Here is a list of top artificial intelligence initiatives unleashed by the Indian Institute of Technology.

A career in technology should be taught from the lower level of education. Once the students feel attracted to the influence of artificial intelligence and its innovations, they take up tech-based courses to quest their thirst. That is what Indian Institute of Technology colleges in India do. First set up in 1951 in Kharagpur, IITs are now located at 23 places across the country. Indian Institute of Technology colleges are educating students with practical knowledge by taking up artificial intelligence initiatives. The professors and research candidates in IITs often work with students on artificial intelligence-powered techniques and unravel a new range of products for the societal cause. In this article, Analytics Insight has listed the top artificial intelligence initiatives unleashed by the Indian Institute of Technology.

• TOP NITS AND IITS OFFERING ARTIFICIAL INTELLIGENCE COURSES IN 2021
• IIT MADRAS’ INITIATIVES ON ARTIFICIAL INTELLIGENCE
• WIZARDS OF TECH: TOP ARTIFICIAL INTELLIGENCE PROFESSORS IN INDIA

IIT Madras’ unleashes an artificial intelligence model to process texts

Indian Institute of Technology Madras has joined hands with AI4Bharat and unraveled artificial intelligence models and datasets to process texts in eleven Indian regional languages. AI4Bharat is a platform helping India to leverage innovative AI solutions to solve societal issues. The dataset includes the country’s official languages including Tamil, Telugu, Hindi, Malayalam, Kannada, etc. The multilingual AI models and datasets will provide the essential building blocks to students, faculty, start-ups, and industry to work on Indian language tools and push the frontiers of technology.

IIT Bombay develops an AI platform for video surveillance

IIT Bombay has extended its innovation of a state-of-the-art video surveillance platform to remotely monitor social distancing norm violations during the Covid-19 pandemic. Initially designed in 2017, the platform Surakshavyuh was used for military surveillance. Later, the product evolved into enterprise-grade video analytics solutions based on machine learning-enabled technology that can detect illegal entry and loitering, monitor perimeters and track objects, count crowds and recognize faces, etc. The state-of-the-art video surveillance was developed in industrial collaboration between the National Center of Excellence in Technology (NCETIS) at IITB and SrivisifAI Technologies Pvt Ltd.

IIT Kharagpur unravels an AI tool to detect the quality of goods

The researchers at the Indian Institute of Technology Kharagpur have developed a portable artificial intelligence-powered tool to automatically inspect goods manufactured by Indian micro, small, and medium enterprises (MSMEs). Most of the MSME companies in India rely on manual labor to check the quality of products. However, this innovation will change the tailwind of how small companies function. The AI-powered device clicks pictures of products when aligned on a batch of goods and sends the image feed to AI-based software for quality control analysis. By doing so, the AI software can detect and reject products that come with low quality.

IIT Madras develops an AI platform to solve complex engineering problems

A group of experts from the Indian Institute of Technology Madras has worked together and developed AI algorithms that enable novel applications using artificial intelligence, machine learning, and deep learning models, which could help solve complex engineering problems. Led by Dr. Vishal Nandigana, an assistant professor at the department of mechanical engineering, the team worked on AI and deep learning algorithm that has the potential to solve a wide variety of problems in engineering fields including thermal management, semiconductors, automobile, electronics, and aerospace.

IIT Madras launches an AI model to convert brain signals into the English language

A research team from the Indian Institute of Technology Madras has worked closely with the brain-machine interface and unraveled an AI model that could convert brain signals of speech-impaired persons into language. Besides helping impaired people, the technology can also be implied to interpret nature’s signals like plant photosynthesis process or their response to any external stimulus. The AI model decodes the waveforms of the brain using physical law and mathematical transforms such as Fourier Transform or Laplace transform. By collaborating mathematical and science laws, the model can interpret brain signals.

IIT Kharagpur unravels an AI-driven gadget to keep the intruders at bay

In order to combat the increasing threat of animals in the agricultural fields in rural and semi-reserved areas and the menace of robbers in a residential environment, the Indian Institute of Technology Kharagpur has developed an artificial intelligence-powered gadget that could keep the threats at bay. Farm Surveillance-Cum-Animal Scarer (FSCAS), the artificial intelligence-driven system, can be installed at a strategic place on the field or residential area. It starts screaming and sending alarms to the users’ mobile if it detects an animal or an intruder.

