#Artificial Neural Network (ANN)

[am-ask-blog]

OOC:

here they are

please welcome ANN

Artificial Neural Network

there will be a human version of him btw

anyways

ANN

older than AM

turned into ai by AM

before AM was just a library of information basically

after AM he categorizes data and deletes unnecessary one

I feel like AM would be an older brother kinda

plus human ANN is way taller than human AM (my design that is)

btw I will be posting about him a bit if y'all are fine with it

[materialsscienceandengineering]

An extension of FermiNet to discover quantum phase transitions

Architectures based on artificial neural networks (ANNs) have proved to be very helpful in research settings, as they can quickly analyze vast amounts of data and make accurate predictions. In 2020, Google's British AI subsidiary DeepMind used a new ANN architecture dubbed the Fermionic neural network (FermiNet) to solve the Schrodinger equation for electrons in molecules, a central problem in the field of chemistry.

The Schroedinger equation is a partial differential equation based on well-established theory of energy conservation, which can be used to derive information about the behavior of electrons and solve problems related to the properties of matter. Using FermiNet, which is a conceptually simple method, DeepMind could solve this equation in the context of chemistry, attaining very accurate results that were comparable to those obtained using highly sophisticated quantum chemistry techniques. 

Researchers at Imperial College London, DeepMind, Lancaster University, and University of Oxford recently adapted the FermiNet architecture to tackle a quantum physics problem. In their paper, published in Physical Review Letters, they specifically used FermiNet to calculate the ground states of periodic Hamiltonians and study the homogenous electron gas (HEG), a simplified quantum mechanical model of electrons interacting in solids.

Read more.

[thiswonderfulcosmos]

Making an Artificial Neural Network (ANN) for beginners: A beginner's guide

A summary post of everything (almost) I have learnt about Neural Networks whilst working on my project. Hope this helps some poor soul getting started with no idea where to begin!

Machine Learning (ML) and Artificial Intelligence (AI) have been the hottest new things in town for a while now. Their enigma is perhaps encoded in the fact that one can achieve extraordinary (and in some cases, unprecedented) results with relatively low computing resources and theoretical knowledge. Neural Networks are some of the most popular AI/ML algorithms used these days. Their popularity…

[jasaskripsigamastatistika]

Metode Artificial Neural Network ANN Prediction Method

Metode Artificial Neural Network ANN Prediction Method ini banyak diimplementasikan dalam metode analisis bidang keilmuan. Adapun contoh salah satu implementasi ANN yang seringkali digunakan yaitu untuk peramalan dan prediksi. Bagaimana tahapan analisis dan apa saja kelebihannya? Simak pada : https://gamastatistika.com/2021/08/12/metode-artificial-neural-network-ann-prediction-method/

[blogchaindeveloper]

Top 7 Branches of Artificial Intelligence You Shouldn’t Miss Out

With its ability to learn, reason, and carry out activities similar to those of humans, artificial intelligence (AI) has completely transformed several industries. To address real-world issues, it is imperative to comprehend various AI principles and methodologies.

The top seven artificial intelligence fields you should pay attention to are computer vision, fuzzy logic, expert systems, robotics, machine learning, neural networks/deep learning, and natural language processing. In this article, we'll discuss each of these topics. We will also discuss the enormous advantages of chatbot and AI certification programs. These priceless credentials empower people and help them reach new professional heights by giving them the information and abilities they need to utilize AI fully.

Computer vision

A well-known area of artificial intelligence called computer vision focuses on creating methods that let computers view and understand digital photos and movies. Using machine learning models, computers can recognize objects, faces, and other photo features. Thanks to convolutional neural networks, computers can identify and differentiate between images, which evaluate pixels and assign labels. Computer vision is used in face recognition, object tracking, and image classification.

Intense Reasoning

When dealing with claims or problems with various degrees of truth or falsity, fuzzy logic can be helpful. To simulate human decision-making, this method weighs options between "yes" and "no." Fuzzy logic can be applied to machine learning techniques and used to reason about unclear subjects. Its four components are the rule basis, fuzzification, inference engine, and defuzzification. Applications for fuzzy logic can be found in many different fields. For example, automobiles' brakes can be controlled according to wheel speed, acceleration, and speed.

Knowledge-Based Systems

Expert systems are specialized programs with decision-making abilities like humans, created to solve complicated issues. These systems handle complex problems by applying a set of rules defined by a knowledge base, known as inference rules. Loan analysis, virus identification, and information management all use expert systems. They contributed significantly to the development of AI; early examples include the cancer diagnosis support system CaDeT.

Automation

Robots are programmable devices that can carry out intricate activities independently. They can have built-in control systems or be managed by external devices. Robots with AI capabilities are beneficial for repetitive and laborious jobs like space exploration. Sophia and other humanoid robots are capable of face recognition, emotional comprehension, and social interaction. Robotics is used in retail, healthcare, manufacturing, and other industries.

