Elton  Bogan

Elton Bogan

1596691440

MachineRay: Using AI to Create Abstract Art

For the past three months, I have been exploring the latest techniques in Artificial Intelligence (AI) and Machine Learning (ML) to create abstract art. During my investigation, I learned that three things are needed to create abstract paintings: (A) source images, (B) an ML model, and © a lot of time to train the model on a high-end GPU. Before I discuss my work, let’s take a look at some prior research.

Background

Artificial Neural Networks

Warren McCulloch and Walter Pitts created a computational model for Neural Networks (NNs) back in 1943[1]. Their work led to research of both the biological processing in brains and the use of NNs for AI. Richard Nagyfi discusses the differences between Artificial Neural Networks (ANNs) and biological brains in this post. He describes an apt analogy that I will summarize here: ANNs are to brains as planes are to birds. Although the development of these technologies was inspired by biology, the actual implementations are very different!

Image for post

Visual Analogy Neural Network chip artwork by mikemacmarketin CC BY 2.0, Brain model by biologycorner CC BY-NC 2.0, Plane photo by Moto@Club4AG CC BY 2.0, Bird photo by ksblack99 CC PDM 1.0

Both ANNs and biological brains learn from external stimuli to understand things and predict outcomes. One of the key differences is that ANNs work with floating-point numbers and not just binary firing of neurons. With ANNs it’s numbers in and numbers out.

The diagram below shows the structure of a typical ANN. The inputs on the left are the numerical values that contain the incoming stimuli. The input layer is connected to one or more hidden layers that contain the memory of prior learning. The output layer, in this case just one number, is connected to each of the nodes in the hidden layer.

Image for post

Diagram of a Typical ANN

Each of the internal arrows represents numerical weights that are used as multipliers to modify the numbers in the layers as they get processed in the network from left to right. The system is trained with a dataset of input values and expected output values. The weights are initially set to random values. For the training process, the system runs through the training set multiple times, adjusting the weights to achieve the expected outputs. Eventually, the system will not only predict the outputs correctly from the training set, but it will also be able to predict outputs for unseen input values. This is the essence of Machine Learning (ML). The intelligence is in the weights. A more detailed discussion of the training process for ANNs can be found in Conor McDonald’s post, here.

Generative Adversarial Networks

In 2014, Ian Goodfellow and seven coauthors at the Université de Montréal presented a paper on Generative Adversarial Networks (GANs)[2].** They came up with a way to train two ANNs that effectively compete with each other to create content like photos, songs, prose, and yes, paintings.** The first ANN is called the Generator and the second is called the Discriminator. The Generator is trying to create realistic output, in this case, a color painting. The Discriminator is trying to discern real paintings from the training set as opposed to fake paintings from the generator. Here’s what a GAN architecture looks like.

Image for post

Generative Adversarial Network

A series of random noise is fed into the Generator, which then uses its trained weights to generate the resultant output, in this case, a color image. The Discriminator is trained by alternating between processing real paintings, with an expected output of 1 and fake paintings, with an expected output of -1. After each painting is sent to the Discriminator, it sends back detailed feedback about why the painting is not real, and the Generator adjusts its weights with this new knowledge to try and do better the next time. The two networks in the GAN are effectively trained together in an adversarial fashion. The Generator gets better at trying to pass off a fake image as real, and the Discriminator gets better at determining which input is real, and which is fake. Eventually, the Generator gets pretty good at generating realistic-looking images. You can read more about GANs, and the math they use, in Shweta Goyal’s post here.

#abstract-art #python #artificial-intelligence #machine-learning #generative-adversarial

What is GEEK

Buddha Community

MachineRay: Using AI to Create Abstract Art
Edna  Bernhard

Edna Bernhard

1598573522

ART + AI

The idea that AI can infiltrate the field of art is frightening and rightfully so. While it has been no secret that AI can definitely replace blue-collar jobs and possibly threaten white-collar jobs, the idea that it can impact the livelihood of artists isn’t one that the media has foretold, nor have dystopian movies explored. However, we can see early traces of AI in art. It has slowly seeped into written literature, journalism, paintings and even music.

