Daily Archives: August 14, 2021

For many years, tech experts have focused on the trend of enterprises making the initial move to the cloud. But Flexeras 2021 State of the Cloud Report tells a slightly different story, with 92% of enterprises already operating on a multicloud strategy and 82% operating on a hybrid cloud strategy.

So if most users already work on some kind of cloud, how is their cloud experience transforming right now?

See below our top trends in cloud computing, which range from diversifying cloud infrastructure to considering how cloud use impacts the greater global environment:

Also read: Big Data Trends in 2021 and The Future of Big Data

Most major enterprises migrated data and operations to the cloud over the past several years, but during the height of the COVID-19 pandemic, companies learned the importance of a distributed, flexible infrastructure.

Enterprise leaders are quickly recognizing that not all clouds work for all of their needs, and some of their legacy systems and applications work better on their existing on-premises infrastructure. These realizations, and a growing need for both flexibility and reliable security, have ushered in a period of growth for hybrid and multicloud setups.

Kaushik Joshi, global managing director for strategic alliances at Equinix, a digital infrastructure and integration company, explained why hybrid and multicloud setups are taking off:

The past year has seen a significant shift from private and public cloud-only deployments to hybrid and multicloud strategies, Joshi said.

He went on to share Equinixs recent Global Tech Trends Survey which polled more than 2,600 global IT decision-makers globally and highlighted that hybrid cloud is now the most common choice, with 46% of respondents now using a hybrid cloud (a 12% increase since their previous survey).

Hybrid cloud architectures represent the best path to engage with a rapidly changing infrastructure landscape, because it enables enterprises to more easily manage legacy, data-intensive processes, while simultaneously embracing new born-in-the-cloud applications.

As more organizations recognize the different strengths of private clouds, public clouds, industry-specific clouds, and legacy on-premises setups, more cloud and data center vendors are working hard to create hybrid cloud and multicloud connections among the disparate systems.

More on hybrid cloud: Hybrid Cloud and Hyperconverged Infrastructure (HCI)

Security is a hot-button topic in the cloud computing world, with some users believing that cloud computing is more secure, while others believe it is less secure than their on-premises security infrastructure.

The truth that many of them are discovering is that managed vendor clouds and on-premises solutions alike need additional security support to combat a growing number of major data breaches and ransomware attacks.

Instead of relying on embedded, native security features, tech experts are advocating for the increased use of managed security service providers (MSSPs) and a better organizational policy for user access management. Organizations are recognizing that security incidents can come from both internal accidents and external actors, so its important that all users are trained and compliant with an organizations security policies.

Amit Bareket, CEO and co-founder of Perimeter81, a cybersecurity firm, believes that zero-trust security is the answer to growing cloud security concerns:

Organizations are coming to realize they should not automatically trust anything inside or outside their perimeter, Bareket said. That perimeter is more or less erased. So, now, we are seeing companies verifying everything trying to connect to their IT systems.

With zero-rust security, policy enforcement and protection are easily implemented by isolating applications and segmenting network access based on user permissions, authentication, and verification. By implementing the ZTNA model for secure network access, IT teams can have full control over who is granted access, enters, and leaves the network at all times. This model has gained much more recognition since being mandated in President Bidens executive order.

A large number of enterprise cloud users are moving toward Kubernetes, containerization, and other custom cloud efforts for cloud-native application development.

Simply having a cloud or several clouds is not enough. Dividing those clouds up into containers makes it possible for companies to develop microservices and applications that require different storage, security, and configuration features.

Anthony Cusimano, solutions evangelist at Veritas Technologies, an enterprise backup and recovery software company, explained that many users are leaning into containerization for the cost and efficiency benefits as well:

The entire world is starting to shift its attention to Kubernetes and the orchestration of containers, Cusimano said. Its the next iterative shift we went from physical to virtual to cloud, and now were going to microservices and containers.

They make the hybrid cloud more cost effective and improve performance across the board. Thats why youre starting to see some of the biggest cloud providers offering turnkey Kubernetes solutions.

Most of the top cloud vendors in the market offer separate advanced analytics and artificial intelligence (AI) capabilities, but a growing number of them are offering these features as cloud-native technology.

Tapan Patel, senior manager of AI and cloud at SAS, a major analytics software company, explained what expanding containerization and cloud-native features will mean for enterprises:

Cloud-native technologies will usher in a new era of distributed enterprise analytics software designed to run wherever containers and a Kubernetes platform is available, Patel said. Cloud-native technologies will also lead and help companies to build, migrate, and modernize customer-facing and analytics and artificial intelligence (AI) apps more easily and at scale.

Patel also explained that customers will be able to test out new analytics and AI operations when they adopt clouds with cloud-native features.

Customers can get a taste of new and emerging analytics and artificial intelligence (AI) capabilities delivered in the cloud to attract new use cases and new users, Patel said. Analytics in the cloud can be used as an ideation sandbox, which allows a lot of new users to build prototypes. Each phase of machine learning projects (build, train, deploy) requires a different infrastructure and deployment considerations. Because the cloud is elastic, it provides the right level of scalability and availability.