IIT Mandi develops an AI-powered app to track people on home quarantine

Indian Institute of Technology Mandi has developed an artificial intelligence-powered biometric application to monitor and accurately detect the identity and location of the home-quarantined Covid-19 patients. Lakshman Rekha, the AI-based mobile application, uses a combination of biometric verification, geofencing, and artificial intelligence to detect if the patients breach their quarantine space or not.

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Technology then and now in Healthcare.

The pandemic has been the best accelerator of innovative technological implementations in the healthcare industry. Rightfully, the healthcare industry is now thriving on modern technological developments.

Few high-end technologies that are now the crucial slices of a healthcare unit are beacon gadgets for crowd management while machine learning devices are deployed to yield appropriate disease detection and treatment methodologies. Such adoption of innovative technologies has helped medical professionals to devote more time to value-added activities like strategizing on the enhancement of patient care.

Technology will Shape the Future of Healthcare

Technology, in healthcare, is progressing along with transforming medical conducts as a whole. Such a phenomenon has struck health experts with a fresh perspective that can be leveraged for improving the healthcare profession.

Precisely, technology innovation is shaping the healthcare industry, making it sustainable. Technology in healthcare will generate a cost-effective and efficient health infrastructure.

A Glimpse of the Current Medical Landscape of India

The past five years have been very crucial and significant for the transformation of the healthcare sector. The transformation involves upgrading diagnostic tools, ventilators, medical, and surgical devices. Such transformations have resulted in positive outcomes.

A relevant example of technological transformation is ATMAN AI. ATMAN AI is an AI-powered tool used to detect complicated side effects of Covid-19 and heart diseases. This development was aimed at rural residents and residents living on the outskirts. Such a development meticulously contributed to reshaping the health infrastructure in socially backward areas, ensuring health equity for all.

Additionally, specialized surgical innovation that is inclusive of high-end technology and research has also evolved over the last two decades.

What Does Technological Transformation Mean for Healthcare System in India?

The healthcare system in India is often doubted and brought under question. The primary reason of which can be lack of skilled medical professionals and overwhelm of traditional medical conducts. There are about 500 surgeons who are adept in robotic-assisted surgeries (RAS).

Economists have pointed out the need to speed up technology adoption by the healthcare systems in India. Increased adoption of technology and proper training of the human workforce to operate disruptive technology incorporations can elevate the status of the Indian healthcare system, giving rise to more equity in healthcare opportunity dissemination.

Technological Adoption: Quick Stats

In 2021 around 8 hospitals out of 10 from all across the globe have faith in results yielded by AI-powered tools. Around 76% of healthcare professionals in India use machine learning tools and gadgets that are driven digitally.

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While there is a plethora of innovative artificial intelligence based companies, none come close to Baidu

Baidu Inc., is one of the largest providers of Chinese language Internet services. Today, it is also one of the leading artificial intelligence innovators in the world. The company has helped China position itself on the global tech map while also boosting its economy along with Alibaba and Tencent.

Sources reveal that in 2020 alone, Baidu’s core R&D expenditure accounted for 21.4% of its revenue, becoming one of the top Internet companies with the highest R&D spending. Further, Baidu also claims to have most artificial intelligence-related patent applications in China. This is a testament to Baidu’s long-term commitment to driving technological advancement. Today, Baidu is actively and often successfully integrating artificial intelligence technologies into all of its major businesses. This ranges from search engine, to drug discovery and even autonomous driving. In 2018, Baidu became the first Chinese company to join an artificial intelligence ethics group (Partnership on AI (PAI)) led by top U.S. tech firms, Alphabet Inc’s Google, Apple Inc and Facebook Inc.

Here are some notable innovations in artificial intelligence applications from Baidu:

The COVID-19 Conundrum

During the COVID-19 outbreak too, the company had leveraged its expertise in artificial intelligence, and associated technologies and products, to support frontline efforts to prevent and control the pandemic. It created an artificial intelligence system that uses infrared technology to predict passengers’ temperatures at Beijing’s Qinghe Railway Station. Its Smart Consulting Assistant has also proved resourceful in helping doctors make rapid diagnoses and initiate treatment online.