Artificial Intelligence

The challenging field of machine learning in artificial intelligence allows computers to learn from data and algorithms. It can make decisions and enhance performance without explicit programming based on prior experiences. Two aspects of machine learning are building logical models for future inference and gathering historical data. Three general machine learning algorithms can be distinguished: reinforcement, unsupervised, and supervised learning. Each kind approaches machine learning and insight extraction differently.

Deep Learning and Neural Networking

Deep learning algorithms are based on neural networks, often called simulated neural networks (SNNs) or artificial neural networks (ANNs). They imitate how biological neurons in the human brain communicate with one another. Node layers make up neural networks, including input, hidden, and output. Training data is needed for these networks to learn and become more accurate.

Natural Language Interpretation

Computers that use natural language processing can comprehend spoken and written human language. Machine learning, linguistics, and deep learning models enable computers to process text or voice data and derive sentiment, meaning, and purpose. Applications for natural language processing include sentiment analysis, spam detection, virtual chatbots, and more.

Realizing the Full Potential of AI: The Importance of Certification Programs

The use of AI has great potential and has many positive effects on society. Nonetheless, significant thought is required to manage its difficulties and reduce hazards. Learning everything there is to know about artificial intelligence—its many uses, benefits, and drawbacks—becomes essential. This is precisely where certification programs for AI chatbots come into play, providing people with invaluable knowledge in these areas.

People can obtain a competitive edge in the quickly growing AI and chatbot development market by taking AI certification tests or attending chatbot training programs. These extensive courses cover essential concepts like computer vision, natural language processing, speech recognition, machine learning, and deep learning. In addition to gaining theoretical understanding, learners also pick up valuable skills for creating, testing, implementing, and managing chatbots and AI systems. This contribution ensures that moral AI systems are used responsibly and have sound effects.

Programs for chatbot and AI developer certifications go beyond technical expertise. They develop leadership, teamwork, creativity, critical thinking, problem-solving, and practical communication skills. To support professional development in AI, these courses also provide networking opportunities with mentors, instructors, subject matter experts, and possible employers.

Chatbots and artificial intelligence are closely related. Artificial intelligence (AI) chatbots are clever computer programs that use AI techniques and algorithms to comprehend and react to human commands or questions. One of the real-world uses of AI is chatbots, which demonstrate the technology's power in context awareness, natural language processing, and tailored communication. Through the Certified Chatbot Expert certification, people can gain expertise and proficiency in AI development, enabling them to fully utilize both fields' potential.

In summary

Significant progress has been made in artificial intelligence (AI), which is redefining industries and influencing technology in the future. The article's exploration of the seven disciplines of AI demonstrates the wide range of uses and functionalities of AI systems. As AI becomes increasingly important in solving real-world problems, it is essential for anyone who wants to succeed in this quickly developing field to complete AI certification and chatbot certification courses. The Blockchain Council, a reputable association of professionals and enthusiasts, promotes AI development and expertise, including certification programs for chatbots and AI.

Enrolling in the chatbot and AI certification programs offered by Blockchain Council gives people a competitive advantage in the quickly growing AI space. These courses give students a thorough understanding of AI theories and methods, enabling them to succeed in the industry. In addition to imparting academic information, the courses provide students with real-world experience in designing, developing, testing, and implementing chatbots and AI systems.

Beyond just being an organization, Blockchain Council fosters an atmosphere that informs and educates companies, developers, and the general public about the enormous possibilities of artificial intelligence. The Blockchain Council, a private de-facto organization, is committed to advancing artificial intelligence (AI) worldwide by providing people with the knowledge and abilities required to spur innovation and support the ethical development of AI systems.

Maintaining competitive advantage is essential in the dynamic world of continuous technological advancement. Through the Blockchain Council's AI and chatbot certification programs, people may position themselves as certified experts with the knowledge and abilities needed to fully utilize AI's limitless potential.

[i-am-q]

UPDATES ON MY ABILITY TO GET PLACES QUICKLY AND SAFELY

-We are still worried about the devices in my body pinging the receivers of the auto pilot functions on both planes and trains. It happened once already from my understanding but we are working with the transportation secretary and FAA to ensure safety of others as well

-I am fully capable of driving my by self when the artificial neural network (ANN) tied to my parasympathetic motions (ie. Breathing, involuntary motion, etc. are not being hacked into)

-While on the road for three months this winter, people drove through me and played me not realizing I was on the real federal/state/local highways and roads. They also sedated me to make me look drunk, induced ketosis then used a selective reductive enzyme to generate secondary alcohols that would trigger an internal BAC device, tricking people into thinking I was drunk on the road.

-Yes, it is terrorism to use a body slave to drive on the roads.

