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Emma Okonji

The federal government through the Ministry of Communications and Digital Economy, has signed a memorandum of understanding (MoU) with Tech giant, International Business Machines (IBM) West Africa.

The deal is for partnership and collaboration in the area of digital skills development in Nigeria.

The Minister of Communications and Digital Economy, Dr. Isa Pantami, who signed on behalf of the federal government, said the partnership would deliver impetus to the digital, innovation and entrepreneurship skills of the economic development plan of President Muhammadu Buhari.

He described the partnership as a quantum leap in the digital economy strategy of the ministry. 

The MoU, which was signed in Abuja recently, is scheduled to take off in February 2020.

The MoU provides a platform to empower Nigerian youths with digital literacy skills, enable innovation, design and development of indigenous solutions, self -sufficiency and make Nigeria a hub for critical skills for Africa and the world at large. 

Under the partnership, and in line with the Digital Literacy initiative and drive of the Minister, IBM would through its Digital Nation Africa Initiative, provide free training to Nigerians for a period of 12 to 16 weeks, in diverse areas of Information Technology (IT). 

The MoU seeks to create awareness and support in the development and use of digital tools and applications to Excellerate the delivery of government services; create a pool of Nigerians with digital skills validated by globally recognised certifications; bridge the gap between the academia and the industry through sensitisation on digital tools and skills; and lower the access barrier to digital tools for the citizens.

Addressing IBM representatives led by the Country General Manager, Pantami expressed satisfaction at the organisation’s response to the digital economy policy by, sufficiently keying in, to bridge the divide between the academia and the industry, education and entrepreneurship. 

Pantami noted that, “to achieve a digital economy, digital skills are central, and this has been adequately captured in the second pillar of the Digital Economy Strategy Policy Document as approved and launched by the President on the 28th of November 2019.”

The minister further disclosed that the importance of broadband in the implementation of a digital economy is the life line to its success and this again has been reflected in the seventh pillar of the strategy document. 

“The importance of broadband penetration in achieving a digital economy has given rise to the National Broadband Committee to ensure that we thoroughly address the impediments to broadband penetration and achieving a Digital Economy,” Pantami said.

The minister urged institutions of learning to deliver priority to skills, especially digital skills over paper qualifications. 

According to him, “Digital skills are more relevant in today’s world of emerging technologies, therefore we must encourage innovation and drive digital literacy and skills among the populace.”

In his remarks, the Country General Manager at IBM, Mr. Dipo Faulkner, said: “IBM works with governments and key Ministries to address the societal impact of digital technology, leveraging our investment in education with platforms such as IBM Digital Nation Africa. This new collaboration furthers our aims of scaling digital job skills across Africa.”

Tue, 12 Jul 2022 12:00:00 -0500 en-US text/html https://www.thisdaylive.com/index.php/2020/01/20/fg-ibm-sign-mou-for-digital-skill-development/
Killexams : Joining The RISC-V Ranks: IBM’s Power ISA To Become Free

IBM’s Power processor architecture is probably best known today as those humongous chips that power everything from massive mainframes and supercomputers to slightly less massive mainframes and servers. Originally developed in the 1980s, Power CPUs have been a reliable presence in the market for decades, forming the backbone of systems like IBM’s RS/6000 and AS/400 and later line of Power series.

Now IBM is making the Power ISA free to use after first opening up access to the ISA with the OpenPower Foundation. Amidst the fully free and open RISC-V ISA making headway into the computing market, and ARM feeling pressured to loosen up its licensing, it seems they figured that it’s best to join the party early. Without much of a threat to its existing business customers who are unlikely to whip up their own Power CPUs in a back office and not get IBM’s support that’s part of the business deal, it seems mostly aimed at increasing Power’s and with it IBM’s foothold in the overall market.

The Power ISA started out as the POWER ISA, before it evolved into the PowerPC ISA, co-developed with Motorola  and Apple and made famous by Apple’s use of the G3 through G5 series of PowerPC CPUs. The PowerPC ISA eventually got turned into today’s Power ISA. As a result it shares many commonalities with both POWER and PowerPC, being its de facto successor.