Last year, Baidu had also open-sourced its Ribonucleic acid (RNA) prediction algorithm LinearFold. This artificial intelligence algorithm aims to accelerate the prediction time of a virus’s RNA secondary structure, which is crucial to understand it and developing vaccines. Researchers found that LinearFold is capable of predicting the secondary structure of the SARS-CoV-2 RNA sequence in only 27 seconds, 120 times faster than other methods. Apart from LinearFold, Baidu has also launched PaddleHelix, a machine learning-based bio-computing framework aimed at facilitating the development of vaccine design, drug discovery, and precision medicine.

Baidu’s Autonomous Vehicles Ventures

 Apollo is an ambitious, open-source platform from Baidu that is designed to support self-driving vehicles. Apollo’s deep-learning inference support is designed to handle complex driving environments, including sensor fusion and AI processing. Baidu’s Automated Valet Parking (AVP) which runs on ACU-Advanced and Xilinx’s hardware is also built on Apollo. Last year, Baidu made headlines for its demonstration of Fully Automated Driving without a safety driver via live streaming. Using Apollo’s new Fully Automated Driving capability, the artificial intelligence system can independently drive without a safety driver inside the vehicle, a breakthrough that will accelerate the large-scale deployment of autonomous driving technology across China.

PaddlePaddle

Baidu’s PaddlePaddle offers software developers of all skill levels the tools, services, and resources they need to rapidly adopt and implement deep learning at scale. It also hosts toolkits for cutting-edge research purposes, like Paddle Quantum for quantum-computing models and Paddle Graph Learning for graph-learning models. Companies like LinkingMed have used PaddlePaddle to develop an AI-powered pneumonia screening and the lesion-detection system being used in the hospital affiliated with Xiangnan University in Hunan Province. By using Paddle Detection, a PaddlePaddle toolkit for image processing, Jinlu Technology trains an instance-segmentation model for sorting waste plastic bottles.

Natural Language Comprehension

One of the most sought after yet trickiest challenges of artificial intelligence algorithms is to enhance its NLP abilities. Baidu’s ERNIE (short for Enhanced Representation through kNowledge Integration), is presently the best in the world by GLUE (General Language Understanding Evaluation) score. ERNIE can understand blocks of language in context and therefore comprehend commands and interactions of all kinds efficiently. Some of the ERNIE’s iterations like ERNIE-GEN enable language generation tasks, like dialogue engagement, question generation, and abstractive summarization. In contrast, ERNIE-ViL helps with visual understanding.

Other Exemplary Inventions

In 2015, Baidu launched its intelligent personal assistant, Duer. Also dubbed as the Chinese Apple Siri, Duer includes multi-modal interaction, natural language processing, and other such technologies for a natural interaction and smarter understanding.

Baidu’s Deep Speech is a state-of-the-art speech recognition system developed using end-to-end deep learning by Baidu Research. It has also developed a production-quality text-to-speech (TTS) system using deep neural network – Deep Voice. Baidu mentions that its Deep Voice is faster and more efficient than Google’s WaveNet. Baidu also has SwiftScribe,  an AI-Powered Transcription Software among its wide array of artificial intelligence innovations. Based on Deep Speech 2, the main function of SwiftScribe is to transcribe audio material into the text in order to solve the problem of consuming a large amount of time-by-word dictation.

Baidu Brain, is another core artificial intelligence innovation from the Beijing based company that features advanced technology for recognizing and processing speech, images and words as well as building user profiles based on big data analysis.

Moreover, last year, Baidu launched its own artificial intelligence-based accelerator called Kunlun K200 SoC. This 256-TOPS accelerator was designed to handle its internal deep-learning workloads. The K200 accelerates common neural-network and SQL operations. On artificial intelligence inference benchmarks, it matches the power efficiency of Nvidia’s T4 card. This year, Baidu will start mass production of Kunlun 2.

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The award-winning series, Advancements with Ted Danson, will focus on recent developments in data science technology, in an upcoming episode, scheduled to broadcast 2Q/2021.

