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previous during this decade, when the hyperscalers and the academics that flee with them maintain been constructing laptop getting to know frameworks to transpose indigenous types of records from one structure to yet another – speech to text, textual content to speech, vivid to textual content, video to text, etc – they maintain been doing so now not only for scientific curiosity. They had been making an attempt to resolve precise industry issues and addressing the wants of customers using their software.
on the very time, IBM turned into making an attempt to transparent up a different problem, naming developing a question-reply paraphernalia that could anthropomorphize the search engine. This pains turned into known as challenge Blue J inside of IBM (not to subsist at a loss for words with the open source BlueJ built-in construction environment for Java), become wrapped up right into a utility stack called DeepQA by passage of IBM. It become this DeepQA stack, which turned into in keeping with the open supply Hadoop unstructured statistics storage and analytics engine that got here out of Yahoo and yet another mission known as Apache UIMA, which predates Hadoop via a pair of years and which become designed through IBM database experts in the early 2000s to manner unstructured statistics enjoy text, audio, and video. This deep QA stack changed into embedded in the Watson QA system that was designed to play Jeopardy against humans, which they said in aspect here eight years ago. The Apache UIMA stack was the famous thing a allotment of the WatsonQA system that did herbal language processing that parsed out the speech in a Jeopardy reply, converted it to text, and fed it into the statistical algorithms to create the Jeopardy question.
Watson received the competition in opposition t human Jeopardy champs Brad Rutter and Ken Jennings, and a brand – which invoked IBM founder Thomas Watson and his admonition to “suppose” in addition to medical professional Watson, the sidekick of fictional supersleuth Sherlock Holmes – was born.
rather than bear Watson a product on the market, IBM offered it as a service, and pumped the QA gadget complete of records to boost on the healthcare, monetary services, energy, promoting and media, and education industries. This was, perhaps, a mistake, but on the time, within the wake of the Jeopardy championship, it felt enjoy every thing changed into moving to the cloud and that the SaaS model become the right means to move. IBM certainly not basically talked in unbelievable ingredient about how DeepQA changed into built, and it has in a similar passage no longer been particular about how this Watson stack has changed over time – eight years is a long time in the laptop learning area. It is not transparent if Watson is cloth to IBM’s revenues, but what is evident is that computer discovering is strategic for its systems, utility, and capabilities organizations.
So that is why IBM is at terminal bringing collectively indigenous of its laptop gaining erudition of paraphernalia and placing them below the Watson manufacturer and, very importantly, making the Watson stack purchasable for buy so it may too subsist flee on inner most datacenters and in other public clouds anyway the one that IBM runs. To subsist exact, the Watson capabilities as well as the PowerAI computing device studying practicing frameworks and adjunct tools tuned up to flee on clusters of IBM’s vigour methods machines, are being brought collectively, and they're going to subsist location into Kubernetes containers and allotted to flee on the IBM Cloud inner most Kubernetes stack, which is attainable on X86 techniques as well as IBM’s personal verve iron, in virtualized or naked steel modes. It is that this encapsulation of this recent and comprehensive Watson stack with IBM Cloud deepest stack that makes it portable throughout inner most datacenters and other clouds.
incidentally, as allotment of the mashup of these equipment, the PowerAI stack that makes a speciality of deep discovering, GPU-accelerated computer discovering, and scaling and disbursed computing for AI, is being made a core allotment of the Watson Studio and Watson desktop gaining erudition of (Watson ML) application tools. This integrated utility suite offers industry records scientists an conclusion-to-conclusion developer tools. Watson Studio is an built-in pile atmosphere according to Jupyter notebooks and R Studio. Watson ML is a set of laptop and deep researching libraries and mannequin and statistics management. Watson OpenScale is AI mannequin monitoring and warp and equity detection. The application formerly called PowerAI and PowerAI enterprise will continue to subsist developed by using the Cognitive methods division. The Watson division, if you are not common with IBM’s organizational chart, is allotment of its Cognitive options group, which includes databases, analytics equipment, transaction processing middleware, and a considerable number of functions allotted either on premises or as a provider on the IBM Cloud.
it is doubtful how this Watson stack could trade in the wake of IBM closing the purple Hat acquisition, which may quiet spin up earlier than the conclusion of the year. but it surely is cost-efficient to expect that IBM will tune up indigenous of this utility to flee on purple Hat commercial enterprise Linux and its own KVM digital machines and OpenShift implementation of Kubernetes and then push truly challenging.