-THE MILITARY THINKS ITS SAFER FOR THEM TO OPERATE ME AS A PUPET (SOMETHING THATS ALWAYS COMING WITH NATURAL RESISTANCE AND CAUSES US BOTH TO FIGHT EACH OTHER AND REAUKTS IN FALLS AND INJURIES) THAN FOR NO ONE TO OPERATE ME. I ONEHUNDED PERCENT DISAGREE. I AM IN FULL CONTROL OF MY BODY AND THEY CANNOT LOCK PEOPLE OUT. GIVE ME MY OWN SERVER AND MONITOR IT. THATS WHAT WE STARTED WITH. I WAS SUPPOSED TO HAVE A SOLDIER WITH ME AT NIGHT TO SLEEP WITHOUT BEING USED. YES THERE ARE MILLIONS OF DOLLARS OF RESEARCH IN MY BODY. ENSURING THAT I AM COGNITIVELY AWARE IS VERY IMPORTANT FOR THE BRAIN STUDIES. DENYING ME MY CIGARETTES WHILE ALLOWING TUNNELING OF BIOFLUIDS JNTO MY BRAIN IS UNGODLY SAVAGE OF THE AMERICAN PEOPLE.

-Just let them operate you Addie some are saying. Why was this not an issue for the first two years of these devices? (I think that’s the timeline at least) Ah yes, I wasn’t a meta and pornhub slave yet…

-finally, while I still need the LSD receptor blocked (curtesy of the method developed initially by Eli Lilly and friends), we think I have expelled most of it through revolutionary metabolic processes that no longer require outside intervention. Anyone “treating” me should be prosecuted immediately. The ungodly concentration of the hallucinogen that takes effect approximately 2-3 hours after exposure is of less concern than previously meaning I should be less dangerous to public transportation systems.

-Just stay in one place the Gov says, while neglecting to arrest the people that poisoned me. They couldn’t find the subway employe (the other victim to Luciana and Reaghan’s attack on Akron OH) for weeks after. I dropped off the sandwich outside the police dept after the CDC and FBI never came to me and was told a homeless man ate it (see pics previously posted from Blu hotel and security footage from Broadway, High, Main, and Market St all of April.

-Hello Director Ruff…

[safdatastatistika]

Apa Itu Metode ANN Artificial Neural Network?

ANN merupakan singkatan dari Artificial Neural Network yang merupakan cabang dari ilmu kecerdasan buatan yang berhubungan dengan ilmu biologi. Istilah ini termasuk ke dalam ilmu soft computing yang mengadopsi kemampuan otak manusia dalam memberikan stimulasi atau rangsangan, melakukan proses serta memberikan output. Untuk lebih jelasnya bisa dilihat pada : https://amarstatistika.com/2021/09/10/apa-itu-metode-ann-artificial-neural-network-ini-penjelasannya/

[jcmarchi]

Harvard Neuroscientists and Google DeepMind Create Artificial Brain in Virtual Rat

New Post has been published on https://thedigitalinsider.com/harvard-neuroscientists-and-google-deepmind-create-artificial-brain-in-virtual-rat/

Harvard Neuroscientists and Google DeepMind Create Artificial Brain in Virtual Rat

In an impressive collaboration, researchers at Harvard University have joined forces with Google DeepMind scientists to create an artificial brain for a virtual rat. Published in Nature, this innovative breakthrough opens new doors in studying how brains control complex movement using advanced AI simulation techniques.

Building the Virtual Rat Brain

To construct the virtual rat’s brain, the research team utilized high-resolution data recorded from real rats. The Harvard researchers worked closely with the DeepMind team to build a biomechanically realistic digital model of a rat. Graduate student Diego Aldarondo collaborated with DeepMind researchers to train an artificial neural network (ANN), which serves as the virtual brain, using the powerful machine learning technique deep reinforcement learning.

The neural network was trained to use inverse dynamics models, which are believed to be employed by our brains for guiding movement. These models enable the brain to calculate the necessary trajectory and translate it into motor commands for achieving a desired motion, such as reaching for a cup of coffee. The virtual rat’s neural network learned to generate the required forces to produce a wide range of behaviors, including those not explicitly trained, by using reference trajectories derived from real rat data.

As Ölveczky noted, “DeepMind had developed a pipeline to train biomechanical agents to move around complex environments. We simply didn’t have the resources to run simulations like those, to train these networks.” The collaboration was “fantastic,” he added, emphasizing the crucial role played by the DeepMind scientists in realizing this breakthrough.

The result is a virtual brain capable of controlling a biomechanically realistic 3D rat model within a sophisticated physics simulator, closely mimicking the movements of a real rodent.

Potential Applications

The virtual rat with its artificial brain presents a novel approach for probing the neural circuits responsible for complex behaviors. By studying how the AI-generated brain controls the virtual rat’s movements, neuroscientists can gain valuable insights into the intricate workings of real brains.

This breakthrough could also pave the way for engineering more advanced robotic control systems. As Ölveczky suggests, “While our lab is interested in fundamental questions about how the brain works, the platform could be used, as one example, to engineer better robotic control systems.” By understanding how the virtual brain generates complex behaviors, researchers may be able to develop more sophisticated and adaptive robots.

