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The basis of artificial intelligence

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The Future of Artificial Intelligence in the Education System: Everything One Should Know

Machine learning *Artificial Intelligence
Sandbox
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Artificial Intelligence refers to the theory of computer systems or human-made robots programmed with performing tasks as humans, such as learning, generalization, and reasoning. With this ability, AI has become a significant part of human lives. Similarly, AI and the education & tutoring web solutions are inseparable from being observed by the astounding inventions enabling machines to mimic human roles.
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Views 2.5K
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AI-assisted IntelliSense for your team’s codebase

Microsoft corporate blog Programming *Visual Studio *Machine learning *Artificial Intelligence
Visual Studio IntelliCode uses machine learning to offer useful, contextually-rich code completion suggestions as you type, allowing you to learn APIs more quickly and code faster. Although IntelliCode’s base model was trained on over 3000 top open source C# GitHub repositories, it does not include all the custom types in your code base. To produce useful, high-fidelity, contextually-rich suggestions, the model needs to be tailored to unique types or domain-specific APIs that aren’t used in open source code. To make IntelliSense recommendations based on the wisdom of your team’s codebase, the model needs to train with your team’s code.

Earlier this year, we extended our ML model training capabilities beyond our initial Github trained base model to enable you to personalize your IntelliCode completion suggestions by creating team models trained on your own code.

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Total votes 2: ↑2 and ↓0 +2
Views 1K
Comments 1

Python for AI: A match made in heaven

Python *Machine learning *Software Artificial Intelligence AR and VR
The artificial intelligence global market is expected to reach $190 billion by 2025. The bright future of this technology allures every entrepreneur. In fact, when we think about the technologies that are going to rule in the future, the one name that comes to our minds is ~ Artificial intelligence.

AI along with its subsets like machine learning and deep learning is making such things possible which were unimaginable by humankind a few years back. It is affecting the realities and sometimes changing reality completely.



The power of AI is well acknowledged by businesses as 84% of respondents in a study voted that they believe artificial intelligence will allow them to enjoy a competitive edge over competitors.

Although entrepreneurs have an idea about AI but what most of them lack is proper implementation. The use of optimum programming tools for a complex technology like AI can create wonders for the world of business.

Every custom web developer knows that a python is an apt tool for building AI-enabled -applications. The language has been used to create 126,424 websites so far. Since its launch in the late 1980s, python has seen remarkable growth not only in users but in applications too.

Python is the favorite language for software developers to create applications that have artificial intelligence, machine learning, etc features embedded in them. But there are reasons behind everything.

This blog is written with the intent to unveil these reasons. Let’s explore why python is extensively used in AI-enabled software development services.
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Views 4.5K
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Use AI in marketing: Let’s get into the customers' mind

Development of mobile applications *Machine learning *Internet marketing Software Artificial Intelligence
Sandbox
“Instead of using technology to automate processes, think about using technology to enhance human interaction.” ~ Tony Zambito, Lead authority in Buyer Personas.

Do you know ~ according to research, 93% of customers make purchase decisions based on visual appearance. Visual elements of your brand are the key deciding factors for a majority of potential customers.

Your logo, website colors, chatbot texts, etc all have an impact on the psychology of people who come across them. Some colors or features attract them and some make them leave your website instantly.

In this era, interactive features with the help of technologies like Artificial intelligence are enhancing such effects. AI has the power to add interactive elements to your presentation. This creates a connection between your company and its customers.
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Total votes 4: ↑3 and ↓1 +2
Views 915
Comments 0

ML.NET Model Builder Updates

Microsoft corporate blog .NET *C# *Machine learning *Artificial Intelligence
ML.NET is a cross-platform, machine learning framework for .NET developers, and Model Builder is the UI tooling in Visual Studio that uses Automated Machine Learning (AutoML) to easily allow you to train and consume custom ML.NET models. With ML.NET and Model Builder, you can create custom machine learning models for scenarios like sentiment analysis, price prediction, and more without any machine learning experience!

ML.NET Model Builder


This release of Model Builder comes with bug fixes and two exciting new features:

  • Image classification scenario – locally train image classification models with your own images
  • Try your model – make predictions on sample input data right in the UI

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Total votes 6: ↑6 and ↓0 +6
Views 1K
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SpaceFusion: Structuring the unstructured latent space for conversational AI

Microsoft corporate blog Algorithms *Machine learning *Artificial Intelligence
A palette makes it easy for painters to arrange and mix paints of different colors as they create art on the canvas before them. Having a similar tool that could allow AI to jointly learn from diverse data sources such as those for conversations, narratives, images, and knowledge could open doors for researchers and scientists to develop AI systems capable of more general intelligence.


