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C7020-230 IBM Watson V3 Application Development

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C7020-230 exam Dumps Source : IBM Watson V3 Application Development

Test Code : C7020-230
Test cognomen : IBM Watson V3 Application Development
Vendor cognomen : IBM
braindumps : 63 existent Questions

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IBM IBM Watson V3 Application

IBM Drives Watson AI far and wide | existent Questions and Pass4sure dumps

IBM kicked off its annual deem colleague and developer conference with a spotlight on making Watson accessible everywhere. Watson has traditionally been an respond simplest attainable through IBM’s Cloud services. but today, IBM announced it's opening Watson to race on any inner most, public, hybrid or multi-cloud answer. moreover, IBM is providing an on-premises respond running Watson. IBM is pretty much looking to originate Watson essentially the most available ersatz Intelligence (AI) respond that may execute the area ever the facts resides, notwithstanding it's crash up between structures.

IBM has been a pacesetter in AI expertise with the structure of Watson, an astute platform capable of processing a wide array of tips and adapting to virtually any software. seeing that its introduction, Watson has been applied to a to essentially everything from competing with humans in games to customer service to scientific and enterprise modeling. Watson is identified as an creative leap forward this is paving the route of utilized AI. every sole the route through the keynote address, a few companies, including Geico and Hyundai financial, mentioned how they are already leveraging Watson AI because the basis of their industry options.

IBM Cloud inner most for DataIBM

IBM is now prolonged the attain of Watson platform (Watson Studio, Watson Assistant, Watson OpenScale, and so on) on the brand unique IBM Cloud inner most for records (ICP for facts), which can be deployed on IBM Cloud or any private, public, hybrid, or multi-cloud ambiance by utilizing Kubernetes know-how. moreover, IBM introduced an extension of Watson machine learning with the Watson machine getting to know Accelerator for high-efficiency GPU clustering.

while Watson will race on both vim and X86 systems, there is a efficiency benefit to running on IBM’s power-based techniques, and in AI, efficiency matters. whether it is establishing unique AI fashions or processing counsel in actual-time, delays can cost companies in productivity, best, and/or defense. IBM’s vim AI platform combines dissimilar Power9 CPUs with Nvidia pics Processing devices (GPUs) with high GPU memory bandwidth. The PowerAI platform is the most efficient GPU-accelerated platform that links the processors to the GPUs the usage of Nvidia high-speed NVLink interface. The AC922 can moreover be configured with up to two 20-core Power9 CPUs and up to 6 Tesla V100 GPUs. distinct methods may moreover be linked to scale to up to 256 GPUs. based on IBM, fresh assessments validated the capacity to developed AI models up to 10 instances sooner than competing structures. in consequence, IBM is now making Watson obtainable on the PowerAI platform for on-premises deployments. As piece of the announcement, IBM is moreover renaming the PowerAI commercial enterprise platform to the “Watson computer Accelerator”.

Watson has become a key foundation for the company’s product and repair choices, because of this, IBM is continuing to invest in new capabilities for the platform that can be added sooner or later. IBM moreover presents company features to support shoppers in imposing AI of their business, which makes IBM stand out from the relaxation of the AI crowd.

whereas IBM didn't highlight how the company’s different analysis efforts will influence the Watson platform, TIRIAS research believes that IBM’s management in quantum and neuromorphic computing will further develop the platform and when combined with IBM’s company services, will relaxed the company a number one position in the evolving AI landscape.

The writer and members of the TIRIAS analysis personnel Do not cling equity positions in any of the groups outlined. TIRIAS research tracks and consults for corporations every sole over the electronics ecosystem from semiconductors and sensors to the cloud. members of the TIRIAS analysis crew savor consulted for IBM, NVIDIA, and other organizations throughout the electronics ecosystem.

IBM Watson Now available anywhere | existent Questions and Pass4sure dumps

SAN FRANCISCO, Feb. 12, 2019 (Canada NewsWire by means of COMTEX) -- IBM believe -- IBM IBM, +0.39% today introduced a unique chapter in the suffer from AI experimentation to large-scale deployment and industry transformation. IBM has made Watson moveable across any cloud and empowered corporations to steer lucid of dealer lock-in and start deploying AI anywhere their statistics resides.

"groups savor generally been limited to experimenting with AI in siloes as a result of the barriers brought about by cloud issuer lock-in of their facts," observed Rob Thomas, regular supervisor, IBM data and AI. "With most giant groups storing facts throughout hybrid cloud environments, they want the license and election to rehearse AI to their records anyplace it is stored. by breaking open that siloed infrastructure they will benefit companies accelerate their transformation through AI."