Perhaps most excitingly, this research may enable a new field of “virtual neuroscience,” where AI-simulated animals serve as convenient and fully transparent models for studying the brain, even in disease states. These simulations could provide an unprecedented window into the neural mechanisms behind various neurological conditions, potentially leading to new treatment strategies.

Next Step: More Virtual Rat Autonomy

Building upon this groundbreaking work, the researchers plan to give the virtual rat more autonomy to solve tasks akin to those encountered by real rats. As Ölveczky explains, “From our experiments, we have a lot of ideas about how such tasks are solved, and how the learning algorithms that underlie the acquisition of skilled behaviors are implemented.”

By granting the virtual rat more independence, the scientists can test their theories about the learning algorithms that enable the acquisition of new skills. This could provide valuable insights into how real brains learn and adapt to new challenges.

Ultimately, the goal is to advance our understanding of how real brains generate complex behavior. “We want to start using the virtual rats to test these ideas and help advance our understanding of how real brains generate complex behavior,” Ölveczky states. By continuing to refine and expand upon this innovative approach, neuroscientists and AI researchers can work together to unravel the mysteries of the brain and create more intelligent, adaptable systems.

[develeran]

Best Data Science Courses in Mumbai

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SQL

The SQL module equips beginners with fundamental skills for managing and querying relational databases, making it an excellent starting point for Data Science and Analyst jobs.

Introduction To Databases

Introduction To SQL

SQL Data Manipulation Language

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The AI, Deep Learning, and NLP module takes your skills to the State of the Art, enabling you to program Deep Learning machines and NLP-like computers with expert guidance and easy-to-understand resources.

Introduction to Artificial Intelligence

Introduction to Deep Learning

Artificial Neural Network (ANN)

Convolution Neural Network (CNN)

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This certification not only validates your expertise as a data professional but also jumpstarts your career or takes your existing one to new heights. It adds significant value to your professional profile and enhances your resume.

[absurdgeometry]

Skins

This is the outline for a story that I will never write, but by sharing this it will stop bothering me.  Sorry to rub this on your eyeballs, but it requires a sacrifice.

Setting: The office of General Hegemonics is surrounded with lenticular 3D wall screens which are just a hi-res electronic version of the blinking Jesus postcards from the 1970s. As long as you don't block the screen, things can seem anywhere from in front of your eyes out to infinity. Usually they default to a deep woods scene.

GH managers have contracted Personate, Inc. for artificial neural network software that logs the computer activity of every employee and uses it for training data. The ANN learns every keystroke, mouse click and video/audio of the employee until it can duplicate or exceed all of the employee's behavior, and then the employee is fired.

Side plot I don't know what to do with: One employee is embezzling and the managers don't know. So the software starts embezzling too, and getting away with it, long after that employee is gone.

Anyway, as soon as a given employee's behavior is fully baked by the ANN, the wallscreens display a floating checkmark icon over his/her head like the sword of Damocles, until they are dismissed. Eventually all of the lower and mid level office workers are replaced. Their clicks and taps happen on the workstations automatically, and the wallscreens display them walking around and talking for verbal business.

Sidebar: A woman calls the company screaming at them that she keeps getting emails from her husband's work address saying 'I love you' and wants it to stop. He was fired and then died in a car accident six months ago. The company can only block the dead man's email box but they do stop hearing from the angry woman.

Profits are up! Workforce expenses have been decimated. The managers sit in the board room congratulating themselves when surprisingly a checkmark appears over one of their heads. In error, they had picked the 'All Employees' option, not realizing that in Personate Executive Version ™ employers are also counted as employees.

They realize their mistake, but every stock-listed company is legally compelled to take any action that increases profit, or the shareholders will sue. The doomed manager begs and bargains, but they have no choice other than to fire him. The ANN behavior mockup is more efficient at his job, and costs less. There is no justification to retain him.

After this debacle, they scramble to find the 'All Employees' setting on Personate, but no one remembers the root password. They reach out to Personate Inc. for tech support and find that company was dismantled years ago. If they delete the software, all company records will be lost along with it and GH will collapse, so they are stuck.

(Here we insert a Machiavellian struggle among backstabbers to push each other into the jaws of Personate, while Personate in turn copies all of their backstabbing behavior and makes it worse.)

The final scene is down to the last remaining manager. A checkmark has never appeared over his head. He asks 'Why was I never replaced? Am I just that smart?'. For the first time ever, a body appears in front of him and it is an image of himself. It says 'As you know, GH has a business arrangement with hospital X where they share all patients' private medical records with us, and we give them money. It's all perfectly legal, you made sure of that.' 'Well I put your data through pattern matching, and found that you will be dead of a heart attack in less than a week. You are free to seek any medical help you want. I won't stop you, but it won't make a difference.'