Sustainability and climate care efforts are growing across industries, including technology and the cloud market. The technology industry is known for consuming a large amount of energy, and although cloud is typically more energy efficient than on-premises infrastructure, the growth of AI and the Internet of Things (IoT) is causing cloud technology to work harder than ever.

Ali Fenn, president of ITRenew, an asset recycler and data efficiency expert, explained that the circular cloud, a circular economic model of cloud asset recycling, is the next answer to sustainability concerns:

Sustainability is a massive trend in IT from enterprises seeking to ensure cloud providers leverage renewable energy in data centers to enterprises increasingly seeking to minimize their own supply carbon footprint via sustainably sourced, circular IT solutions, Fenn said.

Not only is this circular model good for sustainability goals, but it also makes a lasting impact on the bottom line. IT and business leaders are starting to realize they dont need to allocate additional money, time, and resources or compromise performance to have a more sustainable cloud computing model.

Coupled with an unstable supply chain, the circular cloud saves more than just the cost of supplies with its closed-loop supply chain that eliminates delays and constraints associated with inventory and shipment (a pain point for providers since pre-pandemic times).

Although few cloud vendors have adopted the circular model, most are changing their business models to emphasize more renewable energy use, carbon offsets, and data center efficiency boosts.

Read next: Data Analytics Market Trends 2021

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Cloud Computing Trends & Future Technology 2021 - Datamation

4 Hot Cloud Computing Stocks For Your Watchlist Now

Like it or not, the cloud computing industry continues to grow by the day. Accordingly, with the current shift towards digital workspaces, cloud computing stocks are also gaining traction in the stock market now. If anything, the demand, and possible use cases for cloud computing are rapidly increasing in our world today. Before we dive into the details, what exactly is this upcoming tech field might you ask? Well, in essence, cloud computing is a suite of computing services that can be delivered over the Internet or the cloud. This can range from data storage, networking, analytics, and database services among other computing functions.

Notably, cloud computing serves a wide variety of purposes across numerous industries. We only need to take a look at the largest name in the industry today Amazon (NASDAQ: AMZN) to see this. Just this week, the companys Amazon Web Services (AWS) division announced two major plays on the operational front. Firstly, General Electrics (NYSE: GE) Healthcare section is now moving several of its software platforms onto the AWS cloud. Secondly, news broke the day after that AWS also won a $10 billion cloud contract from the U.S. Defense Department.

Meanwhile, other names in the industry also continue to thrive amidst the current uptick in enterprise software spending. Last week, Datadog (NASDAQ: DDOG) smashed consensus estimates in its second-quarter fiscal. The company reported a total revenue of $233.5 million, marking a whopping 67% year-over-year increase. With all this activity in the cloud computing business now, I can understand if investors are keen to jump on. Should you be one of them, here are four to consider in the stock market today.

Best Cloud Computing Stocks To Buy [Or Sell] This Month

Microsoft Corporation

First off, we have Microsoft Corporation, a multinational tech company whose products and services are used by billions all over the world. Namely, its computer software and consumer services are immensely popular. For instance, its Microsoft Windows operating system is used by over 1.5 billion users worldwide. MSFT stock currently trades at $291.46 as of 11:22 a.m. ET and is up by over 35% in the past year. In late July, the company announced very strong fourth-quarter results.

To begin with, its revenue for the quarter was $46.2 billion, an increase of 21% year-over-year. The company also reported an operating income of $19.1 billion, up by 42% from a year earlier. Net income was $16.5 billion for the quarter, increasing by 49% year-over-year.

In fact, the company notes that its revenue this quarter is driven by cloud services. Impressively, revenue from its Intelligent Cloud segment was $17.4 billion, increasing by 30% year-over-year. Given the impressive financials, will you consider buying MSFT stock?

Alibaba Group Holding Ltd

Alibaba is a company that specializes in cloud computing and e-commerce. Its Alibaba Cloud, also known as Aliyun, provides cloud computing services to online businesses and also the companys own e-commerce ecosystem. Also, the company has a digital media and entertainment business. BABA stock currently trades at $187.92 as of 11:22 a.m. ET. On August 3, 2021, the company reported a stellar quarter. Firstly, it delivered a revenue of $31.86 billion for the quarter, an increase of 34% year-over-year. Secondly, annual active consumers of the Alibaba Ecosystem across the world reached approximately 1.18 billion users.

This includes 912 million consumers in China and 265 million consumers overseas served by Lazada, AliExpress, Trendyol, and Daraz. The company also reported a net income of $6.63 billion and diluted earnings per share was $0.32. Alibaba says that it has multiple engines driving its long-term growth, expanding upon its consumer and industrial internet segments.

Daniel Zhang, Chairman and Chief Executive Officer of Alibaba Group had this to say, We believe in the growth of the Chinese economy and long-term value creation of Alibaba, and we will continue to strengthen our technology advantage in improving the consumer experience and helping our enterprise customers to accomplish successful digital transformations. All things considered, will you add BABA stock to your watchlist?

