IBM today announced a new strategy for the implementation of several “error mitigation” techniques designed to bring about the era of fault-tolerant quantum computers.
Up front: Anyone still clinging to the notion that quantum circuits are too noisy for useful computing is about to be disillusioned.
A decade ago, the idea of a working quantum computing system seemed far-fetched to most of us. Today, researchers around the world connect to IBM’s cloud-based quantum systems with such frequency that, according to IBM’s director of quantum infrastructure, some three billion quantum circuits are completed every day.
IBM and other companies are already using quantum technology to do things that either couldn’t be done by classical binary computers or would take too much time or energy. But there’s still a lot of work to be done.
The dream is to create a useful, fault-tolerant quantum computer capable of demonstrating clear quantum advantage — the point where quantum processors are capable of doing things that classical ones simply cannot.
Background: Here at Neural, we identified quantum computing as the most important technology of 2022 and that’s unlikely to change as we continue the perennial march forward.
The short and long of it is that quantum computing promises to do away with our current computational limits. Rather than replacing the CPU or GPU, it’ll add the QPU (quantum processing unit) to our tool belt.
What this means is up to the individual use case. Most of us don’t need quantum computers because our day-to-day problems aren’t that difficult.
But, for industries such as banking, energy, and security, the existence of new technologies capable of solving problems more complex than today’s technology can represents a paradigm shift the likes of which we may not have seen since the advent of steam power.
If you can imagine a magical machine capable of increasing efficiency across numerous high-impact domains — it could save time, money, and energy at scales that could ultimately affect every human on Earth — then you can understand why IBM and others are so desparate on building QPUs that demonstrate quantum advantage.
The problem: Building pieces of hardware capable of manipulating quantum mechanics as a method by which to perform a computation is, as you can imagine, very hard.
IBM’s spent the past decade or so figuring out how to solve the foundational problems plaguing the field — to include the basic infrastructure, cooling, and power source requirements necessary just to get started in the labs.
Today, IBM’s quantum roadmap shows just how far the industry has come:
But to get where it’s going, we need to solve one of the few remaining foundational problems related to the development of useful quantum processors: they’re noisy as heck.
The solution: Noisy qubits are the quantum computer engineer’s current bane. Essentially, the more processing power you try to squeeze out of a quantum computer the noisier its qubits get (qubits are essentially the computer bits of quantum computing).
Until now, the bulk of the work in squelching this noise has involved scaling qubits so that the signal the scientists are trying to read is strong enough to squeeze through.
In the experimental phases, solving noisy qubits was largely a game of Wack-a-mole. As scientists came up with new techniques — many of which were pioneered in IBM laboratories — they pipelined them to researchers for novel application.
But, these days, the field has advanced quite a bit. The art of error mitigation has evolved from targeted one-off solutions to a full suite of techniques.
Current quantum hardware is subject to different sources of noise, the most well-known being qubit decoherence, individual gate errors, and measurement errors. These errors limit the depth of the quantum circuit that we can implement. However, even for shallow circuits, noise can lead to faulty estimates. Fortunately, quantum error mitigation provides a collection of tools and methods that allow us to evaluate accurate expectation values from noisy, shallow depth quantum circuits, even before the introduction of fault tolerance.
In latest years, we developed and implemented two general-purpose error mitigation methods, called zero noise extrapolation (ZNE) and probabilistic error cancellation (PEC).
Both techniques involve extremely complex applications of quantum mechanics, but they basically boil down to finding ways to eliminate or squelch the noise coming off quantum systems and/or to amplify the signal that scientists are trying to measure for quantum computations and other processes.
Neural’s take: We spoke to IBM’s director of quantum infrastructure, Jerry Chow, who seemed pretty excited about the new paradigm.
He explained that the techniques being touted in the new press release were already in production. IBM’s already demonstrated massive improvements in their ability to scale solutions, repeat cutting-edge results, and speed up classical processes using quantum hardware.
The bottom line is that quantum computers are here, and they work. Currently, it’s a bit hit or miss whether they can solve a specific problem better than classical systems, but the last remaining hard obstacle is fault-tolerance.
IBM’s new “error mitigation” strategy signals a change from the discovery phase of fault-tolerance solutions to implementation.
We tip our hats to the IBM quantum research team. Learn more here at IBM’s official blog.
Senior advisor to the ACIO and executive leadership at the IRS.
The ongoing global digital transformation is fueling innovation in all industries. One such innovation is called digital twin technology, which was originally invented 40 years ago. When the Apollo mission was developed, scientists at NASA created a digital twin of the mission Apollo and conducted experiments on the clone before the mission started. Digital twin technology is now becoming very popular in the manufacturing and healthcare industries.