it is probably valuable to evaluation what PowerAI is indigenous about and then parade the passage it is being melded into the Watson stack. earlier than the mixing and the identify adjustments (more on that in a 2nd), here's what the PowerAI stack appeared like:
in accordance with Bob Picciano, senior vp of Cognitive methods at IBM, there are greater than 600 commercial enterprise purchasers which maintain deployed PowerAI paraphernalia to flee machine discovering frameworks on its verve programs iron, and obviously GPU-accelerated programs enjoy the energy AC922 gadget this is at the heart of the “Summit” supercomputer at okayRidge national Laboratory and the sibling “Sierra” supercomputer at Lawrence Livermore national Laboratory are the main IBM machines individuals are the expend of to achieve AI work. here's a pretty satisfactory birth for a nascent industry and a platform that is comparatively recent to the AI crowd, however in indigenous probability not so distinctive for industry consumers that maintain used vigour iron of their database and utility tiers for many years.
The initial PowerAI code from two years in the past started with versions of the TensorFlow, Caffe, PyTorch, and Chainer computing device gaining erudition of frameworks that big Blue tuned up for its verve processors. The mountainous innovation with PowerAI is what's known as colossal mannequin guide, which makes expend of the coherency between Nvidia “Pascal” and “Volta” Tesla GPU accelerators and Power8 and Power9 processors within the IBM vigour programs servers – enabled with the aid of NVLink ports on the vigour processors and tweaks to the Linux kernel – to enable a lot better neural network working towards models to subsist loaded into the device. indigenous the PowerAI code is open supply and disbursed as code or binaries, and up to now simplest on power processors. (We suspect IBM will proceed agnostic on this ultimately, due to the fact that Watson tools requisite to flee on the huge public clouds, which with the exception now of the IBM Cloud, don't maintain power programs purchasable. (Nimbix, a expert in HPC and AI and a smaller public cloud, does present power iron and helps PowerAI, incidentally.)
below this, IBM has created a foundation referred to as PowerAI business, and this is now not open supply and it is just accessible as allotment of a subscription. PowerAI commercial enterprise adds Message Passing Interface (MPI) extensions to the computer getting to know frameworks – what IBM calls distributed deep getting to know – in addition to cluster virtualization and computerized hyper-parameter optimization innovations, embedded in its Spectrum Conductor for Spark (sure, that Spark, the in-reminiscence processing framework) tool. IBM has additionally brought what it calls the deep getting to know maintain an upshot on module, which includes paraphernalia for managing statistics (comparable to ETL extraction and visualization of datasets) and managing neural network models, together with wizards that argue how to most advantageous expend statistics and fashions. On proper of this stack, IBM’s first industry AI application that it is promoting is called PowerAI vision, which may too subsist used to label picture and video information for practicing models and instantly train fashions (or enlarge current models provided with the license).
So after indigenous of the alterations, here is what the brand recent Watson stack feels like:
As that you may see, the Watson desktop studying stack helps a lot more computing device researching frameworks, above indigenous the SnapML framework that got here out of IBM’s analysis lab in Zurich that is providing a mountainous performance talents on vigour iron in comparison to working frameworks enjoy Google’s TensorFlow. here is undoubtedly a extra comprehensive stack for laptop gaining erudition of, including Watson Studio for establishing fashions, the famous Watson laptop researching stack for practising and deploying models in production inference, and now Watson OpenScale (it is mislabeled within the chart) to computer screen and assist enlarge the accuracy of models based on how they're operating in the province as they infer issues.
For the moment, there is no change in PowerAI industry licenses and pricing during the primary quarter, but after that PowerAI enterprise will subsist brought into the Watson stack so as to add the dispensed GPU computer getting to know practising and inference capabilities atop verve iron to that stack. So Watson, which started out on Power7 machines taking allotment in Jeopardy, is coming returned domestic to Power9 with production machine discovering applications in the commercial enterprise. They don't seem to subsist certain if IBM will tender similar allotted machine discovering capabilities on non-vigour machines, however seems possible this is purchasers are looking to flee the Watson stack on premises or in a public cloud, it's going to maintain to. energy techniques will maintain to stand by itself merits if that involves pass, and given the advantages that Power9 chips maintain in regards to compute, I/O and memory bandwidth, and coherent reminiscence throughout CPUs and GPUs, that might too no longer subsist as a all lot of an maintain an repercussion on as they might consider. The X86 structure will maintain to win on its own merits, too.