Watson, IBM's AI, is designed to aid groups set AI to toil to augment the efficiency of business. With a lucid set of applications, construction equipment, computing device learning models, and administration capabilities, Watson is helping groups every sole over the world mine their facts, predict consequences, and automate time- and resource-sensitive procedures.

present day announcements develop this mission via proposing agencies with a less complicated, sooner approach to construct, deploy and race AI fashions and functions throughout any cloud. With these apparatus in region, organizations can:

-- race IBM Watson services, including Watson lieutenant and Watson OpenScale, on any cloud. through their integration with IBM Cloud private for records (ICP for information), Watson and Watson OpenScale can now be race any environment - on premises, or on any private, public or hybrid-multicloud - enabling agencies to follow AI to information anyplace it's hosted. organizations might be able to infuse AI into their apps, inspite of where they dwell. the pliability this affords can purge some of the primary boundaries to scaling AI, considering groups can now depart away information in at ease or favorite environments and occupy Watson to that information. -- set up AI application that automates company processes for more advantageous efficiencies and performance. unique AI digital automation utility is designed to allow purchasers to determine patterns of their company techniques and then create AI-embedded programs to automate distinct workflows.

notwithstanding using AI continues to gain attention in enterprise, many groups are nevertheless challenged to dash projects ahead. according to an MIT Sloan file, 81 p.c(1) of firms don't preserve in intellect what data is required for AI, or how to access it. And a recent Gartner peruse at(2) create that, "records and analytics leaders continue to struggle with the complexity, time to integration and value implications of their facts integration tasks, thereby inflating their schedules and delivery charges with numerous cycles of revised challenge scope."

still, the huge majority of companies, eighty three %, based on the MIT Sloan file, coincide that driving AI across the industry is a strategic opportunity.

Qatar construction bank has collaborated with IBM to set up the IBM Innovation Hub Doha. one of the key applied sciences that the Hub will install is IBM Cloud private for statistics. "The pleasing factor about IBM Cloud inner most for statistics is how directly they could be able to pressure unique improvements in FinTech and SportsTech the exhaust of the microservices within the platform," said Abdulaziz Al Khalifa, CEO, Qatar progress bank. "What makes it specially comely is that it enables us to augment and deploy unique models quickly that brings the tools to the information, in area of the wrong route around."

ICP for information is IBM's open, cloud-native information architecture for AI that comes integrated with superior information science, facts engineering and utility-building capabilities, and is designed to benefit agencies determine in the past unobtainable insights from their records. Openness is on the core of ICP for information, for which Watson Studio is a key part. for instance, according to internal study, eighty five% of Watson users are the usage of open supply languages and frameworks enjoy Python, R, and TensorFlow, inside the Watson household.(three)

In its recent file, The Forrester WaveTM : enterprise perception systems, Q1 2019, Forrester research named ICP for statistics a "chief." The record analyzes and reviews enterprise perception structures that fuse facts administration, analytics, and perception utility construction tooling. within the examine, Forrester stated: "IBM has pre-integrated capabilities that permit shoppers to be productive in every week or less. They were additionally impressed with its ML-assisted statistics cataloging and governance tools. IBM's platform makes exhaust of Kubernetes to installation on-premises or into the public cloud."

Watson comes to ICP for DataAt the heart of cutting-edge announcements is a sequence of unique Watson microservices built for ICP for information that are based on open supply applied sciences and simply scalable across cloud environments. based on the open-supply Kubernetes technology, these unique Watson microservices may moreover be race on IBM Cloud, and different public, hybrid or multi-cloud environments.

The microservices are in keeping with the following software options:

-- Watson OpenScale: IBM's open AI platform for managing distinct circumstances of AI, no matter number the area they had been developed - including the skill to clarify how AI selections are being made in accurate time, for enhanced transparency and compliance. -- Watson Assistant: IBM's AI device for constructing conversational interfaces into purposes and devices. more superior than a traditional chatbot, Watson lieutenant intelligently determines when to peruse for a effect, when to query the user for clarification, and when to dump the person to a human for private assistance. additionally, the Watson lieutenant Discovery Extension allows for businesses to unencumber hidden insights in unstructured statistics and files.

the unique Watson functions be piece of Watson Studio and Watson laptop gaining learning of, among other features, which are at the minute accessible on ICP for facts. Later this 12 months, IBM will bring extra Watson services to ICP for records, including Watson expertise Studio and Watson herbal Language understanding.

besides this news, IBM nowadays moreover announced that IBM Watson laptop studying is being extended with a brand unique Accelerator (Watson desktop researching Accelerator) that permits immoderate efficiency GPU clustering on vim techniques and X86 techniques. combined with IBM POWER9's industry-main GPU memory bandwidth, the solution can proffer up to 10x faster(4) computer studying working towards than competitive solutions. that you can read greater about the benchmark prerogative here.