Do you know that the densely populated city of Shanghai has its own fully deployed digital twin (virtual clone) covering more than 4,000 kilometers? This was created by mapping every physical device to a new virtual world and applying artificial intelligence, machine learning and IoT technologies to that map. Similarly, Singapore is bracing for a full deployment of its own digital twin. The McLaren sports car already has its own digital twin.
Companies like Siemens, Philips, IBM, Cisco, Bosch and Microsoft are already miles ahead in this technology, fueling the Fourth Industrial Revolution. The conglomeration of AI, IoT and data analytics predicts the future performance of a product even before the product’s final design is approved. Organizations can create a planned process using digital twin technology. With a digital twin, process failures can be analyzed ahead of production. Engineering teams can perform scenario-based testing to predict the failures, identify risks and apply mitigation in simulation labs.
Digital twins produce a digital thread that can then enable data flows and provide an integrated view of asset data. These digital threads are the key to the product life cycle and help optimize product life cycles. The simulation of a digital thread can identify gaps in operational efficiencies and produce a wealth of process improvement opportunities through the application of AI.
Another reason behind the overwhelming success of digital twin technology is its use in issue identification and minor product design corrections while products are in operations. For example, for a high-rise building, with a digital twin, we can identify minor structural issues and implement them in the virtual world before carrying them over to the real world, cutting down long testing cycles.
By the end of this decade, scientists may come up with a fully functional digital twin of a human being that can tremendously help in medical research. There may be a digital version of some of us walking around, and when needed, it can provide updates to our family or healthcare providers regarding any critical health conditions we may have. Some powerful use cases for the use of digital twin humans include drug testing and proactive injury prevention.
Organizations starting to think about implementing digital twin technology in product manufacturing should first look at the tremendous innovation done by leaders like Siemens and GE. There are hundreds of case studies published by these two organizations that are openly available on the market. The next step is to create a core research team and estimate the cost of implementing this technology with the right ROI justification for your business stakeholder. This technology is hard to implement, and it’s also hard to maintain. That’s why you should develop a long-term sustainable strategy for digital twin implementation.
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“The first code for Neo4j and the property graph database was written in IIT Bombay”, said the chief Marketing Officer at Neo4j, Chandra Rangan.
In an exclusive interview with Analytics India Magazine, Rangan said that the first piece of code was sketched by Emil Eifrem — who is the founder and CEO of Neo4j — on a flight to Bombay, where he worked with an intern from IIT Bombay to develop the graph database platform.
Rangan joined Neo4j as the chief marketing officer (CMO) on May 10, 2022. Prior to this, he worked at Google, running Google Cloud Platform product marketing and, more recently, product-led growth, strategy, and operations for Google Maps Platform. Rangan has over two decades of technology infrastructure experience across marketing leadership, strategy, and operations at Hewlett Packard Enterprise, Gartner, Symantec, McKinsey, and IBM.
Founded in 2007, Neo4j has more than 700 employees globally. In June 2022, the company raised about $325 million in a Series F funding round led by Eurazeo, alongside participation from GV (formerly Google Ventures) and other existing investors like One Peak, Creandum, Greenbridge Partners, DTCP, and Lightrock.
This is one of the largest investments in a private database company. It raised Neo4j’s valuation to over $2 billion. In contrast, even bigger than MongoDB, which raised a total of $311 million, and post-IPO, it raised about $192 million in IPO, making it worth $1.2 billion.
With its latest funding round, Neo4j is looking to invest in expanding its footprint globally, and India is one of its top choices, thanks to a larger developer ecosystem, alongside a burgeoning startup ecosystem and IT service providers using its platform to offer solutions to global customers.
Neo4j’s community edition, which is open source, is widely adopted by developers in the country. “We have an overall community of almost a quarter million users who are familiar with our platform”, said Rangan, explaining that it has one of the largest developers in the country. With the fresh infusion of funds, the company looks to tap into the market, expand its services, sales and support, and invest in the right strategies going forward.
As part of its expansion plans, Neo4j started hiring in sales leadership and country manager roles from last year onwards and would also continue that momentum this year. “This is a big bet for us in multiple ways”, added Rangan, pointing at its Indian root and all the innovations in the country.
Besides India, Neo4j has a strong presence in Silicon Valley and Sweden and has a huge developer ecosystem in the US, China, Europe, South East Asia and others.
Over the years, Neo4j has grown through developers and some of the early adopters of its platform. “Unfortunately, developers interested in graph databases will typically start with us”, said Rangan affirmatively.
Further, explaining the conversion cycle, he said that once they know about graph databases, they later join the community edition. Then, once they get comfortable with the use cases and start putting this into production, they eventually get into a paid version for the advanced security, support, scalability, and commercial constructs.