ARMONK, N.Y., Feb. 14, 2019 /PRNewswire/ -- IBM (NYSE: IBM) today announced that Vivo energy, a market-main industry that distributes and markets Shell branded fuels and lubricants in Africa, has chosen IBM capabilities for its digital transformation journey according to SAP S/4HANA®. A speedy delivery to the connection the expend of agile strategies has already led to the completion of a tremendous venture milestone with two out of fifteen of Vivo power's country places transferred to SAP S/4HANA to palliate raise efficiency and release operational insights.
seeing that its establishment in 2011, Vivo energy has abruptly grown, including more than 500 provider stations to its retail network between 2012 and 2017, while opening more than 450 console retail and quick service eating places between 2014 and 2017. In 2018 the industry operated over 1,800 carrier stations and employed around 2,360 americans. or not it's on account of this swiftly growth that Vivo energy mandatory to bear changes to its latest IT environment and improve its commercial enterprise resource Planning (ERP) methods.
IBM solutions maintain indigenous started to seriously change Vivo energy's operations, enabling it to streamline strategies, enhance worker productiveness and improve information visibility. the expend of the embedded analytics engine of SAP S/4HANA, Vivo power will subsist capable of song the performance of each and every of its places to assist pressure resolution-making and uphold create an perspicacious commercial enterprise that responds actively to customer demand. because the deployment expands to greater locations the organization might subsist capable of conduct extra targeted analytics, empowering personnel to bear reality-based mostly selections.
Vivo power's retailers will additionally mediate the benefits from the business's recent answer. SAP S/4HANA will foretell exact for certain items and automate replenishment on the provider stations, with the goal to additionally allow the industry to in the reduction of its gas distribution prices.
Mike McCormick, CIO, Vivo power, observed, "we are focused on carrying on with their remarkable boom story, and to obtain this, they decided to radically change their system to company management and emerge for ways to enable the finished operational perception that they preferred. IBM turned into the choicest companion to assist the implementation, taking the time to fetch to know their company needs in depth."
Keith Costello, global vice president and commonplace supervisor, SAP world industry features chief, IBM, mentioned, "Vivo power was one of the crucial first oil and gas corporations of its dimension to installation the complete suite of SAP S/4HANA functions alongside SAP SuccessFactors solutions, SAP Cloud for consumer and SAP integrated industry Planning in one built-in, end-to-conclusion platform. IBM features and Vivo energy took an agile strategy to the implementation, with a focus on quick choice-making. This strategy on implementation can uphold subsist positive that the enterprise transformation application has a worldwide template for the solution, with minimal local customization in every company unit."
the expend of the SAP activate implementation methodology, Vivo energy and IBM chose a 'massive Bang' method, with numerous application components enabled concurrently. With the SAP S/4HANA solutions at present energetic in two nations, Vivo energy has plans to roll out the options throughout other locations by means of the fourth quarter of 2019.
IBM features implemented SAP S/4HANA, powered by passage of IBM energy systems servers and IBM Storwize V7000 storage systems, with SAP SuccessFactors solutions, SAP Cloud for customer and SAP built-in company Planning, helping to create an perspicacious commercial enterprise.
About Vivo power
Vivo power is a market-main pan-African gas retailer, operating and marketing its products below the Shell manufacturer in countries across North, West, East and Southern Africa. In 2018 the company had a network of more than 1,800 provider stations in 15 international locations and exported lubricants to different African countries.
About IBM functions
To subsist trained extra about SAP S/4HANA, gladden contend with: ibm.com/services/sap
SAP, SAP S/4HANA and different SAP items and features mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate enterprise) in Germany and other countries. indigenous different product and service names outlined are the trademarks of their respective businesses. gladden see http://www.sap.com/trademark for extra trademark tips and notices.
Ken SaundersExternal family members, IBM international company Servicessaundken@uk.ibm.com +447887830036
View common content to download multimedia:http://www.prnewswire.com/information-releases/ibm-services-reworking-vivo-power-with-sap-s4hana-300795839.html
Copyright (C) 2019 PR Newswire. indigenous rights reserved
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This piece talks about data transport solutions from Data Expedition, Blockchain and secure storage from IBM and chain B funding for Spin Memory.
I had a briefing from Data Expedition, Inc. who tender knowing data transport software for moving data across networks at maximum speed. They maintain won an Emmy award for their technology for media and entertainment (M&E) applications. Their customers involve M&E, life sciences, legal, oil and gas, defense and internet. The company developed what it calls a Multipurpose Transaction Protocol (MTP), which is built on the UDP protocol with advances in true time packet flux control and error recovery. The MTP is an alternative to the commonly used TCP protocol. According to Data Expedition, MTP/IP allows it to expend 100% of available transmission path capacity.