In addition, IBM is also opening its OpenCAPI accelerator and OpenCAPI Memory Interface variant that will be part of the upcoming Power9′ CPU. These technologies are aimed at reducing the number of interconnections required to link CPUs together, ranging from NVLink, to Infinity Fabric and countless more, not to mention memory, where OMI memory could offer interesting possibilities.

Would you use Power in your projects? Let us know in the comments.

Fri, 05 Aug 2022 12:00:00 -0500 Maya Posch en-US text/html https://hackaday.com/2019/08/23/joining-the-risc-v-ranks-ibms-power-isa-to-become-free/
Killexams : How this Database Company started from IIT Bombay

“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 database was structured and sketched on a napkin on a flight to Bombay by an intern, alongside Emil Eifrem—who is the founder and CEO of Neo4j—where they worked together to create the first code for its 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.

Sun, 07 Aug 2022 22:30:00 -0500 en-US text/html https://analyticsindiamag.com/the-origin-of-neo4j/
Killexams : Amazon, IBM Move Swiftly on Post-Quantum Cryptographic Algorithms Selected by NIST

A month after the National Institute of Standards and Technology (NIST) revealed the first quantum-safe algorithms, Amazon Web Services (AWS) and IBM have swiftly moved forward. Google was also quick to outline an aggressive implementation plan for its cloud service that it started a decade ago.

It helps that IBM researchers contributed to three of the four algorithms, while AWS had a hand in two. Google contributed to one of the submitted algorithms, SPHINCS+.

A long process that started in 2016 with 69 original candidates ends with the selection of four algorithms that will become NIST standards, which will play a critical role in protecting encrypted data from the vast power of quantum computers.

NIST's four choices include CRYSTALS-Kyber, a public-private key-encapsulation mechanism (KEM) for general asymmetric encryption, such as when connecting websites. For digital signatures, NIST selected CRYSTALS-Dilithium, FALCON, and SPHINCS+. NIST will add a few more algorithms to the mix in two years.

Vadim Lyubashevsky, a cryptographer who works in IBM's Zurich Research Laboratories, contributed to the development of CRYSTALS-Kyber, CRYSTALS-Dilithium, and Falcon. Lyubashevsky was predictably pleased by the algorithms selected, but he had only anticipated NIST would pick two digital signature candidates rather than three.

Ideally, NIST would have chosen a second key establishment algorithm, according to Lyubashevsky. "They could have chosen one more right away just to be safe," he told Dark Reading. "I think some people expected McEliece to be chosen, but maybe NIST decided to hold off for two years to see what the backup should be to Kyber."

IBM's New Mainframe Supports NIST-Selected Algorithms

After NIST identified the algorithms, IBM moved forward by specifying them into its recently launched z16 mainframe. IBM introduced the z16 in April, calling it the "first quantum-safe system," enabled by its new Crypto Express 8S card and APIs that provide access to the NIST APIs.

IBM was championing three of the algorithms that NIST selected, so IBM had already included them in the z16. Since IBM had unveiled the z16 before the NIST decision, the company implemented the algorithms into the new system. IBM last week made it official that the z16 supports the algorithms.

Anne Dames, an IBM distinguished engineer who works on the company's z Systems team, explained that the Crypto Express 8S card could implement various cryptographic algorithms. Nevertheless, IBM was betting on CRYSTAL-Kyber and Dilithium, according to Dames.

"We are very fortunate in that it went in the direction we hoped it would go," she told Dark Reading. "And because we chose to implement CRYSTALS-Kyber and CRYSTALS-Dilithium in the hardware security module, which allows clients to get access to it, the firmware in that hardware security module can be updated. So, if other algorithms were selected, then we would add them to our roadmap for inclusion of those algorithms for the future."

A software library on the system allows application and infrastructure developers to incorporate APIs so that clients can generate quantum-safe digital signatures for both classic computing systems and quantum computers.