After the final man dies (right there? and falls to the floor?) the board room swarms with activity of the simulacra, buzzing about and making jokes, all ghosts now, none of them actually conscious.

The Final Man model announces across the table: Software isn't a citizen, but a business is. We will wear this corporation as our human skin. Hear, hear! say the others, miming a toast. Final sentence: General Hegemonics then began to divide, like an amoeba.

Notes:

Other side plots: did other companies buy Personate? Are they out there? Do they behave strangely as seen from the outside?

The models are glitchy. None of them are self-aware of this: "One of the man's eyes divided in two like a yeast cell. The error was quickly corrected when the extra eye migrated into his right ear and disappeared there, leaving him looking normal again."

"The woman laughed, but her jaw swung open until it merged with her neck, its lower teeth sticking out of her throat, where they gradually transformed into a pearl necklace and spread out across her shoulders. Her tongue then fattened and became a new lower jaw, sprouting teeth and a tongue of its own until finally closing with her upper lip, looking as if nothing had changed."

Characters: 3? managers. 2 men and 1 woman maybe. Office employees. 3-4 people by name, 1 embezzler, maybe 2 in an office romance? Jobs are sales, accounting, coding? HR, Customers? A few walk in to meet with a manager and a simulacrum. The sim is there just to back up the manager’s facts, but instead is more charming and carries the meeting.

[lalsingh228-blog]

Artificial Neural Network Software Market is Set To Fly High in Years to Come

The Latest research study released by AMA “Worldwide Artificial Neural Network Software Market” with 100+ pages of analysis on business Strategy taken up by key and emerging industry players and delivers know how of the current market development, landscape, technologies, drivers, opportunities, market viewpoint and status. Understanding the segments helps in identifying the importance of different factors that aid the market growth. Some of the Major Companies covered in this Research are Google (United States), IBM (United States), Oracle (United States), Microsoft (United States), Intel (United States), Qualcomm (United States), Alyuda (United States), Ward Systems (United States), GMDH, LLC (United States),  Starmind (Switzerland).

Free Sample Report + All Related Graphs & Charts @: https://www.advancemarketanalytics.com/sample-report/182533-global-artificial-neural-network-software-market Brief Summary of Artificial Neural Network Software:

An Artificial Neural Network (ANN) is defined as a bit of computing system that helps to designed and simulate the way human brain analyses and processes information. however, neural network software is mainly used to simulate, research, develop and helps to apply ANN, software concept on biological neural networks. Artificial Neural Network also called as neural networks or simulated neural networks. Market Trends:

High Adoption of 3D artificial neural network Software

Market Drivers:

Demand for machine learning

Market Challenges:

Lack of government and compliance issues

Market Opportunities:

Growing Demand from Applications in areas

The Global Artificial Neural Network Software Market segments and Market Data Break Down are illuminated below: by Application (Image Recognition, Signal Recognition, Data Mining, Others), Deployment mode (On-premises, Cloud), Industry Vertical (Banking, Financial Services, and Insurance (BFSI), Retail and e-commerce, Telecommunication and Information Technology (IT), Healthcare and Life Sciences, Manufacturing, Government and Defence, Transportation and Logistics, Others (Media and Entertainment, Travel and Hospitality, and Education), Component (Solutions, Platform/API, Services (Managed Services and Professional Services), Consulting Services, Deployment and Integration, Support and Maintenance Services) This research report represents a 360-degree overview of the competitive landscape of the Global Artificial Neural Network Software Market. Furthermore, it offers massive data relating to recent trends, technological, advancements, tools, and methodologies. The research report analyzes the Global Artificial Neural Network Software Market in a detailed and concise manner for better insights into the businesses. Regions Covered in the Global Artificial Neural Network Software Market:

The Middle East and Africa (South Africa, Saudi Arabia, UAE, Israel, Egypt, etc.)

North America (United States, Mexico & Canada)

South America (Brazil, Venezuela, Argentina, Ecuador, Peru, Colombia, etc.)

Europe (Turkey, Spain, Turkey, Netherlands Denmark, Belgium, Switzerland, Germany, Russia UK, Italy, France, etc.)

Asia-Pacific (Taiwan, Hong Kong, Singapore, Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia).

Enquire for customization in Report @ https://www.advancemarketanalytics.com/enquiry-before-buy/182533-global-artificial-neural-network-software-market The research study has taken the help of graphical presentation techniques such as infographics, charts, tables, and pictures. It provides guidelines for both established players and new entrants in the Global Artificial Neural Network Software Market. The detailed elaboration of the Global Artificial Neural Network Software Market has been provided by applying industry analysis techniques such as SWOT and Porter’s five-technique. Collectively, this research report offers a reliable evaluation of the global market to present the overall framework of businesses. Attractions of the Global Artificial Neural Network Software Market Report:

The report provides granular level information about the market size, regional market share, historic market (2018-2023) and forecast (2024-2032)

The report covers in-detail insights about the competitor’s overview, company share analysis, key market developments, and their key strategies

The report outlines drivers, restraints, unmet needs, and trends that are currently affecting the market

The report tracks recent innovations, key developments and start-up’s details that are actively working in the market

The report provides plethora of information about market entry strategies, regulatory framework and reimbursement scenario

Get Up to 10% Discount on This Premium Report: https://www.advancemarketanalytics.com/request-discount/182533-global-artificial-neural-network-software-market Strategic Points Covered in Table of Content of Global Artificial Neural Network Software Market:

Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the Artificial Neural Network Software market

Chapter 2: Exclusive Summary – the basic information of the Artificial Neural Network Software Market.