“In India, that’s the similar motion we are seeing”, said Rangan. He revealed that they already have a huge developer community. Banking on this community, they plan to invest in continuing the engagement with the community in a meaningful way.
Of late, the company has also started hiring several community leaders to encourage proactive engagement within the community. In addition, it is also investing heavily in sales and marketing engines, including technical sales, which work closely with organisations in building the use cases, alongside the implementation of services and support.
One thing that makes Neo4j stand apart from other players is its intuitiveness in helping deploy applications faster because of its flexible schema. This helps developers to add properties, nodes, and more. “It gives tremendous flexibility for developers so they can get to the outcome much more quickly”, said Rangan.
But what about the learning curve? Rangan said, “Literally, for a new developer, if they start learning graphs for the first time, it is very intuitive.” He explained that the learning curve is not that steep and doesn’t take long. “But, for folks who have been working in the development space and building applications and are very familiar and comfortable with RDBMS, i.e., rows and tables. Strangely enough, the learning curve is a little higher and steeper”, added Rangan, discussing that they have to unlearn to model intuitively versus modelling tables. He said the best way to overcome that learning curve is to try it out.
“So, when you think about the learning curve, it is a very easy learning curve, especially if you can put aside the former way of thinking about things like rows and tables and go back to first principles.”—Chandra Rangan.
The International Consortium of Investigative Journalists (ICIJ) released the full list of companies and individuals in the Panama Papers, implicating at least 140 politicians from more than 50 countries in tax evasion schemes. The journalist used Neo4j to draw the relationship with their data and found common touchpoints and names of people involved in having multiple offshore accounts and evading tax.
“We believe a whole bunch of sectors can actually get value. We have seen new sectors kind of pop up on a pretty regular basis”, said Rangan while citing various use cases in financial service sectors (fraud detection), healthcare (vaccine distribution), pharmaceuticals (drug discovery), supply chain and logistics (mapping automation), tech companies (managing IT networks), retail (recommendation systems), and more.
Chandra Rangan further explained that people are still discovering what they can use graph databases for and how useful it is in some sense. He said that it is unleashing a whole bunch of innovations. “So, we are hoping for a lot of that to happen here in India because of the developer community”, he added.
Rangan said Neo4j would be aggressively investing in the community and ecosystem here in India. Besides this, he said they are investing in building a marketing and sales team, which has grown significantly in the last year. In addition, Neo4j is also investing in building a partner ecosystem to support a wider range of customers.
“Depending on how quickly we can grow or cannot grow—again, responsible growth—we want to grow as fast as possible. But, we also want to make sure as we hire people as we establish the relationship, we are investing enough time, effort, and money to make sure that these relationships are successful”, concluded Rangan.
The high-end Power10 server launched last year has enjoyed “fantastic” demand, according to IBM. Let’s look into how IBM Power has maintained its unique place in the processor landscape.
This article is a bit of a walk down memory lane for me, as I recall 4 years working as the VP of Marketing at IBM Power back in the 90s. The IBM Power development team is unique as many of the engineers came from a heritage of developing processors for the venerable and durable mainframe (IBMz) and the IBM AS400. These systems were not cheap, but they offered enterprises advanced features that were not available in processors from SUN or DEC, and are still differentiated versus the industry standard x86.
While a great deal has changed in the industry since I left IBM, the Power processor remains the king of the hill when it comes to performance, security, reliability, availability, OS choice, and flexible pricing models in an open platform. The new Power10 processor-based systems are optimized to run both mission-critical workloads like core business applications and databases, as well as maximize the efficiency of containerized and cloud-native applications.
IBM introduced the high-end Power10 server last September and is now broadening the portfolio with four new systems: the scale-out 2U Power S1014, Power S1022, and Power S1024, along with a 4U midrange server, the Power E1050. These new systems, built around the Power10 processor, have twice the cores and memory bandwidth of the previous generation to bring high-end advantages to the entire Power10 product line. Supporting AIX, Linux, and IBM i operating systems, these new servers provide Enterprise clients a resilient platform for hybrid cloud adoption models.
The latest IBM Power10 processor design includes the Dual Chip Module (DCM) and the entry Single Chip Module SCM) packaging, which is available in various configurations from four cores to 24 cores per socket. Native PCIe 5th generation connectivity from the processor socket delivers higher performance and bandwidth for connected adapters. And IBM Power10 remains the only 8-way simultaneous multi-threaded core in the industry.