"We also have a CRYSTALS-Kyber interface in place so that we can generate a key and provide it wrapped by a Kyber key so that could be used in a potential key exchange scheme," Dames said. "And we've also incorporated some APIs that allow clients to have a key exchange scheme between two parties."

Dames noted that clients might use Kyber to generate digital signatures on documents. "Think about code signing servers, things like that, or documents signing services, where people would like to actually use the digital signature capability to ensure the authenticity of the document or of the code that's being used," she said.

AWS Engineers Algorithms Into Services

During Amazon's AWS re:Inforce security conference last week in Boston, the cloud provider emphasized its post-quantum cryptography (PQC) efforts. According to Margaret Salter, director of applied cryptography at AWS, Amazon is already engineering the NIST standards into its services.

During a breakout session on AWS' cryptography efforts at the conference, Salter said AWS had implemented an open source, hybrid post-quantum key exchange based on a specification called s2n-tls, which implements the Transport Layer Security (TLS) protocol across different AWS services. AWS has contributed it as a draft standard to the Internet Engineering Task Force (IETF).

Salter explained that the hybrid key exchange brings together its traditional key exchanges while enabling post-quantum security. "We have regular key exchanges that we've been using for years and years to protect data," she said. "We don't want to get rid of those; we're just going to enhance them by adding a public key exchange on top of it. And using both of those, you have traditional security, plus post quantum security."

Last week, Amazon announced that it deployed s2n-tls, the hybrid post-quantum TLS with CRYSTALS-Kyber, which connects to the AWS Key Management Service (AWS KMS) and AWS Certificate Manager (ACM). In an update this week, Amazon documented its stated support for AWS Secrets Manager, a service for managing, rotating, and retrieving database credentials and API keys.

Google's Decade-Long PQC Migration

While Google didn't make implementation announcements like AWS in the immediate aftermath of NIST's selection, VP and CISO Phil Venables said Google has been focused on PQC algorithms "beyond theoretical implementations" for over a decade. Venables was among several prominent researchers who co-authored a technical paper outlining the urgency of adopting PQC strategies. The peer-reviewed paper was published in May by Nature, a respected journal for the science and technology communities.

"At Google, we're well into a multi-year effort to migrate to post-quantum cryptography that is designed to address both immediate and long-term risks to protect sensitive information," Venables wrote in a blog post published following the NIST announcement. "We have one goal: ensure that Google is PQC ready."

Venables recalled an experiment in 2016 with Chrome where a minimal number of connections from the Web browser to Google servers used a post-quantum key-exchange algorithm alongside the existing elliptic-curve key-exchange algorithm. "By adding a post-quantum algorithm in a hybrid mode with the existing key exchange, we were able to test its implementation without affecting user security," Venables noted.

Google and Cloudflare announced a "wide-scale post-quantum experiment" in 2019 implementing two post-quantum key exchanges, "integrated into Cloudflare's TLS stack, and deployed the implementation on edge servers and in Chrome Canary clients." The experiment helped Google understand the implications of deploying two post-quantum key agreements with TLS.

Venables noted that last year Google tested post-quantum confidentiality in TLS and found that various network products were not compatible with post-quantum TLS. "We were able to work with the vendor so that the issue was fixed in future firmware updates," he said. "By experimenting early, we resolved this issue for future deployments."

Other Standards Efforts

The four algorithms NIST announced are an important milestone in advancing PQC, but there's other work to be done besides quantum-safe encryption. The AWS TLS submission to the IETF is one example; others include such efforts as Hybrid PQ VPN.

"What you will see happening is those organizations that work on TLS protocols, or SSH, or VPN type protocols, will now come together and put together proposals which they will evaluate in their communities to determine what's best and which protocols should be updated, how the certificates should be defined, and things like things like that," IBM's Dames said.

Dustin Moody, a mathematician at NIST who leads its PQC project, shared a similar view during a panel discussion at the RSA Conference in June. "There's been a lot of global cooperation with our NIST process, rather than fracturing of the effort and coming up with a lot of different algorithms," Moody said. "We've seen most countries and standards organizations waiting to see what comes out of our nice progress on this process, as well as participating in that. And we see that as a very good sign."

