000-590 practice test changes on daily basis, download daily

killexams.com IBM Certification concentrate on guides comprise of real test questions and replies. Exceptionally our 000-590 sample test are legitimate, Latest, and 2022 refreshed on an ordinary premise. Many applicants breeze through their 000-590 test with our genuine inquiries braindumps. On the off chance that you like to appreciate achievement, you ought to download 000-590 practice test.

Exam Code: 000-590 Practice exam 2022 by Killexams.com team
IBM Tivoli Storage Manager V6.3 Implementation
IBM Implementation approach
Killexams : IBM Implementation approach - BingNews https://killexams.com/pass4sure/exam-detail/000-590 Search results Killexams : IBM Implementation approach - BingNews https://killexams.com/pass4sure/exam-detail/000-590 https://killexams.com/exam_list/IBM Killexams : IBM unveils a bold new ‘quantum error mitigation’ strategy

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.

Subscribe to our newsletter now for a weekly recap of our favorite AI stories in your inbox.

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 keen 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.

Per IBM:

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 exact 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.

Thu, 28 Jul 2022 03:42:00 -0500 en text/html https://thenextweb.com/news/ibm-unveils-bold-new-quantum-error-mitigation-strategy
Killexams : CXL Borgs IBM’s OpenCAPI, Weaves Memory Fabrics With 3.0 Spec

System architects are often impatient about the future, especially when they can see something good coming down the pike. And thus, we can expect a certain amount of healthy and excited frustration when it comes to the Compute Express Link, or CXL, interconnect created by Intel, which with the absorption of Gen-Z technology from Hewlett Packard Enterprise and now OpenCAPI technology from IBM will become the standard for memory fabrics across compute engines for the foreseeable future.

The CXL 2.0 specification, which brings memory pooling across the PCI-Express 5.0 peripheral interconnect, will soon available on CPU engines. Which is great. But all eyes are already turning to the just-released CXL 3.0 specification, which rides atop the PCI-Express 6.0 interconnect coming in 2023 with 2X the bandwidth, and people are already contemplating what another 2X of bandwidth might offer with CXL 4.0 atop PCI-Express 7.0 coming in 2025.

In a way, we expect for CXL to follow the path blazed by IBM’s “Bluelink” OpenCAPI interconnect. Big Blue used the Bluelink interconnect in the “Cumulus” and “Nimbus” Power9 processors to provide NUMA interconnects across multiple processors, to run the NVLink protocol from Nvidia to provide memory coherence across the Power9 CPU and the Nvidia “Volta” V100 GPU accelerators, and to provide more generic memory coherent links to other kinds of accelerators through OpenCAPI ports. But the path that OpenCAPI and CXL will not be exactly the same, obviously. OpenCAPI is kaput and CXL is the standard for memory coherence in the datacenter.

IBM put faster OpenCAPI ports on the “Cirrus” Power10 processors, and they are used to provide those NUMA links as with the Power9 chips as well as a new OpenCAPI Memory Interface that uses the Bluelink SerDes as a memory controller, which runs a bit slower than a DDR4 or DDR5 controller but which takes up a lot less chip real estate and burns less power – and has the virtue of being exactly like the other I/O in the chip. In theory, IBM could have supported the CXL and NVLink protocols running atop its OpenCAPI interconnect on Power10, but there are some sour grapes there with Nvidia that we don’t understand – it seems foolish not to offer memory coherence with Nvidia’s current “Ampere” A100 and impending “Hopper” H100 GPUs. There may be an impedance mismatch between IBM and Nvidia in regards to signaling rates and lane counts between OpenCAPI and NVLink. IBM has PCI-Express 5.0 controllers on its Power10 chips – these are unique controllers and are not the Bluelink SerDes – and therefore could have supported the CXL coherence protocol, but as far as we know, Big Blue has chosen not to do that, either.