An example of the advanced technology offered in Power10 is the Open Memory Interface (OMI) connected differential DIMM (DDIMM) memory cards delivering increased performance, resilience, and security over industry-standard memory technologies, including the implementation of transparent memory encryption. The Power10 servers include PowerVM Enterprise Edition to deliver virtualized environments and support a frictionless hybrid cloud deployment model.
Surveys say IBM Power experiences 3.3 minutes or less of unplanned outage due to security issues, while an ITIC survey of 1,200 corporations across 28 vertical markets gives IBM Power a 99.999% or greater availability rating. Power10 also stepped up the AI Inferencing game with 5X faster inferencing per socket versus Power9 with each Power10 processor core sporting 4 Matrix Math Accelerators.
But perhaps even more telling of the IBM Power strategy is the consumption-based pricing in the Power Private Cloud with Shared Utility Capacity commercial model allowing customers to consume resources more flexibly and efficiently for all supported operating systems. As x86 continued to lower server pricing over the last two decades, IBM has rolled out innovative pricing models to keep these advanced systems more affordable in the face of ever-increasing cloud adoption and commoditization.
While most believe that IBM has left the hardware business, the company’s investments in underlying hardware technology at the IBM Research Labs, and the continual enhancements to IBM Power10 and IBM z demonstrate that the firm remains committed to advanced hardware capabilities while eschewing the battles for commoditized (and lower margin) hardware such as x86, Arm, and RISC-V.
Enterprises demanding more powerful, flexible, secure, and yes, even affordable innovation would do well to familiarize themselves with IBM’s latests in advanced hardware designs.
AMA introduce new research on Global IT Consulting Services covering micro level of analysis by competitors and key business segments (2021-2027). The Global IT Consulting Services explores comprehensive study on various segments like opportunities, size, development, innovation, sales and overall growth of major players. The research is carried out on primary and secondary statistics sources and it consists both qualitative and quantitative detailing.
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Some of the Major Key players profiled in the study are Fujitsu Limited (Japan), HCL Technologies Limited (India), Hexaware Tech Limited (India), Infosys Limited (India), Ernst &Young (U.K), KPMG (Europe), PricewaterhouseCoopers (U.K), Avante (United States), Cognizant Tech Corp. (United States), Gartner, Inc. (United States), Syntel Inc. (United States), IBM Corp (United States), McKinsey & Company (United States),.
IT consulting market is expected to face significantly higher demand due to factors like digitization, analytics, cloud, robotics, and the Internet of Things (IoT). IT consulting services involves professional business computer consultancy and advisory services which provide expertise, experience, industry intelligence to the enterprise. This industry deals with professional service firms, staffing firms, contractors, information security consultants. The IT consulting segment includes both advisory and implementation services but excludes transactional IT activities. The IT consulting services market consists of eight main divisions i.e. IT Strategy, IT Architecture, IT Implementation, ERP services, Systems Integration, Data Analytics, IT Security and Software Management.
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Which market aspects are illuminated in the report?
Executive Summary: It covers a summary of the most vital studies, the Global IT Consulting Services market increasing rate, modest circumstances, market trends, drivers and problems as well as macroscopic pointers.
Study Analysis: Covers major companies, vital market segments, the scope of the products offered in the Global IT Consulting Services market, the years measured and the study points.
Company Profile: Each Firm well-defined in this segment is screened based on a products, value, SWOT analysis, their ability and other significant features.
Manufacture by region: This Global IT Consulting Services report offers data on imports and exports, sales, production and key companies in all studied regional markets
Highlighted of Global IT Consulting Services Market Segments and Sub-Segment:
IT Consulting Services Market by Key Players: Fujitsu Limited (Japan), HCL Technologies Limited (India), Hexaware Tech Limited (India), Infosys Limited (India), Ernst &Young (U.K), KPMG (Europe), PricewaterhouseCoopers (U.K), Avante (United States), Cognizant Tech Corp. (United States), Gartner, Inc. (United States), Syntel Inc. (United States), IBM Corp (United States), McKinsey & Company (United States),
IT Consulting Services Market: by Application (Information protection (Data loss prevention, authentication and encryption), Threat protection (Data center and end point), Web and cloud based protection, Services (Advisory, Design, Implementation, Financial, Healthcare, IT telecom))
IT Consulting Services Market by Geographical Analysis: Americas, United States, Canada, Mexico, Brazil, APAC, China, Japan, Korea, Southeast Asia, India, Australia, Europe, Germany, France, UK, Italy, Russia, Middle East & Africa, Egypt, South Africa, Israel, Turkey & GCC Countries
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The study is a source of reliable data on: Market segments and sub-segments, Market trends and dynamics Supply and demand Market size Current trends/opportunities/challenges Competitive landscape Technological innovations Value chain and investor analysis.
