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Processors and graphics cards continue to sell well, but in the context of the energy transition and the call for more sustainability, electric cars, new house insulation and organic shoes are also in demand. But does that have to be all? It is also environmentally friendly if you continue to use your previous belongings instead of replacing them a brief overview of the most important messages.

Although the second quarter has traditionally been rather weak, the three big chip manufacturers have Intel, Nvidia and AMD further increased their sales figures. Despite the lack of chips, sales of CPUs and graphics cards continue to rise. Intel was able to assert itself as the market leader, but Nvidia increased its market share for graphics cards a little.

These Consumer culture is also evident in other areas. A survey on the personal participation in the protection of future human habitat shows what the respondents bought. New electric cars. New house insulation. New organic shoes. New e-bikes. New bamboo straws. New zinc sheet watering cans. the The downside is missing, the garbage behind it. The Missing Link is about overconsumption and false consumption promises: Dont buy an electric car!

Not bought, but supposedly with one Malware steals bitcoins did two years ago british youngsters. With a Civil action an American wants to regain these 16 bitcoins. At the time of the theft, the two alleged perpetrators were still minors and lived with their parents. After the loss of 16 bitcoins, the stolen person also sued the parents of the alleged thieves.

Microsofts cloud service Azure was not infested with malware, but apparently offered one security breach, through which unauthorized persons could gain full access to the customers cloud databases. Microsoft says it has closed the gap in the meantime, but affected customers should take action themselves to prevent unauthorized access. After the cloud database disaster, Microsoft has therefore informed its Azure customers about the serious gap.

In contrast to the Azure vulnerability, which has not had any consequences so far, the most recent Break into the servers of T-Mobile US above 50 million customer data stolen. The system made it easy for the hacker, he himself explains in a letter to the press. Cracking the defense mechanisms of the US Telecom subsidiary cost him little effort. The hacker used a devastating security hole for the data breach at T-Mobile US.

A devastating development is also becoming apparent in the coronavirus pandemic, because the number of nationwide Covid-19 patients treated in intensive care units is in the fourth corona wave rose above 1000 for the first time. In the DIVI Register daily report on Sunday, 1008 Covid 19 patients were reported in intensive care, 485 of whom had to be ventilated. The low was 354 on July 22nd. Since then, the occupancy has increased again, so that the number of Covid-19 patients in intensive care units has risen again to over 1000.

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Monday: Hardware & consumption boom, Bitcoin theft, cloud & T-Mobile gaps - Market Research Telecast

August 30, 2021Alex Woodie

Every now and then, a technology emerges that lifts up everything around it. GraphQL has the potential to be a technology like that, and thats good news for customers running older, established applications, such as those that run on IBM iron.

IBMs mainframe and its midrange IBM i server often are maligned as old, washed-up, legacy platforms, but people who say that are missing a key distinction: its usually not the server thats old. In most cases, its the application that was first deployed in the Clinton Administration (or earlier) that is the problem.

Companies typically have many reasons for why they havent modernized applications or migrated to something newer. For starter, the applications just work. And, despite the changing technological winds around us, the fact that these applications continue to do what they were originally designed to do process transactions reliably and securely, day in and day out, often for years on end, without much maintenance is not a trivial thing, nor is it something to fool around with. If it aint broke, dont fix it probably best encapsulates this attitude.

You were supposed to abandon these monolithic applications in favor of client-server architectures 30 years ago. In the late 1990s, you were supposed to migrate your RPG and COBOL code to Java, per IBMs request. The explosion of the World Wide Web in the early 2000s provided another logical architecture to build to, followed by the growth of smart devices after the iPhones appearance in 2007. Today, everybody aspires to run their applications as containerized microservices in the cloud, which surely is the pinnacle of digital existence.

After all these boundary-shaking technological inflection points, its a wonder that mainframes and IBM i servers even at exist at this point. But of course, despite all the best laid plans to accelerate their demise, they do (as you, dear IT Jungle reader, know all too well).