Given that we think CXL is the way a lot of GPU accelerators and their memories will link to CPUs in the future, this strategy by IBM seems odd. We are therefore nudging IBM to do a Power10+ processor with support for CXL 2.0 and NVLink 3.0 coherent links as well as with higher core counts and maybe higher clock speeds, perhaps in a year or a year and a half from now. There is no reason IBM cannot get some of the AI and HPC budget given the substantial advantages of its OpenCAPI memory, which is driving 818 GB/sec of memory bandwidth out of a dual chip module with 24 cores. We also expect for future datacenter GPU compute engines from Nvidia will support CXL in some fashion, but exactly how it will sit side-by-side with or merge with NVLink is unclear.

It is also unclear how the Gen-Z intellectual property donated to the CXL Consortium by HPE back in November 2021 and the OpenCAPI intellectual property donated to the organization steering CXL by IBM last week will be used to forge a CXL 4.0 standard, but these two system vendors are offering up what they have to help the CXL effort along. For which they should be commended. That said, we think both Gen-Z and OpenCAPI were way ahead of CXL and could have easily been tapped as in-node and inter-node memory and accelerator fabrics in their own right. HPE had a very elegant set of memory fabric switches and optical transceivers already designed, and IBM is the only CPU provider that offered CPU-GPU coherence across Nvidia GPUs and the ability to hook memory inside the box or across boxes over its OpenCAPI Memory Interface riding atop the Bluelink SerDes. (AMD is offering CPU-GPU coherence across its custom “Trento” Epyc 7003 series processors and its “Aldebaran” Instinct MI250X GPU accelerators in the “Frontier” exascale supercomputer at Oak Ridge National Laboratories.)

We are convinced that the Gen-Z and OpenCAPI technology will help make CXL better, and Improve the kinds and varieties of coherence that are offered. CXL initially offered a kind of asymmetrical coherence, where CPUs can read and write to remote memories in accelerators as if they are local but using the PCI-Express bus instead of a proprietary NUMA interconnect – that is a vast oversimplification – rather than having full cache coherence across the CPUs and accelerators, which has a lot of overhead and which would have an impedance mismatch of its own because PCI-Express was, in days gone by, slower than a NUMA interconnect.

But as we have pointed out before, with PCI-Express doubling its speed every two years or so and latencies holding steady as that bandwidth jumps, we think there is a good chance that CXL will emerge as a kind of universal NUMA interconnect and memory controller, much as IBM has done with OpenCAPI, and Intel has suggested this for both CXL memory and CXL NUMA and Marvell certainly thinks that way about CXL memory as well. And that is why with CXL 3.0, the protocol is offering what is called “enhanced coherency,” which is another way of saying that it is precisely the kind of full coherency between devices that, for example, Nvidia offers across clusters of GPUs on an NVSwitch network or IBM offered between Power9 CPUs and Nvidia Volta GPUs. The kind of full coherency that Intel did not want to do in the beginning. What this means is that devices supporting the CXL.memory sub-protocol can access each other’s memory directly, not asymmetrically, across a CXL switch or a direct point-to-point network.

There is no reason why CXL cannot be the foundation of a memory area network as IBM has created with its “memory inception” implementation of OpenCAPI memory on the Power10 chip, either. As Intel and Marvell have shown in their conceptual presentations, the palette of chippery and interconnects is wide open with a standard like CXL, and improving it across many vectors is important. The industry let Intel win this one, and we will be better off in the long run because of it. Intel has largely let go of CXL and now all kinds of outside innovation can be brought to bear.

Ditto for the Universal Chiplet Interconnect Express being promoted by Intel as a standard for linking chiplets inside of compute engine sockets. Basically, we will live in a world where PCI-Express running UCI-Express connects chiplets inside of a socket, PCI-Express running CXL connects sockets and chips within a node (which is becoming increasingly ephemeral), and PCI-Express switch fabrics spanning a few racks or maybe even a row someday use CXL to link CPUs, accelerators, memory, and flash all together into disaggregated and composable virtual hardware servers.