Interpretative Tools in the Market: The report integrates the entirely examined and evaluated information of the prominent players and their position in the market by methods for various descriptive tools. The methodical tools including SWOT analysis, Porter’s five forces analysis, and investment return examination were used while breaking down the development of the key players performing in the market.
Key Growths in the Market: This section of the report incorporates the essential enhancements of the marker that contains assertions, coordinated efforts, R&D, new item dispatch, joint ventures, and associations of leading participants working in the market.
Key Points in the Market: The key features of this IT Consulting Services market report includes production, production rate, revenue, price, cost, market share, capacity, capacity utilization rate, import/export, supply/demand, and gross margin. Key market dynamics plus market segments and sub-segments are covered.
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*What are the major Product Type of IT Consulting Services?
*What are the major applications of IT Consulting Services?
*Which IT Consulting Services technologies will top the market in next 5 years?
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Table of Content
Chapter One: Industry Overview
Chapter Two: Major Segmentation (Classification, Application and etc.) Analysis
Chapter Three: Production Market Analysis
Chapter Four: Sales Market Analysis
Chapter Five: Consumption Market Analysis
Chapter Six: Production, Sales and Consumption Market Comparison Analysis
Chapter Seven: Major Manufacturers Production and Sales Market Comparison Analysis
Chapter Eight: Competition Analysis by Players
Chapter Nine: Marketing Channel Analysis
Chapter Ten: New Project Investment Feasibility Analysis
Chapter Eleven: Manufacturing Cost Analysis
Chapter Twelve: Industrial Chain, Sourcing Strategy and Downstream Buyers
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IBM Corp. beat second-quarter earnings estimates today, but shareholders were unimpressed, sending the computing giant’s shares down more than 4% in early after-hours trading.
Revenue rose 16%, to $15.54 billion in constant currency terms, and rose 9% from the $14.22 billion IBM reported in the same quarter a year ago after adjusting for the spinoff of managed infrastructure-service business Kyndryl Holdings Inc. Net income jumped 45% year-over-year, to $2.5 billion, and diluted earnings per share of $2.31 a share were up 43% from a year ago.
Analysts had expected adjusted earnings of $2.26 a share on revenue of $15.08 billion.
The strong numbers weren’t a surprise given that IBM had guided expectations toward high single-digit growth. The stock decline was attributed to a lower free cash flow forecast of $10 billion for 2022, which was below the $10 billion-to-$10.5 billion range it had initially forecast. However, free cash flow was up significantly for the first six months of the year.
It’s also possible that a report saying Apple was looking at slowing down hiring, which caused the overall market to fall slightly today, might have spilled over to other tech stocks such as IBM in the extended trading session.
On the whole, the company delivered what it said it would. Its hybrid platform and solutions category grew 9% on the back of 17% growth in its Red Hat Business. Hybrid cloud revenue rose 19%, to $21.7 billion. Transaction processing sales rose 19% and the software segment of hybrid cloud revenue grew 18%.
“This quarter says that [Chief Executive Arvind Krishna] and his team continue to get the big calls right both from a platform strategy and also from the investments and acquisitions IBM has made over the last 18 months,” said Bola Rotibi, research director for software development at CCS Insight Ltd. Despite broad fears of a downturn in the economy, “the company is bucking the expected trend and more than meeting expectations,” she said.
Software revenue grew 11.6% in constant currency terms, to $6.2 billion, helped by a 7% jump in sales to Kyndryl. Consulting revenue rose almost 18% in constant currency, to $4.8 billion, while infrastructure revenue grew more than 25%, to $4.2 billion, driven largely by the announcement of a new series of IBM z Systems mainframes, which delivered 69% revenue growth.
With investors on edge about the risk of recession and his potential impact on technology spending, Chief Executive Arvind Krishna (pictured) delivered an upbeat message. “There’s every reason to believe technology spending in the [business-to-business] market will continue to surpass GDP growth,” he said. “Demand for solutions remains strong. We continue to have double-digit growth in IBM consulting, broad growth in software and, with the z16 launch, strong growth in infrastructure.”
Krishna called IBM’s current sales pipeline “pretty healthy. The second half at this point looks consistent with the first half by product line and geography,” he said. He suggested that technology spending is benefiting from its leverage in reducing costs, making the sector less vulnerable to recession. ”We see the technology as deflationary,” he said. “It acts as a counterbalance to all of the inflation and labor demographics people are facing all over the globe.”
While IBM has been criticized for spending $34 billion to buy Red Hat Inc. instead of investing in infrastructure, the deal appears to be paying off as expected, Rotibi said. Although second-quarter growth in the Red Hat business was lower than the 21% recorded in the first quarter, “all the indices show that they are getting very good value from the portfolio,” she said. Red Hat has boosted IBM’s consulting business but products like Red Hat Enterprise Linux and OpenShift have also benefited from the Big Blue sales force.
