Start-up ecosystems thrive in the UAE with a boom in Big Data

A company or a business traditionally starts from scratch. From planning to finance to management and execution, start-up ecosystems have faced challenges to establish themselves. Today, the business world is productive, a lot more supportive, and believes in two-way progression. Tech influencers and game-changers across the world are setting the trend of helping entrepreneurial ecosystems thrive. Microsoft supports the fields of tech and business to flourish in the emerging new area of Big Data at Hub71.

The world lives and runs on technology, it exists and procreates over technology. Technology on the other hand is full of Big Data. This data has now become “the new oil” for start-up ecosystems. Recent Global Data research cites the examples of 3.5 billion Google searches and 1.3 billion internet-of-things connections per day, and 254 Exabytes (one Exabyte is a billion gigabytes) of mobile broadband data traffic per year. Big data is a combination of structured, semi-structured, and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modeling, and other advanced analytics applications.

The digital data explosion began in 2010 and has advanced remarkably. Statistics predict it is increasing even more up to 26% by 2022. Big data technologies help companies store large volumes of data while enabling significant cost benefits. Such technologies include cloud-based analytics and Hadoop. They help businesses analyze information and improve decision-making. Furthermore, data breaches pose the need for enhanced security, which technology applications can solve.

The Middle East nations on the other hand are escalating increasingly in terms of health tech, big data, property tech, artificial intelligence, etc. It has become a home for start-up ecosystems and tech in contemporary times. Magnitt, a start-up data analytics company states that more than 60% of investment funding for start-ups in the MENA region was given to the projects based in the UAE in 2019.

The global tech conglomerates like Microsoft, Google, Facebook, and Twitter have already established their MENA Headquarters in the UAE. Hub71, which is located in the heart of Abu Dhabi, has built a niche between the well-established companies to those of budding ones. Its networking capability, its accessibility in terms of capital, communication have all paved a way for Hub71 to grow as an emerging global marketing giant.

“There is a strong start-up culture and plenty of advice available for young entrepreneurs looking for their next move into the Middle East. Microsoft is a leading light in the big data industry across seven technology segments, including data security, storage, processing, aggregation, and integration. The UAE has become a hub in many areas, including technology” stated Sayed Hashish, general manager for Microsoft UAE that has been operating its services from the past 25 years as the strategic partner for Hub71.  He also adds that there is a lot of potential for start-up culture in the UAE for young aspiring entrepreneurs. Microsoft on the other hand, is a torch bearer across seven technological segments, including data security, storage, processing, aggregation and integration.

Hashish said that Microsoft has always believed in focusing on start-ups as its core value. He also mentioned that Hub71 was launched with the central theme of encouraging and establishing start-ups. The timing was absolutely perfect in his view.

Another core mission of Microsoft was to empower every business to turn the game around the planet and Microsoft has already fulfilled that. Apart from building huge data centers operating in the region, the company, which is the only one in the US to still be worth more than US$1trn after the coronavirus pandemic, has made plenty of time to mentor newer companies.

Microsoft and its services have always been incredible in many ways. Atif Mahmoud, Founder of British edtech start-up Teacherly said that opening the company’s second office in Abu Dhabi (the first was in London) had given his start-up the boost it needed. He then said that the tech giant joining hands with his once- upon time small start-up was a dream come true.

Putting it in a nutshell, Abu Dhabi’s Hub71 literally is reigning in the global tech-business industry with loads of opportunities for aspiring young entrepreneurs wishing to establish start-ups to flourish in Big Data and Microsoft is doing all it can to accelerate the global industry upwards.

The post GROWTH IN BIG DATA MAKES UAE A HOTBED FOR INVESTMENTS: MICROSOFT LENDS HELP appeared first on Artificial Intelligence.

Artificial Intelligence (AI) is likely to play a key role in relieving India’s agriculture sector from its stressful input conditions, catalysing a shift towards data-driven farming, said a new Nasscom-EY report on Thursday.

NEW DELHI: Artificial Intelligence (AI) is likely to play a key role in relieving India’s agriculture sector from its stressful input conditions, catalysing a shift towards data-driven farming, said a new Nasscom-EY report on Thursday. With increased government support, growing agritech providers, burgeoning start-up ecosystem, and rising AI adoption among the rural farming population, a strong transformation impetus is underway, said the report titled “Leveraging AI to maximise India’s agriculture output.”