For now, what is on the immediate horizon is CXL 3.0 running atop the PCI-Express 6.0 transport, and here is how CXL 3.0 is stacking up against the prior CXL 1.0/1.1 release and the current CXL 2.0 release on top of PCI-Express 5.0 transports:

When the CXL protocol is running in I/O mode – what is called CXL.io – it is essentially just the same as the PCI-Express peripheral protocol for I/O devices. The CXL.cache and CXL.memory protocols add caching and memory addressing atop the PCI-Express transport, and run at about half the latency of the PCI-Express protocol. To put some numbers on this, as we did back in September 2021 when talking to Intel, the CXL protocol specification requires that a snoop response on a snoop command when a cache line is missed has to be under 50 nanoseconds, pin to pin, and for memory reads, pin to pin, latency has to be under 80 nanoseconds. By contrast, a local DDR4 memory access one a CPU socket is around 80 nanoseconds, and a NUMA access to far memory in an adjacent CPU socket is around 135 nanoseconds in a typical X86 server.

With the CXL 3.0 protocol running atop the PCI-Express 6.0 transport, the bandwidth is being doubled on all three types of drivers without any increase in latency. That bandwidth increase, to 256 GB/sec across x16 lanes (including both directions) is thanks to the 256 byte flow control unit, or flit, fixed packet size (which is larger than the 64 byte packet used in the PCI-Express 5.0 transport) and the PAM-4 pulsed amplitude modulation encoding that doubles up the bits per signal on the PCI-Express transport. The PCI-Express protocol uses a combination of cyclic redundancy check (CRC) and three-way forward error correction (FEC) algorithms to protect the data being transported across the wire, which is a better method than was employed with prior PCI-Express protocols and hence why PCI-Express 6.0 and therefore CXL 3.0 will have much better performance for memory devices.

The CXL 3.0 protocol does have a low latency CRC algorithm that breaks the 256 B flits into 128 B half flits and does its CRC check and transmissions on these subflits, which can reduce latencies in transmissions by somewhere between 2 nanosecond and 5 nanoseconds.

The neat new thing coming with CXL 3.0 is memory sharing, and this is distinct from the memory pooling that was available with CXL 2.0. Here is what memory pooling looks like:

With memory pooling, you put a glorified PCI-Express switch that speaks CXL between hosts with CPUs and enclosures with accelerators with their own memories or just blocks of raw memory – with or without a fabric manager – and you allocate the accelerators (and their memory) or the memory capacity to the hosts as needed. As the diagram above shows on the right, you can do a point to point interconnect between all hosts and all accelerators or memory devices without a switch, too, if you want to hard code a PCI-Express topology for them to link on.

With CXL 3.0 memory sharing, memory out on a device can be literally shared simultaneously with multiple hosts at the same time. This chart below shows the combination of device shared memory and coherent copies of shared regions enabled by CXL 3.0:

System and cluster designers will be able to mix and match memory pooling and memory sharing techniques with CXL 3.0. CXL 3.0 will allow for multiple layers of switches, too, which was not possible with CXL 2.0, and therefore you can imagine PCI-Express networks with various topologies and layers being able to lash together all kinds of devices and memories into switch fabrics. Spine/leaf networks common among hyperscalers and cloud builders are possible, including devices that just share their cache, devices that just share their memory, and devices that share their cache and memory. (That is Type 1, Type 3, and Type 2 in the CXL device nomenclature.)

The CXL fabric is what will be truly useful and what is enabled in the 3.0 specification. With a fabric, a you get a software-defined, dynamic network of CXL-enabled devices instead of a static network set up with a specific topology linking specific CXL devices. Here is a simple example of a non-tree topology implemented in a fabric that was not possible with CXL 2.0:

And here is the neat bit. The CXL 3.0 fabric can stretch to 4,096 CXL devices. Now, ask yourself this: How many of the big iron NUMA systems and HPC or AI supercomputers in the world have more than 4,096 devices? Not as many as you think. And so, as we have been saying for years now, for a certain class of clustered systems, whether the nodes are loosely or tightly coupled at their memories, a PCI-Express fabric running CXL is just about all they are going to need for networking. Ethernet or InfiniBand will just be used to talk to the outside world. We would expect to see flash devices front-ended by DRAM as a fast cache as the hardware under storage clusters, too. (Optane 3D XPoint persistent memory is no longer an option. But there is always hope for some form of PCM memory or another form of ReRAM. Don’t hold your breath, though.)