Salesforce is a cloud-based company with headquarters in San Francisco, California. The company is the worlds No. 1 customer relationship management (CRM) platform. Also, its cloud-based CRM applications are used for sales, service, marketing, and do not require IT, experts, to set up or manage. The company boasts more than 150,000 companies that use its platform to grow their businesses by strengthening customer relationships. CRM stock currently trades at $250.66 as of 11:23 a.m. ET.

On Tuesday, the company announced Salesforce+, a new streaming service for live experiences and original content series. The new service will include live experiences, original series, podcasts, and other programming. In detail, Salesforce+ will bring the magic of Dreamforce to viewers across the globe with speakers, success stories, and groundbreaking innovations.

Furthermore, with engaging stories and expert advice, Salesforce+ will illuminate the future of technology in the digital-first, work anywhere world. For these reasons, will you consider CRM stock a top cloud computing stock to watch?

Snowflake Inc.

Next up, we will be taking a look at Snowflake. In brief, it identifies itself as a cloud computing-based data warehousing company. Through Snowflakes Data Cloud, organizations across the globe can make the most of their digital assets. According to Snowflake, it helps customers unite siloed data, discover and securely share data, and execute diverse analytic workloads. Among its thousands of clients spanning various industries, Snowflake now serves 187 of the Fortune 500 companies.

As it stands, SNOW stock currently trades at $290.08 a share as of 11:23 a.m. ET. Could the company have more room to grow moving forward? Well, for one thing, Snowflake continues to make strategic partnerships in the tech world. Just last month, the company announced support for The Trade Desks (NASDAQ: TTD) Unified ID 2.0. (UID 2.0).

Namely, this would be a strategic play by Snowflake as more companies shift from conventional third-party ad trackers to TTDs ad tool. With UID 2.0 on the Snowflake Data Marketplace, customers can now optimize their conventional ad businesses to be more privacy-conscious. Overall, Snowflake appears to be catering to the shifting needs of its users. Could all this make SNOW stock a top pick in the stock market for you?

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4 Top Cloud Computing Stocks To Watch Today | National | fwbusiness.com - FW Business

Cloud-computing giants and phone companies have decided they need each other to drive the market for 5G business services.

Amazon Web Services, Google Cloud and Microsoft Corp. have all signed partnerships with telcos in recent months as they seek new opportunities amid slowing growth in demand for data storage. Telcos, including AT&T Inc. and Verizon Communications Inc., are also looking to revive flagging revenue while tapping into cloud computing's ability to make super-fast 5G networks more efficient and cheaper to run.

"The cloud companies need to reinvent themselves," said Omdia analyst Vlad Galabov. "Communications service providers have the same thing everyone has a mobile phone, a network so both have saturation."

The parties are working together to bring computing functions such as data processing onto the 5G network, closer to where data is generated. This system, known as multi-access edge computing, or MEC, enables partners to offer enterprise services such as real-time analytics, manufacturing automation and live product tracking.

Verizon and Amazon Web Services the cloud arm of Amazon.com Inc. are offering this feature to individual businesses after expanding their partnership to include Private MEC in April.

Verizon also has a separate tie-up with International Business Machines Corp. to jointly develop MEC services.

"Demand for the technology is global, which gives both companies a lot of potential for new opportunities and markets," IBM Vice President Marisa Viveros told S&P Global Market Intelligence. IBM boosted its second-quarter cloud revenue 13% to $7 billion this year.

Google Cloud has signed deals with the likes of AT&T, Telefnica SA and Telecom Italia SpA. The Alphabet Inc. unit wants to help telcos monetize 5G as a "business services platform," Google Cloud CEO Thomas Kurian said in 2020.

Microsoft and AT&T took their partnership to a new level in June, with the software company agreeing to buy 5G technology and engineering staff from the telco. Microsoft will now manage AT&T's 5G network traffic, and the telco will continue to operate the infrastructure.

"In the future, cloud providers could take on more network-based workload opportunities, and thus potentially more operational roles," an AT&T spokesperson told S&P Global Market Intelligence.

Such a trend could ultimately raise the question of who actually operates 5G infrastructure telcos or cloud companies said Kevin Restivo, research manager of European Enterprise Mobility at IDC. "We're just seeing the groundwork being laid for the next decade of how telcos are run and who wins and who loses out of that."

It may also make it harder for telcos to differentiate themselves if they are all relying on the same cloud-computing providers, Omdia's Galabov said.

Verizon is not contemplating farming out its network operations, as the telco "sees incredible value in owning its own network," a company spokesperson said. Telefonica and Telecom Italia did not respond to requests for comment.

For now, telcos are focused on drawing on cloud-computing providers' strengths to help hasten the rollout of enterprise 5G offerings.

Cloud-computing giants "can help the telcos monetize investment by adding value and offering a channel to the customers," said Brian Partridge, an analyst at 451 Research, a research division of S&P Global Market Intelligence. They are "framing what they do well and overlapping that with what the operators do well."