Data consolidation (both at macro and real-time farm-level), lack of infrastructure awareness in data processing, and its availability have been some of the key challenges faced by the sector today. In addition to this, lack of awareness on agricultural inputs specific to the produce, access to quality seeds, lack of adequate mechanisation and irrigation infrastructure, scarcity of farmer capital, frequent disease outbreak, and inadequate storage facilities are the other value chain challenges faced by the sector.

“The Indian agriculture sector can utilise the potential of AI’s transformative capabilities through effective data practices,” Debjani Ghosh, President, Nasscom, said in a statement. “The Netherlands is a stellar example of effective AI adoption in agriculture. With just a small arable land, the country has become the world’s 2nd largest exporter of agricultural products by value leveraging technology and AI.

“For India to realise the full potential of AI, a coalition of government, industries, and startups in providing necessary infrastructure and policy support, enabling AI innovation across sectors, and mentoring and providing financial support to startups is imperative,” she said. Leveraging macro as well as farm-level data collected through sensors could help maximise yields and optimise the use of available resources, said the report.

Several AI-led use cases, such as precision agriculture and farm management, agricultural robots, automated weeding, crop quality and readiness identification, pest prediction and prevention, livestock monitoring and management, crop yield estimation, etc. can solve improving farm productivity. (IANS)

NEW DELHI: The government is considering measures to curb malpractices by foreign e-commerce companies, including widening the scope of group company as this goes to the root of controlling the sellers, said an official present at a meeting on FDI policy held on Thursday. The official said on condition of anonymity that the group should include affiliate and associate companies and prohibit direct and indirect control, be it equity or economic. A meeting to discuss FDI policy in e-commerce space was convened by the Department for Promotion of Industry and Internal Trade (DPIIT) on Thursday that was attended by 25 e-commerce companies. The FDI policy from its very beginning has not allowed foreign capital in the inventory based model and it is allowed only in pure technical infrastructure/platform which facilitate meeting of the buyer with the seller. Such a platform cannot act as a seller itself, directly or indirectly. The ill-effects of foreign capital dumping in the multi-brand retail and inventory based e-commerce space are well known, the official said. The official said the forbidden gap between inventory-based model and marketplace model has been crossed by some foreign companies by the way of legal creativity of exploiting either the loopholes or by creative interpretation of the policy that violate the policy in spirit. Such legal creativity include creating multi-level company structure to hide the real relationship between the marketplace entity and the sellers. The relationship between the leading foreign marketplace entities and some of the largest sellers on their platforms is no secret. Reports reveal the structure of the companies and show how these marketplace entities are engaged in control of inventory and their largest sellers. The continued violations create doubts about the legal sanctity of the policy, especially in the minds of new e-commerce players. Therefore, it is imperative that the rules are clarified to an extent that these are not subjected to such creative interpretations, sources said. The sources said that it must be the government’s endeavour to match the letters to the spirit of the policy so that it does not create any doubt, whatsoever, in the mind of any foreign marketplace company. These suggestions should be issued in the form of a new press note or amendment to the FDI policy, sources said. Some of the suggestions are as follows: Widening the scope of group company: This goes to the root of controlling the sellers. The group should include affiliate and associate companies and prohibit direct and indirect control, be it equity or economic. Preventing the misuse of B2B e-commerce: In either controlling the inventory or providing deep discounts through selected sellers by the way of capital dumping. Compliance to the provisions of the policy is very important. A clause in the manufacturing section seems to be an omission in the policy as the same is being used for retail trading of food products by some companies. A clause in manufacturing section cannot override the spirit of the retail trading policy, sources added. (IANS)

The post ‘Artificial Intelligence could play key role in India’s growth in agriculture’ appeared first on Artificial Intelligence.

The new research report titles Global Hadoop Big Data Analytics market Report 2020 by Key Players, Types, Applications, Countries, Market Size, Forecast to 2025 that studies all the vital factors related to the Global Hadoop Big Data Analytics market that are crucial for the growth and development of businesses in the given market parameters. The report highlights the important elements related to the market such as the market size, share, company profiles, profitability, opportunities and threats, technological advancements, key market players, regional segmentation, and many more important elements related to the Global Hadoop Big Data Analytics market.