In this segment, Advancements will explore how Alteryx uses data science to enable its customers to solve analytics use cases. Viewers will also learn how Alteryx accelerates digital transformation outcomes through analytics and data science automation. Spectators will see how, regardless of user skillset, the code-free and code-friendly platform empowers a self-service approach to upskill workforces, while speeding analytic and high-impact outcomes at scale.

“As digital transformation accelerates across the globe, the ability to unlock critical business insights through analytics is of the utmost importance in achieving meaningful outcomes,” said Alan Jacobson, chief data and analytics officer of Alteryx. “Alteryx allows data workers at almost any experience level to solve complex problems with analytics and automate processes for business insights and quick wins. We look forward to sharing our story with the Advancements audience and to exploring how analytics and data science will shape the technology landscape of the future.”

The segment will also uncover how the platform accelerates upskilling across the modern workforce, while furthering digital transformation initiatives and leveraging data science analytics to drive social outcomes.

“As a proven leader in analytics and data science automation, we look forward to highlighting Alteryx and to educating viewers about the importance of analytics,” said Richard Lubin, senior producer for Advancements.

About Alteryx:
As a leader in analytic process automation (APA), Alteryx unifies analytics, data science, and business process automation in one, end-to-end platform to accelerate digital transformation. Organizations of all sizes, all over the world, rely on the Alteryx Analytic Process Automation Platform™ to deliver high-impact business outcomes and the rapid upskilling of the modern workforce. Alteryx is a registered trademark of Alteryx, Inc. All other product and brand names may be trademarks or registered trademarks of their respective owners.

About Advancements and DMG Productions:
The Advancements series is an information-based educational show targeting recent advances across a number of industries and economies. Featuring state-of-the-art solutions and important issues facing today’s consumers and business professionals, Advancements focuses on cutting-edge developments, and brings this information to the public with the vision to enlighten about how technology and innovation continue to transform our world.

Backed by experts in various fields, DMG Productions is dedicated to education and advancement, and to consistently producing commercial-free, educational programming on which both viewers and networks depend.

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App Annie, the leading mobile data and analytics company helping brands and publishers create winning experiences on mobile, announces its newest innovation designed to put data-driven insights in the hands of executives — the App Annie Pulse app.

For busy executives, time is of the essence. To keep pace with the ever-changing app economy, it’s important to access critical information about trends, markets and the competition in real time. With over USD 143 billion spent on mobile and 218 billion new app downloads in 2020, unlocking mobile insights and capitalizing quickly on opportunities is more important than ever.

Now available on the Apple App Store, App Annie Pulse provides one touch access to mobile market data. This is the industry’s only answer to benchmark competition, track market movers, and identify insights that are powered by the industry’s best estimates and data science.

This is the first mobile app to fully leverage AI-driven features:

• App Annie Performance Score: A composite metric, based on sentiment, acquisition, monetization, and engagement metrics. This allows businesses to quantify and benchmark their performance. The score can be tailored to your favorite metrics.
• App Annie Insights: Automatically monitors shifts in data and identifies potential causality

“We are unmatched in our data science capabilities – the only market data provider that derives all estimates and insights from a pure AI model,” said Ted Krantz, CEO, App Annie. “App Annie Pulse marks the introduction of the industry’s first Mobile Performance Score and ability to track your own custom metrics.”

The company is also announcing the appointment of Ketaki Rao as Chief Product Officer. Ketaki will lead the way on innovation and continue to deliver the most advanced products on the market. Ketaki joins with over 20 years of experience in product development at technology companies including Salesforce, Amazon, and Sun Microsystems.

“App Annie’s best-in-class intelligence for mobile, recent breakthroughs in AI technology, privacy-forward approach, and a bold product vision are primed to meet the new needs of a rapidly changing digital landscape. I am thrilled to join the talented and energetic App Annie team as the Chief Product Officer.” Ketaki Rao, Chief Product Officer, App Annie.

Look for the company to continue to unveil more intuitive and streamlined user experience redesigns for all its products. App Annie Intelligence redesign beta launches today and will become generally available in H2 2021. App Annie Pulse will be available on Android at the end of Q2.