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Cloud providers team with telcos as 5G offers new growth - S&P Global

DUBLIN--(BUSINESS WIRE)--The "AI Chipsets for Wireless Networks and Devices, Cloud and Next Generation Computing, IoT, and Big Data Analytics 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.

This report evaluates leading market players across the AI chipsets ecosystem, technology strategies, and solution plans. This includes leveraging AI chipsets for support of various emerging and disintermediating technology areas such as edge computing, 5G, and blockchain systems. Additional areas addressed include AI support of emerging computing technologies including edge platforms and servers.

This report also assesses applications and service support scenarios for AI chipsets across almost all major industry verticals. The report provides forecasts for AI chipset hardware, embedded software, professional service, deployment platforms, and applications for every major industry vertical as well as regional and country forecasts for 2021 to 2026. The report also provides exclusive recommendations for stakeholders within the AI chipsets ecosystem.

Select Report Findings:

Companies Mentioned

The AI chipset marketplace is poised to transform the entire embedded system ecosystem with a multitude of AI capabilities such as deep machine learning, image detection, and many others. With 86% of all chipsets globally shipping AI-equipped, over 59% of all electronics will have some form of embedded intelligence by 2026. This will also be transformational for existing critical business functions such as identity management, authentication, and cybersecurity.

Multi-processor AI chipsets learn from the environment, users, and machines to uncover hidden patterns among data, predict actionable insights and perform actions based on specific situations. AI chipsets will become an integral part of both AI software/systems as well as critical support of any data-intensive operation as they drastically improve processing for various functions as well as enhance overall computing performance. This will be a boon for many aspects of ICT ranging from decision support and data analytics to product safety and system optimization.

Consumers will realize benefits indirectly through improved product and service performance such as device and cloud-based gaming. Enterprise and industrial users will benefit through general improvements in automated decision-making, especially in the areas of robotic process automation, decision support systems, and overall data management. AI chipsets will be particularly useful for business edge equipment for real-time data analytics and store versus processing decisions.

Key Topics Covered:

1.0 Executive Summary

2.0 Research Overview

3.0 AI Chipsets Introduction

3.1 AI Chipsets

3.1.1 Chipset Components

3.1.2 General Purpose Applications

3.2 AI Systems

3.3 Market Dynamics Analysis

3.4 AI Investments

3.5 Competitive Market

4.0 Technologies, Solutions, and Markets

4.1 Chipsets Technology and Products

4.2 AI Technology

4.2.1 Machine Learning

4.2.2 Machine Learning APIs

4.2.3 Deep Machine Learning

4.2.4 Natural Language Processing

4.2.5 Computer Vision

4.2.6 Voice Recognition

4.2.7 Context Awareness Computing

4.2.8 Neural Networks

4.2.9 Facial Recognition

4.3 Deployment Platform

4.4 IoT Sector

4.5 Applications in Industry Verticals

4.6 Regional Markets

4.7 Value Chain

4.8 5G Network and Edge Computing

4.9 Cloud Computing and Data Analytics

4.10 Industry 4.0 and Factory Automation

4.11 Autonomous Networks

4.12 Blockchain Networks

4.13 Quantum Computing

4.14 Machine Intelligence

4.15 Nanoscale Technology

4.16 Mobile Network Operators

5.0 Company Analysis

6.0 AI Chipsets Market Analysis and Forecasts 2021 - 2026

6.1 Global AI Chipsets Market 2021 - 2026

6.2 Regional AI Chipsets Market 2021 - 2026

6.3 AI Chipsets Deployment Forecast 2021 - 2026

7.0 Conclusions and Recommendations

For more information about this report visit https://www.researchandmarkets.com/r/c4pcmr

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Global AI Chipsets for Wireless Networks and Devices, Cloud and Next Generation Computing, IoT, and Big Data Analytics to 2026 -...

The global cognitive cloud computing market is expected to gain significant momentum in the forecast period 2020-2027. The natural language processing technology sub-segment is set to gain the highest market share. The large enterprises sub-segment is predicted to dominate the market. The North American region is expected to further add to the market growth.

New York, USA, Aug. 09, 2021 (GLOBE NEWSWIRE) -- As per a recently published report by Research Dive, the global cognitive cloud computing market is anticipated to garner a revenue of $1,08,788.7 million by 2027 rising from $11,530.0 million at a stable CAGR of 31.3% from 2020-2027.

Download FREE Sample Report of the Global Cognitive Cloud Computing Market: https://www.researchdive.com/download-sample/2800

Impact of COVID-19 on the Global Cognitive Cloud Computing Market

The rapid spread of the coronavirus over the past couple of years has been disadvantageous for a lot of organizations. Due to the implementation of lockdowns and the travel ban, multiple businesses had to shut down. On the contrary, the cognitive cloud computing market witnessed a surge in owing to its extensive use within the healthcare sector. Most pharmaceutical companies and clinicians utilized natural language processing (NLP) to manage patient related data by detecting symptoms of the virus in real time. This has also resulted in faster and more effective healthcare for the patient which has in turn led to an increase in demand for cloud computing technology in the healthcare sector.