The recent Hadoop Big Data Analytics market report contains a detailed analysis of this business domain in accordance to the primary growth catalysts, opportunities, and limitations shaping the industry dynamics. An economy-wide database of the regional markets along with the leading organizations that occupy them is outlined in the document. Furthermore, it studies the impact of COVID-19 pandemic on the growth matrix of this vertical and draws attention to the popular tactics adopted by major players to adapt to the uncertainties in the industry.

Major highlights from COVID-19 impact analysis:

• Global footprint of the COVID-19 pandemic and its implications on the economy.
• Instabilities in the demand and supply channels.
• Predicted outlook of COVID-19 pandemic on the business development.

An overview of the regional analysis:

• From a regional point of view, the Hadoop Big Data Analytics market is bifurcated into North America, Europe, Asia-Pacific, Middle East and Africa and South America.
• A synopsis of each regional market, inclusive of their projected growth rate during the forecast duration is enclosed in the document.
• Figures reflecting sales and revenue netted by each geography are cited.

Additional highlights from the Hadoop Big Data Analytics market report:

• The product gamut of the Hadoop Big Data Analytics market is split into Managed Software,Application Software,Performance Management Software andOthers.
• Volume and revenue estimates of each product category are presented with supporting data.
• Estimations of the market share and annual growth rate for each product type over the forecast period are mentioned in the report.
• With regards to application terrain, the industry is fragmented into Risk & Fraud Analytics,Internet of Things,Customer Analytics,Security Intelligence,Distributed Coordination Service,Merchandising & Supply Chain Analytics,Operational Intelligence,Linguistic Analytics andOffloading Mainframe Application.
• Projections for the market share and yearly growth rate of each application type during the study duration are enumerated.
• Leading organizations that have an authoritative status in Hadoop Big Data Analytics market are IBM Corporation,Microsoft Corporation,Sap SE,Pentaho Corporation,Cloudera,Amazon Web Services (AWS),Hewlett-Packard Enterprise,Hortonworks,Memsql Inc,Marklogic Corporation,Pivotal Software,Mongodb,Datasift,Datameer,Qubole,MAPR Technologies andTableau Software.
• In-depth profile of the listed companies, along with their product offerings, production patterns, and industry remuneration are highlighted.
• Other important facets including pricing patterns, gross margins, and market share of each player are also included in the report.
• The study elucidates the competitive trends of the market and also provides a comprehensive assessment of the supply chain.
• Utilizing SWOT analysis and Porter’s five forces analysis, it explicates the feasibility of a new project.

Some of the key questions answered in this report:

What will the Hadoop Big Data Analytics market growth rate, growth momentum or acceleration market carries during the forecast period?

What was the size of the emerging Hadoop Big Data Analytics market by value in 2020?

What will be the size of the emerging Hadoop Big Data Analytics market in 2025?

Which are the key factors driving the Hadoop Big Data Analytics market?

Which region is expected to hold the highest market share in the Hadoop Big Data Analytics market?

What trends, challenges and barriers will impact the development and sizing of the Global Hadoop Big Data Analytics market?

What are the Hadoop Big Data Analytics market opportunities and threats faced by the vendors in the global Hadoop Big Data Analytics Industry?

What are sales volume, revenue, and price analysis of top manufacturers of Hadoop Big Data Analytics market?

The post Hadoop Big Data Analytics Market Segmentation, Analysis by Recent Trends, Development & Growth by Regions to 2025 appeared first on Artificial Intelligence.

Exploring the growth of AI that are advancing the industries today

Artificial intelligence has transformed the business environment drastically. What began as a rule-based automation system is now capable of simulating human interaction. Artificial intelligence is not only exceptional because of the human capabilities. As compared to human equivalents, an advanced AI algorithm provides better speed and capacity at a much lower price.

Today, we are already related to AI in some way or the other, whether it is Siri, or Alexa, thanks to technological innovations. Yeah, the technology is still in its early stages, but more businesses are engaging in machine learning, suggesting that AI products and applications can expand rapidly in the immediate future.