As we sit here mulling all of this over, we can’t help thinking about how memory sharing might simplify the programming of HPC and AI applications, especially if there is enough compute in the shared memory to do some collective operations on data as it is processed. There are all kinds of interesting possibilities. . . .

Anyway, making CXL fabrics is going to be interesting, and it will be the heart of many system architectures. The trick will be sharing the memory to drive down the effective cost of DRAM – research by Microsoft Azure showed that on its cloud, memory capacity utilization was only an average of about 40 percent, and half of the VMs running never touched more than half of the memory allocated to their hypervisors from the underlying hardware – to pay for the flexibility that comes through CXL switching and composability for devices with memory and devices as memory.

What we want, and what we have always wanted, was a memory-centric systems architecture that allows all kinds of compute engines to share data in memory as it is being manipulated and to move that data as little as possible. This is the road to higher energy efficiency in systems, at least in theory. Within a few years, we will get to test this all out in practice, and it is legitimately exciting. All we need now is PCI-Express 7.0 two years earlier and we can have some real fun.

Tue, 09 Aug 2022 06:18:00 -0500 Timothy Prickett Morgan en-US text/html https://www.nextplatform.com/2022/08/09/cxl-borgs-ibms-opencapi-weaves-memory-fabrics-with-3-0-spec/
Killexams : The Rise Of Digital Twin Technology

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.


Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?


Wed, 03 Aug 2022 02:00:00 -0500 Kiran Palla en text/html https://www.forbes.com/sites/forbestechcouncil/2022/08/03/the-rise-of-digital-twin-technology/
Killexams : IBM Rolls Out New Power10 Servers And Flexible Consumption Models

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.

What has IBM announced?

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.

Conclusions

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.

Mon, 18 Jul 2022 04:29:00 -0500 Karl Freund en text/html https://www.forbes.com/sites/karlfreund/2022/07/18/ibm-rolls-out-new-power10-servers-and-flexible-consumption-models/
Killexams : The origin of Neo4j

“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. 

Bets big on India 

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. 

Strategies for expansion 

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. 

What makes Neo4j special? 

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. 

Discovering use cases with Neo4j 

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. 

What’s next? 

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.

Mon, 08 Aug 2022 20:07:00 -0500 en-US text/html https://analyticsindiamag.com/the-origin-of-neo4j/
Killexams : IBM earnings show solid growth but stock slides anyway

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.

Delivered on promises

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.”

Healthy pipeline

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.

Hybrid focus

“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.”

Dollar worries

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.”

Photo: SiliconANGLE

Show your support for our mission by joining our Cube Club and Cube Event Community of experts. Join the community that includes Amazon Web Services and Amazon.com CEO Andy Jassy, Dell Technologies founder and CEO Michael Dell, Intel CEO Pat Gelsinger and many more luminaries and experts.

Mon, 18 Jul 2022 12:15:00 -0500 en-US text/html https://siliconangle.com/2022/07/18/ibm-earnings-show-solid-growth-stock-slides-anyway/
Killexams : IT Consulting Services Market May See a Big Move | Fujitsu, IBM, Gartner

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.

Ask sample Report PDF @ https://www.advancemarketanalytics.com/sample-report/6525-global-it-consulting-services—procurement-market

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.

Influencing Market Trend

  • IT consulting services are helping organizations to manage their investment and technology and business strategies.

Market Drivers

  • Current trend on Generalization of business and operating module
  • Requirement of IT investment monitoring
  • Change in traditional IT solutions to computing solution
  • Transition in IT infrastructure to cloud computing infrastructure.