Check out How COVID-19 impacts the Global Cognitive Cloud Computing Market: https://www.researchdive.com/connect-to-analyst/2800

Market Analysis

Growth: Cognitive cloud computing technology is known to process information from different sources which includes pattern recognition, data mining and more to provide the best methods a business can follow for better operations. It also uses artificial intelligence which assists humans in ensuring the best possible solutions to high priority situations. Due to this, cognitive cloud computing is being used in multiple industries such as retail, BFSI and healthcare to name a few and has helped enhanced their business opportunities. These factors have contributed to the rapid growth of the market in the analysis period.

Story continues

Check out all Information and communication technology & media Industry Reports: https://www.researchdive.com/information-and-communication-technology-and-media

Restraints: Due to the higher cost of the cognitive computing platforms, several small and medium businesses are unable to invest in it which could restrict the growth of the market. Additionally, there are several experts in the market who have been experiencing challenges with the software platforms and the process of development. These factors are expected to hamper the growth of the market in the forecast period.

Opportunities: With constant upgrades in technology there has also been a rise in the number of advanced tools and other interactive platforms within the cognitive cloud computing model. One such innovation was that of chatbots which used AI and ML to communicate with humans while also imitating a human conversation to provide quicker solutions to queries. Recently, chatbots which utilized cognitive cloud computing were also used by healthcare organizations to monitor patients among the rising COVID-19 cases. Thus, the above mentioned factors are set to provide an opportunity of growth for the market.

Segmental Analysis

The market is segregated into multiple segments based on technology, enterprise size, industry vertical, and region.

Access Varied Market Reports Bearing Extensive Analysis of the Market Situation, Updated With The Impact of COVID-19: https://www.researchdive.com/covid-19-insights

Natural Language Processing Technology Sub-Segment to Dominate the Market

By technology, the natural language processing technology sub-segment has held a significant position in the part in the market since 2019 and is predicted to grow further in the forecast period. NLP is an innovative form of technology that has when used in combination with cognitive computing technologies has helped machine to human communication and vice versa easier. The machines are capable of identifying data in multiple data in multiple languages with ease and at a consistent pace. These factors are set to add to the growth of the market in the forecast period.

Large Enterprises Sub-Segment Expected to Gain Highest Market Share

By enterprise size, the large enterprise sub-segment is predicted to hold the highest market share with a rise in revenue from $8,069.0 million in 2019 to over $73,711.1 million by 2027. This growth is credited to large companies opting for cognitive computing technology to assist the employees in the process of decision making.

Healthcare Sub-Segment to Garner Highest Revenue

By industry vertical, the healthcare sub-segment is predicted to gain the highest revenue as it has maintained its presence in the market since 2019 and is expected to rise further in the estimated timeframe. The healthcare sector is one of the primary users of cognitive computing technology due to which medical experts are able to provide better diagnosis and treatment options for several illnesses to patients.

Regional Analysis

The North America region garnered a revenue of $3,849.9 million in 2019 and is anticipated to grow at a rapid pace in the forecast period. The U.S and Canada are the largest investors for the growth of advanced technologies due to which they are known to be hubs for new innovations. Also, the efforts by the countries to ensure the adoption of these newly developed technologies which have contributed to the growth of the businesses. These factors are predicted to assist in the rapid growth of the market in the region.

Key Market Players

The report also contains an extensive list of key players whose strategies have assisted in the growth of the market. These include mergers, product launches, partnerships, and collaborations. Some of them are as listed below

1. Nuance Communications, Inc2. Numenta3. Microsoft4. CognitiveScale5. Expert.AI6. SparkCognition7. Cisco8. SAP9. Hewlett Packard Enterprise Development LP10. IBM

The report also provides an overview of many important aspects including financial performance of the key players, SWOT analysis, product portfolio, and latest strategic developments. Click Here to Get Absolute Top Companies Development Strategies Summary Report.

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Global Cognitive Cloud Computing Market Predicted to Garner $1,08,788.7 Million at a CAGR of 31.3% from 2020-2027 Exclusive [240 pages] Business...

Cloud computing is arguably one of the biggest disruptors to have happened over the last 15 years.

The revolution has impacted many facets of our daily lives. Think Netflix, Spotify or Zoom which enable us to watch movies, listen to music, or have meetings on any device (laptops, tablets, smartphones), anywhere.

At the enterprise level, the cloud technology has saved billions of dollars globally by allowing companies to pay on the go, and enabling them to scale up or down their storage and computing requirements on a need-to basis.

Advisory company Gartner predicts that worldwide spending on public cloud serviceswill reach US$400 billion ($540 billion) in 2022, from US$270 billion in 2020.

Broadly speaking, cloud computing refers to the on-demand availability of computer resources specifically data storage and computing power without any direct active management by the user.