With IBM being the first major information technology provider to report results, Pund-IT Inc. Chief Analyst Charles King said the numbers bode well for reports soon to come from other firms. “The strength of IBM’s quarter could portend good news for other vendors focused on enterprises,” he said. “While those businesses aren’t immune to systemic problems, they have enough heft and buoyancy to ride out storms.”
One area that IBM has talked less and less about over the past few quarters is its public cloud business. The company no longer breaks out cloud revenues and prefers to talk instead about its hybrid business and partnerships with major public cloud providers.
“IBM’s primary focus has long been on developing and enabling hybrid cloud offerings and services; that’s what its enterprise customers want, and that’s what its solutions and consultants aim to deliver,” King said.
IBM’s recently expanded partnership with Amazon Web Services Inc. is an example of how the company has pivoted away from competing with the largest hyperscalers and now sees them as a sales channel, Rotibi said. “It is a pragmatic recognition of the footprint of the hyperscalers but also playing to IBM’s strength in the services it can build on top of the other cloud platforms, its consulting arm and infrastructure,” she said.
Krishna asserted that, now that the Kyndryl spinoff is complete, IBM is in a strong position to continue on its plan to deliver high-single-digit revenue growth percentages for the foreseeable future. Its consulting business is now focused principally on business transformation projects rather than technology implementation and the people-intensive business delivered a pretax profit margin of 9%, up 1% from last year. “Consulting is a critical part of our hybrid platform thesis,” said Chief Financial Officer James Kavanaugh.
Pund-IT’s King said IBM Consulting “is firing on all cylinders. That includes double-digit growth in its three main categories of business transformation, technology consulting and application operations as well as a notable 32% growth in hybrid cloud consulting.”
With the U.S. dollar at a 20-year high against the euro and a 25-year high against the yen, analysts on the company’s earnings call directed several questions to the impact of currency fluctuations on IBM’s results.
Kavanaugh said these are unknown waters but the company is prepared. “The velocity of the [dollar’s] strengthening is the sharpest we’ve seen in over a decade; over half of currencies are down-double digits against the U.S. dollar,” he said. “This is unprecedented in rate, breadth and magnitude.”
Kavanaugh said IBM is more insulated against currency fluctuations than most companies because it has long hedged against volatility. “Hedging mitigates volatility in the near term,” he said. “It does not eliminate currency as a factor but it allows you time to address your business model for price, for source, for labor pools and for cost structures.”
The company’s people-intensive consulting business also has some built-in protections against a downturn, Kavanaugh said. “In a business where you hire tens of thousands of people, you also churn tens of thousands each year,” he said. “It gives you an automatic way to hit a pause in some of the profit controls because if you don’t see demand you can slow down your supply-side. You can get a 10% to 20% impact that you pretty quickly control.”
The MarketWatch News Department was not involved in the creation of this content.
Aug 01, 2022 (Heraldkeepers) -- Market Research Engine has published a new report titled as "Airport Market Size By Application (Landside, Airside, Terminal Side), By End User (Implementation, Upgrades & Services), By Region (North America, Europe, Asia-Pacific, Rest of the World), Market Analysis Report, Forecast 2021-2026 - Executive Data Report."
Airports across emerging economies are increasingly adopting a smart airport approach by implementing innovative technologies, such as smart robots, self-check-in kiosks, beacon services, predictive analysis, and border control automation solutions
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The report covers:
Global Airport market sizes from 2015 to 2024, along with CAGR for 2018-2024
Market size comparison for 2017 vs 2024, with genuine data for 2017, estimates for 2018 and forecast from 2019 to 2024
Global Airport market trends, covering comprehensive range of consumer trends & manufacturer trends
Value chain analysis covering participants from raw material suppliers to the downstream buyer in the global Airport market
Major market opportunities and challenges in forecast timeframe to be focused
Competitive landscape with analysis on competition pattern, portfolio comparisons, development trends and strategic management
Comprehensive company profiles of the key industry players
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The global Airport market Based on Application the global Airport market is segmented in Landside, Airside, and Terminal Side. Based on End User the global Airport market is segmented in Implementation and Upgrades & Services.
The global Airport market report provides geographic analysis covering regions, such as North America, Europe, Asia-Pacific, and Rest of the World. The Airport market for each region is further segmented for major countries including the U.S., Canada, Germany, the U.K., France, Italy, China, India, Japan, Brazil, South Africa, and others.