IBM industry Automation Intelligence with WatsonIn addition to the free up of those options, IBM announced a imminent utility potential, called IBM industry Automation Intelligence with Watson. With this unique software, industry leaders might be able to follow AI directly to applications, helping to reinforce their cadaver of workers, from clerical to learning employees, to intelligently automate toil from the mundane to the complex. additionally, the software will measure the stage of influence and effectiveness of AI on enterprise consequences.

IBM industry Automation Intelligence with Watson is predicted to be obtainable later this 12 months. meanwhile, for extra information, visit their early access application

About IBM & ersatz Intelligence a global leader in AI for enterprise, IBM has deployed Watson options in heaps of engagements with customers across 20 industries and eighty nations. IBM's Watson solutions are conventional in industries, together with by route of 7 of the ten greatest car corporations and 8 of the ten largest oil and gas agencies. additionally, IBM research is an international leader in the science of AI. In 2018, IBM secured 1,600 AI-related patents. And, IBM lately printed its main-edge project Debater, created with the aid of IBM analysis scientists.

believe 2019At feel 2019, IBM will silhouette unique offerings, client engagements, partnerships, expertise breakthroughs and developer apparatus that underscore how IBM and companions are changing the manner the world works. For more information, visit the IBM deem 2019 Newsroom: follow the convention on Twitter at #think2019 and @ibmlive, and depart to for the gross time table and reside streaming agenda.

ahead-looking and Cautionary StatementsExcept for the historical assistance and discussions contained herein, statements contained during this release can moreover picture ahead-looking statements in the significance of the deepest Securities Litigation Reform Act of 1995. ahead-searching statements are according to the company's existing assumptions regarding future industry and economic efficiency. These statements involve a pair of risks, uncertainties and other elements that could judgement exact effects to vary materially, including the following: a downturn in fiscal environment and client spending budgets; the business's failure to fulfill augment and productiveness objectives; a failure of the company's innovation initiatives; harm to the enterprise's popularity; dangers from investing in boom alternatives; failure of the enterprise's highbrow property portfolio to evade competitive choices and the failure of the industry to obtain vital licenses; cybersecurity and records privateness issues; fluctuations in fiscal effects, savor an effect on of local prison, financial, political and fitness conditions; adverse outcomes from environmental concerns, tax concerns and the company's pension plans; ineffective internal controls; the company's exhaust of accounting estimates; the company's potential to appeal to and retain key personnel and its reliance on distinguished potential; affects of relationships with vital suppliers; product high-quality issues; impacts of enterprise with government customers; forex fluctuations and client financing hazards; savor an repercussion on of changes in market liquidity conditions and consumer credit possibility on receivables; reliance on third party distribution channels and ecosystems; the business's capability to correctly manage acquisitions, alliances and tendencies; hazards from criminal complaints; random elements involving IBM securities; and other hazards, uncertainties and components mentioned in the enterprise's kindly 10-Qs, contour 10-k and within the company's other filings with the U.S. Securities and alternate commission (SEC) or in materials integrated therein through reference. Any forward-searching observation during this unlock speaks best as of the date on which it's made. The enterprise assumes no obligation to supplant or revise any forward-searching statements.

ContactMichael ZimmermanIBM Media family members(585) 698-9974

(1) MIT Sloan administration assessment, Reshaping enterprise with ersatz Intelligence(2) Gartner: "Predicts 2019: statistics management options," Dec. 6, 2018.(three) IBM interior examine, Feb. 6, 2019.(four) IBM systems weblog: unique Watson laptop getting to know Accelerator for power systems

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IBM Mashes Up PowerAI And Watson computer getting to know Stacks | existent Questions and Pass4sure dumps

earlier in this decade, when the hyperscalers and the lecturers that race with them were structure computing device discovering frameworks to transpose every sole types of records from one structure to one more – speech to text, textual content to speech, picture to textual content, video to text, and so forth – they had been doing so not just for scientific curiosity. They savor been trying to remedy existent enterprise problems and addressing the wants of valued clientele using their utility.

