 

From the technical point of time, there are various challenges that every business faces, including selecting the right platform for the app, the right technology stack or framework, and creating an app that fulfills the needs and expectations of customers.  

Similarly, there are more challenges that every business faces and needs to cope with while creating its dream product. 

So, what to do??

Well, what if I say that the answer to all your queries and questions is Flutter app development with Artificial Intelligence (AI)  integration……

Surprised? Wondering how? 

Well, AI in Flutter app development is one of the best advancements in the software market. The concept of AI was first introduced during the 20th century with loads of innovations and advancements that we are still integrating into our mobile app development. 

But, what are Artificial Intelligence and Flutter app development? 

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