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The report titled ‘Global Deep Learning Software Market Report,’ published by Market Expertz, gives a detailed description of each of the vital components of the market that helps in the better assessment of the present, as well as the future market situations. The report provides a thorough examination of the market, including its key opportunities and growth trends, which further enable the readers to devise business expansion strategies. The report takes the reader through a particular course of market development, simultaneously offering insights into the relevant industries, businesses, organizations, vendors, and local manufacturers.

The latest report is prepared, bearing in mind the current COVID-19 pandemic, which has severely impacted various segments of the market on both regional and global levels. The report encompasses exhaustive market research based on the post-COVID-19 market scenario for the market. Besides detailing the present and future impacts of the pandemic on the global market, the report throws light on the more efficient products and services developed by the industry participants, which thus form the basis of the competitive landscape of the global market.

The report covers extensive analysis of the key market players in the market, along with their business overview, expansion plans, and strategies. The key players studied in the report include:

Artelnics
Bright Computing
BAIR
Intel
Cognex
IBM
Keras
Microsoft
VLFeat
NIVIDA
PaddlePaddle
Torch
SignalBox
Wolfram

The global Deep Learning Software market has witnessed exponential growth on a wide scale, and certain market drivers, such as upstream raw materials, the surging population, thriving demand and supply, expanding regions, and technological advancements, have resulted in significant revenue generation. Furthermore, market history, constantly changing market scenarios, fluctuating demand and supply, and technological developments are among the other imperative factors detailed in the report.

Market Breakdown:

The market breakdown provides market segmentation data based on the availability of the data and information. The market is segmented on the basis of types and applications.

Market segment by Type, the product can be split into
Cloud based
On premise

Market segment by Application, Deep Learning Software can be split into
Large Enterprise
SMB

The report studies multiple paradigms of the global market, also including the regulations, standards, and policy changes implemented by the government on the industry over recent years. Furthermore, some of the advanced analytical tools, for instance, Porter’s Five Forces analysis and SWOT analysis, have been put to best use for delivering a comprehensive study of the global market, alongside pinpointing the fundamental market growth trends.

Focal Points of the Report:

Market Coverage: This section of the report gives a detailed account of the key manufacturers, market segments, product scope, product range, forecast period, and application landscape.
Executive Summary: This chapter focuses on the market growth rate, significant market drivers and restraints, current market trends, and competitive outlook.
Regional Analysis: This section delves into the latest import and export trends of the market, production and consumption ratio, the leading market players in each region, and revenue generation.
Manufacturers’ Portfolio: Complete portfolios of all the local and global manufacturers, along with the SWOT analysis, production value and capacity, product catalogue, and other important details of their businesses, constitute this section of the report.
Key Takeaways:

The global Deep Learning Software market report offers an in-depth study of the market’s dynamic growth patterns and sizes, the top industry players, and the important segments.
The report includes an emphasis on some of the highly valuable business priorities followed by companies across the industry in order to build on their existing business strategies.
The key highlights and recommendations in the report provide meaningful information to companies about the newest industry trends, thereby helping them strategize their long-term goals and accelerating their decision-making process.
The report further contains information on the latest market trends, driving and constraining factors, industry chain analysis, and product segmentation.

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In recent years, we have seen so much innovation and digital transformation in all corners of the construction industry from the planning and design process to on-site work. Robotics has been one of the biggest technological advancements the industry has been graced by.

As robotics in the construction industry continues to play a big part in keeping things moving efficiency, we explore the four latest and greatest solutions.

Husky A200

Despite its relatively small size, the four-wheeled Husky A200 robot packs a punch. It has the ability to help contractors save time by carrying various tools, materials and other objects across the construction site. 

Although the robot hasn’t quite reached the mainstream market yet, engineers at the Italy-based Fraunhofer Italia Innovation Engineering Center (IEC) are working to adapt the A200 to do just that.

GE Tunneling Earthworm

GE has always been known to innovate and lead the way in many industries, delivering some of the most useful innovations and products to both businesses and consumers.

As the company focuses on the construction and mining industry, a research team based in New York are developing a small tunnelling robot which will have the ability to dig a tunnel over 540 yards long at a speed of almost four inches per second. 