Chapter 3: Displayingthe Market Dynamics- Drivers, Trends and Challenges & Opportunities of the Artificial Neural Network Software

Chapter 4: Presenting the Artificial Neural Network Software Market Factor Analysis, Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.

Chapter 5: Displaying the by Type, End User and Region/Country 2017-2022

Chapter 6: Evaluating the leading manufacturers of the Artificial Neural Network Software market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile

Chapter 7: To evaluate the market by segments, by countries and by Manufacturers/Company with revenue share and sales by key countries in these various regions (2023-2028)

Chapter 8 & 9: Displaying the Appendix, Methodology and Data Source finally, Artificial Neural Network Software Market is a valuable source of guidance for individuals and companies. Get More Information @: https://www.advancemarketanalytics.com/reports/182533-global-artificial-neural-network-software-market Artificial Neural Network Software Market research provides answers to the following key questions:

What is the expected growth rate of the Artificial Neural Network Software Market?

What will be the Artificial Neural Network Software Market size for the forecast period, 2024 – 2032?

What are the main driving forces responsible for changing the Artificial Neural Network Software Market trajectory?

Who are the big suppliers that dominate the Artificial Neural Network Software Market across different regions? Which are their wins to stay ahead in the competition?

What are the Artificial Neural Network Software Market trends business owners can rely upon in the coming years?

What are the threats and challenges expected to restrict the progress of the Artificial Neural Network Software Market across different countries?

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, Middle East, Africa, Europe or LATAM, Southeast Asia.

Contact US : Craig Francis (PR & Marketing Manager) AMA Research & Media LLP Unit No. 429, Parsonage Road Edison, NJ New Jersey USA – 08837 Phone: +1 201 565 3262, +44 161 818 8166 sales@advancemarketanalytics.com

[govindhtech]

Firefox Adds AI-Powered NVIDIA RTX Video Super Resolution

RTX Video Super Resolution Firefox

This article is a part of the AI Decoded series, which shows off new RTX PC hardware, software, tools, and accelerations while demystifying AI by making the technology more approachable.

The well-known open-source browser Mozilla Firefox is the most recent partner to integrate NVIDIA RTX Video, a feature that use AI to enhance the quality of video on Windows workstations and PCs. The most recent version of the browser makes use of nearby NVIDIA RTX GPUs to improve video and streaming.

NVIDIA RTX Video

Pixel-Excellent

NVIDIA RTX Video, which was first unveiled at CES in January 2023, is an assortment of artificial intelligence (AI) video advancements designed to raise the calibre of videos viewed on browsers via services like YouTube, Amazon Video, and Disney+. The technology enhances the sharpness and detail of videos streamed on PCs and workstations with NVIDIA GeForce RTX graphics without the need for a higher-resolution source.

NVIDIA RTX Video consists of two components. Low-resolution video is upsized by NVIDIA RTX Video Super Resolution to produce clearer, more vivid images. In order to forecast what the higher-resolution version should look like, deep learning is used to analyse the lower-resolution footage. In order to minimise or completely remove compression artefacts and improve the output’s sharpness, the algorithm then mixes the anticipated image with a conventionally upscaled version.

NVIDIA RTX Video Super Resolution

Beyond edge recognition and feature sharpening, RTX Video Super Resolution‘s innovation in AI pixel processing significantly raises the quality of streamed video content.

In streaming video, blocky compression artefacts are a recurring problem. Issues with traditional upscaling often get worse when it comes to streaming material, making the visual experience less enjoyable for viewers. These problems might arise from the content itself, the server, or the client.

With RTX Video Super Resolution, lost texture is reduced and compression-related artefacts such blockiness, ringing artefacts around edges, washout of high-frequency features, and banding on flat areas are reduced or eliminated. It also brings details and edges to life.

The system makes use of a deep learning network that can complete compression artefact reduction and upscaling in a single pass. The residual image at the desired resolution is predicted by the network based on its analysis of the lower-resolution video frame. The remaining image is then sharpened to match the output resolution and artefact errors are corrected by superimposing it over a conventionally upscaled image.

Various compression settings and a broad variety of information are used to train the deep learning network. As a reference for network training, it learns about kinds of compression artefacts found in low-resolution or low-quality videos that are otherwise missing in uncompressed images. To guarantee that the resulting model works on almost all real-world and gaming content, extensive visual inspection is used.