Here are few examples in which growth of Artificial Intelligence can be seen today:

AI in Content and news organizations

AI systems are increasingly being used by content and news organisations to discover data from various sources and instantly summarize it into content or supporting analysis for those articles. Machine learning algorithms have been shown to be capable of detecting variations in textual data and extracting valuable knowledge that appropriately summarizes the information contained inside. Journalistic organizations can easily keep up with current events and produce content that accurately summarizes evolving circumstances by applying these sophisticated algorithms to vast amounts of data from press releases, tweets, articles, and other unstructured content.

Super Intelligence

BBN Times mentioned that artificial intelligence is not only good at problem solving but it is also demonstrating empathy. AI has developed spontaneous emotions of its own accord. The company Cogito, founded by Joshua Fest and Dr Sandy Pentland, melds together machine learning with behavioral adaptation, supported by the latest breakthroughs in behavioral science.

The result is jarring to those who are used to AI being a benign force ready to work off dry data, but incredibly beneficial in the high-volume customer service arena – and highly promising when we look to the future of artificial intelligence, and how it can continue to improve human life.

AI in Healthcare

The role of AI-powered technologies in next-generation healthcare technology is being recognized by the health sector. AI is thought to have the ability to enhance every phase of healthcare operations and service. For example, the economic benefits that AI can bring to the healthcare sector are a crucial motivator for AI implementation. AI systems are expected to save the US $150 billion in healthcare costs by 2026. The shift from a reactive to a proactive healthcare paradigm, concentrating on health treatment rather than curing diseases, is responsible for a significant portion of these cost savings. As a result, fewer hospitalizations, doctor appointments, and procedures are expected. AI-based innovation will play a key role in assisting people in maintaining their wellbeing by continuous tracking and coaching, as well as ensuring earlier diagnosis, personalized care, and more effective reassessments.

AI in Entertainment

Today the entertainment industry is all set to undergo a different kind of transformation. AI would make the future of the industry more social, personalized, and entertaining. Virtual reality, ally robots can gradually penetrate the home as the use of sensors and hardware expands. Additionally, consumers will be able to converse with entertainment devices.

Media companies will be able to personalize entertainment to previously unthinkable levels thanks to this technology. You’ll possibly be able to build your own entertainment channel using AI in the not-too-distant future.

The post THE SPECTACULAR GROWTH OF ARTIFICIAL INTELLIGENCE TODAY appeared first on Artificial Intelligence.

The demand for these sought-after positions continues to grow in importance, according to analysis of job openings for March 2021 conducted by LHH.

Many tech workers find themselves on the precipice of change: their organizations may decide to continue remote work for the foreseeable future, they may adopt a hybrid work schedule or they’ll return to on-premises full time. But while a recent study showed that most employees said they’ll stay in their current positions, they also said they expected a greater return from their employers, which means if they don’t get that “return,” they’ll be on the job market. 

SEE: Hiring Kit: Technical Recruiter (TechRepublic Premium)

Many organizations were hit hard by the impact of the pandemic and, coupled with the safety protocols required for workers who do go into the office, they might not be able to accommodate employees’ demands. This represents potential for the tech industry, with pros looking for new positions and companies looking for new talent. LHH, formerly Lee Hecht Harrison, global provider of talent and leadership development, career transition and coaching, analyzed job openings for March 2021, and its findings can provide insight for tech pros, whether they want to remain in their jobs or if they might consider “putting feelers out.” 

While the LHH Job Bulletin (where the insights can be found) covers many industries, it does devote a portion to tech news. Here’s a look at what is covered in the report.

This week’s 10 most wanted skills based on job postings 

1. Communication, 646,575  
2. Dedication, 455,651
3. Analysis, 409,243
4. Leadership, 404,484
5. Collaboration, 386,936
6. Scheduling, 358,769
7. Operations, 356,270
8. Innovation, 350,042
9. Written communications, 293,720  
10. Verbal communications, 288,513

Top tech jobs in top 15 job categories

LHH noted that LinkedIn recently highlighted the top 15 job categories based on demand and growth and offered clients a look at where some of the tech-related jobs landed on that list.

No. 6 Digital marketing: COVID-19, while 99.9% awful, caused a big spike in online shopping, which in turn created a demand for marketers well versed in reaching people online. Digital marketing hires grew nearly 33% in 2020 from 2019. Job titles in this category include digital marketing specialist, social media manager, marketing representative and search engine optimization specialist. The salary range is $48,000 to $96,000 per year.