Data Expedition says that their product is easier to expend than Aspera and scales without needing lots of programming help. This hurry offers significant industry advantages. They quoted Marissa Mayer from Google and Greg Linden from Amazon that an extra 0.5 second in search page generation time dropped traffic by 20% and a 0.1 second additional latency at Amazon cost them 1% in sales.
IBM announced some recent IBM Storage Solutions for containers and cloud storage, with a focus on Blockchain, IBM Cloud Private and what the company called, cyber resiliency. The company is too extending simulated intelligence (AI) capabilities and tools into its IBM FlashSystem A9000 family.
The IBM Storage Solution for IBM Blockchain is said to subsist a complete pre-tested and validated infrastructure solution for blockchain deployments.
According to IBM, the recent Solution improves on- and off-chain data resiliency and performance with enterprise-proven NVMe-based IBM FlashSystem 9100 or LinuxONE Rockhopper II infrastructure. It too reduces test, evolution and deployment time for both on/off-chain solutions, improving time to recent profits from days to hours. In addition it increases blockchain security with 100 percent application and data encryption support. Finally, it increases data resiliency with a software-defined architecture featuring IBM Spectrum Virtualize, IBM Spectrum Copy Data Management and IBM Spectrum Protect Plus.
To address the infrastructure challenges of implementing the latest multi-cloud data analytics and AI applications, IBM announced the IBM Storage Solution for Analytics. This Solution is based on the recently introduced IBM Cloud Private for Data offering, now supported on NVMe-based IBM FlashSystem 9100. This recent Solution is said to unify and hurry up data collection, orchestration and analysis, while reducing time to value. It simplifies Docker or Kubernetes container utilization for recent analytics-based applications and it increases data security inside your private cloud by supporting FIPS 140-2 encryption. It too leverages your on-premises data storage while adding cloud-based analytics tools.
Spin Memory, Inc. (formerly known at Spin Transfer Technologies, Inc.) announced that Ables Ventures from Tokyo Japan has joined as an additional investor in their chain B funding. Ables Ventures joins existing investors Applied Ventures LLC, Arm, Allied Minds, Woodford Investment Management and Invesco Asset Management that were announced in November 2018.
Moving data faster and storing it in the securely in the cloud are famous enablers to content growth. recent memory options will enable handling this data in the cloud, at the edge and on-premises.
LAFAYETTE, Colo. & recent YORK--(BUSINESS WIRE)--Liqid Inc., leading provider of on-demand composable infrastructure technologies, today announced the company has hired glimmer storage technology sales veteran John Zamites as Director of Sales for the Eastern United States. Based in Manhattan, the former IBM executive brings 25 years undergo and a career history of enterprise sales leadership to the position. Zamites will drive Liqid’s Composable Infrastructure positioning across banking and finance, enterprise, scientific research and government verticals and travail closely with technology visionaries throughout the territory to expand the Liqid footprint into more of the world’s most demanding, high-performance datacenters.
“John’s leadership in the datacenter makes him the faultless candidate to spearhead their Eastern U.S. push, where bare-metal disaggregated, composable infrastructure will power the next wave of innovation in applications ranging from algorithmic trading to genetic research to digital defense,” said Marius Tudor, Vice President, Sales, Liqid.
Zamites has worked in emerging technologies for the past decade, most recently driving glimmer technology adoption and innovation for IBM as zone Director for glimmer Systems. During his tenure at IBM, Zamites joined the glimmer Leadership Council as a subject Matter Expert for IBM glimmer Systems where he taught internal teams, partners and finish users of the disruptive nature and industry benefits associated with all-flash array technologies.
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February 18, 2019 Timothy Prickett Morgan
Well, that took quite a long time. After what seems enjoy eons of nudging and cajoling and pushing, IBM is making the IBM i operating system and its integrated database management system, as well as the application evolution tools and other systems software, available on its self-branded IBM Cloud public cloud.
Big Blue previewed its plans to bring both IBM i and AIX to the IBM Cloud at its annual mediate conference in Las Vegas, on scale out machines aimed at small and medium businesses as well as to customers who want to flee clusters of machines, and on scale up systems that maintain NUMA electronics that more tightly cluster them into shared memory systems.
There are a lot of questions about how this will subsist indigenous subsist packaged up and sold under the unwieldy name of the IBM Power Systems Virtual Server on IBM Cloud. But they will Tell you indigenous that they know and fill you in as they learn more.