The robot will be able to mimic the movement of an earthworm moving understand which will enable maximum efficiency and flexibility. It will have no trouble squeezing into tight spaces either, thanks to its muscle- and skeleton-like structure.

Coffee Feet Robot

This is certainly one on the list with the most interesting name. The Coffee Feet Robot is being designed by the University of California San Diego. The researchers have found a way to help commercially available robots move up to 40% faster on uneven terrain. This has been achieved by placing a membrane filled with coffee ground on the feet of a robot, hence the name.

Boston Dynamics’ robot dog

Boston Dynamics is known for its clever robot innovations. This robot is set apart from the others on the list as it is commercially available right now priced at $74,500.

The robot dog, officially known as SpotWalk, includes image-capturing devices and laser scanners giving it the ability to navigate and patrol predetermined pathways through a job site. It also has the ability to navigate difficult terrain due thanks to the robots’ clever design. The machine aims to reduce worker hours doing the same tasks repeatedly, but is also designed to provide the latest imagery of the construction site.

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Spot, the robotic “dog” design from Boston Dynamics, has had a busy pandemic, between counseling patients and enforcing social distancing guidelines. Now, a new partnership with a New Zealand robotics firm is setting up the four-legged automaton for a new line of work: farming.

Technically, the partnership is much bigger than that. Rocos specializes in the remote monitoring and operation of robot fleets. By working together, the capabilities of Boston Dynamics robots like Spot will expand thanks to human operators who can manage their performance from a great distance.

Think of the farming thing as a proof-of-concept. A video released by Rocos shows Spot exploring rough terrain, inspecting crops, and herding sheep – all of which is meant to serve as a demonstration of the various ways remote operation can be used to put robots to work.

“Equipped with payloads like heat, LIDAR, gas and high resolution camera sensors, Spot navigates rugged environments to capture data in real time – feeding this data back into existing business systems, wherever they are located ,” the Rocos news announcement reads, before offering some examples.

“In the energy sector this provides real-time anomaly detection as well as access to historic digital records for comparison. In agriculture, farmers can access information such as more accurate and up-to-date yield estimates. This provides access to a new category of automation, and a safer, more efficient business.”

Automation has been creeping into industrial spaces for many years now and the coronavirus pandemic has only accelerated that shift. As the illness has come for warehouse and assembly line workers, who all tend to operate in close quarters, the question of how and where robots can step in to help has become louder and more pressing.

We were already starting to see robots pop up in supermarkets before the pandemic threat really started having an impact in the United States. Amazon is also reportedly looking at installing robots in its warehouses.

Not everyone is on board with throwing open all the doors to using robots as replacements for human labor, of course. Amazon in particular has faced harsh criticism in recent months for what many have described as unsafe warehouse working conditions. The move toward automation in general seems inevitable, but Amazon’s will face particular scrutiny over any such decision due to the stories that have come out.

Individual company stories aside, the march toward automation continues on. Boston Dyanmics’ partnership with Rocos ought to speed that along, given the capabilities of robots like Spot and all the potential ways remote operation could put them to work.

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One of the most difficult challenges for artificial intelligence systems is predicting the weather – with an almost infinite number of variables to assess and model. But Google says its AI is making progress in the accuracy of its “nowcasts.”

Nowcasting is forecasting the weather in the very short term, over the next one or two hours. While a quick glance out of the window might give you some idea, knowing exactly when rain is about to start or stop (for example) can be incredibly useful for event planning, farming, disaster prevention and many other purposes.

Google has applied deep learning techniques, modeled on the neural networks of the human brain, to produce improved nowcasts for small areas (one sq km or 0.39 sq mi) over the course of an hour.

The new system, presented in a paper that has not yet been peer reviewed, is a significant step forward from existing prediction models, Google says. It can make accurate predictions in minutes rather than hours, which is much more useful when you want to know what the weather is going to do in the short-term.

That speed increase is achieved by ditching the heavy lifting of computationally intensive physics models, and replacing it with neural networks that are trained on historical data.