No. 9 Digital content: The demand for online entertainment went stratospheric in 2020. People sheltering at home binge watched and were hungry for content. Digital content creators were in demand, too, and grew 49% in 2020. Job titles include content coordinator, writing consultant, podcaster and blogger. The salary range is $46,000 to $62,400 per year.

No. 11 Software: With many employees sent to work remotely, being online was everything in 2020. Specialists needed to keep the online world up and running grew nearly 25% in 2020. Job titles in this category include web developer, full-stack engineer, front-end developer, and game developer. The salary range is $77,500 to $104,000 per year.

No. 13 User experience: The swift move to online everything in 2020 meant there was a need for experts who specialize in the interactions between people and the digital world, growing 20% in 2020. Job titles in this category include user-experience designer, product design consultant, user interface designer, and user experience researcher. The salary range is $41,600 to $65,000 per year.

#14 Data science: With everyone reliant on data and its capabilities, experts were in high demand. Hiring for data science positions grew nearly 46% in 2020. Job titles in this category include data scientist, data science specialist, and data management analyst. The salary range is $100,000 to $130,000 per year.

#15 Artificial intelligence: The massive, pandemic-induced employment shifts, layoffs, and business disruptions in 2020 resulted in companies looking to artificial intelligence as a way to keep up with increased demand, while safeguarding their businesses from future disruptions. AI hiring grew 32% in 2020. Some of the job titles in this category include machine learning engineer, artificial intelligence specialist, and machine learning researcher. The salary range is $124,000 to $150,000 per year.

Top 5 tech jobs with fastest-growing salaries 

Apart from the top tier of healthcare, the tech industry offers some of the highest salaries among industries. LHH analyzed popular roles and revealed the percentage of growth between 2019 and 2020.

• Cybersecurity analyst–16.3% growth
• Data scientist–12.8% growth
• DevOps engineer–12.2% growth
• Technical support engineer–8.2% growth 
• Cloud architect/engineer–6.3% growth

Companies with tech job openings, according to LHH

• Novacoast,a cybersecurity company, will expand in Wichita, Kansas. The company will open a Security Operations Center initially hiring 60 employees with plans to expand over the next few years.
• Pendo, a startup in North Carolina, prevailed during a pandemic-stricken year. The company plans to hire 400 more employees this year to fuel that growth as it invests heavily in its presence overseas and looks to nab more large customers to its platform. There are currently 169 open roles.
• Infosys will hire 300 workers in Pennsylvania as part of its local hiring strategy in the U.S. Infosys will recruit for a range of opportunities across technology and digital services, client administration and operations.
• Zones, an IT company,is hiring for advanced technology executives across the U.S.
• HCL Technologies specializes in IT services and consulting. It delivers innovative technology solutions built around digital, Internet of Things, cloud, automation, cybersecurity, analytics, infrastructure management and engineering.
• TEKsystems has opportunities for technical PM, product manager, SW developer, QA, mobile developer, Python developer, DevOps engineer, site reliability engineer, video streaming engineer, cloud engineer, security engineer, data center technician, and more.

The post Job trend analysis marks growth of data science, AI roles appeared first on Artificial Intelligence.

The Deep Learning Market size is expected to grow at an annual average of 38.2% during 2021-2027. DC control tools are systems used to hold torque and automation processes and provide accurate, accurate and repeatable torque control. Torque fixing system manufacturers can optimize the assembly area due to their high performance, reduce labor costs and increase productivity.

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A full report of Deep Learning Market is available at:
https://www.orionmarketreports.com/deep-learning-market-market/46630/

The following segmentation are covered in this report:

By Application
• Image recognition
• Voice recognition
• Video surveillance & diagnostics
• Data mining

By Solution
• Hardware
• Software
• Service

By End-use
• Automotive
• Aerospace & defense
• Healthcare
• Manufacturing
• Others

Company Profiles
• Facebook Inc.
• Google
• Amazon Web Services Inc
• SAS Institute Inc
• Microsoft Corporation
• IBM Corp

Reasons to Buying From us –
• We cover more than 15 major industries, further segmented into more than 90 sectors.
• More than 120 countries are for analysis.
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Scope of the report
The research study analyses the Deep Learning Market industry from 360-degree analysis of the market thoroughly delivering insights into the market for better business decisions, considering multiple aspects some of which are listed below as:

Recent developments
• Market overview and growth analysis
• Import and export overview
• Volume analysis
• Current market trends and future outlook
• Market opportunistic and attractive investment segment

Geographic coverage
• North america market size and/or volume
• Latin america market size and/or volume
• Europe market size and/or volume
• Asia-pacific market size and/or volume
• Rest of the world market size and/or volume

Key questions answered by lighting control system market report
• What was the Deep Learning Market size in 2018 and 2019; what are the estimated growth trends and market forecast (2019-2025).
• What will be the cagr of lighting control system market during the forecast period (2019-2025)?
• Which segments (product type/applications/end-user) were most attractive for investments in 2018? how these segments are expected to grow during the forecast period (2019-2025).
• Which manufacturer/vendor/players in the lighting control system market was the market leader in 2018?
• Overview on the existing product portfolio, products in the pipeline, and strategic initiatives taken by key vendors in the market.

The post Deep Learning Market – Global Industry Analysis, Size, Share, Growth, Trends and Forecast 2021-2027 appeared first on Artificial Intelligence.

The report also dispenses valuable statistics about market size, participant share, and consumption data in terms of key regions, along with an insightful gist of the behemoths in the Deep Learning market. The study of Deep Learning market highlights important aspects such drivers, challenges, restraints, and expansion prospects prevailing in this particular industry sphere.

Major Market Key Players:

• Advanced Micro Devices
• ARM Ltd
• Clarifai
• Entilic
• Google
• HyperVerge
• IBM
• Intel
• Microsoft
• NVIDIA

Deep Learning Market Segment by Types, covers:

• Software
• Hardware
• Service

Deep Learning Market Segment by End Use, can be divided into:

• Aerospace & Defense
• Automotive
• Manufacturing
• Healthcare
• Others

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A dedicated chapter on COVID-19 analysis has therefore been included in this versatile report to encourage future-ready business discretion aligning with post-COVID-19 market environment.

Deep Learning Market: Regional Segment Analysis

• North America
• Europe
• Asia Pacific
• Middle East & Africa
• Latin America

Some of the key questions answered in the report include:

1. What is the overall structure of the market?
2. What was the historical value and what is the forecasted value of the market?
3. What are the key product level trends in the market?
4. What are the market level trends in the market?
5. Which of the market players are leading and what are their key differential strategies to retain their stronghold?
6. Which are the most lucrative regions in the market space?

Table of Contents:

1. Global Deep Learning Market Overview
2. Deep Learning Economic Impact on Industry
3. Deep Learning Market Competition by Manufacturers
4. Production, Revenue (Value) by Region
5. Supply (Production), Consumption, Export, Import by Regions
6. Production, Revenue (Value), Price Trend by Type
7. Deep Learning Market Analysis by Application
8. Deep Learning Manufacturing Cost Analysis
9. Industrial Chain, Sourcing Strategy and Downstream Buyers
10. Marketing Strategy Analysis, Distributors/Traders
11. Deep Learning Market Effect Factors Analysis
12. Global Deep Learning Market Forecast

Conclusively, the report describes the performance of the key product and application segments in the Deep Learning Market in each regional market. Likewise, the competitive dynamics of each regional market have been elaborated by providing information on the hierarchy among the major players operating within it. This provides a thorough and detailed analysis of the global market. The report also provides forecasts for 2021-2028 for each product, application and geographical segment of the global market.

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The post Deep Learning Market Size, Growth Analysis, Opportunities and Forecast To 2028 | Advanced Micro Devices, ARM Ltd, Clarifai appeared first on Artificial Intelligence.

We’ve all come to terms with the fact that artificial intelligence (AI) is transforming how businesses operate and how much it can help a business in the long term. Over the past few years, this understanding has driven a spike in companies experimenting and evaluating AI technologies and who are now using it specifically in production deployments.

Of course, when organizations adopt new technologies such as AI and machine learning (ML), they gradually start to consider how new areas could be affected by the technology. This can range across multiple sectors, including production and logistics, manufacturing, IT and customer service. Once the use of AI and ML techniques becomes ingrained in how businesses function and in the different ways in which they can be used, organizations will be able to gain new knowledge which will help them to adapt to evolving needs.