So what does all this have to do with GraphQL? We first wrote about the technology in March 2020, just before the COVID pandemic hit (so perhaps you missed it).

GraphQL, in short, is a query language and runtime that was originally created at Facebook in 2012 and open sourced in 2015. Facebook developers, tired of maintaining all of the repetitive and brittle REST code needed to pull data out of backend servers to feed to mobile clients, desired an abstraction layer that could insulate them from REST and accelerate development. The result was GraphQL, which continues to serve data to Facebooks mobile clients to this day.

Since it was open source, GraphQL adoption has grown exponentially, if downloads of the open source technology mean anything. According to Geoff Schmidt, the chief executive officer and co-founder of GraphQL-backer Apollo, says 30 percent of the Fortune 500 have adopted Apollo tools to manage their growing GraphQL estates.

Following Apollos recent Series D funding round, which netted the San Francisco company $130 million at a $1.5 billion valuation, Schmidt is quite excited about the potential for GraphQL to alleviate technical burdens for enterprises with lots of systems to integrate, including monolithic applications running on mainframes.

Frankly, there are great use cases around mainframe systems or COBOL systems, Schmidt says. You just slide this graph layer in between the mainframe and the mobile app, and you dont have to change anything. You just get that layer in there, start moving the traffic over to GraphQL and route it all through the graph.

Once the GraphQL layer is inserted between the backend systems and the front-end interfaces, front-end developers have much more freedom to develop the compelling app experiences, without going to the backend developer to tweak a REST API. In addition to accelerating the developers productivity, it also insulates the backend system from changes.

Once you put that abstraction layer in place, not only can you combine all that stuff and get it to every platform in a very agile, fast manner, Schmidt tells IT Jungle, but at the same time, if you want to refactor thatif you have a monolithic backend that you want to move into microservices, or you just want to change how the back is architected you can now do that without having to disturb all those clients that exist in the field.

Microservices and Web services that utilize the REST approach are the defacto standard in the industry at the moment. But that could change. Schmidt cites a recent survey that found 86 percent of JavaScript developers ranked GraphQL as a top interest.

This graph layer makes sense, Schmidt says. Its at the edge of your data center. Its the abstraction layer that you want to put around all your backend services, whether its to support front-end teams or to support partners. And partners are even a more powerful use case, because if they need a change to the API hey, that can be six months or a year.

One of Apollos customers is Walmart. The Arkansas-based retailer maintains systems for managing transactions in the store and on its ecommerce website. Using GraphQL, Walmart is able to deliver an incredible 360-degree customer experience, Schmidt says.

Whether the customer wants to shop in store or they want to shop online, were giving them the very best possible shopping experience, the CEO says. The customer is going to describe how they want to shop, not the retailer, and thats what Walmart is able to deliver with a graph that bring to get all the mainframe that power their brick-and-mortar stores together with all of their cutting-edge ecommerce investment to serve the customer wherever they are.

Walmart, of course, has powered its share of innovation in IT. While some details of the implementation are not available, the fact that the retail giant is adopting GraphQL to address its data and application integration requirements may tell you something about the potential of this technology in an IBM environment, particularly considering the rallying cry from Rochester over the need to build next-gen IBM i apps.

The way Schmidt sees it, GraphQL lets customers think about their businesses as platforms, as a bunch of capabilities that we can combine to meet customer needs, in any channel, anytime, he says.

IT leaders who put a graph strategy in place now, maybe even before the business realizes the need for it theyre the ones who are going to have this platform strategy, he continues. The IT leaders who put that in place are going to be heroes, because whatever the business asks for, theyre going to be to be able to deliver a year faster than the competition.

So You Want To Do Containerized Microservices In the Cloud?