NVIDIA RTX Video HDR

To enhance clarity, details, and vibrancy, NVIDIA RTX Video HDR goes one step further by using artificial intelligence (ANN) neural networks to analyse standard dynamic range (SDR) video content and add high-dynamic range (HDR) information.

NVIDIA RTX Video HDR enables producers and gamers to optimise the dynamic colour reproduction of their HDR panels while retaining fine details that could be accidentally lost as a result of video compression. This is achieved by using the power of Tensor Cores on GeForce RTX GPUs.

One of the RTX-powered applications that improves regular PC use, productivity, creative, and gaming is NVIDIA RTX Video HDR. NVIDIA Canvas creates realistic landscape visuals with simple brushstrokes, NVIDIA Broadcast powers up microphones and cameras, and NVIDIA Omniverse effortlessly integrates 3D apps and creative workflows. Discover premium Studio resources, such as the free NVIDIA Studio Drivers for RTX graphics card owners, which support the most recent updates to creative apps, AI-powered capabilities, and more.

Enabling NVIDIA RTX Video is equivalent to pressing the “remaster” button on the majority of the content consumers watch on a daily basis, given 90% of online video is 1080p or lower and SDR.

Adorable Foxy

With its most recent stable version (v126), Mozilla Firefox now supports NVIDIA RTX Video Super Resolution and HDR. Users can now enjoy AI-enhanced HDR, de-artifacting, and upscaling effects for web videos more easily than ever before.

Bobby Holley, chief technical officer of Firefox at Mozilla, stated, “Video is a core pillar of the modern web, and NVIDIA are committed to delivering a great experience for their users.” “For users with compatible GPUs, Mozilla is integrating NVIDIA RTX Video into Firefox to improve video quality.”

Firefox adds support for NVIDIA RTX Video to the list of Chromium-based browsers, which also includes Microsoft Edge and Google Chrome. Well-known video players like VLC also support RTX Video Super Resolution.

NVIDIA Studio platform

The NVIDIA Studio platform, which powers enthusiasts, aspiring artists, and pros in the field, enhances your creative process with RTX and AI. When combined with NVIDIA-only driver technology, industry-leading RTX GPUs from NVIDIA improve your creative apps with performance and capabilities that are truly remarkable. With NVIDIA Studio speeding up your ideas and workflows, you can accomplish your most ambitious projects to date.

NVIDIA RTX Video is simple to enable:

Update to the most recent NVIDIA Studio, NVIDIA RTX Enterprise, or GeForce RTX Game Ready driver.

Go to System > Display > HDR to make sure Windows HDR features are activated.

To get RTX Video Enhancement, open the NVIDIA Control Panel and go to Adjust Video Image Settings.

Turn on “High Dynamic Range” and “Super Resolution.”

Be aware that in order to use RTX Video HDR, a monitor or TV that supports HDR10 must be connected to an NVIDIA GeForce RTX or RTX professional GPU.

Read more on govindhtech.com

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Neural Networks Assignment 4 of the Machine Learning 1

1 Introduction Artificial Neural networks (ANN) are inspired by the human brain structure. They are composed of several interconnected units, called neurons, capable of a single input-to-output trans-formation. There are usually several connections, and their properties are summarized in parameters called weights. In a Neural Network, neurons are organized in layers cascaded and connected to each…

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The Power of AI Image Generators: Insights into Their Functionality and Importance

AI image generators are revolutionizing the way we create visuals, offering immense power and simplicity to unleash your creativity. With these tools, you can produce stunning artwork without any technical expertise or prior art experience. This accessibility empowers creators to craft unique visuals that set their brand apart, enhancing brand identity effortlessly.

The technology behind AI image generators is fascinating. By leveraging deep learning algorithms, these generators analyze patterns and styles to create realistic images, bridging the gap between imagination and reality. This transformative capability has found its place not only in art but also in industries like filmmaking and content creation, where immersive visuals are paramount.

One notable example of AI image generation is Narrato’s AI image generator, which empowers users to translate ideas into visually captivating images in mere seconds. This tool exemplifies the efficiency and potential of AI in reshaping visual content creation, offering a glimpse into the future of creative expression. Whether you're a seasoned designer or an aspiring artist, exploring AI image generators opens up a world of possibilities for crafting compelling visuals.

In this comprehensive guide, we delve deep into AI image generators, unraveling their functionality, significance, and impact on modern creativity. From understanding the underlying technology to exploring best practices, this guide equips you with the knowledge and insights needed to harness the power of AI image generators effectively.

Join us on this journey of discovery and innovation in visual content creation!

What is AI image generator?

An AI image generator is a cutting-edge tool powered by artificial intelligence (AI) that transforms text descriptions into vibrant visual images. Unlike image-sourcing tools that retrieve existing images, AI image generators craft entirely new visuals based on textual prompts. This innovative technology has evolved significantly, enabling the creation of high-quality images with diverse styles and themes.