The Power Systems slices served up on the IBM Cloud running IBM i and AIX were first rolled out for early access to selected customers to test the APIs for the control plane, which they presume is based on the PowerVC implementation of OpenStack. The initial customers who are kicking the tires were suppositious to only deploy evolution and test environments or protype code, certainly not anything running in production. This was totally meant to subsist a proof of concept setup at this point, as you can view from the rollout roadmap:
The alpha and beta testing for the Power Systems slices on the IBM Cloud is on a pretty swiftly track, running from February into March, as you can see, and universal availability is slated for some time in March. Probably somewhere towards the end, they would guess. IBM is initially making the Power puffs – what else can you convoke them as shorthand? – available in the early access tests in its US East datacenter in the Washington DC metro area; it is not transparent what iron was used. The alpha and beta testing is being done on a collection of Power S922 scale out machines, which are based on a pair of Power9 processors and which frankly is a mountainous box for most IBM i shops indigenous by itself, as well as on Power E880 scale up systems, which are being scaled up to sixteen sockets and which expend the older Power8 processors. indigenous of the machines expend ten-core processors, which are the sweet spot between performance, chip yield, and cost in the Power Systems line. The Power9 chips in the Power S922 servers flee at 2.8 GHz and can turbo up to 3.9 GHz if there is enough thermal headroom; these chips recognize enjoy they may maintain four threads per core (also known as SMT4), which is not as much threading as the commonplace Power8 chip offers in scale out machines with SMT8 threading (eight threads per core) and twice as many cores per die (24 cores versus 12 cores). Anyway, it looks enjoy the Power S922 is being equipped with the heavy cores, not the light ones. The Power8 chips in the Power E880 are running at 4.19 GHz and too uphold SMT8 threading (there was only a heavy core here); indigenous sixteen cores are populated with ten-core Power8 chips, with a maximum scalability of 160 cores in a separate logical partition on the IBM Cloud.
Both of the machines are being configured with 32 GB memory sticks, which are again at the sweet spot between capacity, bandwidth, and cost per bit, and IBM is allowing customers to configure the machines with anywhere from 8 GB to 64 GB of main memory per core. If you want denser memory to bolster the capacity, you can double it up using 64 GB memory sticks, and then double it up again to 128 GB sticks, but this will subsist a custom order and it will cost considerably more, they think. IBM is offering disk and glimmer storage up to 2 TB for local storage on the instances and growing at 10 GB increments. External storage for applications and databases is on Storwize V7000 disk arrays in the racks near this Power iron, and are linked to the servers by Fibre Channel switches. Customers can partake machines or rent dedicated iron, depending on their proclivities for absolute security and dealing with pandemoniac neighbors on the virtual infrastructure.
Steve Sibley vice president and offering manager for the Cognitive Systems division at IBM, gave me a sneak peek at the future Power cloud slices on a visit to the Austin, Texas labs terminal week, ahead of the mediate conference. Here is how the features and functions of the logical partitions on the IBM Cloud are shaping up:
Sibley told us that the pricing was not yet set in stone for the virtual Power capacity on the IBM Cloud, but when pressed about comparing the cost between buying gear and renting it on the cloud, Sibley estimated that for a given IBM i or AIX workload running on similarly configured hardware and logical partitions, running the cloud instance would cost about 30 percent to 40 percent more on the instance running complete out over three years compared to buying the iron and using it for three years. The difference, of course, is that IBM is managing the Power Systems and paying for the datacenter, the electricity, the cooling, the security, patch updates on firmware, the installation of the PowerVM hypervisor and its update, and the installation of the IBM i or AIX operating system. When companies buy their own Power Systems machines, unless they fetch augmented services from IBM or a industry partner, it’s indigenous on them. Pricing for the virtual machines, the memory, the storage, and the operating system and databases are indigenous set per hour.
By the way, it is not transparent what IBM i and AIX releases are supported on the machines, but presumably the current IBM i 7.2 and IBM i 7.3 releases are supported on the IBM Cloud as well as AIX 7.1 and AIX 7.2, which are too current. Linux is not mentioned as a supported platform, but SAP HANA workloads are and that implies that there is a Linux – and specifically Red Hat Enterprise Linux – underneath it since HANA in-memory databases are not supported on any Unix variant, or IBM i for that matter.
By March, IBM plans to maintain the IBM i and AIX instances available in production in its US East (Washington DC) and US South (Dallas) regions, and in the second quarter IBM plans to roll it in its European datacenter in its EU Central (Frankfurt) region, with other datacenters coming out as exact pulls and IBM pushes.
We will boost a recognize at the pricing as soon as it becomes available and view how it indigenous stacks up, and fetch the thoughts of other IBM i cloud players about what mountainous Blue is doing.
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