Public Cloud Dreams Becoming A Reality for IBM i Users

In Search Of Next Gen IBM i Apps

Modernization Trumps Migration for IBM i and Mainframe, IDC Says

COVID-19: A Great Time for Application Modernization

How GraphQL Can Improve IBM i APIs

Excerpt from:
GraphQL's Emerging Role in Modernization of Monolithic Applications - IT Jungle

POLAND - 2021/02/05: In this photo illustration a Nvidia logo seen displayed on a smartphone screen ... [+] with stock market graphic on the background. (Photo Illustration by Omar Marques/SOPA Images/LightRocket via Getty Images)

Nvidia has a market cap of roughly $550 billion compared to Apples nearly $2.5 trillion. We believe Nvidia can surpass Apple by capitalizing on the artificial intelligence economy, which will add an estimated $15 trillion to GDP. This is compared to the mobile economy that brought us the majority of the gains in Apple, Google and Facebook, and contributes $4.4 trillion to GDP.For comparison purposes, AI contributes $2 trillion to GDP as of 2018.

While mobile was primarily consumer, and some enterprise with bring-your-own-device, artificial intelligence will touch every aspect of both industry and commerce, including consumer, enterprise, and small-to-medium sized businesses, and will do so by disrupting every vertical similar to cloud. To be more specific, AI will be similar to cloud by blazing a path that is defined by lowering costs and increasing productivity.

I have an impeccable record on Nvidia including when I stated the sell-off in 2018 was overblown and missing the bigger picture as Nvidia has two impenetrable moats: developer adoption and the GPU-powered cloud. This was when headlines were focused exclusively on Nvidias gaming segment and GPU sales for crypto mining.

Although Nvidias stock is doing very well this year, this has been a fairly contrarian stance in the past. Not only was Nvidia wearing the dunce hat in 2018, but in August of 2019, the GPU data center revenuewas flat to declining sequentially for three quarters, and in fiscal Q3 2020, also declined YoY (calendar Q4 2019). We established and defended our thesis on the data center as Nvidia clawed its way back in price through China tensions, supply shortages, threats of custom silicon from Big Tech, cyclical capex spending, and on whether the Arm acquisition will be approved.

Suffice to say, three years later and Nvidia is no longer a contrarian stock as it once was during the crypto bust. Yet, the long-term durability is still being debated - its a semiconductor company after all - best to stick with software, right? Right? Not to mention, some institutions are still holding out for Intel. Imagine being the tech analyst at those funds (if theyre still employed!).

Before we review what will drive Nvidias revenue in the near-term, it bears repeating the thesis we published in November of 2018:

Nvidia is already the universal platform for development, but this wont become obvious until innovation in artificial intelligence matures. Developers are programming the future of artificial intelligence applications on Nvidia because GPUs are easier and more flexible than customized TPU chips from Google or FGPA chips used by Microsoft [from Xilinx]. Meanwhile, Intels CPU chips will struggle to compete as artificial intelligence applications and machine learning inferencing move to the cloud. Intel is trying to catch-up but Nvidia continues to release more powerful GPUs and cloud providers such as Amazon, Microsoft and Google cannot risk losing the competitive advantage that comes with Nvidias technology.

The Turing T4 GPU from Nvidia should start to show up in earnings soon, and the real-time ray-tracing RTX chips will keep gaming revenue strong when there is more adoption in 6-12 months. Nvidia is a company that has reported big earnings beats, with average upside potential of 33.35 percent to estimates in the last four quarters. Data center revenue stands at 24% and is rapidly growing. When artificial intelligence matures, you can expect data center revenue to be Nvidias top revenue segment. Despite the corrections weve seen in the technology sector, and with Nvidia stock specifically, investors who remain patient will have a sizeable return in the future.

Notably, the stock is up 335% since my thesis was first published a notable amount for a mega cap stock and nearly 2-3X more returns than any FAAMG in the same period. This is important because I expect this to trend to continue until Nvidia has surpassed all FAAMG valuations.

Although Nvidias stock is doing very well this year, this has been a fairly contrarian stance in ... [+] the past.

