Mediaboss Marketing

Anyone who has held paper and a paintbrush knows the effort it goes into making a piece of art. The effort went for a toss last year when our timelines across social media platforms got inundated by AI-generated artworks, stunning yet scary to fathom. Machines replacing human labour is something we have often heard, that it could happen to artists was somewhat inconceivable. And that an AI tool can generate artwork by just mere prompts can leave any artist uneasy.

While artificial intelligence (AI) is doing its thing, an academic research group of PhD students and professors at the University of Chicago, USA, have launched a tool to thwart it. Glaze is their academic research project aimed at thwarting AI from mimicking the style of artists. What if you could add a cloak layer to your digital artwork that makes it harder for AI to mimic? Say hello to Glaze, it says on its website.

Also read: Heres how much Mukesh Ambanis chef earns; Check salary and compensation here

Glaze is a tool to help artists to prevent their artistic styles from being learned and mimicked by new AI-art models such as MidJourney, Stable Diffusion and their variants. It is a collaboration between the University of Chicago SAND Lab and members of the professional artist community, most notably Karla Ortiz. Glaze has been evaluated via a user study involving over 1,100 professional artists, Glazes website reads.

Glaze Beta2 has been made available for download starting March 18.

It is a normal exercise for several artists to post their work online to build a portfolio and even earn from it. However, generative AI tools have been equipped to create artworks in the same style after just seeing a few of the original ones.

This is what Glaze aims to thwart by creating a cloaked version of the original image.

Glaze generates a cloaked version for each image you want to protect. During this process, none of your artwork will ever leave your own computer. Then, instead of posting the original artwork online, you could post the cloaked artwork to protect your style from AI art generators, it says.

The way it happens is, when an artist wants to post her work online but does not want AI to mimic it, she can upload her work, in digital form, to Glaze. The tool then makes a few changes, which are hardly visible to the human eye. We refer to these added changes as a style cloak and changed artwork as cloaked artwork, it says. While the cloaked artwork appears identical to the original to humans, the machine picks up the altered version. Hence, whenever it gets a prompt, say Mughal women in south Delhi in MF Husain style, the artwork generated by AI will be very different from the said artists style. This protects the artistic style to be mimicked without the artists consent.

While Glaze Beta2 is available for download, the research is under peer review.

Glaze, however, has its share of shortcomings. Like changes made to certain artworks that have flat colours and smooth backgrounds, such as animation styles, are more visible. While this is not unexpected, we are searching for methods to reduce the visual impact for these styles, the makers say.

Also, unfortunately, Glaze is not a permanent solution against AI mimicry, they say. It is because, AI evolves quickly, and systems like Glaze face an inherent challenge of being future-proof. Techniques we use to cloak artworks today might be overcome by a future countermeasure, possibly rendering previously protected art vulnerable, they add.

Although the tool is far from perfect, its utility for artists is beyond any doubt. The issue becomes all the more glaring when one considers multiple artists who find it tough to earn a decent living through this craft. The AI companies, on the other hand, many of whom charge a subscription fee, earn millions.

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Rules and laws are yet to catch up with the pace at which AI is advancing, leaving little for artists to fight with to protect their work. This is where projects like Glaze rise to prominence.

It is important to note that Glaze is not panacea, but a necessary first step towards artist-centric protection tools to resist AI mimicry. We hope that Glaze and followup projects will provide some protection to artists while longer term (legal, regulatory) efforts take hold, it says on Glazes website.

Meanwhile, the technology has already hopped to the next stop. The startup Runway AI has come up with a video generator that generates videos, merely by a prompt.

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This project at University of Chicago aims at thwarting artificial intelligence from mimicking artistic styles details - The Financial Express

Contrive Datum Insights Pvt Ltd

According to a market research study published by Contrive Datum Insights, North America is the largest market for AI, with the United States and Canada being major players in the development and adoption of AI technologies.

Farmington, March 22, 2023 (GLOBE NEWSWIRE) -- The Global Artificial Intelligence Market Size Was Valued At Around USD 136.55 Billion In 2022 And Is Projected To Expand USD 1,811.75 Billion, With a CAGR Of 37.3% From 2023 To 2030. The AI market is made up of several smaller markets, such as natural language processing, machine learning, deep learning, computer vision, and others. These technologies are used a lot in many different fields, like healthcare, the auto industry, finance, retail, and more.

At the moment, North America is the biggest market for AI. Europe and the Asia-Pacific region come next. Some of the main things that are making the AI market grow are the growing use of AI in different industries, the growing demand for products and services that use AI, and the growth of big data.