Opportunities:

  • Cloud Infrastructure prospective is projected to create market opportunities for the market manufacturers.

Challenges:

  • Changing and rigorous legislative and accreditation needs is the major challenge faced by this market.

For more data or any query mail at [email protected]

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

For More Query about the IT Consulting Services Market Report? Get in touch with us at: https://www.advancemarketanalytics.com/enquiry-before-buy/6525-global-it-consulting-services—procurement-market

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.

Basic Questions Answered
*who are the key market players in the IT Consulting Services Market?
*Which are the major regions for dissimilar trades that are expected to eyewitness astonishing growth for the
*What are the regional growth trends and the leading revenue-generating regions for the IT Consulting Services Market?
*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?

Examine Detailed Index of full Research Study [email protected]: https://www.advancemarketanalytics.com/reports/6525-global-it-consulting-services—procurement-market

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

Buy the Full Research report of Global IT Consulting Services [email protected]: https://www.advancemarketanalytics.com/buy-now?format=1&report=6525

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, Europe or Asia.

Contact US:
Craig Francis (PR & Marketing Manager)
AMA Research & Media LLP
Unit No. 429, Parsonage Road Edison, NJ
New Jersey USA – 08837
Phone: +1 (206) 317 1218
[email protected]

Connect with us at
https://www.linkedin.com/company/advance-market-analytics
https://www.facebook.com/AMA-Research-Media-LLP-344722399585916
https://twitter.com/amareport

Thu, 28 Jul 2022 20:22:00 -0500 Newsmantraa en-US text/html https://www.digitaljournal.com/pr/it-consulting-services-market-may-see-a-big-move-fujitsu-ibm-gartner
Killexams : Amentum Recognized as the Best Maximo Asset Data Governance Program at the 2022 MaximoWorld Conference

Amentum, a premier global government and private-sector partner supporting the most critical missions of government and commercial organizations worldwide, was awarded Best Maximo Asset Data Governance Program at the 2022 MaximoWorld Conference in Austin, TX, today for their work with Interloc Solutions, Inc. (Interloc) in optimizing data and decision making through a progressive and reliability centered data governance strategy. MaximoWorld, hosted by ReliabilityWeb.com, for over 20 years, has been the largest cross-industry gathering for Maximo users, partners, and subject matter experts.

AUSTIN, Texas, Aug. 9, 2022 /PRNewswire-PRWeb/ -- Amentum, a premier global government and private-sector partner supporting the most critical missions of government and commercial organizations worldwide, was awarded Best Maximo Asset Data Governance Program at the 2022 MaximoWorld Conference in Austin, TX, today for their work with Interloc Solutions, Inc. (Interloc) in optimizing data and decision making through a progressive and reliability centered data governance strategy. MaximoWorld, hosted by ReliabilityWeb.com, for over 20 years, has been the largest cross-industry gathering for Maximo users, partners, and subject matter experts.

Through an IBM Maximo Asset Management data governance strategy, elevated and enabled by Interloc's Mobility first philosophy to EAM, Amentum fosters excellent data quality, asset knowledge, and decision-making for its clients its clients around the world. By employing a program that enhances data quality through real-time visibility, and improved inspections and data readings, Amentum increases its asset knowledge, and predictive maintenance capabilities and analysis, giving its clients a proactive edge. Amentum's award-winning approach decreases mean time to repair (MTTR) and increases mean time between failures (MTBF) for its clients' key assets by taking advantage of the quality Maximo data gained via Mobile Informer and analyzing it through a robust data analytics platform.

Amentum's emphasis on mobility has also resulted in significant gains for its clients' sustainability initiatives. Mobile Informer's ability to eliminate reliance on paper-based procedures and immensely Improve data collection and quality led to one client in particular saving tens of thousands of dollars in annual paper, toner, and labor costs, as well as a near 20,000 lbs reduction in annual C02 emissions.