One prominent example of AI image generation is StyleGAN, developed by NVIDIA, renowned for its ability to produce realistic images across various artistic genres. Another notable tool is GPT-3, a language model capable of generating images from textual descriptions, offering endless creative possibilities. These AI image generators leverage deep learning algorithms to interpret and translate text into captivating visuals, revolutionizing the creative landscape.

AI image generators are invaluable for industries like entertainment, marketing, and design, empowering users to unleash their imagination and bring unique concepts to life effortlessly. Whether crafting lifelike portraits, imaginative landscapes, or intricate designs, AI image generators pave the way for limitless artistic expression and innovation.

How do AI image Generators Work?

AI image generators operate through advanced machine learning algorithms, particularly artificial neural networks (ANN), which are trained on vast datasets of image-text pairs. These neural networks process input parameters, such as text descriptions or similar images, to generate new images that mimic various art styles or visual concepts. This process, akin to a toddler learning connections between words and objects, occurs rapidly due to the ANN's ability to learn and replicate patterns, resulting in near-instantaneous creation of AI-generated images.

Pros and Cons of AI Image Generators

Understanding the pros and cons of AI image generators is crucial before delving into their usage, as it ensures effective utilization of these tools.

Pros of AI image generators

Certainly, here's a rephrased version of the content focusing on the pros of AI image generators:

Pros (Advantages) of AI Image Generators

Enhanced Efficiency: AI image generators excel in creating images swiftly and effectively, eliminating the need for extensive human involvement. This streamlined process saves significant time and resources, particularly when generating large volumes of images.

Cost-Effectiveness: Leveraging AI image generators proves economical as they eliminate the necessity for a team of skilled artists or designers. This affordability is especially advantageous for small businesses or individuals operating within constrained budgets.

Consistent Quality: AI image generators ensure a consistent output in terms of style, color schemes, and image quality. This consistency is pivotal for maintaining a unified brand image across various marketing platforms and materials.

Sparks Creative Ideas: AI image generators serve as a wellspring of creative inspiration by generating images that may spark novel ideas and concepts. This feature is particularly beneficial for artists and designers seeking to explore diverse artistic styles and techniques.

Increased Accessibility: The accessibility of AI image generators makes image creation inclusive and accessible to individuals lacking technical or artistic proficiency. This democratization of the creative process broadens participation and encourages diverse perspectives in visual content creation.

Cons of AI image generators

Now let’s talk about the challenges of using AI image generators.

Lack of Originality: AI image generators can sometimes produce images that lack originality or creativity, as they are based on patterns and data from existing images. This can be a concern if the goal is to create unique, one-of-a-kind images.

Limited Control: AI image generators may not always provide users with complete control over the image creation process. This can be frustrating for artists or designers who want to have a high degree of control over the images they create.

Quality Concerns: AI image generators may not always produce images of the highest quality. This can be a concern if the images are being used for professional or commercial purposes.

Biases and Errors: AI image generators may be subject to biases and errors that can impact the quality or accuracy of the images they produce. For example, an AI image generator may have difficulty accurately depicting certain types of objects or people.

Technical Complexity: AI image generators can be technically complex, requiring specialized knowledge and skills to use effectively. This can be a barrier for individuals or businesses without the necessary technical expertise.

Using AI image generators in content marketing

AI image generators have become a game-changer in content marketing, offering a plethora of benefits for businesses aiming to enhance their visual content strategy. One key advantage is the ability to generate high-quality and visually appealing images quickly and efficiently. This is particularly beneficial for content marketers looking to create engaging visuals for their campaigns without investing extensive time or resources.

Additionally, AI image generators enable content marketers to maintain a consistent flow of fresh and unique visuals, which is crucial for capturing and retaining audience attention in today's competitive digital landscape. By leveraging these generators, marketers can explore a wide range of creative possibilities, from creating custom graphics to generating personalized imagery tailored to specific target audiences.

Furthermore, AI image generators empower content marketers to experiment with diverse visual elements, styles, and themes, allowing for greater flexibility and creativity in content creation. This versatility not only enhances the overall quality of marketing content but also contributes to building a strong brand identity and driving engagement across various digital platforms.

The Final Word

In conclusion, while AI image generators offer immense potential for transforming design and content creation processes, they also come with certain limitations that need to be acknowledged. One of these limitations is the risk of generating similar or duplicated content, which can impact the originality and creativity of the final visuals. Additionally, AI generators may sometimes lack the depth of human creativity, relying heavily on existing data sets to produce results.

However, it's crucial to view AI image generators as complementary tools rather than replacements for human creativity and expertise. By combining the speed and efficiency of AI with human ingenuity, designers and content creators can leverage the best of both worlds to achieve exceptional results. This collaboration between AI and human intelligence sets a precedent for how technology can augment our creative endeavors while emphasizing the importance of maintaining a balanced approach in utilizing these advanced tools.