IBM, Google, Microsoft, Amazon, Intel, NVIDIA, and other companies are some of the most important ones in the global AI market. These companies put a lot of money into research and development to come up with new AI-based products and services and to improve the speed and accuracy of AI systems they already have.

Request Sample Copy of Report Artificial Intelligence Market Size, Share & Trends Estimation Report By Solution Outlook (Hardware, Software & Services), By Technology Outlook (Deep Learning, Machine Learning, Natural Language Processing (NLP) & Machine Vision), By End User Outlook (Healthcare, Robot-Assisted Surgery, Virtual Nursing Assistants, Hospital Workflow Management, Dosage Error Reduction & Clinical Trial Participant Identifier) By Region, And Segment Forecasts, 2023 - 2030, published by Contrive Datum Insights.

Segmentation Overview:

Solution Insights:

In the AI services market, vendors offer consulting, integration, and support services to help businesses set up and maintain AI technologies.

Story continues

Each of these solution outlook segments gives businesses and organisations in the AI market a different set of chances and problems. Understanding the pros and cons of each segment can help businesses come up with good plans for using AI to improve their operations and drive growth.

Technology Insights:

In the technology outlook segment analysis of the global artificial intelligence market, the different kinds of AI technologies that are used now or are likely to be used in the future are listed. Some of the most important technology outlooks in the AI market are:

Deep learning is a type of machine learning in which neural networks are used to process and analyse complicated data. It is used to do things like recognise speech, process images, and translate languages.

End User Insights:

The global artificial intelligence market's end user segment analysis shows which industries and sectors are using AI technologies. Some of the most important types of end users in the AI market are:

AI is being used in the manufacturing industry for things like predictive maintenance, quality control, and optimising the supply chain. AI is also being used to make manufacturing operations more productive and cut costs. Agriculture, energy, and education are some other fields that are using AI technologies.

Regional Outlook:

North America is the biggest market for AI, and the US and Canada are two of the biggest players in developing and using AI technologies. The area has a strong ecosystem of AI startups and technology companies, and the people who work there are very skilled.

AI is becoming more popular in Latin America, where countries like Brazil and Mexico are investing in research and development. The area has a lot of people and a growing digital economy, which makes it a good place for AI to be used in areas like finance and e-commerce.

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Scope of Report:

Report Attributes

Details

Growth Rate

CAGR of 38.5% from 2023 to 2030.

Revenue Forecast by 2030

USD 1,811.75 Billion

By Technology

Hardware, Software, Services, Other

By Technology

Retail, Advertising & Media, Automotive & Transportation, Agriculture, Manufacturing, Other

By Law

Deep Learning, Machine Learning, Natural Language Processing (NLP), Machine Vision, Other

By End-use

Healthcare, Robot-Assisted Surgery, Virtual Nursing Assistants, Hospital Workflow Management, Dosage Error Reduction, Clinical Trial Participant Identifier, Preliminary Diagnosis, Automated Image Diagnosis, BFSI, Risk Assessment, Financial Analysis/Research, Investment/Portfolio Management, Other

By Companies

Advanced Micro Devices, AiCure, Arm Limited, Atomwise, Inc., Ayasdi AI LLC, Baidu, Inc., Clarifai, Inc., Cyrcadia Health, Enlitic, Inc., Google LLC, H2O.ai., HyperVerge, Inc., International Business Machines Corporation, IBM Watson Health, Intel Corporation, Iris.ai AS., Lifegraph, Microsoft, NVIDIA Corporation, Sensely, Inc., Zebra Medical Vision, Inc.

Regions andCountries Covered

North America: (US, Canada, Mexico, Rest of North America)

Europe(Germany, France, Italy, Spain, UK, Nordic Countries, Benelux Union, Rest of Europe)

Asia-Pacific (Japan, China, India, Australia, South Korea, Southeast Asia, Rest of Asia-Pacific)

The Middle East & Africa(Saudi Arabia, UAE, Egypt, South Africa, Rest of the Middle East & Africa)

Latin America(Brazil, Argentina, Rest of Latin America)

Rest Of the World

Base Year

2022

Historical Year

2017 to 2022

Forecast Year

2023 to 2030

Market Dynamics:

Latest Trends:

Advancements in technology: As machine learning, deep learning, and natural language processing get better, AI gets more accurate, efficient, and cost-effective. AI is being used in more and more industries because of these changes in technology.

Rising need for personalization: Consumers want more and more personalised experiences from businesses, and AI can be used to analyse and process large amounts of data to create customised experiences for customers.

Cost savings: AI can help businesses save money by automating processes and optimising operations. This makes businesses more efficient and cuts down on labour costs.

