Archive for the ‘Artificial Intelligence’ Category

AI in Construction – How Artificial Intelligence is Paving the Way for Smart Construction – Appinventiv

Artificial Intelligence has definitely made our lives easier in multiple ways. We can access multiple benefits right through our smartphones with the power of digital assistants like Google Assistant, Siri, Alexa, and more.

In todays world, multiple industries such as healthcare, e-commerce, financial services, etc., are leveraging the benefits of AI to the fullest of its potential. The technology has helped businesses grow in leaps and bounds with improved quality, security, and efficiency.

However, it is observed that engineering and construction are lagging behind in implementing artificial intelligence and machine learning solutions. The construction industry is worth more than $10 trillion a year.

Due to the complex challenges that the construction industry faces, the growth in the industry is severely limited. Dealing with challenges like cost and time overruns, labor shortage, health and safety, and productivity can bring revolution in the industry.

The construction industry has tremendous potential, and just by digitization, economically, the worth of the construction industry can be raised to $1.6 trillion a year. AI in construction can be instrumental in bringing this shift.

According to a report, Artificial Intelligence in the construction market is estimated to generate a revenue of $ 2,642.4 million by 2026, at a compound annual growth rate of 26.3% from 2019 to 2026. Technological advancements in AI and the Internet of Things (IoT) will create more opportunities for growth in construction and engineering.

Artificial Intelligence in the construction industry is undergoing a digital transformation. Focussing on technologies like artificial intelligence and machine learning at every stage of engineering and construction, from design to preconstruction to construction to operations and asset management, is exploiting the potential of the construction industry to new levels.

The areas where artificial intelligence in the construction industry is bringing impactful difference by getting the tasks done in a lesser amount of time and in a cost-effective manner.

Planning and designing sub-segment of construction are expected to benefit the most. In the global construction industry, the Europe market is anticipated to top the growth rate.

This technological shift is set to positively impact all the stakeholders across the project including contractors, owners, and service providers. With other adjacent industries such as transportation and manufacturing having already started working as an ecosystem, it becomes all the more important for the construction industry to adapt to the digitization of the processes.

As the technological shift is at a nascent stage in the engineering and construction industry, it will be advantageous for the companies that upgrade the technology. With artificial intelligence in construction, companies can comfortably tackle current issues while avoiding past mistakes.

With the use of statistical techniques of machine learning in construction, it becomes much more convenient and less time-consuming to scrutinize the data pertaining to changed orders, information requests, etc. This will help in proactively alerting the project leaders about the things that need critical attention. Safety monitoring also can be done with more efficiency.

We have established that AI is a critical component of modern engineering and construction approaches. Artificial intelligence in construction helps the industry solve its greatest challenges like cost and schedule overruns and safety issues. AI can be exploited throughout the construction project from inception and design, bidding, financing, transportation management, and operation and asset management.

Let us look in detail at how is AI being used in the construction industry:

AI-based Building Information Modeling (BIM) process has been helping architecture, engineering, and construction professionals make 3D model designs to plan efficiently, design, build, and repair the buildings and infrastructures.

With machine learning in construction, the industry uses AI-powered generative design to identify and collaborate the architecture, engineering, mechanical, electrical, and plumbing plan to ensure that there are no clashes within the sub-teams. Such measures mitigate the risk of rework. The algorithm of ML explores all the options and variations of the solutions to create design alternatives. Models with multiple variations are created and learned from each iteration, and this process is repeated until a perfect model is created.

It is expected that the planning and design sub-segment will grow exponentially with a CAGR of 28.9% between 2019 and 2026.

Construction companies can use AI-powered robots that are equipped with cameras. These robots can move autonomously through the construction site to capture 3D pictures.

With the help of neural networks, these pictures can be cross-checked with reference to the information from BIM and the bill of materials. The engineers managing large projects utilize this information to keep track of the progress of the work. It also helps identify quality errors at an early stage and keep a tap on financial information and time schedules.

It will not be an exaggeration to say that robotics and AI in the construction industry are ensuring the delivery of the best construction projects while saving costs and time.

Construction companies are exploiting the features of the Internet of Things (IoT) to manage the fleets of equipment and vehicles. With the inputs from the AI metrics, IoT provides solutions like location awareness, predictive maintenance capabilities, fuel and battery consumption, and much more.

With IoT devices and tags, it is now possible to predict the equipment breakdown possibility, which is an invaluable tool that saves time and money.

Construction sites are prone to accidents for various reasons. Analyzing and predicting risks with machine learning can avoid many such accidents. Monitoring the sources like photos and videos through the software can flag the potential risk that the site manager can address at the right time.

Reports pertaining to potential safety risks, such as unsafe scaffolding, waterlogging, and personnel missing protective equipment like gloves, helmets, and safety glasses, can be accessed by the user to rank the projects.

As mentioned in the introduction, there exists huge scope for tapping the potential of AI in construction management. There always is a dearth of labor in the construction industry as it involves risks and is a physically demanding job. The average turnover rate in the construction field is way more than in any other industry.

In such a scenario, AI-powered robots empower the project managers to oversee the real-time situation and resource requirements of multiple job sites. Based on the requirements, labor can be shifted to either a different part of the project or a different job site. The robots monitor the site to find the pain areas.

Companies that want to stay ahead in this competitive edge should quickly upgrade their technology. Smart construction can be enabled by incorporating AI. Lets explore how AI in construction is significant.

The current process of construction design is outdated and thus slow. By taking insights from building data, material data, and environmental data, you can optimize your project design.

When done manually, the building process tasks are tedious, time-consuming, and error-prone. The project manager spends most of his time assigning work and managing employee records.

However, Artificial intelligence can automate many such mundane tasks that can be performed with minimal or zero errors. AI automation can additionally take care of task delegation based on the data gathered from the employees. This not only streamlines the workflow process but also encourages workers to focus on their field of expertise.

With camera-enabled robots or AI-enabled construction equipment, data can be collected in different formats. By feeding these details into the deep neural network, the projects progress can automatically be classified from various aspects.

Such data empowers the management to know and address the minutest error or problem in the initial stage mitigating the subsequent major issues.

Employing self-driving construction machines can perform repetitive tasks tirelessly, efficiently, and quickly, such as welding, bricklaying, pouring concrete, etc.

Similarly, you can employ automated or semi-automated bulldozers for excavation and pre-work. Once the exact specifications are fed into these machines, they complete the job exactly as per the specifications. You can free up your human workforce for actual construction work and reduce the human risks involved in performing these tasks.

You can dramatically reduce the time in performing the land surveys in detail and taking aerial photos of the job site for better project management. With the help of drones, Geospatial Information System (GIS) and Geospatial AI (GeoAI) will help you keep track of project progress status and problems on the construction site while leveraging you with better decision making for efficient project management.

With the inception of technology, the construction industry will have cobots and robots working alongside workers. Robots take over the tasks that can be automated, and cobots are designed to work autonomously or with limited guidance.

Such an arrangement will help speed up construction, reduce costs, injuries, and better decision-making. AI in construction will not only overcome the labor shortage issue but will also lead to alterations in business models, and reduce expensive errors, making building operations more efficient. Thus, it is advised that business leaders at construction companies should focus on investment based on areas where AI can have the maximum impact based on needs.

Early adopters of this digital transformation are sure to gain the lead in the business. Getting an edge will make them leaders in setting the direction and reaping short-term and long-term benefits.

The construction industry is lagging behind in technology adoption. Now is the right time to get your processes automated and leverage AI in civil engineering.

Harness the power of automation with Appinventiv and take your construction goals to next level with functionally beautiful building designs.

As an AI development company, our team believes in molding their expertise based on our clients requirements as we have successfully done in the past helping business transformations.

Talk to our experts to tap the full potential of Artificial Intelligence in construction with Appinventive AI and ML development services.

From planning to designing to construction, AI has been spreading its benefits in all the sub-segments of construction. Future of construction with AI will oversee the complete construction project while advising on risk management, schedule adherence, structural integrity, and much more. Harnessing the potential of AI in construction will boost the profits, and reduce the injuries and risks involved.

Sudeep Srivastava

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AI in Construction - How Artificial Intelligence is Paving the Way for Smart Construction - Appinventiv

Artificial Intelligence in Drug Discovery Market to Witness Robust Growth by 2027| Top Players mbu timeline – mbu timeline

According to Reports and Data, theArtificial Intelligence in Drug Discovery Marketwas valued at USD 253.8 million in 2019 and is expected to reach USD 2,127.9 million by the year 2027, at a CAGR of 31.9%. Artificial intelligence has known to have enormous applications in the field of drug discovery as it helps to analyze outbreaks, develop cures for diseases, and also predict which animal viruses tend to mutate. In drug discovery, artificial intelligence has known to improve research and development, which allowed researchers to discover treatments for chronic diseases. The use of machine learning to manage the huge number of data sets is increasing advances in drug discovery. The rising need to manage drug discovery costs is expected to drive the market in the future.

Drug discovery includes various processes and stages that demand a huge amount of funds. Moreover, clinical trials and acceptance of the drug in the market could be a challenging task. Artificial intelligence is capable of reducing such high costs in research and development as it finds solutions faster and with precision. Furthermore, increasing collaborations among companies to produce patented drugs could also be a major driver for the market. Artificial intelligence may reduce a large amount of time utilized in the drug discovery process. Therefore, reduction in time factor could be a primary market driver in the forecast period. The increasing demand for cloud-based software that enables the researcher to design drugs quickly and accurately is expected to drive the market widely.

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Some Key Factors Contributing to the Global Pharma & Healthcare Market Growth

Unprecedented revenue growth of the global pharma & healthcare industry is attributed to factors such as rising prevalence of chronic and acute diseases worldwide, increasing geriatric population, rising awareness of health & wellness among consumers, and growing demand for more advanced healthcare services. Increasing demand for advanced drugs and therapeutics, growing availability of next-generation diagnostics and treatment options especially in developing countries like India and China rise in R&D activities and clinical trials in the pharmaceutical and biotechnology sectors, increasing public and private investments in healthcare research projects, and rising consumer expenditure on healthcare are among the other significant factors contributing to the industry revenue growth.

Further key findings from the report suggest

Top Players in the Global Artificial Intelligence in Drug Discovery Market:

NVIDIA Corporation, Deep Genomics, Cloud Pharmaceuticals, IBM Corporation, Microsoft and Google, Insilico Medicine, BenevolentAI, Cyclica, BERG LLC, and Envisagenics.

The coronavirus pandemic has had a drastic impact on the global healthcare industry, with rising cases of COVID-19 worldwide, substantially growing hospital admission and readmission rates, and rising demand for telehealth and telemedicine services for remote patient monitoring. Furthermore, rising focus on development of rapid COVID-19 diagnostics such as the RT-PCR test kits, increased government funding for vaccine development, stringent regulatory norms and protocols for COVID-19 safety, and increasing sales of COVID-19 safety equipment, such as N-95 masks, face shields, PPE kits, and hand sanitizers, have driven the global pharma & healthcare industry revenue growth over the recent past.

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Artificial Intelligence in Drug Discovery Market Segmentation:

By Drug Type Outlook (Revenue in Million USD; 20172027)

By Offerings Outlook (Revenue in Million USD; 20172027)

By Technology Outlook (Revenue in Million USD; 20172027)

By Application Outlook (Revenue in Million USD; 20172027)

By End Use Outlook (Revenue in Million USD; 20172027)

Global Artificial Intelligence in Drug Discovery Market Report: Regional Segmentation

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Global Artificial Intelligence in Drug Discovery Market: Table of Contents

Chapter 1. Methodology & Sources

1.1. Market Definition

1.2. Research Scope

1.3. Methodology

1.4. Research Sources

1.4.1. Primary Sources

1.4.2. Secondary Sources

1.4.3. Paid Sources

1.5. Market Estimation Technique

Chapter 2. Executive Summary

Chapter 3. Key Insights

Chapter 4. Global Pharma & Healthcare Market Segmentation

4.1. Global Pharma & Healthcare Market COVID-19 Impact Analysis

4.2. Industrial Outlook

4.2.1. Market indicators analysis

4.2.2. Market drivers analysis

4.2.3. Market restraints analysis

4.3. Technological Insights

4.4. Porters Five Forces Analysis

4.5. Regulatory Framework

4.6. Price trend Analysis

4.7. Competitive Metric Space Analysis

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Reports and Data is a market research and consulting company that provides syndicated research reports, customized research reports, and consulting services. Our solutions purely focus on your purpose to locate, target, and analyze consumer behavior shifts across demographics, across industries, and help clients to make smarter business decisions. We offer market intelligence studies ensuring relevant and fact-based research across multiple industries, including Healthcare, Touch Points, Chemicals, Products, and Energy. We consistently update our research offerings to ensure our clients are aware of the latest trends existent in the market. Reports and Data has a strong base of experienced analysts from varied areas of expertise. Our industry experience and ability to develop a concrete solution to any research problems provides our clients with the ability to secure an edge over their respective competitors.

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Artificial Intelligence in Drug Discovery Market to Witness Robust Growth by 2027| Top Players mbu timeline - mbu timeline

The European Union AI Act: Next steps and issues for building international cooperation in AI – Brookings Institution

In April of 2021, the European Commission submitted its proposal for a European Union regulatory framework on artificial intelligence. The Artificial Intelligence Act represents the first attempt globally to horizontally regulate artificial intelligence (AI). The extraterritorial application of the AI Act and its likely demonstration effect (the so-called Brussels effect) for policymakers means that the AI Act will have a range of implications for the development of AI regulation globally, as well as efforts to build international cooperation on AI.

The following outlines next steps for the AI Act as it winds its way through the EU system before becoming law, the key issues in the AI Act that will receive the most attention, and how the AI Act may affect international cooperation in AI. This policy brief draws from discussions in the multistakeholder Forum on Cooperation in AI (FCAI), jointly led by Josh Meltzer, Cameron Kerry, and Andrea Renda, as well analysis originally published in the October 2021 FCAI report, Strengthening International Cooperation on AI.

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The European Union AI Act: Next steps and issues for building international cooperation in AI - Brookings Institution

Mintlify Uses Artificial Intelligence To Address Software Documentation Challenges, Raises $2.8 Million – Tech Times

Mintlify, which automates software documentation tasks announced that it raised $2.8 million in a seed round led by Bain Capital Ventures. The startup developing software's CEO Han Wang said that the proceeds will go to product development and double their staff. Currently, Mintlify is a three-person team.

The New York-based software company was founded in 2021 by Han Wang and Hahnbee Lee. Both are software engineers and their profession drove them to build Mintlify.

Both Wang and Lee's experiences in software development involved working with documentation that wasn't always high quality or complete.

"We've worked as software engineers at companies in all stages ranging from startups to big tech and found that they all suffer from bad documentation if it even existed at all," Wang said.

He also added that documentation is crucial to engineers and those that are working on new codebases.

Also read:AI-Powered Video Editing Platform: Why Should You Use It- Virtual Doppelganger?

With that, Mintlify is established to address documentation challenges with auto-generating documentation. The software reads code and creates docs to explain it using technologies, such as Natural Language Processing (NLP) and web scraping.

This only shows that generating documentation from code is possible with the help of Artificial Intelligence (AI).

However, Mintlify isn't the first one to do this. In fact, the software company already has a few competitors that are taking similar approaches.

Still, Wang assures that their software delivers higher-quality results and they don't force developers to host documentation on a cloud service.

"Mintlify's mission is to solve documentation rot by developing continuous documentation into a standard practice for software teams," Wang said.

Aside from document generation, the software also scans for stale documentation and detects how users engage with the documentation. These help improve its readability. The software that will not store code and ensures all user data at rest and in transit are encrypted.

The platform is free for developers and can be integrated with existing systems.

Since its launch in January, Mintlify continues to grow with 6,000 active accounts. With this, they are looking to offering a premium that is aimed at enterprise customers.

It has also received good feedback from developers and people who have texted the software. For many, it saves a lot of time and keystrokes from writing docstrings from scratch and it would be useful for reading and understanding undocumented code by ghosts.

They also noted that the global pandemic's impact on the work environment has even made it more important to have high-quality documentation for more efficient product development. And this is exactly what Mintlify is doing as they expand into workflow automation that addresses documentation challenges.

Related article:Top 5 Best Bot Platforms Software for Better Customer Support

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Written by April Fowell

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Mintlify Uses Artificial Intelligence To Address Software Documentation Challenges, Raises $2.8 Million - Tech Times

Lessons from Europe: Deployment of Artificial Intelligence in the Public Sphere – Wilson Center

The application of AI has been largely a private sector phenomenon. The public sector has advanced regulatory questions, especially in Europe, but struggled to find its own role in how to use AI to improve society and well-being of its citizens. The Wilson Center invites you to take a critical look at the use of AI in public service, examining the societal implications across sectors: environmental sustainability, finance, and health. Where are the biases in the design, data, and application of AI and what is needed to ensure its ethical use? How can governments utilize AI to create more equitable societies? How can AI be used by governments to engage citizens and better meet societal needs? The webinar aims to engage in a dialogue between research and policy, inviting perspectives from Finland and the United States.

This webinar has been organized in coordination with the Finnish-American Research & Innovation Accelerator.

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Lessons from Europe: Deployment of Artificial Intelligence in the Public Sphere - Wilson Center