Thu, 04 Aug 2022 10:39:00 -0500 en text/html https://www.darkreading.com/dr-tech/amazon-ibm-move-swiftly-on-post-quantum-cryptographic-algorithms-selected-by-nist
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, 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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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 : Can IBM Get Back Into HPC With Power10?

The “Cirrus” Power10 processor from IBM, which we codenamed for Big Blue because it refused to do it publicly and because we understand the value of a synonym here at The Next Platform, shipped last September in the “Denali” Power E1080 big iron NUMA machine. And today, the rest of the Power10-based Power Systems product line is being fleshed out with the launch of entry and midrange machines – many of which are suitable for supporting HPC and AI workloads as well as in-memory databases and other workloads in large enterprises.

The question is, will IBM care about traditional HPC simulation and modeling ever again with the same vigor that it has in past decades? And can Power10 help reinvigorate the HPC and AI business at IBM. We are not sure about the answer to the first question, and got the distinct impression from Ken King, the general manager of the Power Systems business, that HPC proper was not a high priority when we spoke to him back in February about this. But we continue to believe that the Power10 platform has some attributes that make it appealing for data analytics and other workloads that need to be either scaled out across small machines or scaled up across big ones.

Today, we are just going to talk about the five entry Power10 machines, which have one or two processor sockets in a standard 2U or 4U form factor, and then we will follow up with an analysis of the Power E1050, which is a four socket machine that fits into a 4U form factor. And the question we wanted to answer was simple: Can a Power10 processor hold its own against X86 server chips from Intel and AMD when it comes to basic CPU-only floating point computing.

This is an important question because there are plenty of workloads that have not been accelerated by GPUs in the HPC arena, and for these workloads, the Power10 architecture could prove to be very interesting if IBM thought outside of the box a little. This is particularly true when considering the feature called memory inception, which is in effect the ability to build a memory area network across clusters of machines and which we have discussed a little in the past.

We went deep into the architecture of the Power10 chip two years ago when it was presented at the Hot Chip conference, and we are not going to go over that ground again here. Suffice it to say that this chip can hold its own against Intel’s current “Ice Lake” Xeon SPs, launched in April 2021, and AMD’s current “Milan” Epyc 7003s, launched in March 2021. And this makes sense because the original plan was to have a Power10 chip in the field with 24 fat cores and 48 skinny ones, using dual-chip modules, using 10 nanometer processes from IBM’s former foundry partner, Globalfoundries, sometime in 2021, three years after the Power9 chip launched in 2018. Globalfoundries did not get the 10 nanometer processes working, and it botched a jump to 7 nanometers and spiked it, and that left IBM jumping to Samsung to be its first server chip partner for its foundry using its 7 nanometer processes. IBM took the opportunity of the Power10 delay to reimplement the Power ISA in a new Power10 core and then added some matrix math overlays to its vector units to make it a good AI inference engine.

IBM also created a beefier core and dropped the core count back to 16 on a die in SMT8 mode, which is an implementation of simultaneous multithreading that has up to eight processing threads per core, and also was thinking about an SMT4 design which would double the core count to 32 per chip. But we have not seen that today, and with IBM not chasing Google and other hyperscalers with Power10, we may never see it. But it was in the roadmaps way back when.