Improved decision-making: AI can help organisations make data-driven decisions by analysing large amounts of data and giving insights that humans may not be able to see.

The global AI market is growing because of how fast technology is changing, how much data is being made, and how many people want automation and personalization.

Restraining Factors:

Integration with legacy systems: Many organisations have legacy systems that aren't compatible with AI technologies, which can make integration and implementation hard and expensive.

Lack of understanding and trust: People and businesses may not fully understand and trust AI technologies, which could slow down their use and investment.

Regulatory hurdles: AI regulations are still in their early stages, so it's not clear how AI technologies will be governed. This uncertainty could make it harder to invest and get things done.

These things could slow the growth of the global AI market, but continued investments in talent development, ethical guidelines, and regulatory frameworks, as well as more awareness and understanding of AI, could help to overcome these problems.

Opportunity Factors:

Improved customer experience: AI can be used to analyse customer data and give customers more personalised experiences, which makes customers happier and more loyal.

Enhanced cybersecurity: AI can be used to find and stop cyber threats, which improves security and makes cyber attacks less likely.

Increased accessibility: AI can be used to make products and services easier for people with disabilities to use, making them more accessible and welcoming.

Improved decision-making: AI can be used to look at a lot of data and give insights to help people make decisions based on the data.

Cost savings: AI can help businesses save money by automating processes and improving how they work. This makes them more efficient and saves money on labour costs.

There are a lot of opportunities in the AI market, which has the potential to drive innovation, improve customer experiences, and give businesses in all fields new ways to make money. As technology keeps changing and getting better, businesses that invest in AI are likely to get a competitive edge in their markets.

Challenges Factors:

Lack of skilled professionals: There aren't enough data scientists, machine learning engineers, and AI researchers who are skilled in AI right now. This can make it hard for companies to find the people they need to build and use AI technologies.

Regulatory hurdles: AI regulations are still in their early stages, so it's not clear how AI technologies will be governed. This uncertainty could make it harder to invest and get things done.

Data quality: The accuracy and reliability of AI systems depend on the quality of the data used to train AI models. AI models that are biased and wrong can be the result of bad data.

These problems could make it hard for AI technologies to grow and be used by more people. To solve these problems, governments, businesses, and other stakeholders will need to work together to create ethical guidelines, regulatory frameworks, and talent development programmes that support the development and use of AI in a responsible way.

Key Segments Covered:

Top Market Players: Advanced Micro Devices, AiCure, Arm Limited, Atomwise, Inc., Ayasdi AI LLC, Baidu, Inc., Clarifai, Inc., Cyrcadia Health, Enlitic, Inc., Google LLC, H2O.ai., HyperVerge, Inc., International Business Machines Corporation, IBM Watson Health, Intel Corporation, Iris.ai AS., Lifegraph, Microsoft, NVIDIA Corporation, Sensely, Inc., Zebra Medical Vision, Inc., and others.

By Solution

By Technology

By End-use

Healthcare

Robot-Assisted Surgery

Virtual Nursing Assistants

Hospital Workflow Management

Dosage Error Reduction

Clinical Trial Participant Identifier

Preliminary Diagnosis

Automated Image Diagnosis

BFSI

Risk Assessment

Financial Analysis/Research

Investment/Portfolio Management

Others

By Law

Regions andCountries Covered

North America: (US, Canada, Mexico, Rest of North America)

Europe: (Germany, France, Italy, Spain, UK, Nordic Countries, Benelux Union, Rest of Europe)

Asia-Pacific: (Japan, China, India, Australia, South Korea, Southeast Asia, Rest of Asia-Pacific)

The Middle East & Africa: (Saudi Arabia, UAE, Egypt, South Africa, Rest of the Middle East & Africa)

Latin America: (Brazil, Argentina, Rest of Latin America)

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Artificial Intelligence Market Is Expected To Reach USD 1,811.75 Billion by 2030, Grow at a CAGR Of 37.3% during Forecast Period 2023 To 2030 | Data...

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Biomonitoring and precision health in deep space supported by ... - Nature.com

Artificial intelligence (AI) has proven helpful to the world in many ways, including the assistants and robots that have taken on many of the tasks associated with daily life and replaced humans in surgical procedures and other professions. Several AI models and tools that are immediately in front of our eyes are ensuring that the world will be a better place, so it's not just the robots that have a beneficial influence on humans, there are models including ChatGPT and Dall-E that have revolutionized the tech industry.

For those who may not be aware, ChatGPT is a chatbot that was introduced in November of 2022. It was created to help users with a variety of tasks. Another significant tech company, "Dell-E," is utilized to produce lifelike images only from a description. They were both created by a business named "OpenAI."