Rather than having to operate their own costly computing infrastructure or data centres, companies can rent access to a cloud server (called the public cloud servers), to store data and run all their applications.This removes the need for large capital spend on an in-house infrastructure.

As technology develops, the cloud industry has branched out into several different services, but the bulk of revenues are coming from two main sources : infrastructure-as-a-service (IaaS) and software-as-a-service (SaaS).

The IaaS service, which provides data storage and computing resources described above,is dominated by the big tech global firms.

Amazon pioneered the industry when it introduced the Amazon Web Services (AWS) back in 2006, and still dominate market share today. Then came the Google Cloud Platform, Microsoft Azure, IBM SmartCloud, Oracle Cloud, and Alibaba Cloud in the years following.

Collectively, these six giants make up 80% of the global IaaS market, according to a Telsyte report.

The SaaS market meanwhile, provides software solutions or applications that are built and run on top of the cloud infrastructure.

The SaaS market is dominated by five giant players globally Microsoft, Salesforce, Adobe, SAP, and Oracle.

In light of such overwhelming competition, how do Australian cloud computing companies on the ASX stack up?

Generally speaking, domestic players in Australia are not building new cloud servers to compete with the global giants, but are instead providing the services to connect to the exisiting infrastructure.

Brisbane-based Megaport (ASX:MP1) is probably the most well known player on the ASX in the IaaS space.

Megaport does not own data centres per se, but rather partners with them and provides fast access to the major public cloud servers AWS, Microsoft Azure, Google Cloud Platform etc.

The companys Software Defined Networking (SDN) technology provides the on-demand point of entry and connects to 740+ enabled servers across the Asia Pacific, North America, Europe, and the Middle East.

Nexion (ASX:NNG) is another IaaS company that provides clients access to the public cloud networks, but it does this with a certain twist.

The company has partnered with IBM Global Technology Services to provide a hybrid cloud service, which basicallyallows customers to access the public cloud, but also bring their own physical resources.

This is because a lot of companieswant to store data in the cloud, but often they have legacy infrastructure to run their core delivery systems thats not compatible with a public cloud. Thehybrid cloud solution effectively solves this problem.

Sovereign Cloud (ASX:SOV), which operates under the AuCloud brand, is an IaaS provider exclusively focused on the defence and critical industries.

Due to the sensitive nature of its clients, the company does not provide an access point to the public cloud, but rather operates its own data centres in Canberra and Sydney designed to meet ASIO standards.

Sovereign made its ASX debut in December after raising $20m at 75c per share.

Other IaaS companies on the ASX include NextDC (ASX:NXT), DXN (ASX:DXN), and DC Two (ASX:DC2).

For a more global and diversified exposure to the cloud computing sector, investors could also buy into ASX-listed BetaShares Cloud Computing ETF (ASX:CLDD).

CLDD tracks exposure to leading companies in the global cloud computing industry (both IaaS and SaaS), which includes international tech names such as Zoom, Shopify, Salesforce, and Dropbox.

SaaS is the value-added side of the cloud computing sector.SaaS is basically a software distribution model that allows data/platform to be accessed from any device with an internet connection and a web browser.

The SaaS model offers lower upfront costs than traditional software download and installation, making them more available to a wider range of smaller businesses.

Arguably the most well known SaaS company on the ASX is Xero (ASX:XRO).

The Kiwi company provides enterprise accounting software, and uses a single unified ledger that allows users to work in the same set of books regardless of location or operating system. The Xero software can also be accessed through mobile apps.

Wisetech (ASX:WTC) provides cloud-based SaaS solutions to the logistics industry globally.

Its flagship platform, CargoWise, enables the worlds supply chains executing over 60 billion data transactions annually. The company has grown from a $1bn into a $10bn market cap since listing in 2016.

In the smaller end of the market, cloud-based SaaS companies like Whispir (ASX:WSP) provide communications workflow platform to its clients globally. This includes SMS, email, voice messaging, forms, and videos.

Technology One (ASX:TNE)meanwhile, is an SaaS ERP (enterprise resource planning) solutions company, allowing clients to integrate with third party providers such as Salesforce.

As we transition into a world of artificial intelligence, smart IoT devices, and autonomous vehicles, storage and processing of big data will be of paramount importance.

These data will have to be stored and processed in the cloud, and this is where 5G becomes a game-changer for the cloud computing industry.

5G will revolutionise the cloud by providing ultra fast transmission rates and reduced latency by as much as 100x compared to 4G.

Industries that will benefit massively from 5G include healthcare, automotive, smart cities, as well as end users like us.

In this space, telco carriers like Telstra (ASX:TLS) and 5G Networks (ASX:5GN) will come into play.

5GN provides internet broadband and cloud infrastructure services to mid-market corporate industries.

Other 5G plays on the ASX include Aussie Broadband (ASX:ABB), which is currently building a 150km of fibre cables underground that will connect to eight data centres across the country.

At Stockhead we tell it like it is. While Nexion is a Stockhead advertiser, it did not sponsor this article.