“A significant advantage of machine learning is that inference is computationally cheap given an already-trained model, allowing forecasts that are nearly instantaneous and in the native high resolution of the input data,” writes Jason Hickey, a Senior Software Engineer at Google Research, in a blog post.

Google’s AI nowcasts proved more accurate than three existing prediction techniques they were compared with, though the roles were reversed for forecasts more than six hours ahead – for now, this type of artificial intelligence processing is best suited for making short-term predictions in weather patterns.

AI also excels at chewing through – and making sense of – large amounts of data. The National Oceanic and Atmospheric Administration (NOAA) now collects nearly 100 terabytes of data per day from radar, satellites, weather stations and other sources.

One of the tricks Google’s system pulls is treating nowcasting as a computer vision problem, rather than trying to model real-world physics. Radar images are collated and analyzed using convolutional neural networks or CNNs – the same layered networks used to recognize objects in images and to interpret natural speech.

These CNNs are particularly good at achieving fast results with a high level of accuracy, as long as they’ve had enough training data, and the early signs are they could be very useful for nowcasting as well.

On a broader scale, knowing how weather conditions are shifting in real time is going to be crucial in assessing how climate change continues to impact the planet, and it seems AI is up to the challenge.

“As weather patterns are altered by climate change, and as the frequency of extreme weather events increases, it becomes more important to provide actionable predictions at high spatial and temporal resolutions,” write Google’s researchers in their paper.

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Data discovery is the process of obtaining actionable information by finding patterns in data from multiple sources with interactive visual analysis. The term is used to express a mode of analysis in which users attempt to get a holistic view of all their data sources. The two main ingredients are the ability to join data sources and the interactive visual analysis component which allows to explore the data to find patterns.

The Data Discovery Market research report presents a comprehensive assessment of the market and contains thoughtful insights, facts, historical data and statistically-supported and industry-validated market data and projections with a suitable set of assumptions and methodology. It provides analysis and information by categories such as market segments, regions, and product type and distribution channels.

By Market Players: Tableau Software, Inc., Datawatch Corporation, Datameer, Inc., Tibco Software Inc., SAP SE., Cloudera, Inc., Birst, Inc., Clearstory Data, Platfora, Oracle Corporation, Qlik Technologies, Inc., Microstrategy, Inc.

The report begins with a brief introduction and market overview, in which the Data Discovery industry is first defined before estimating its market scope and size. Next, the report elaborates on the market scope and market size estimation. This is followed by an overview of the market segmentations such as type, application, and region. The drivers, limitations, and opportunities are listed for the Data Discovery industry, followed by industry news and policies.

The report includes an analysis of the growth rate of every segment with the help of charts and tables. In addition, the market across various regions is analyzed in the report, including North America, Europe, Asia-Pacific, and LAMEA. The report manifests the growth trends and future opportunities in every region.

Global Data Discovery market is presented to the readers as a holistic snapshot of the competitive landscape within the given forecast period. It presents a comparative detailed analysis of the all regional and player segments, offering readers a better knowledge of where areas in which they can place their existing resources and gauging the priority of a particular region in order to boost their standing in the global market.

The Global Data Discovery Market is gaining pace and businesses have started understanding the benefits of analytics in the present day highly dynamic business environment. The market has witnessed several important developments over the past few years, with mounting volumes of business data and the shift from traditional data analysis platforms to self-service business analytics being some of the most prominent ones.

For the future period, sound forecasts on market value and volume are offered for each type and application. In the same period, the report also provides a detailed analysis of market value and consumption for each region. These insights are helpful in devising strategies for the future and take necessary steps. New project investment feasibility analysis and SWOT analysis are offered along with insights on industry barriers. Research findings and conclusions are mentioned at the end.

Reasons for Buying This Report:
•It Provides A Forward-Looking Perspective on Different Factors Driving or Restraining Market Growth.
•It Provides A Five-Year Forecast Assessed on The Basis of How the Market Is Predicted to Grow
•It Helps in Understanding the Key Product Segments and Their Future.
•It Provides Pin Point Analysis of Changing Competition Dynamics and Keeps You Ahead of Competitors.
•It Helps in Making Informed Business Decisions by Having Complete Insights of Market and By Making an In-Depth Analysis of Market Segments.

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