Yet, we are fully aware that it is always bad along with good, therefore to learn more about how people see artificial intelligence, a study titled "Trust in Artificial Intelligence" was conducted during September and October 2022. The University of Queensland and KGPM Australia conducted the study and provided the data on which it was based. A total of 17,193 respondents from seventeen different nations participated in the survey.

There were three separate sections in the survey's poll: "agree," "disagree," and "neutral." Despite everything that has been said about how AI has helped humanity, some individuals still believe that the world would be a far better place without it. 42% of respondents, or two out of every five, agreed with this statement.

What may be the cause of it, then? Several individuals are concerned about their occupations and careers being replaced by AI robots that resemble humans as a result of the study. While 39% of individuals polled denied that AI can take over their future, it's likely that they still believe that some jobs couldn't be replaced by it or that they aren't aware of how rapidly AI's value is increasing. The poll also found that 19% of respondents had a neutral opinion on the matter.

Nonetheless, each person sees the world from a unique perspective. According to the poll, 67% of respondents remain hopeful and upbeat about the future of AI. Even if they are aware of all the negative effects and how they will affect us, some people (57%) are still relaxed about it.

Furthermore, 47% of people report feeling extremely nervous because they fear AI would progressively destroy the human world and that there are very significant risks associated with using AI in daily life, which is not surprising. Also, 24% of them express an angry sentiment against AI and its applications.

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As per the "Trust in Artificial Intelligence" study, 42% individuals fear ... - Digital Information World

UNIVERSITY PARK, Pa. Two artificial intelligence-driven models designed by researchers from the Penn State College of Information Sciences and Technology could help promote the rights of low-income renters in the United States when facing forced eviction. Both models aim to forecast where and how many renters could be at risk of eviction to help better inform policymaking and resource allocation.

The researchers first model, "Weakly-supervised Aid to Relieve Nationwide Eviction Rate," helps to identify areas where there could be a high concentration of individuals facing eviction. To identify these hotspots, their framework uses sociological data such as renters educational and financial characteristics that are historically associated with housing instability to label satellite data based on certain features in each image, such as the presence of trees and signs of gentrification. This data is used to train a machine learning model, which identifies eviction filing hotspots in other locations.

Not all states make data on housing instability and eviction rates available, and there is a high cost to collect this data when its even available, said Amulya Yadav, PNC Career Development Assistant Professor and co-author on the study. Our model presents a novel approach by using other data points related to eviction filings to create more efficient and accurate reporting that is highly generalizable to different counties across the country.

The second model, Multi-view model forecasting the number of tenants at-risk of formal eviction," aims to provide an accurate forecast of tenants at-risk of eviction at a certain point in the future.

In a similar approach, the model uses data from available eviction filing records, the U.S. Census American Community Survey, and labor and employment statistics to estimate the number of tenants who may face eviction in each census tract.

Through a collaboration with the Child Poverty Action Lab, a leading non-profit leveraging data-driven approaches to inform actions for relieving poverty-related issues across Dallas County, Texas, the team tested both models against a real-world dataset in that county, where eviction records are more complete and readily available. The models proved to be more accurate than existing baseline models, outperforming some by up to 36%.

There are resources available to help renters facing housing instability, but they are allocated with tremendous variability and sometimes theyre not used at all, said Maryam Tabar, doctoral student and lead author on the study. There is a need to use these funds and resources more efficiently, which is possible through more accurate forecasting of potential evictions.

The team presented the "Weakly-supervised Aid to Relieve Nationwide Eviction Rate" model at the 31st ACM International Conference on Information and Knowledge Management and the multi-view model forecasting the number of tenants at-risk of formal eviction at the 31st International Joint Conference on Artificial Intelligence late last year.

Both models are being evaluated by subject matter experts for a pilot deployment in the field. The team said they hope they can assist non-government organizations and policymakers in making more data-driving decisions about where to allocate resources to better address housing instability, as well as support advocacy efforts with elected officials and agencies related to housing instability.

Eviction disproportionately impacts individuals from underrepresented backgrounds and can exacerbate existing societal problems related to income disparity, educational attainment, and mental health, said Dongwon Lee, professor and co-author on the study. These models can help us better address these challenges and improve the lives of those vulnerable to eviction.

Additional contributors to the projects include doctoral candidate Wooyong Jung at Penn State College of Information Sciences and Technology, as well as Owen Wilson Chavez and Ashley Flores of The Child Poverty Action Lab. The work was supported in part by the National Science Foundation and the Bill and Melinda Gates Foundation.

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Artificial intelligence models aim to forecast eviction, promote renter ... - Pennsylvania State University