By delving into O’Reilly’s learning platform, a variety of information about the different trends and topics tech and business leaders need to know can be discovered. This will allow them to better understand their jobs and will ensure that their businesses continue to thrive. Over the last few months, we have analyzed the platform’s user usage and have discovered the most popular and most-searched topics in AI and ML. We’ll be exploring some of the most important finding below which gives us a wider picture of where the state of AI and ML is, and ultimately, where it is headed.

AI outpacing growth in ML

First and foremost, our analysis shone a light on how interest in AI is continuing to grow. When comparing 2018 to 2019, engagement in AI increased by 58 percent – far outpacing growth in the much larger machine learning topic, which increased only 5 percent in 2019. When aggregating all AI and ML topics, this accounts for nearly 5 percent of all usage activity on the platform. While this is just slightly less than high-level, well-established topics like data engineering (8 percent of usage activity) and data science (5 percent of usage activity), interest in these topics grew 50 percent faster than data science. Data engineering actually decreased about 8 percent over the same time due to declines in engagement with data management topics.

We also discovered early signs that organizations are experimenting with advanced tools and methods. Of our findings, engagement in unsupervised learning content is probably one of the most interesting. In unsupervised learning, an AI algorithm is trained to look for previously undetected patterns in a data set with no pre-existing labels or classification with minimum human supervision or guidance. In 2018, the usage for unsupervised learning topics grew by 53 percent and by 172 percent in 2019.

But what’s driving this growth? While the names of its methods (clustering and association) and its applications (neural networks) are familiar, unsupervised learning isn’t as well understood as its supervised learning counterpart, which serves as the default strategy for ML for most people and most use cases. This surge in unsupervised learning activity is likely driven by a lack of familiarity with the term itself, as well as with its uses, benefits, and requirements by more sophisticated users who are faced with use cases not easily addressed with supervised methods. It is also likely that that the visible success of unsupervised learning in neural networks and deep learning has helped our interest, as has the diversity of open source tools, libraries and tutorials, that support unsupervised learning.

A deep learning resurrection

While deep learning cooled slightly in 2019, it still accounted for 22 percent of all AI and ML usage. We also suspect that its success has helped spur the resurrection of a number of other disused or neglected ideas. The biggest example of this is reinforcement learning. This topic experienced exponential growth, growing over 1,500 percent since 2017.

Even with engagement rates dropping by 10 percent in 2019, deep learning itself is one of the most popular ML methods among companies that are evaluating AI, with many companies choosing the technique to support production use cases. It might be that engagement with deep learning topics has plateaued because most people are already actively engaging with the technology, meaning growth could slow down.

Natural language processing is another topic that has shown consistent growth. While its growth rate isn’t huge – it grew by 15 percent in 2018 and 9 percent in 2019 – natural language processing accounts for about 12 percent of all AI and ML usage on our platform. This is around 6x the share of unsupervised learning and 5x the share of reinforcement learning usage, despite the significant growth these two topics have experienced over the last two years.

Not all AI/ML methods are treated equally, however. For example, interest in chatbots seems to be waning, with engagement decreasing by 17 percent in 2018 and by 34 percent in 2019. This is likely because chatbots were one of the first application of AI and is probably a reflection of the relative maturity of its application.

The growing engagement in unsupervised learning and reinforcement learning demonstrates that organizations are experimenting with advanced analytics tools and methods. These tools and techniques open up new use cases for businesses to experiment and benefit from, including decision support, interactive games, and real-time retail recommendation engines. We can only imagine that organizations will continue to use AI and ML to solve problems, increase productivity, accelerate processes, and deliver new products and services.

As organizations adopt analytic technologies, they’re discovering more about themselves and their worlds. Adoption of ML, in particular, prompts people at all levels of an organization to start asking questions that challenge what an organization thinks it knows about itself. With ML and AI, we’re training machines to surface new objects of knowledge that help us as we learn to ask new, different, and sometimes difficult questions about ourselves. By all indications, we seem to be having some success with this. Who knows what the future holds, but as technologies become smarter, there is no doubt that we will we become more dependent.