What IBM has done in the entry machines is put two Power10 chips inside of a single socket to increase the core count, but it is looking like the yields on the chips are not as high as IBM might have wanted. When IBM first started talking about the Power10 chip, it said it would have 15 or 30 cores, which was a strange number, and that is because it kept one SMT8 core or two SMT4 cores in reserve as a hedge against bad yields. In the products that IBM is rolling out today, mostly for its existing AIX Unix and IBM i (formerly OS/400) enterprise accounts, the core counts on the dies are much lower, with 4, 8, 10, or 12 of the 16 cores active. The Power10 cores have roughly 70 percent more performance than the Power9 cores in these entry machines, and that is a lot of performance for many enterprise customers – enough to get through a few years of growth on their workloads. IBM is charging a bit more for the Power10 machines compared to the Power9 machines, according to Steve Sibley, vice president of Power product management at IBM, but the bang for the buck is definitely improving across the generations. At the very low end with the Power S1014 machine that is aimed at small and midrange businesses running ERP workloads on the IBM i software stack, that improvement is in the range of 40 percent, deliver or take, and the price increase is somewhere between 20 percent and 25 percent depending on the configuration.

Pricing is not yet available on any of these entry Power10 machines, which ship on July 22. When we find out more, we will do more analysis of the price/performance.

There are six new entry Power10 machines, the feeds and speeds of which are shown below:

For the HPC crowd, the Power L1022 and the Power L1024 are probably the most interesting ones because they are designed to only run Linux and, if they are like prior L classified machines in the Power8 and Power9 families, will have lower pricing for CPU, memory, and storage, allowing them to better compete against X86 systems running Linux in cluster environments. This will be particularly important as IBM pushed Red Hat OpenShift as a container platform for not only enterprise workloads but also for HPC and data analytic workloads that are also being containerized these days.

One thing to note about these machines: IBM is using its OpenCAPI Memory Interface, which as we explained in the past is using the “Bluelink” I/O interconnect for NUMA links and accelerator attachment as a memory controller. IBM is now calling this the Open Memory Interface, and these systems have twice as many memory channels as a typical X86 server chip and therefore have a lot more aggregate bandwidth coming off the sockets. The OMI memory makes use of a Differential DIMM form factor that employs DDR4 memory running at 3.2 GHz, and it will be no big deal for IBM to swap in DDR5 memory chips into its DDIMMs when they are out and the price is not crazy. IBM is offering memory features with 32 GB, 64 GB, and 128 GB capacities today in these machines and will offer 256 GB DDIMMs on November 14, which is how you get the maximum capacities shown in the table above. The important thing for HPC customers is that IBM is delivering 409 GB/sec of memory bandwidth per socket and 2 TB of memory per socket.

By the way, the only storage in these machines is NVM-Express flash drives. No disk, no plain vanilla flash SSDs. The machines also support a mix of PCI-Express 4.0 and PCI-Express 5.0 slots, and do not yet support the CXL protocol created by Intel and backed by IBM even though it loves its own Bluelink OpenCAPI interconnect for linking memory and accelerators to the Power compute engines.

Here are the different processor SKUs offered in the Power10 entry machines:

As far as we are concerned, the 24-core Power10 DCM feature EPGK processor in the Power L1024 is the only interesting one for HPC work, aside from what a theoretical 32-core Power10 DCM might be able to do. And just for fun, we sat down and figured out the peak theoretical 64-bit floating point performance, at all-core base and all-core turbo clock speeds, for these two Power10 chips and their rivals in the Intel and AMD CPU lineups. Take a gander at this:

We have no idea what the pricing will be for a processor module in these entry Power10 machines, so we took a stab at what the 24-core variant might cost to be competitive with the X86 alternatives based solely on FP64 throughput and then reckoned the performance of what a full-on 32-core Power10 DCM might be.

The answer is that IBM can absolutely compete, flops to flops, with the best Intel and AMD have right now. And it has a very good matrix math engine as well, which these chips do not.

The problem is, Intel has “Sapphire Rapids” Xeon SPs in the works, which we think will have four 18-core chiplets for a total of 72 cores, but only 56 of them will be exposed because of yield issues that Intel has with its SuperFIN 10 nanometer (Intel 7) process. And AMD has 96-core “Genoa” Epyc 7004s in the works, too. Power11 is several years away, so if IBM wants to play in HPC, Samsung has to get the yields up on the Power10 chips so IBM can sell more cores in a box. Big Blue already has the memory capacity and memory bandwidth advantage. We will see if its L-class Power10 systems can compete on price and performance once we find out more. And we will also explore how memory clustering might make for a very interesting compute platform based on a mix of fat NUMA and memory-less skinny nodes. We have some ideas about how this might play out.