Having said that, this isn’t a novel (😉) idea. Sometime in the 90s, a music theory professor trained a program to write Bach-styled compositions. Then, to his students, he played both the real and computer-generated versions. To them, both were indistinguishable. Since then, technology has rapidly improved to a state that AI can create music of its own.

#ai #art #artificial-intelligence #art-and-ai #is-ai-art-really-art #is-art-unique-to-humans #creativity #future

Otho  Hagenes

Otho Hagenes

1619511840

Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution

Elton  Bogan

Elton Bogan

1596691440

MachineRay: Using AI to Create Abstract Art

For the past three months, I have been exploring the latest techniques in Artificial Intelligence (AI) and Machine Learning (ML) to create abstract art. During my investigation, I learned that three things are needed to create abstract paintings: (A) source images, (B) an ML model, and © a lot of time to train the model on a high-end GPU. Before I discuss my work, let’s take a look at some prior research.

Background

Artificial Neural Networks

Warren McCulloch and Walter Pitts created a computational model for Neural Networks (NNs) back in 1943[1]. Their work led to research of both the biological processing in brains and the use of NNs for AI. Richard Nagyfi discusses the differences between Artificial Neural Networks (ANNs) and biological brains in this post. He describes an apt analogy that I will summarize here: ANNs are to brains as planes are to birds. Although the development of these technologies was inspired by biology, the actual implementations are very different!

Image for post

Visual Analogy Neural Network chip artwork by mikemacmarketin CC BY 2.0, Brain model by biologycorner CC BY-NC 2.0, Plane photo by Moto@Club4AG CC BY 2.0, Bird photo by ksblack99 CC PDM 1.0

Both ANNs and biological brains learn from external stimuli to understand things and predict outcomes. One of the key differences is that ANNs work with floating-point numbers and not just binary firing of neurons. With ANNs it’s numbers in and numbers out.

The diagram below shows the structure of a typical ANN. The inputs on the left are the numerical values that contain the incoming stimuli. The input layer is connected to one or more hidden layers that contain the memory of prior learning. The output layer, in this case just one number, is connected to each of the nodes in the hidden layer.

Image for post

Diagram of a Typical ANN

Each of the internal arrows represents numerical weights that are used as multipliers to modify the numbers in the layers as they get processed in the network from left to right. The system is trained with a dataset of input values and expected output values. The weights are initially set to random values. For the training process, the system runs through the training set multiple times, adjusting the weights to achieve the expected outputs. Eventually, the system will not only predict the outputs correctly from the training set, but it will also be able to predict outputs for unseen input values. This is the essence of Machine Learning (ML). The intelligence is in the weights. A more detailed discussion of the training process for ANNs can be found in Conor McDonald’s post, here.

Generative Adversarial Networks

In 2014, Ian Goodfellow and seven coauthors at the Université de Montréal presented a paper on Generative Adversarial Networks (GANs)[2].** They came up with a way to train two ANNs that effectively compete with each other to create content like photos, songs, prose, and yes, paintings.** The first ANN is called the Generator and the second is called the Discriminator. The Generator is trying to create realistic output, in this case, a color painting. The Discriminator is trying to discern real paintings from the training set as opposed to fake paintings from the generator. Here’s what a GAN architecture looks like.

Image for post

Generative Adversarial Network

A series of random noise is fed into the Generator, which then uses its trained weights to generate the resultant output, in this case, a color image. The Discriminator is trained by alternating between processing real paintings, with an expected output of 1 and fake paintings, with an expected output of -1. After each painting is sent to the Discriminator, it sends back detailed feedback about why the painting is not real, and the Generator adjusts its weights with this new knowledge to try and do better the next time. The two networks in the GAN are effectively trained together in an adversarial fashion. The Generator gets better at trying to pass off a fake image as real, and the Discriminator gets better at determining which input is real, and which is fake. Eventually, the Generator gets pretty good at generating realistic-looking images. You can read more about GANs, and the math they use, in Shweta Goyal’s post here.

#abstract-art #python #artificial-intelligence #machine-learning #generative-adversarial

Why Use WordPress? What Can You Do With WordPress?