Data drives decision-making, and thanks to the powerful capabilities of and an innovative and progressive approach to Maximo, Amentum is making the best possible decisions based on the highest quality data for its clients around the world.

About Amentum

Headquartered in Germantown, Md., Amentum is a premier global services partner supporting critical programs of national significance across defense, security, intelligence, energy, commercial and environmental sectors. Amentum employs approximately 57,000 people on all seven continents and draws from a century-old heritage of operational excellence, mission focus, and successful execution. Amentum's reliability-centered and data-driven approach to asset management has proven successful at critical industrial and manufacturing facilities across various industries and facilities, such as pharmaceutical, life sciences, heavy industrial manufacturing, chemical refinement, aviation, automotive production, data centers, consumer production, industrial production, and more.

Learn more about Amentum at https://www.amentum.com/ .

About Interloc Solutions

Since 2005, Interloc Solutions, an IBM Gold Business Partner and the largest independent IBM Maximo Enterprise Asset Management systems integrator in North America, has been helping clients and partners realize the greatest potential from their Maximo investment, providing application hosting, innovative consulting, and managed services. Interloc has enhanced the implementation and adoption of Maximo through its transformative Mobile Informer solution, which is currently in use across a wide range of disciplines and industries— including U.S. Federal Agencies, Utilities, Transportation, Airport Operations, Manufacturing, Healthcare, and the Oil and Gas.

As a consulting organization of highly qualified technology and maintenance professionals, experienced in all versions of Maximo, Interloc excels in delivering comprehensive, best-practice Maximo EAM consulting services and mobile solutions.

Learn more about Interloc's award-winning services and solutions at http://www.interlocsolutions.com .

Media Contact

Scott Peluso, Interloc Solutions, 9168174590, info@interlocsolutions.com

SOURCE Interloc Solutions

© 2022 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.

Ad Disclosure: The rate information is obtained by Bankrate from the listed institutions. Bankrate cannot guaranty the accuracy or availability of any rates shown above. Institutions may have different rates on their own websites than those posted on Bankrate.com. The listings that appear on this page are from companies from which this website receives compensation, which may impact how, where, and in what order products appear. This table does not include all companies or all available products.

All rates are subject to change without notice and may vary depending on location. These quotes are from banks, thrifts, and credit unions, some of whom have paid for a link to their own Web site where you can find additional information. Those with a paid link are our Advertisers. Those without a paid link are listings we obtain to Improve the consumer shopping experience and are not Advertisers. To receive the Bankrate.com rate from an Advertiser, please identify yourself as a Bankrate customer. Bank and thrift deposits are insured by the Federal Deposit Insurance Corp. Credit union deposits are insured by the National Credit Union Administration.

Consumer Satisfaction: Bankrate attempts to verify the accuracy and availability of its Advertisers' terms through its quality assurance process and requires Advertisers to agree to our Terms and Conditions and to adhere to our Quality Control Program. If you believe that you have received an inaccurate quote or are otherwise not satisfied with the services provided to you by the institution you choose, please click here.

Rate collection and criteria: Click here for more information on rate collection and criteria.

Tue, 09 Aug 2022 04:15:00 -0500 text/html https://www.benzinga.com/pressreleases/22/08/n28421975/amentum-recognized-as-the-best-maximo-asset-data-governance-program-at-the-2022-maximoworld-confer
Killexams : AI Tech Stocks and the Growing Implementation in the Sports Market

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, Improve the player's health, and to Improve 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 Improve 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.

About Investorideas.com - News that Inspires Big Investing Ideas

Investorideas.com publishes breaking stock news, third party stock research, guest posts and original articles and podcasts in leading stock sectors. Learn about investing in stocks and get investor ideas in cannabis, crypto, AI and IoT, mining, sports biotech, water, renewable energy, gaming and more. Investor Idea's original branded content includes podcasts and columns : Crypto Corner , Play by Play sports and stock news , Investor Ideas Potcasts Cannabis News and Stocks on the Move podcast , Cleantech and Climate Change , Exploring Mining , Betting on Gaming Stocks Podcast and the AI Eye Podcast.