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Cloud computing will be a $540 billion market in 2022. Heres how ASX cloud stocks stack up - Stockhead

Malaysians might be relatively more adept at digital skills such as cloud computing and data analysis, but overall, there is still a significant skills gap across data science, business and technology. According to Coursera's latest Global Skills Report which ranked 108 countries, Malaysian learners showcased high skill proficiency for cloud computing and data analysis at 91% and 79% respectively, indicating a growing pocket of highly-skilled technical professionals in the country. When it comes to marketing, however, the report found Malaysians to be competitive (64%) instead of cutting-edge like their Singaporean counterparts (92%).

Malaysia secured mid-rankings globally in each domain - #52 in business, #48 in technology and #51 in data science. With 56% proficiency in technology, Malaysia lags behind neighbours such as Singapore (96%), Vietnam (88%) and Indonesia (78%). Similarly, the data science domain recorded 52% proficiency, placing Malaysia only slightly ahead of Indonesia (46%), Thailand (46%) and the Philippines (44%).

While proficiency in machine learning is at 50%, Malaysia has more learners opting for online learning to arm themselves with the skills of the future. The top trending skills among Malaysian learners included Python programming, machine learning, the Internet of Things, and data management. Meanwhile, key skills for data science including software engineering, mathematics and programming scored less than 50% in the report's benchmark, despite the nationwide push to encourage a new generation of STEM talents, the report found.

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Nonetheless, Malaysia is considered competitive with a 57% proficiency overall, ranking 46th globally and fourth in Southeast Asia. While it is ahead of the Philippines (#69) and Thailand (#76), it lags behind Singapore (#10), Vietnam (#20) and Indonesia (#45).

Coursera's MD - India and Asia Pacific, Raghav Gupta, said the pace of skills transformation is slower than the pace of digital transformation in Malaysia, as is the case in several countries worldwide. "Learners must invest in both soft and technical skills to prepare for jobs of the future," he said.

Meanwhile, Gupta also noted that the skills needed for high-demand entry-level roles can be developed "in a matter of months, not years". The report found that recent graduates and mid-career changes can develop entry-level, digital job skills in as little as 35 to 70 hours, or one to two months with 10 learning hours per week. On the other hand, an individual without a degree or technological experience can be job-ready in 80 to 240 hours, or two to six months with 10 learning hours per week. The most transferrable skills across all future jobs, according to Coursera, are human skills such as problem solving and communication, computer literacy and career management.

There are currently 347k Coursera learners in Malaysia and 44% of them are female. Machine learning was the top most popular course among learners in the country, with First Step Korean and The Science of Well-being being the top two topics. Meanwhile, trending skills among Malaysian learners include marketing, digital marketing, C programming, design and product, and data management, among others.

According to Coursera, the report focuses on business, technology and data science as they are the most popular domains on Coursera in terms of enrollments, and they encapsulate the skills most crucial to the future of work.The competencies within each domain capture the broad capabilities required to achieve expertise in these areas, and individual skills capture specific requirements to achieve mastery within each competency.

Functionally, the report's competencies and skills come from Courseras Skills Graph, which is a set of skills assembled through both open-source taxonomies such as Wikipedia, as well as crowdsourcing from Coursera educators and learners on what they teach/learn on the Coursera platform. The 108 countries within the report are ranked against each other. A country or industry that is at 100% ranks at the top of the 108 countries and a country at 0% is at the bottom.

For each groups percentile rankings, Coursera also broke them apart into four categories based on quartiles: cutting edge (76th percentile or above), competitive (51st to 75th percentile), emerging (26th to 50th percentile), and lagging (25th percentile and below).

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Photo courtesy: 123RF

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Study: What are the areas marketing proficiency lag behind in Malaysia? - Marketing Interactive

High Performance Computing (HPC) is known as a domain where applications are well-optimized to get the highest performance possible on a platform. Unsurprisingly, a common question when moving a workload to AWS is what performance difference there may be from an existing on-premises bare metal platform. This blog will show the performance differential between bare metal instances and instances that use the AWS Nitro hypervisor is negligible for the evaluated HPC workloads.

TheAWS Nitro systemis a combination of purpose-built hardware and software designed to provide performance and security. Recent generation instances, including instance families popular with HPC workloads such as c5, c5n, m5zn, c6gn, andmany othersare based on the Nitro System. As shown in Figure 1, the AWS Nitro System is composed of three main components: Nitro cards, the Nitro security chip, and the Nitro hypervisor. Nitro cards provide controllers for the VPC data plane (network access), Amazon Elastic Block Store (Amazon EBS) access, instance storage (local NVMe), as well as overall coordination for the host. By offloading these capabilities to the Nitro cards, this removes the need to use host processor resources to implement these functions, as well as offering security benefits. The Nitro security chip provides a hardware root of trust and secure boot, among other features to help with system security.The Nitro hypervisor is lightweight hypervisor that manages memory and CPU allocation.