Below, we discuss the Ampere architecture and A100 GPUs, the Enterprise AI Suite and an update on the Arm acquisition. These are some of the near-term stepping stones that will help sustain Nvidias price in the coming year. We are also bullish on the Metaverse with Nvidia specifically but will leave that for a separate analysis in the coming month.

Nvidias acceleration may happen one or two years earlier as they are the core piece in the stack that is required for the computing power for the front-runners referenced in the graph above. There is a chance Nvidia reflects data center growth as soon as 2020-2021. -published August 2019, Premium I/O Fund

Last year, Nvidia released the Ampere architecture and A100 GPU as an upgrade from the Volta architecture. The A100 GPUs are able to unify training and inference on a single chip, whereas in the past Nvidias GPUs were mainly used for training. This allows Nvidia a competitive advantage by offering both training and inferencing. The result is a 20x performance boost from a multi-instance GPU that allows many GPUs to look like one GPU. The A100 offers the largest leap in performance to date over the past 8 generations.

At the onset, the A100 was deployed by the worlds leading cloud service providers and system builders, including Alibaba cloud, Amazon Web Services, Baidu Cloud, Dell Technologies, Google Cloud platform, HPE and Microsoft Azure, among others. It is also getting adopted by several supercomputing centers, including the National Energy Research Scientific Computing Center and the Jlich Supercomputing Centre in Germany and Argonne National Laboratory.

One year later and the Ampere architecture is becoming one of the best-selling GPU architectures in the companys history. This quarter, Microsoft Azure recently announced the availability of Azure ND A100 v4 Cloud GPU which is powered by NVIDIA A100 Tensor Core GPUs. The company claims it to be the fastest public cloud supercomputer. The news follows the launch by Amazon Web Services and Google Cloud general availability in prior quarters. The company has been extending its leadership in supercomputing. The latest top 500 list shows that Nvidia power 342 of the worlds top 500 supercomputers, including 70 percent of all new systems and eight of the top 10. This is a remarkable update from the company.

Ampere architecture-powered laptop demand has also been solid as OEMs adopted Ampere Architecture GPUs in a record number of designs. It also features the third-generation Max-Q power optimization technology enabling ultrathin designs. The Ampere architecture product cycle for gaming has also been robust, driven by RTXs real-time ray tracing.

In the area of GPU acceleration, Nvidia isworking with Apache Sparkto release Spark 3.0 run onDatabricks. Apache Spark is the industrys largest open source data analytics platform. The results are a 7x performance improvement and 90 percent cost savings in an initial test. Databricks and Google Cloud Dataproc are the first to offer Spark with GPU acceleration, which also opens up Nvidia for data analytics.

The demand has been strong for the companys products which have exceeded supply. In the earnings call, Jensen Huang mentioned And so I would expect that we will see a supply-constrained environment for the vast majority of next year is my guess at the moment. However, he assured that they have secured enough supplies to meet the growth plans for the second half of this year when he said, We expect to be able to achieve our Company's growth plans for next year.

Virtualization allows companies to use software to expand the capabilities of physical servers onto a virtual system. VMWare is popular with IT departments as the platform allows companies to run many virtual machines on one server and networks can be virtualized to allow applications to function independently from hardware or to share data between computers. The storage, network and compute offered through full-scale virtual machines and Kubernetes instances for cloud-hosted applications comes with third-party support, making VMWare an unbeatable solution for enterprises.

Therefore, it makes sense Nvidia would choose VMWares VSphere as a partner on the Enterprise AI Suite, which is a cloud native suite that plugs into VMWares existing footprint to help scale AI applications and workloads. As pointed out by the write-up by IDC, many IT organizations struggle to support AI workloads as they do not scale as deep learning training and AI inferencing is very data hungry and requires more memory bandwidth than what standard infrastructures are capable of. CPUs are also not as efficient as GPUs, which have parallel processing. Although developers and data scientists can leverage the public cloud for the more performance demanding instances, there are latency issues with where the data repositories are stored (typically on-premise).