Mon, 11 Jul 2022 12:01:00 -0500 Timothy Prickett Morgan en-US text/html https://www.nextplatform.com/2022/07/12/can-ibm-get-back-into-hpc-with-power10/
Killexams : EdTech and Smart Classrooms Market Analysis by Size, Share, Key Players, Growth, Trends & Forecast 2027

"Apple (US), Cisco (US), Blackboard (US), IBM (US), Dell EMC (US),Google (US), Microsoft (US), Oracle(US),SAP (Germany), Instructure(US)."

EdTech and Smart Classrooms Market by Hardware (Interactive Displays, Interactive Projectors), Education System Solution (LMS, TMS, DMS, SRS, Test Preparation, Learning & Gamification), Deployment Type, End User and Region - Global Forecast to 2027

MarketsandMarkets forecasts the global EdTech and Smart Classrooms Market to grow from USD 125.3 billion in 2022 to USD 232.9  billion by 2027, at a Compound Annual Growth Rate (CAGR) of 13.2% during the forecast period. The major factors driving the growth of the EdTech and smart classrooms market include increasing penetration of mobile devices and easy availability of internet, and growing demand for online teaching-learning models, impact of COVID-19 pandemic and growing need for EdTech solutions to keep education system running.

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Interactive Displays segment to hold the highest market size during the forecast period

Interactive displays helps to collaborate teaching with tech boost social learning. As per a study it has been discovered that frequent group activity in classrooms, often aided by technology, can result in 20% higher levels of social-emotional skill development. Students in these classes are also 13% more likely to feel confident contributing to class discussions. Interactive display encourages the real time collaboration. SMART Boards facilitate the necessary collaboration for students to develop these skills. Creating an audience response system on the interactive display allows students to use devices to participate in class surveys, quizzes, and games, and then analyse the results in real time. A large interactive whiteboard (IWB), also known as an interactive board or a smart board, is a large interactive display board in the shape of a whiteboard. It can be a standalone touchscreen computer used to perform tasks and operations on its own, or it can be a connectable apparatus used as a touchpad to control computers from a projector. They are used in a variety of settings, such as classrooms at all levels of education, corporate board rooms and work groups, professional sports coaching training rooms, broadcasting studios, and others.

Cloud deployment type to record the fastest growth rate during the forecast period

Technology innovation has provided numerous alternative solutions for businesses of all sizes to operate more efficiently. Cloud has emerged as a new trend in data centre administration. The cloud eliminates the costs of purchasing software and hardware, setting up and running data centres, such as electricity expenses for power and cooling of servers, and high-skilled IT resources for infrastructure management. Cloud services are available on demand and can be configured by a single person in a matter of minutes. Cloud provides dependability by storing multiple copies of data on different servers. The cloud is a potential technological creation that fosters change for its users. Cloud computing is an information technology paradigm that delivers computing services via the Internet by utilizing remote servers, database systems, networking, analytics, storage systems, software, and other digital facilities. Cloud computing has significant benefits for higher education, particularly for students transitioning from K-12 to university. Teachers can easily deliver online classes and engage their students in various programs and online projects by utilizing cloud technology in education. Cloud-based deployment refers to the hosted-type deployment of the game-based learning solution. There has been an upward trend in the deployment of the EdTech solution via cloud or dedicated data center infrastructure. The advantages of hosted deployment include reduced physical infrastructure, lower maintenance costs, 24×7 accessibility, and effective analysis of electronic business content. The cloud-based deployment of EdTech solution is crucial as it offers a flexible and scalable infrastructure to handle multiple devices and analyze ideas from employees, customers, and partners.