Cisco Systems Inc., IBM Corporation, Collins Aerospace, Honeywell International Inc., Sabre Corp., and others are among the major players in the global Airport market. The companies are involved in several growth and expansion strategies to gain a competitive advantage. Industry participants also follow value chain integration with business operations in multiple stages of the value chain.
The Airport Market has been segmented as below:
Airport Market, By Application
Airport Market, By End User
Upgrades & Services
Airport Market, By Region
Rest of the World
The global Airport market report scope includes detailed study covering underlying factors influencing the industry trends.
The report covers analysis on regional and country level market dynamics. The scope also covers competitive overview providing company market shares along with company profiles for major revenue contributing companies.
The report scope includes detailed competitive outlook covering market shares and profiles key participants in the global Airport market share. Major industry players with significant revenue share include Cisco Systems Inc., IBM Corporation, Collins Aerospace, Honeywell International Inc., Sabre Corp., and others.
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Table of Contents:
1.1 Key Insights
1.2 Report Overview
1.3 Markets Covered
2. Research Methodology
2.1 Research Scope
2.2 Market Research Process
2.3 Research Data Analysis
2.4.1 Secondary Research
2.4.2 Primary Research
2.4.3 Models for Estimation
2.5 Market Size Estimation
2.5.1 Bottom-Up Approach – Segmental Market Analysis
2.5.2 Top-Down Approach – Parent Market Analysis
3. Executive Summary
4. Market Overview
4.2 Porter’s Five Force Analysis
5. Airport Market, By Application
5.2.1 Market Overview
5.2.2 Market Size and Forecast
5.3.1 Market Overview
5.3.2 Market Size and Forecast
5.4 Terminal Side
5.4.1 Market Overview
5.4.2 Market Size and Forecast
6. Airport Market, By End User
6.2.1 Market Overview
6.2.2 Market Size and Forecast
6.3 Upgrades & Services
6.3.1 Market Overview
6.3.2 Market Size and Forecast
7. Airport Market, By Geography
7.2 North America
7.2.1 North America Airport, By Application
7.2.2 North America Airport, By End User
7.3.1 Europe Airport, By Application
7.3.2 Europe Airport, By End User
7.4.1 Asia-Pacific Airport, By Application
7.4.2 Asia-Pacific Airport, By End User
7.5 Rest of the World
7.5.1 Rest of the World Airport, By Application
7.5.2 Rest of the World Airport, By End User
Other Related Market News :
Company Name: Market Research Engine
Contact Person: John Bay
Country: United States
The MarketWatch News Department was not involved in the creation of this content.
Vancouver, Kelowna and Delta, British Columbia--(Newsfile Corp. - July 21, 2022) - Investorideas.com (www.investorideas.com), a global investor news source covering Artificial Intelligence (AI) stocks releases a sector snapshot looking at the growing AI tech implementation in the sports market, featuring AI innovator GBT Technologies Inc. (OTC Pink: GTCH).
Read the full article at Investorideas.com
As with so many other sectors, the sports industry is seeing increasing penetration of Artificial Intelligence (AI) related technologies as aspects of the medium become more and more digitized. A recently published report from Vantage Market Research finds that the global market for AI in Sports is projected to grow from $1.62 billion USD in 2021 to $7.75 billion by 2028, registering a compound annual growth rate (CAGR) of 29.7 percent in the forecast period 2022-28. According to a market synopsis from the report, AI is being leveraged by a number of firms to track player performance, Excellerate the player's health, and to Excellerate sports planning.
One such firm is GBT Technologies Inc. (OTC Pink: GTCH), an early stage technology developer in IoT and Artificial Intelligence (AI) Enabled Mobile Technology Platforms, which recently completed phase one of its intelligent soccer analytics platform through its 50 percent-owned joint venture GBT Tokenize Corp. (GTC). Given the internal codename of smartGOAL, the platform is "an intelligent, automatic analytics and prediction system for soccer game's results," which works by analyzing and predicting "possible outcomes of soccer games results according to permutations, statistics, historical data, using advanced mathematical methods and machine learning technology." GBT's CTO, Danny Rittman, explained:
"Considering the popularity of the game in the present world, we believe organizations will be interested in prediction systems for the better performance of their teams. As interesting as it may seem, prediction of the results of a soccer game is a very hard task and involves a large amount of uncertainty. However, it can be said that the result of football is not a completely random event, and hence, we believe a few hidden patterns in the game can be utilized to potentially predict the outcome. Based on the studies of numerous researchers that are being reviewed in our study as well as those done in the previous years, one can say that with a sufficient amount of data an accurate prediction system can be built using various machine learning algorithms. While each algorithm has its advantages and disadvantages, a hybrid system that consists of more than one algorithm can be made with the goal of increasing the efficiency of the system as a whole. There also is a need for a comprehensive dataset through which better results can be obtained. Experts can work more toward gathering data related to different leagues and championships across the globe which may help in better understanding of the prediction system. Moreover, the distinctive characteristics of a soccer player, as well as that of the team, can also be taken into consideration while predicting as this may produce a better result as compared to when all the players in a game are treated to be having an equal effect on the game. The more information the system is trained with, we believe the more accurate the predictions and analysis will be. One of our joint venture companies, GTC, aimed to evaluate machine learning-driven applications in various fields, among them are entertainment, media and sports. We believe smartGOAL is an intelligent application that has the ability to change the world's soccer field when it comes to analytics and game score predictions."