Can you use WordPress for anything other than blogging? To your surprise, yes. WordPress is more than just a blogging tool, and it has helped thousands of websites and web applications to thrive. The use of WordPress powers around 40% of online projects, and today in our blog, we would visit some amazing uses of WordPress other than blogging.
What Is The Use Of WordPress?

WordPress is the most popular website platform in the world. It is the first choice of businesses that want to set a feature-rich and dynamic Content Management System. So, if you ask what WordPress is used for, the answer is – everything. It is a super-flexible, feature-rich and secure platform that offers everything to build unique websites and applications. Let’s start knowing them:

1. Multiple Websites Under A Single Installation
WordPress Multisite allows you to develop multiple sites from a single WordPress installation. You can download WordPress and start building websites you want to launch under a single server. Literally speaking, you can handle hundreds of sites from one single dashboard, which now needs applause.
It is a highly efficient platform that allows you to easily run several websites under the same login credentials. One of the best things about WordPress is the themes it has to offer. You can simply download them and plugin for various sites and save space on sites without losing their speed.

2. WordPress Social Network
WordPress can be used for high-end projects such as Social Media Network. If you don’t have the money and patience to hire a coder and invest months in building a feature-rich social media site, go for WordPress. It is one of the most amazing uses of WordPress. Its stunning CMS is unbeatable. And you can build sites as good as Facebook or Reddit etc. It can just make the process a lot easier.
To set up a social media network, you would have to download a WordPress Plugin called BuddyPress. It would allow you to connect a community page with ease and would provide all the necessary features of a community or social media. It has direct messaging, activity stream, user groups, extended profiles, and so much more. You just have to download and configure it.
If BuddyPress doesn’t meet all your needs, don’t give up on your dreams. You can try out WP Symposium or PeepSo. There are also several themes you can use to build a social network.

3. Create A Forum For Your Brand’s Community
Communities are very important for your business. They help you stay in constant connection with your users and consumers. And allow you to turn them into a loyal customer base. Meanwhile, there are many good technologies that can be used for building a community page – the good old WordPress is still the best.
It is the best community development technology. If you want to build your online community, you need to consider all the amazing features you get with WordPress. Plugins such as BB Press is an open-source, template-driven PHP/ MySQL forum software. It is very simple and doesn’t hamper the experience of the website.
Other tools such as wpFoRo and Asgaros Forum are equally good for creating a community blog. They are lightweight tools that are easy to manage and integrate with your WordPress site easily. However, there is only one tiny problem; you need to have some technical knowledge to build a WordPress Community blog page.

4. Shortcodes
Since we gave you a problem in the previous section, we would also give you a perfect solution for it. You might not know to code, but you have shortcodes. Shortcodes help you execute functions without having to code. It is an easy way to build an amazing website, add new features, customize plugins easily. They are short lines of code, and rather than memorizing multiple lines; you can have zero technical knowledge and start building a feature-rich website or application.
There are also plugins like Shortcoder, Shortcodes Ultimate, and the Basics available on WordPress that can be used, and you would not even have to remember the shortcodes.

5. Build Online Stores
If you still think about why to use WordPress, use it to build an online store. You can start selling your goods online and start selling. It is an affordable technology that helps you build a feature-rich eCommerce store with WordPress.
WooCommerce is an extension of WordPress and is one of the most used eCommerce solutions. WooCommerce holds a 28% share of the global market and is one of the best ways to set up an online store. It allows you to build user-friendly and professional online stores and has thousands of free and paid extensions. Moreover as an open-source platform, and you don’t have to pay for the license.
Apart from WooCommerce, there are Easy Digital Downloads, iThemes Exchange, Shopify eCommerce plugin, and so much more available.

6. Security Features
WordPress takes security very seriously. It offers tons of external solutions that help you in safeguarding your WordPress site. While there is no way to ensure 100% security, it provides regular updates with security patches and provides several plugins to help with backups, two-factor authorization, and more.
By choosing hosting providers like WP Engine, you can improve the security of the website. It helps in threat detection, manage patching and updates, and internal security audits for the customers, and so much more.

Read More

#use of wordpress #use wordpress for business website #use wordpress for website #what is use of wordpress #why use wordpress #why use wordpress to build a website

Murray  Beatty

Murray Beatty

1598606037

This Week in AI | Rubik's Code

Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.

#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai