Scientists in many disciplines are at the forefront of finding new ways to exploit powerful model-detection and statistical reasoning enabled by modern AI.In Life Sciences, AI provides insights into the human genome, predicts cancer development, and accelerates drug discovery at an unprecedented place.In the earth sciences, AI improves atmospheric and environmental time series by representing missing data and integrating conflicting observations, correcting bias, and building better models of attendance than previously possible.Do you want to where Artificial Intelligence is used in our daily life,apart from oceanography, then….The long-standing and uninterrupted geological research question of when and when the next major earthquake will occur, for the first time, maybe soluble using neural networks.

The promise of machine learning solutions for problems that are impossible or too challenging to use traditional methods is appealing.Marine science has its unique challenges and uncertainties — collecting data on vast spatiotemporal scales, tracking and isolating the effects of different water masses in highly dynamic systems, or accessing remote and often dangerous areas.Thanks to pioneering projects such as high-resolution, long-term in situ observational datasets, Argo now boasts about 4000 widely dispersed autonomous platforms, which cover the upper 2000 m of the ocean.

Biogeochemical arc floats are also increasingly online, allowing measurements of chlorophyll fluorescence, acoustic backscatter, dissolved oxygen, and other crucial marine properties.For large datasets, such as the Global Argo Observational Output, deep learning techniques can be used to address turbulent processes, sub-surface flows, air-sea currents, and energy transport; Interpolating dimensions in areas with little coverage; improving model parameterization; Automatic quality control and more.

By building multiple layers of neurons and optimizing the output functions of neurons, behavior mimics the structure of the human visual system.

For processing, such as acoustic spectrograms and subsea imagery, traditionally performed by researchers with the help of undergraduate research assistants, CNNs can provide exceptional improvements in both speed and accuracy.Where it takes time to manually select small features in mostly uninteresting seafloor images, CNNs can segment images intelligently and output only the features of interest for later detection.

Also, if sufficient labeled data is available for optimization of the CNN, the presence of an animal to be classified taxonomically, a network can be established to distinguish between taxa and perform detection.An exciting application of deep learning for biological oceanography and for the Ph.D. project I follow, using CNNs to process Microscope images.

                                                    What is a chatbot?A chatbot is an Artificial Intelligence (AI) software that can mimic (or chat) with a user in natural language via messaging apps, websites, mobile applications or the telephone.Why are chatbots important?A chatbot is often described as one of the most sophisticated and hopeful expressions of interaction between humans and machines.

At the same time, they provide new opportunities for companies to improve the customer engagement process and operational efficiency by reducing the typical cost of customer service.To be successful, the chatbot solution must be able to do both of these things effectively.

By enhancing machine learning and natural language processing, AI-powered chatbots can understand the purpose behind your customers' requests, calculate their entire conversation history and interact with their questions in a natural, human way.If you're currently using a standard chatbot and want to upgrade to an AI-powered one, we've put together a list of the best AI chatbots for 2019.

A pre-trained Watson assistant with content in your specific industry can understand your historical chat or call logs, search for answers in your knowledge base, ask customers for more clarity, send them to human representatives, and even give you training recommendations for improvement.

Bold 360AI Chatbot - Bold 360 Trusted by customers like Intuit, Edible Arrangements, and Vodafone, Bold 360 has patented its own natural language processing technology that helps brands build chatbots that understand your customers' intent without the need for keyword matching and learn how to provide the most accurate answers.

You can build Rulai Chatbot from scratch with its drag-and-drop design console, and let its AI suit your customers, or you can run a pre-trained chatbot that delivers data from your specific industry.

The concept of AI scares people because we don't know how they work because we fear to create bots.

Even worse, most of the content produced by the media does not include testimony from experts in the field of AI.

But when is there anything that lacks flaws?

There was also a study in which 10 different radiologists were given different mammograms of breast tumors.

To address these issues, I will discuss some algorithms in the field of machine learning.AI comes down to a lot of math and a lot of logic.

Unsupervised learning often involves clustering algorithms; you plot the data and try to group the different parts of the data into groups to find relationships and patterns in the data.

Each sector is evaluating options and adopting ways to create value in a technology-driven world.

To meet these expectations, banks have expanded their industry landscape to retail, IT and telecoms to enable services such as mobile banking, e-banking and real-time money transfer.These advances enable customers to access many banking services at any time, anywhere, and at their fingertips, which can be costly for the banking sector as well.The integration of the banking and IT, telecom and retail sectors transmitted critical information through cyberattacks and fraudulent virtual networks.

These events not only affect the profitability of the banks, but also the banks’ confidence and relationship with customers.Learn more about: What Can AI Do for Cyber Security?The rise of online security threats in banking transactions has tightened government regulations.

According to the 2016 World Retail Banking Report, more than half of consumers worldwide are likely to swap their banks with this Player1.AI in the banking and finance industryBanking on Artificial Intelligence:The use of cognitive technology with Artificial Intelligence (AI) brings the benefit of digitization to banks and helps them to compete with Fintech players.

In fact, according to research by the National Business Research Institute and Native Science 2, 32% of financial services firms are already using AI technologies such as predictive analytics and voice recognition.Artificial intelligence is the future of banking (the importance of AI technology through industry) because it brings the power of sophisticated data analytics to deal with fraudulent transactions and improve compliance.

The AI algorithm achieves anti-moneylending actions in a few seconds.

The construction industry still has a long way to go before we can confidently say that artificial intelligence solutions are properly implemented in this field.The good news is that construction is an industry with tremendous potential.

The total value of the sector is estimated at 10 trillion per year, but the lack of digitization in the industry makes the productivity gap in an account for 1.6 trillion these are only due to the AI SERVICES implemented in construction.That being said, it quickly becomes clear that the structure needs to change.

Paving the way for the growth and successful implementation of artificial intelligence in digital shift architecture.Construction requires artificial intelligence:Now that we have a better understanding of the research focus, it is time to consider why the construction industry needs artificial intelligence.Shrinking workforce:The lack of skilled labor is the most critical issue for the construction industry on a global scale.

This element is especially important when we refer to labor-intensive industries such as construction.AI can provide visual solutions to this problem through time-intensive tasks such as labor automation and program creation, cost estimation, resource management, health and safety management, and more.

Political conditions also have a critical impact on workforce availability.Lower profit margins:Low-profit margins have always been a serious pain in US construction compared to other industries.In short, the most important factors that led to this problematic situation are summarized in the next five:· Competitive tendering· Higher bidding cost per return ratio· Increased costs due to Sterling decline· Due to Low productivity· Risk of poor risk managementThe implementation of artificial intelligence technologies to the construction process can eliminate these factors and add more precision to the way the construction works and builds.Risk Management:Risk management as one of the factors leading to a lower profit margin.

With the help of AI, resources and energy-efficient smart buildings can become ideal in both construction and use.Such an approach is beneficial to the construction industry and to people who work or live in buildings.Challenges facing AI implementation in architecture:Despite the various problems that architecture currently faces, successfully implementing AI technology is not easy.

 venkat vajradhar  If you’ve attended any digital marketing or eCommerce conference this year, you know that artificial intelligence is one of the hottest topics around.

If you shy away from AI discussions, they are too complicated or not right for your brand, then you are missing out.Source: googleAI solutions are easier to use and apply to your eCommerce business than ever before.

AI occurs when a robot can follow certain rules (called an algorithm) for making decisions.Machine learning: The robot can make its own rules and improve the algorithm to get better results.

Machine learning is often considered a subset of artificial intelligence.

However, machine learning is required to take the robot scarf, study its features, and fold it into a towel rather than a pair of pants or socks.AI for commerce is affordable and easyThe next step in understanding how artificial intelligence can help your eCommerce strategy is to eliminate the misconception that investing in AI is expensive and complicated.

You don’t have to reinvent the wheel to use AI on your site, and many companies are already testing AI tools on their web pages.In 2017, more than 60 percent of businesses used AI tools in some form, a significant increase from 2016’s 38 percent.

  The demand for artificial intelligence has increased significantly over the past few years.

The increasing use of big data, increased demand for greater transparency and visibility in supply chain data and processes, and the adoption of AI to improve customer service and customer satisfaction are other factors driving demand in this market.

The global artificial intelligence in the supply chain market can be categorized based on technology, application, end-user industry, and offerings.

The drivers and restraints adopted in the report help to understand the different growth factors that directly or indirectly affect the market growth.

Competitive landscape and segmentation are also provided in the report.Global Artificial Intelligence in the Supply Chain Market: Trends and OpportunitiesThe introduction of artificial intelligence is a recent technological innovation, despite that fact; AI is heavily used in various industries.

The use of technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Context-Aware Computing and Computer Vision has increased the demand for AI in the worldwide supply chain.

In such cases, unpredictability can be helped by AI SERVICESAI uses observed data to make appropriate decisions.

For example, smart traffic light algorithms and real-time tracking can effectively control high and low traffic patterns.

Companies need new strategies to navigate this dynamic environment.

The pre-scouted helps develop such strategies.1.

Autonomous cars: Driving toward the future:Autonomous cars have quickly moved from the realm of sci-fi to reality.

The technology behind these trucks can also be used in freight transport, shipping 2,000,000 pallets each year.Source: Steve Jurvetson / Wikimedia Commons3.

In the past, this bias went through human judgments and various social and economic factors but if you include this part of the new model, it is a recipe for disaster.

Also, the amount of money the user spends represents more revenue per restaurant application.

Ethical AI is a great topic of research and debate, as you will see a lot of development (as well as general marketing buzzwords) and governance in this area.

USM is a pioneer in providing AI & ML solutions that suit's your business needs and help to grow your customer base.

Take the time to verify the data sources and attributes that are used to create the model.Describe model output - Applications design should be a key design principle in terms of detail.

Again, offerings/services should be vertical instead of pure-play horizontal AI services (otherwise it ends up as chatbots hypeAccountability - Ultimately, humans need to look at the product that comes from the AI   system and take corrective action for critical tasks.

                                                                                                                                     Artificial Intelligence (AI) is one of the few emerging technologies that promise to bring about some amazing transformations in the developing world of application development (AI application development).

When it comes to improving business relationships, growth and expectations, anyone looking to make a meaningful impact on the business world through technology has received the highest spotlight.

Get your dream app for a free consultation on the AI book @ USMSystems here By involving Artificial Intelligence (AI) highlights with Android app development, most smartphones will soon begin to play some advanced technology roles such as landmark recognition, image labeling, barcode scanning, face recognition, and text recognition.In addition to helping bring about amazing user experience, building Android apps with built-in AI features can go a long way toward simplifying the work of many smartphone users.Artificial learning ideas for mobile appsThere are many ways to apply artificial intelligence to the mobile app development company Android app.

Depending on the preparation, any app developer can learn to incorporate AI into their app development project to get the help they need.

Optimize the search process Mobile users engage in the search process, adding hints, spelling corrections, and voice search when AI is integrated into a search engine, which is more evident.

This is more or less a priority for most app development companies that want to take this route.Nowadays, it is becoming more common to find better mobile apps with the chatbots feature.

We have the opportunity to hear the compelling and informative case for AI, Perong's co-founder and CTO Kirong Ho.

However, it has the potential to produce excellent value as illustrated by industry 4.0 and cement production.Cement production is made up of large physical plants and machinery and a well-defined process with 10,000 to 20,000 sensors per factory.

Security is a mission-critical process first.

There are cost reduction results due to improved energy recovery and higher consumption of alternative fuels.

The deliverable is the Automatic Medical Report Generation, which requires raw data enrichment; the model/algorithm structure requires interaction between different systems.

The CTO of Asia's Thoracic Clinic reported that average commentary and report writing time was reduced by 60%.

 When we think of companies that are at the forefront of technological innovations, global financial institutions do not necessarily recall.Instead, giant tech giants like Amazon, Apple, and Alphabet dominate the conversation around innovation and attract more attention.

However, with Artificial Intelligence (The Power of AI & ML Technologies in the Banking & Financial Sector) becoming mainstream, even the classic gatekeepers of the financial sector cannot ignore them.Now, the biggest banks around the world are doubling down on their AI dramas.

In 2018, the Russian Bank hosted its "Classic AI Competition," where teams from across the country were invited to use AI to compose a poem equivalent to the author's claim of 1,000,000 rubles.Most recently, Sberbank hosted a demo-day event in Moscow, showing some of the top AI innovations in Russia.

The event was featured on the Sberbank and 500 Startups Accelerator Program, and as a result, seven finalist teams will go to the 500 Startups Startup Launch Program in San Francisco.

In addition to the finalists, Sberbank continues to collaborate with all 30 teams competing in the accelerator batch and helps integrate and integrate with the bank ecosystem.The finalists include a project that uses AI to create tools for labeling large data sets, Mishka AI, a smart soft toy that incorporates AI to automatically deliver child-centric content, and an excellent Healthcare AI Play that promotes AI and neural networks.

Bank Happolim - IsraelContinuing on the Forbes Global 2000 list is Israel's largest financial institution, Bank Hapolim, which does not let the AI   trend overtake it.

By using large datasets and machine learning to manage tasks and gather insights, AI solutions are supported through several stages of the recruitment process.

So how can AI help you?Sourcing:Sourcing a candidate can be very time-consuming.

Recruiters must write job descriptions, qualified leads and through dozens of (if not hundreds) resumes in a day.

Analyzing the language by processing the software and making recommendations based on the results of the system process can help companies write better job descriptions.Screening:The screening process means that AI will start taking on more human-based expressions.

Chatbots are the earliest and most recognizable tools that work this way.

Recruiters are currently using chatbots to automate candidate scheduling, collect basic interview responses, and answer standard questions.Natural Language Processing (NLP) is a foundational concept in artificial intelligence.

Here are some of the highlights: AI biasBecause AI algorithms are built by humans, those who deliberately or inadvertently put them into the algorithm have built-in bias.

If AI algorithms are built with a bias, or if the data in the training sets they are given to learn is biased, they may yield biased results.

This reality may lead to unintended consequences that we have become racist with non-discriminatory recruiting algorithms and Microsoft's Twitter chatbot.

Loss of some jobsMany jobs are created by artificial intelligence, and although most jobs predict a net increase, or at least the same amount of money created to replace those lost thanks to AI technology, the jobs that machines do today are people who take over.

This will require changes in training and education programs to prepare our future workforce and help current workers move to new positions that utilize their unique human capabilities.

The economic benefits of increased efficiency are very clear on the profit-loss statements of businesses, but the overall benefits to society and the human condition are somewhat opaque.

Each sector is evaluating options and adopting ways to create value in a technology-driven world.

To meet these expectations, banks have expanded their industry landscape to retail, IT and telecoms to enable services such as mobile banking, e-banking and real-time money transfer.

The integration of the banking and IT, telecom and retail sectors transmitted critical information through cyberattacks and fraudulent virtual networks.

These events not only affect the profitability of the banks, but also the banks' confidence and relationship with customers.Learn more about: What Can AI Do for Cyber   Security?The rise of online security threats in banking transactions has tightened government regulations.

According to the 2016 World Retail Banking Report, more than half of consumers worldwide are likely to swap their banks with this Player1.AI in the banking and finance industryBanking on Artificial Intelligence:The use of cognitive technology with Artificial Intelligence (AI) brings the benefit of digitization to banks and helps them to compete with Fintech players.

In fact, according to research by the National Business Research Institute and Native Science 2, 32% of financial services firms are already using AI technologies such as predictive analytics and voice recognition.Artificial intelligence is the future of banking (the importance of AI technology through industry) because it brings the power of sophisticated data analytics to deal with fraudulent transactions and improve compliance.

    Before the role of AI SERVICES & ML SOLUTIONS in Industry 4.0, we should know what it is?

Here are the breakdowns of industrial development and the great changes in related categories.Source: engineering.comIndustry 1.0: The Industrial Age began due to rapid advances in science and mechanization, e.g.

Introduction of heavy production of assembly-line cars and electricity.Industry 3.0: The invention of semiconductor features and the popularity of computers, e.g.

Future projections also include smart cities, adaptive cruise control and a brain/computer interface.This leads to an exciting world of artificial intelligence, machine learning, cybernetics, neural networks, and deep learning.

Remote monitoring of processes and decisions using big data analytics is also possible.What is Artificial intelligence?Artificial intelligence, as the name suggests, illustrates the ability of machines to simulate human mental prowess.

However, this intelligence is not limited to machines — it also applies to software systems; Hence, the differentiation of the boundary between robotics and machine learning or AI & AI SOLUTIONS.