A palette allows a painter to arrange and mix paints of different colors. SpaceFusion seeks to help AI scientists do similar things for different models trained on different datasets.
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Total votes 5: ↑5 and ↓0 +5
Views 580
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The science behind how our brains work best, and how technology and our environment can help

Microsoft corporate blog Machine learning *Artificial Intelligence Brain


You’re utterly focused. You’ve lost track of time. Nothing else in the world exists. You’re living in the moment.

While this might sound like meditation, it’s a description that can also be applied to the state of flow – the feeling of being so engaged by your work, that you lose yourself to it completely, while massively increasing your productivity in the process.

It’s the holy grail that we all strive for, whether it’s a hobby we’re passionate about, or a project at work. Achieving our best and utilising our maximum potential at all times, can however, be a struggle.
We had the pleasure of talking with Dr. Jack Lewis, a neuroscientist with a passion for exploring how our minds work, to see what motivates us to do our best work, and the important roles that workplace environments, culture, and technology can play.
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Total votes 4: ↑4 and ↓0 +4
Views 1.2K
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Machine Learning for your flat hunt. Part 2

Python *Programming *Data Mining *Data visualization Machine learning *


Have you thought about the influence of the nearest metro to the price of your flat? 
What about several kindergartens around your apartment? Are you ready to plunge in the world of geo-spatial data?


The world provides so much information…



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Total votes 4: ↑4 and ↓0 +4
Views 1.3K
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Keyword Tree: graph analysis for semantic extraction

Data visualization Machine learning *Natural Language Processing *

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This post is a small abstract of full-scaled research focused on keyword recognition. Technique of semantics extraction was initially applied in field of social media research of depressive patterns. Here I focus on NLP and math aspects without psychological interpretation. It is clear that analysis of single word frequencies is not enough. Multiple random mixing of collection does not affect the relative frequency but destroys information totally — bag of words effect. We need more accurate approach for the mining of semantics attractors.

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Total votes 8: ↑7 and ↓1 +6
Views 879
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More than a game: Mastering Mahjong with AI and machine learning

Microsoft corporate blog Machine learning *Artificial Intelligence Logic games


Microsoft researchers have developed an artificial intelligence (AI) system that has taught itself the intricacies of Mahjong and can now match the skills of some of the world’s top players.

The complex board game of chance, bluff, and strategy was invented in China thousands of years ago and remains a passionate pastime for millions of Asians today, with many dedicated competitors playing online.

Computers have learned to play Chess and another ancient Chinese game, Go, amid much fanfare in the past. But scientists at Microsoft Research (MSR) Asia see their achievement as far more than just a case of technology mastering yet another game.

The researchers – who named their system Super Phoenix, or Suphx for short – developed a series of AI algorithmic breakthroughs to navigate the uncertain nature of Mahjong. With more work, these could potentially be applied in real situations to solve problems thrown up by unknown factors and random events.
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Total votes 11: ↑11 and ↓0 +11
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What's new in ML.NET and Model Builder

Microsoft corporate blog .NET *Big Data *Machine learning *Artificial Intelligence
We are excited to announce updates to Model Builder and improvements in ML.NET. You can learn more in the «What’s new in ML.NET?.» session at .NET Conf.

ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers.

ML.NET offers Model Builder (a simple UI tool) and CLI to make it super easy to build custom ML Models using AutoML.

Using ML.NET, developers can leverage their existing tools and skillsets to develop and infuse custom AI into their applications by creating custom machine learning models for common scenarios like Sentiment Analysis, Recommendation, Image Classification and more!..

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Total votes 4: ↑4 and ↓0 +4
Views 643
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A/B test is not enough

Machine learning *Internet marketing

A/B test is not enough


There is a common opinion that A/B test is a universal, half-automatic tool that always helps to increase conversion, loyalty and UX. However misinterpretation of results or wrong sampling leads to the loss of loyal audience and decrease of margin. Why? A/B is based on the basic assumption that this sample is homogeneous and representative, scalability of results. In reality, the audience is heterogeneous — recall the “20/80” distribution for income. Heterogeneity means that sensitivity to A/B varies significantly within the sample.
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Total votes 8: ↑8 and ↓0 +8
Views 930
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How we made landmark recognition in Cloud Mail.ru, and why

VK corporate blog Algorithms *Image processing *Machine learning *Artificial Intelligence


With the advent of mobile phones with high-quality cameras, we started making more and more pictures and videos of bright and memorable moments in our lives. Many of us have photo archives that extend back over decades and comprise thousands of pictures which makes them increasingly difficult to navigate through. Just remember how long it took to find a picture of interest just a few years ago.