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Major EdTech and smart classrooms vendors include Apple (US), Cisco (US),  Blackboard (US), IBM (US), Dell EMC (US), Google (US), Microsoft (US), Oracle(US), SAP (Germany), Instructure(US). These market players have adopted various growth strategies, such as partnerships, agreements, and collaborations, and new product enhancements to expand their presence in the EdTech and smart classrooms market. Product enhancements and collaborations have been the most adopted strategies by major players from 2018 to 2020, which helped companies innovate their offerings and broaden their customer base.

A prominent player in the EdTech and smart classrooms market, Apple focuses on inorganic growth strategies such as partnerships, collaborations, and acquisitions. For instance, in August 2021 Apple launched Mobile Student ID through which students will be able to navigate campus and make purchases using mobile student IDs on the iPhone and Apple Watch. In July 2020 Apple partnered with HBCUs to offer innovative opportunities for coding to communities across the US. Apple deepened the partnership with an additional 10 HBCUs regional coding centers under its Community Education Initiative. The main objective of this partnership is to bring coding, creativity, and workforce development opportunities to learners of all ages. Apple offers software as well as hardware to empower educators with powerful products and tools. Apple offers several applications for K-12 education, including Schoolwork and Classroom. The company also offers AR in education to provide a better learning experience. Teaching tools helps to simplify teaching tasks with apps that make the classroom more flexible, collaborative, and personalized for each student. Apple has interactive guide that makes it easy to stay on task and organized while teaching remotely with iPad. The learning apps helps to manage schedules and screen time to minimize the distractions and also helps to create productive learning environments and make device set up easy for teachers and parents. Apple has various products, such as Macintosh, iPhone, iPad, wearables, and services. It has an intelligent software assistant named Siri, which has cloud-synchronized data with iCloud.

Blackboard has a vast product portfolio with diverse offerings across four divisions: K-12, higher education, government, and business. Under the K-12 division, the company offers products such as LMS, Synchronous Collaborative Learning, Learning Object Repository, Web Community Manager, Mass Notifications, Mobile Communications Application, Teacher Communication, Social Media Manager, and Blackboard Ally. Its solutions include Blackboard Classroom, Collaborate Starter, and Personalized Learning. Blackboard’s higher education division products include Blackboard Learn, Blackboard Collaborate, Analytics for Learn, Blackboard Intelligence, Blackboard Predict, Outcomes and Assessments, X-ray for Learning Analytics, Blackboard Connect, Blackboard Instructor, Moodlerooms, Blackboard Transact, Blackboard Ally, and Blackboard Open Content. The company also provides services, such as student pathway services, marketing, and recruiting, help desk services, enrollment management, financial aid and student services, engagement campaigns, student retention, training and implementation services, strategic consulting, and analytics consulting services. Its teaching and learning solutions include LMS, education analytics, web conferencing, mobile learning, open-source learning, training and implementation, virtual classroom, and competency-based education. Blackboard also offers campus enablement solutions such as payment solutions, security solutions, campus store solutions, and transaction solutions. Under the government division, it offers solutions such as LMS, registration and reporting, accessibility, collaboration and web conferencing, mass notifications and implementation, and strategic consulting. The company has launched Blackboard Unite on April 2020 for K-12. This solution compromises a virtual classroom, learning management system, accessibility tool, mobile app, and services and implementation kit to help emote learning efforts.

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Killexams : Cloud Augmented Intelligence Market – Major Technology Giants in Buzz Again | MicroStrategy, SAP, IBM, SAS, CognitiveScale

Advance Market Analytics published a new research publication on “Cloud Augmented Intelligence Market Insights, to 2027” with 232 pages and enriched with self-explained Tables and charts in presentable format. In the Study you will find new evolving Trends, Drivers, Restraints, Opportunities generated by targeting market associated stakeholders. The growth of the Cloud Augmented Intelligence market was mainly driven by the increasing R&D spending across the world.

Get Free Exclusive PDF sample Copy of This Research @ https://www.advancemarketanalytics.com/sample-report/200211-global-cloud-augmented-intelligence-market#utm_source=DigitalJournalLal

Some of the key players profiled in the study are: AWS (United States), Microsoft (United States), Salesforce (United States), SAP (Germany), IBM (United States), SAS (United States), CognitiveScale (United States), QlikTech International (United States), TIBCO (United States), Google (United States), MicroStrategy (United States) and Sisense (United States).