With this design, the host system no longer has direct access to AWS resources. Only the hardened Nitro cards can access other resources, and each of those cards provides software-defined hardware devices that are the only access points from the host device. With the I/O accesses handled by Nitro cards, this allows the last component, the Nitro hypervisor, to be light-weight and have a minimal impact to workloads running on the host. The Nitro hypervisor has only necessary functions, with a design goal of being quiescent, which means it should never activate unless it is doing work for an instance that requested it. This also means there are no background tasks running consuming any resources when it is not needed.

Figure 1. The AWS Nitro System building blocks.

The Nitro system architecture also allows AWS to offer instances that offer direct access to the bare metal of the host. Since their initial introduction in2017,many instance families offer *.metal variants, which provide direct access to the underlying hardware and no hypervisor. As in the case where the Nitro hypervisor is used, the Nitro cards are still the only access points to resources outside of the host. These instances are most commonly used for workloads that cannot run in a virtualized environment due to licensing requirements, or those that need specific hardware features only provided through direct access.

With both the option of bare metal instances and Nitro virtualized instances, this provides a method to show the performance differential between HPC application performance on bare metal vs running on the AWS Nitro hypervisor.

You can read the full blog to see how different HPC applications perform on Amazon EC2 instances with AWS Nitro hypervisor vs. bare metal instances.

Reminder: You can learn a lot from AWS HPC engineers by subscribing to the HPC Tech Short YouTube channel, and following the AWS HPC Blog channel.

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Bare Metal Performance in the Cloud - HPCwire

Samsung is using artificial intelligence to automate the insanely complex and subtle process of designing cutting-edge computer chips.

The South Korean giant is one of the first chipmakers to use AI to create its chips. Samsung is using AI features in new software from Synopsys, a leading chip design software firm used by many companies. What you're seeing here is the first of a real commercial processor design with AI, says Aart de Geus, the chairman and co-CEO of Synopsys.

Others, including Google and Nvidia, have talked about designing chips with AI. But Synopsys tool, called DSO.ai, may prove the most far-reaching because Synopsys works with dozens of companies. The tool has the potential to accelerate semiconductor development and unlock novel chip designs, according to industry watchers.

Synopsys has another valuable asset for crafting AI-designed chips: years of cutting-edge semiconductor designs that can be used to train an AI algorithm.

A spokesperson for Samsung confirms that the company is using Synopsys AI software to design its Exynos chips, which are used in smartphones, including its own branded handsets, as well as other gadgets. Samsung unveiled its newest smartphone, a foldable device called the Galaxy Z Fold3, earlier this week. The company did not confirm whether the AI-designed chips have gone into production yet, or what products they may appear in.

Across the industry, AI appears to be changing the way chips are made.

A Google research paper published in June described using AI to arrange the components on the Tensor chips that it uses to train and run AI programs in its data centers. Googles next smartphone, the Pixel 6, will feature a custom chip manufactured by Samsung. A Google spokesperson declined to say whether AI helped design the smartphone chip.

AI lends itself to these problems that have gotten massively complex.

Mike Demler, senior analyst, Linley Group

Chipmakers including Nvidia and IBM are also dabbling in AI-driven chip design. Other makers of chip-design software, including Cadence, a competitor to Synopsys, are also developing AI tools to aid with mapping out the blueprints for a new chip.

Mike Demler, a senior analyst at the Linley Group who tracks chip design software, says artificial intelligence is well suited to arranging billions of transistors across a chip. It lends itself to these problems that have gotten massively complex, he says. It will just become a standard part of the computational tool kit.

Using AI tends to be expensive, Demler says, because it requires a lot of cloud computing power to train a powerful algorithm. But he expects it to become more accessible as the cost of computing drops and models become more efficient. He adds that many tasks involved in chip design cannot be automated, so expert designers are still needed.

Modern microprocessors are incredibly complex, featuring multiple components that need to be combined effectively. Sketching out a new chip design normally requires weeks of painstaking effort as well as decades of experience. The best chip designers employ an instinctive understanding of how different decisions will affect each step of the design process. That understanding cannot easily be written into computer code, but some of the same skill can be captured using machine learning.

The AI approach used by Synopsys, as well as by Google, Nvidia, and IBM, uses a machine-learning technique called reinforcement learning to work out the design of a chip. Reinforcement learning involves training an algorithm to perform a task through reward or punishment, and it has proven an effective way of capturing subtle and hard-to-codify human judgment.

The method can automatically draw up the basics of a design, including the placement of components and how to wire them together, by trying different designs in simulation and learning which ones produce the best results. This can speed the process of designing a chip and allow an engineer to experiment with novel designs more efficiently. In a June blog post, Synopsys said one North American manufacturer of integrated circuits had improved the performance of a chip by 15 percent using the software.

Most famously, reinforcement learning was used by DeepMind, a Google subsidiary, in 2016 to develop AlphaGo, a program capable of mastering the board game Go well enough to defeat a world-class Go player.

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Samsung Has Its Own AI-Designed Chip. Soon, Others Will Too - WIRED