The result is that IT organizations and developers can deploy virtual machines with accelerated AI computing where previously this was only done with bare metal servers. This allows for departments to scale and pay only for workloads that are accelerated with Nvidia capitalizing on licensing and support costs. Nvidias AI Enterprise targets customers who are starting out with new enterprise applications or deploying more enterprise applications and require a GPU. As enterprise customers of the Enterprise AI Suite mature and require larger training workloads, its likely they will upgrade to the GPU-powered cloud.

Subscription licenses start at $2,000 per CPU socket for one year and it includes standard business support five days a week. The software will also be supported with a perpetual license of $3,595, but support is extra. You also have the option to have get 24x7 support with additional charges. According to IDC, companies are on track to spend a combined nearly $342 billion on AI software, hardware, and services like AI Enterprise in 2021. So, the market is huge and Nvidia is expecting a significant business.

Nvidia also announced Base Command, which is a development hub to move AI projects from prototype to production. Fleet Command is a managed edge AI software SaaS offering that allows companies to deploy AI applications from a central location with real-time processing at the edge. Companies like Everseen use these products to help retailers manage inventory and for supply chain automation.

Over the past year, there have been some quarters where data center revenue exceeded gaming, while in the most recent quarter, the two segments are inching closer with gaming revenue at $3.06 billion, up 85 percent year-over-year, and data center revenue at $2.37 billion, up 35 percent year-over-year.

It was good timing for Jensen Huang to appear in a fully rendered kitchen for the GTC keynote as professional visualization segment was up 156% year-over-year and 40% quarter-over-quarter. Not surprisingly, automotive was down 1% sequentially although up 37% year-over-year.

Gross margins were 64.8% when compared to 58.8% for the same period last year, which per management reflected the absence of certain Mellanox acquisition-related costs. Adjusted gross margins were 66.7%, up 70 basis points, and net income increased 282% YoY to $2.4 billion or $0.94 per share compared to $0.25 for the same period last year.

Adjusted net income increased by 92% YoY to $2.6 billion or $1.04 per share compared to $0.55 for the same period last year.

The company had a record cash flow from operation of $2.7 billion and ended the quarter with cash and marketable securities of $19.7 billion and $12 billion in debt. It returned $100 million to the shareholders in the form of dividends. It also completed the announced four-for-one split of its common stock.

The company is guiding for third quarter fiscal revenue of $6.8 billion with adjusted margins of 67%. This represents growth of 44% and with the lions share of sequential growth driven by the data center.

Weve covered the Arm acquisition extensively with in a full-length analysis you can find here on Why the Nvidia-Arm acquisition Should Be Approved. In the analysis, we point towards why we are positive on the deal, as despite Arms extremely valuable IP, the company makes very little revenue for powering 90% of the worlds mobile processors/smartphones (therefore, it needs to be a strategic target). We also argue that the idea of Arm being neutral in a competitive industry is idealistic, and to block innovation at its most crucial point would be counterproductive for the governments reviewing the deal. We also discuss how the Arm acquisition will help facilitate Nvidias move towards edge devices.

In the recent earnings call, CFO Colette Kress reiterated that the Arm deal is a positive for both the companies and its customers as Nvidia can help expand Arms IP into new markets like the Data Center and IoT. Specifically, the CFO stated, We are confident in the deal and that regulators should recognize the benefits of the acquisition to Arm, its licensees, and the industry.

The conclusion to my analysis is the same as the introduction, which is that I believe Nvidia is capable of out-performing all five FAAMG stocks and will surpass even Apples valuation in the next five years.

As stated in the article, Beth Kindig and I/O Fund currently own shares of NVDA. This is not financial advice. Please consult with your financial advisor in regards to any stocks you buy.

Please note: The I/O Fund conducts research and draws conclusions for the Funds positions. We then share that information with our readers. This is not a guarantee of a stocks performance. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis.

Follow me onTwitter.Check outmywebsiteorsome of my other workhere.

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Here's Why Nvidia Will Surpass Apple's Valuation In 5 Years - Forbes