Elsewhere, Amazon Web Services (AWS), a subsidiary of tech giant Amazon announced a collaboration with Maple Leaf Sports & Entertainment (MLSE), a sports and entertainment company that owns a host of Toronto-based sports franchises, to innovate the creation and delivery of "extraordinary sports moments and enhanced fan engagement." This will see MLSE utilize AWS AI, machine learning (ML), and deep learning cloud services to support their teams, lines of business, and how fans connect with each other and experience games. Humza Teherany, Chief Technology & Digital Officer at MLSE, commented:
"We built Digital Labs at MLSE to become the most technologically advanced organization in sport. As technology advances and how we watch and consume sports evolves, MLSE is dedicated to creating solutions and products that drive this evolution and elevate the fan experience. We aim to offer new ways for fans to connect digitally with their favorite teams while also seeking to uncover digital sports performance opportunities in collaboration with our front offices. With AWS's advanced machine learning and analytics services, we can use data with our teams to help inform areas such as: team selection, training and strategy to deliver an even higher caliber of competition. Taking a cloud-first approach to innovation with AWS further empowers our organization to experiment with new ideas that can help our teams perform their very best and our fans feel a closer connection to the action."
Similarly, IBM, the "Official Technology Partner of The [tennis] Championships for the past 33-years, has recently, alongside the All England Lawn Tennis Club, unveiled "new ways for Wimbledon fans around the world to experience The Championships digitally, powered by artificial intelligence (AI) running on IBM Cloud and hybrid cloud technologies." Kevin Farrar, Sports Partnership Leader, IBM UK & Ireland, explained:
"The digital fan features on the Wimbledon app and Wimbledon.com, beautifully designed by the IBM iX team and powered by AI and hybrid cloud technologies, are enabling the All England Club to immerse tennis lovers in the magic of The Championship, no matter where they are in the world. Sports fans love to debate and we're excited to introduce a new tool this year to enable that by allowing people to register their own match predictions and compare them with predictions generated by Match Insights with Watson and those of other fans."
Another firm cited in the Vantage Market Research report on AI in Sports was sports performance tech firm Catapult Group International Limited, who recently reported a multi-year deal with the German Football Association (DFB-Akademie) to "capture performance data via video, track athlete performance via wearables, and Excellerate the analysis infrastructure at all levels of the German National Football Teams." Will Lopes, CEO of Catapult, commented:
"We strive every day to unleash the potential of every athlete and team, and we're proud to partner with the prestigious German Football Association to fulfill that ambition. We're looking forward to partnering with the DFB to unlock what even the best coaches in the world cannot see on film or from the sidelines. This technology will empower athletes at all levels with data and insights to perform at their best."
With the seemingly inexorable tendency toward digitization in the presentation and analysis of sports, the accompanying use of AI-related technologies seems equally inevitable as is already borne out by current industry trends.
For a list of artificial intelligence stocks on Investorideas.com visit here.
About GBT Technologies Inc.
GBT Technologies, Inc. (OTC Pink: GTCH) ("GBT") (http://gbtti.com) is a development stage company which considers itself a native of Internet of Things (IoT), Artificial Intelligence (AI) and Enabled Mobile Technology Platforms used to increase IC performance. GBT has assembled a team with extensive technology expertise and is building an intellectual property portfolio consisting of many patents. GBT's mission, to license the technology and IP to synergetic partners in the areas of hardware and software. Once commercialized, it is GBT's goal to have a suite of products including smart microchips, AI, encryption, Blockchain, IC design, mobile security applications, database management protocols, with tracking and supporting cloud software (without the need for GPS). GBT envisions this system as a creation of a global mesh network using advanced nodes and super performing new generation IC technology. The core of the system will be its advanced microchip technology; technology that can be installed in any mobile or fixed device worldwide. GBT's vision is to produce this system as a low cost, secure, private-mesh-network between any and all enabled devices. Thus, providing shared processing, advanced mobile database management and sharing while using these enhanced mobile features as an alternative to traditional carrier services.
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