Scope of the Report of Cloud Augmented Intelligence
The global market for cloud augmented intelligence is growing as organisations increasingly leverage cutting-edge technologies like big data, block chain, artificial intelligence, and the internet of things to meet customer expectations. Additionally, the market’s expansion is positively impacted by the spike in demand for business intelligence products. However, factors including software implementation challenges and a shortage of cloud augmented intelligence specialists are anticipated to restrain market expansion. In contrast, it is anticipated that throughout the forecast period, significant companies would advance their use of augmented intelligence solutions and the volume and variety of data will expand within an automated process, providing lucrative chances for the market’s growth.

The titled segments and sub-section of the market are illuminated below:

by Technology (Machine Learning, Natural Language Processing, Computer Vision, Others), Industry Vertical (IT & Telecom, Retail & E-Commerce, BFSI, Healthcare, Manufacturing, Automotive, Others), Component (Software, Service), Organisation Size (Small & Medium, Large) Players and Region – Global Market Outlook to 2027

Opportunities:
Solutions for Cloud Augmented Intelligence Are Widely Used By SMES
Increased Use of Technology for Machine Learning, Artificial Intelligence, and Natural Language Processing

Market Drivers:
A Growing Amount of Sophisticated Corporate Data
Expanding Use of Cutting-Edge Cloud Augmented Intelligence and Analytics Tools

Have Any Questions Regarding Global Cloud Augmented Intelligence Market Report, Ask Our [email protected] https://www.advancemarketanalytics.com/enquiry-before-buy/200211-global-cloud-augmented-intelligence-market#utm_source=DigitalJournalLal

Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & Africa

Country Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc.

Latest Market Insights:

In January 2022, Microsoft Corp. announced its plans to acquire Activision Blizzard Inc., a leader in game development and interactive entertainment content publisher. This acquisition will accelerate the growth in Microsoft’s gaming business across mobile, PC, console and cloud and will provide building blocks for the met averse.

In March 2022, Schlumberger partnered with Dataiku to provide customers with a single, centralized platform for designing, deploying, governing, and managing AI and analytics applications, allowing everyday users to create low-code no-code AI solutions. and In April 2021, Oracle made its GoldenGate technology available as a highly automated, fully managed cloud service that clients can use to help ensure that their valuable data is always available and analyzable in real-time, wherever they need it.

Strategic Points Covered in Table of Content of Global Cloud Augmented Intelligence Market:

Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the Cloud Augmented Intelligence market

Chapter 2: Exclusive Summary – the basic information of the Cloud Augmented Intelligence Market.

Chapter 3: Displaying the Market Dynamics- Drivers, Trends and Challenges & Opportunities of the Cloud Augmented Intelligence

Chapter 4: Presenting the Cloud Augmented Intelligence Market Factor Analysis, Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.

Chapter 5: Displaying the by Type, End User and Region/Country 2015-2020

Chapter 6: Evaluating the leading manufacturers of the Cloud Augmented Intelligence market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile

Chapter 7: To evaluate the market by segments, by countries and by Manufacturers/Company with revenue share and sales by key countries in these various regions (2021-2027)

Chapter 8 & 9: Displaying the Appendix, Methodology and Data Source

finally, Cloud Augmented Intelligence Market is a valuable source of guidance for individuals and companies.

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Mon, 01 Aug 2022 19:24:00 -0500 Newsmantraa en-US text/html https://www.digitaljournal.com/pr/cloud-augmented-intelligence-market-major-technology-giants-in-buzz-again-microstrategy-sap-ibm-sas-cognitivescale
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, 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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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

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Thu, 21 Jul 2022 01:18:00 -0500 en-CA text/html https://ca.news.yahoo.com/ai-tech-stocks-growing-implementation-120000467.html A2010-590 exam dump and training guide direct download
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