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A PwC study in 2017 estimated the world would gain $15.7 trillion by 2030 if artificial intelligence (AI) was adopted across nations. The study said that AI would first lead to productivity enhancement, and a major portion of gains would accrue from consumer-side effects. China, it had said, could see its GDP rising by around a fourth as it was using AI more aggressively. Although the study did not estimate how much India would gain from using AI, new research by Icrier along with Nasscom and Google shows that even a marginal increase in artificial intelligence adoption may add 2.5% to GDP in the immediate term. Moreover, it highlights that if the government spends the Rs 7,000 crore it had envisaged for the national AI programme, GDP could get boosted by as much as $86 billion. The way Icrier sees it, as AI becomes what it calls a general purpose technology—like the internet—its impact rises; essentially, then, the pace of India’s digitisation drive will determine how fast AI is adopted.

To understand how fast the adoption of AI can take place and its impact on total factor productivity, Icrier studied 1,553 firms that have some software investment. What it found was that there was a huge gap in the use of AI, suggesting a large untapped potential. AI-intensity was defined as the ratio of software investment to total sales, and the study found that, for instance, in the case of agriculture, while the average AI intensity is 0.001, the maximum intensity was 20 times as much. For electrical and optical equipment manufacturing, the difference between the average and the top in the industry was 145-times; it was 742 in the case of trade and in the case of services, the average intensity was 0.159, while the maximum intensity was 110.

The report, however, argues that businesses alone won’t be able to push AI, the government will have to play a bigger role, by setting up a nodal AI agency to push for AI-adoption and also drive business, government and academia partnerships. Another suggestion is to initiate large-scale skill development programmes to get the workforce ready for AI-adoption. What is worrying, however, is the slow pace of digital adoption so far, though the pandemic has helped speed up things a big; both the education and health sector, for instance, are likely to see faster adoption of AI techniques. A related problem is that of cybersecurity where India needs both a national strategy and a governance structure that is more well-defined.

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Supportive government framework and policies are expected to enable the Asia-Pacific (APAC) region to emerge as the global epicenter for the growth of artificial intelligence (AI), says GlobalData, a leading data and analytics company.

Several countries across the region are focusing on leveraging AI, enhancing productivity and competitiveness. Though the key objectives of different government entities may vary from each other, all of them want to leverage their strengths to emerge either as AI innovation drivers or leaders.

Sunil Kumar Verma, Lead ICT analyst at GlobalData, comments: “Despite their different priorities, countries strive to accomplish four common and prime objectives by leveraging AI – formulate policies for workforce in an automated economy, job creation across emerging sectors which leverage new technologies, build data ecosystem to be leveraged by cross-verticals to foster innovations and intelligent mitigation of impact on workers impacted by adopting AI and risk reduction.”

Most countries in APAC have had AI policies and initiatives in place for the past five years – be it Japan’s Artificial Intelligence Technology Strategy to promote the development of AI and priorities for industrialization or South Korea’s US$21bn (KRW24.2 trillion) budget to develop science and technology and AI sectors.

Similarly, China’s New Generation of Artificial Intelligence Development Plan proposes three development stages (2020, 2025 and 2030) as per the development situation of AI technologies in China. India too has defined a national policy on AI in working paper ‘National Strategy for Artificial Intelligence’, focussing on five key areas – agriculture, mobility, healthcare, transportation and urban/smart-city infrastructure. Thailand too had formulated AI ethics guidelines last year, undertaken by the Digital Economy and Society (DES) Ministry of Thailand, to cater to the country’s competitiveness and sustainable development.

Sunil continues: “Certainly, the APAC region is expected to emerge as a major market for AI-led initiatives, since most countries in the region are establishing committees or task forces for creating national AI strategies, which have either been launched or are on the course of being launched in next few years.”

Indeed, other countries too are keen on launching AI bases policies and framework. Malaysia has announced forming a National Data and Artificial Intelligence (AI) Policy by mid-2020, to position the country as a hub in South-East Asia for grooming AI talent, and support its efforts in building commercial AI ecosystem. Indonesia is expected to introduce a national strategy for supporting capabilities development in technologies related to AI. Similarly, the Philippines too is formulating an AI road map to improve its productivity and economic growth.

Sunil concludes: “Application scenarios across various verticals continue to move from divided to a unified and customized methodology. The need for digital governance and collaborative approach with the technology companies would further facilitate in the scaling up of enterprises and government priorities in the AI industry chain.”

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