Disclaimer/Disclosure: Investorideas.com is a digital publisher of third party sourced news, articles and equity research as well as creates original content, including video, interviews and articles. Original content created by investorideas is protected by copyright laws other than syndication rights. Our site does not make recommendations for purchases or sale of stocks, services or products. Nothing on our sites should be construed as an offer or solicitation to buy or sell products or securities. All investing involves risk and possible losses. This site is currently compensated for news publication and distribution, social media and marketing, content creation and more. Disclosure is posted for each compensated news release, content published /created if required but otherwise the news was not compensated for and was published for the sole interest of our readers and followers. Contact management and IR of each company directly regarding specific questions. Disclosure: GTCH is a paid featured monthly AI stock on Investorideas.com More disclaimer info: https://www.investorideas.com/About/Disclaimer.asp Learn more about publishing your news release and our other news services on the Investorideas.com newswire https://www.investorideas.com/News-Upload/ Global investors must adhere to regulations of each country. Please read Investorideas.com privacy policy: https://www.investorideas.com/About/Private_Policy.asp

Follow us on Twitter https://twitter.com/Investorideas
Follow us on Facebook https://www.facebook.com/Investorideas
Follow us on YouTube https://www.youtube.com/c/Investorideas

Contact Investorideas.com
800-665-0411

To view the source version of this press release, please visit https://www.newsfilecorp.com/release/131475

Thu, 21 Jul 2022 23:10:00 -0500 en-US text/html https://finance.yahoo.com/news/ai-tech-stocks-growing-implementation-120000467.html
Killexams : AI Tech Stocks and the Growing Implementation in the Sports Market

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, Improve the player's health, and to Improve 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 Improve 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.

About Investorideas.com - News that Inspires Big Investing Ideas

Investorideas.com publishes breaking stock news, third party stock research, guest posts and original articles and podcasts in leading stock sectors. Learn about investing in stocks and get investor ideas in cannabis, crypto, AI and IoT, mining, sports biotech, water, renewable energy, gaming and more. Investor Idea's original branded content includes podcasts and columns : Crypto Corner , Play by Play sports and stock news , Investor Ideas Potcasts Cannabis News and Stocks on the Move podcast , Cleantech and Climate Change , Exploring Mining , Betting on Gaming Stocks Podcast and the AI Eye Podcast.

Disclaimer/Disclosure: Investorideas.com is a digital publisher of third party sourced news, articles and equity research as well as creates original content, including video, interviews and articles. Original content created by investorideas is protected by copyright laws other than syndication rights. Our site does not make recommendations for purchases or sale of stocks, services or products. Nothing on our sites should be construed as an offer or solicitation to buy or sell products or securities. All investing involves risk and possible losses. This site is currently compensated for news publication and distribution, social media and marketing, content creation and more. Disclosure is posted for each compensated news release, content published /created if required but otherwise the news was not compensated for and was published for the sole interest of our readers and followers. Contact management and IR of each company directly regarding specific questions. Disclosure: GTCH is a paid featured monthly AI stock on Investorideas.com More disclaimer info: https://www.investorideas.com/About/Disclaimer.asp Learn more about publishing your news release and our other news services on the Investorideas.com newswire https://www.investorideas.com/News-Upload/ Global investors must adhere to regulations of each country. Please read Investorideas.com privacy policy: https://www.investorideas.com/About/Private_Policy.asp

Follow us on Twitter https://twitter.com/Investorideas
Follow us on Facebook https://www.facebook.com/Investorideas
Follow us on YouTube https://www.youtube.com/c/Investorideas

Contact Investorideas.com
800-665-0411

To view the source version of this press release, please visit https://www.newsfilecorp.com/release/131475

Thu, 21 Jul 2022 01:18:00 -0500 en-CA text/html https://ca.news.yahoo.com/ai-tech-stocks-growing-implementation-120000467.html 000-590 exam dump and training guide direct download
Training Exams List