One of Mail.ru Cloud’s objectives is to provide the handiest means for accessing and searching your own photo and video archives. For this purpose, we at Mail.ru Computer Vision Team have created and implemented systems for smart image processing: search by object, by scene, by face, etc. Another spectacular technology is landmark recognition. Today, I am going to tell you how we made this a reality using Deep Learning.
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Total votes 45: ↑44 and ↓1 +43
Views 1.8K
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Important Things to Know About Tensorflow 2.0

Open source *Development of mobile applications *Machine learning *Mobile applications design *Artificial Intelligence


Deep Learning applications have changed a lot of things. Some which give hope for a brighter future, and some which raise suspicions. However, for developers, the growth of deep learning applications has made them more perplexed about choosing the best among so many deep learning frameworks out there.

TensorFlow is one of the deep learning frameworks that comes in mind. It is arguably the most popular deep learning framework out there. Nothing justifies the statement better than the fact that Tensorflow is used by the likes of Uber, Nvidia, Gmail among other big corporations for developing state-of-the-art deep learning applications.

But right now, I am on a quest to find whether it indeed is the best deep learning framework. Or perhaps find what makes it the best out of all other frameworks it competes against.
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Total votes 14: ↑11 and ↓3 +8
Views 2.5K
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Internet of Things (IoT) is going to Change the World. Future of IoT

Machine learning *Development for IOT *Software Artificial Intelligence IOT
For the past two years, there’s been a lot of buzzing about the Internet of Things (IoT). This has to lead to the rapid selection of connected devices over industries and is determined to pass the 11 billion mark by the end of the year. Major Companies including IoT software development as their major services.

All these “things” are now creating their things, namely, lots and lots of data. This data will be at the core of commercial and industrial digital transformation (which is essentially the underlying force behind the fourth industrial revolution).

In other words, life as we know it is about to change forever! How is it going to change? Let’s take a look.

1. AI (Artifical Intelligence) can Effectively Manage Oceans of information

We can’t talk about IoT without AI as the latter has the power to make IoT a whole lot smarter and more efficient.

In fact, consultants believe that AI is the brains behind IoT systems that may facilitate build them run power tool.

For example, as more and more connected devices start communicating with each other, enterprises will need to leverage deep learning, image recognition, natural language processes, and neural-network driven decisions to help them understand each other (and us humans) better.

So far, we can say that IoT has felt like an isolated experience where it was just about simple data. Going forward, businesses will strive to achieve highly integrated experiences by using AI to better understand their employees, customers, and the general public living in smart cities.
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Total votes 10: ↑10 and ↓0 +10
Views 1.3K
Comments 6

Machine Learning and Theory of Constraints

Machine learning *Web analytics *Product Management *Business Models
Backlog prioritization requires simplification and weighting of tasks. Each one belongs to strategy like ads acquisition or CRO. We may consider turnover, operational costs, other metrics as input; profit margin, ROI — as output in case of retail. The perfect goal is to find 20/80 solution and focus resources on a single strategy at a time. Metrics tied to strategies gives the dimension of model. Sometimes unit economy relations are violated because of non-linearity. In practice it means low/insignificant correlation and poor regression. Example: it is impossible to separate acquisition and conversion — the quantity of acquisition affect its quality and vice versa. Decomposition of tasks/strategies assumes linear decomposition of nonlinear system. Besides nonlinear statistical evaluation of strategies is required when CJM can't be tracked or online/offline channels can't be separated.
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Total votes 13: ↑12 and ↓1 +11
Views 1K
Comments 2

Contextual Emotion Detection in Textual Conversations Using Neural Networks

VK corporate blog Python *Data Mining *Big Data *Machine learning *

Nowadays, talking to conversational agents is becoming a daily routine, and it is crucial for dialogue systems to generate responses as human-like as possible. As one of the main aspects, primary attention should be given to providing emotionally aware responses to users. In this article, we are going to describe the recurrent neural network architecture for emotion detection in textual conversations, that participated in SemEval-2019 Task 3 “EmoContext”, that is, an annual workshop on semantic evaluation. The task objective is to classify emotion (i.e. happy, sad, angry, and others) in a 3-turn conversational data set.
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Total votes 37: ↑37 and ↓0 +37
Views 2.4K
Comments 0

AI-Based Photo Restoration

VK corporate blog Algorithms *Image processing *Machine learning *


Hi everybody! I’m a research engineer at the Mail.ru Group computer vision team. In this article, I’m going to tell a story of how we’ve created AI-based photo restoration project for old military photos. What is «photo restoration»? It consists of three steps:

  • we find all the image defects: fractures, scuffs, holes;
  • we inpaint the discovered defects, based on the pixel values around them;
  • we colorize the image.

Further, I’ll describe every step of photo restoration and tell you how we got our data, what nets we trained, what we accomplished, and what mistakes we made.
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Total votes 34: ↑33 and ↓1 +32
Views 14K
Comments 5

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