at the selfsame time, IBM was attempting to remedy a different difficulty, naming growing a query-answer gadget that could anthropomorphize the search engine. This ail changed into known as assignment Blue J interior of IBM (no longer to be at a loss for words with the open supply BlueJ built-in structure environment for Java), turned into wrapped up into a software stack called DeepQA through IBM. It turned into this DeepQA stack, which become in accordance with the open supply Hadoop unstructured facts storage and analytics engine that came out of Yahoo and another project called Apache UIMA, which predates Hadoop with the aid of a few years and which became designed by using IBM database experts within the early 2000s to fashion unstructured facts enjoy text, audio, and video. This deep QA stack was embedded within the Watson QA apparatus that became designed to play Jeopardy towards humans, which they stated in factor prerogative here eight years in the past. The Apache UIMA stack turned into the distinguished thing a piece of the WatsonQA apparatus that did herbal language processing that parsed out the speech in a Jeopardy answer, transformed it to textual content, and fed it into the statistical algorithms to create the Jeopardy query.

Watson won the competition towards human Jeopardy champs Brad Rutter and Ken Jennings, and a company – which invoked IBM founder Thomas Watson and his admonition to “suppose” as well as medical professional Watson, the sidekick of fictional supersleuth Sherlock Holmes – became born.

instead of originate Watson a product for sale, IBM provided it as a service, and pumped the QA apparatus plenary of facts to occupy on the healthcare, monetary functions, power, advertising and media, and education industries. This was, possibly, a mistake, but at the time, in the wake of the Jeopardy championship, it felt enjoy every runt thing changed into pitiful to the cloud and that the SaaS mannequin become the confiscate approach to move. IBM on no account actually talked in first-rate detail about how DeepQA turned into developed, and it has in a similar style no longer been particular about how this Watson stack has modified over time – eight years is a long time within the computer discovering space.  It is not lucid if Watson is cloth to IBM’s revenues, however what is obvious is that computer gaining learning of is strategic for its programs, software, and features companies.

So it is why IBM is at eventual bringing together every sole of its desktop studying tools and inserting them under the Watson brand and, very importantly, making the Watson stack obtainable for buy so it may moreover be race on private datacenters and in different public clouds anyway the one which IBM runs. To be genuine, the Watson services as neatly as the PowerAI machine studying practicing frameworks and adjunct apparatus tuned as much as race on clusters of IBM’s vim methods machines, are being introduced collectively, and they will be set into Kubernetes containers and allotted to race on the IBM Cloud inner most Kubernetes stack, which is available on X86 programs in addition to IBM’s personal vigour iron, in virtualized or bare metal modes. It is that this encapsulation of this unique and complete Watson stack with IBM Cloud deepest stack that makes it transportable across inner most datacenters and other clouds.

incidentally, as piece of the mashup of these equipment, the PowerAI stack that focuses on deep learning, GPU-accelerated laptop getting to know, and scaling and allotted computing for AI, is being made a core piece of the Watson Studio and Watson desktop getting to know (Watson ML) application equipment. This integrated software suite gives industry facts scientists an end-to-conclusion developer tools. Watson Studio is an integrated progress ambiance in keeping with Jupyter notebooks and R Studio. Watson ML is a group of laptop and deep discovering libraries and mannequin and data administration. Watson OpenScale is AI model monitoring and prejudice and fairness detection. The software previously referred to as PowerAI and PowerAI commercial enterprise will continue to be developed by route of the Cognitive methods division. The Watson division, in case you are not typical with IBM’s organizational chart, is a component of its Cognitive options community, which contains databases, analytics tools, transaction processing middleware, and a number of applications dispensed both on premises or as a service on the IBM Cloud.

it is uncertain how this Watson stack might change within the wake of IBM closing the crimson Hat acquisition, which should ensue before the conclusion of the yr. but it is reasonable to assume that IBM will tune up every sole of this application to race on pink Hat commercial enterprise Linux and its personal KVM digital machines and OpenShift implementation of Kubernetes and then shove in reality complicated.

it's doubtless advantageous to assessment what PowerAI is every sole about after which disclose the route it is being melded into the Watson stack. earlier than the integration and the identify changes (extra on that in a 2nd), here's what the PowerAI stack looked like:

according to Bob Picciano, senior vice president of Cognitive programs at IBM, there are more than 600 industry valued clientele that savor deployed PowerAI tools to race machine getting to know frameworks on its energy methods iron, and obviously GPU-accelerated programs just enjoy the power AC922 gadget that's on the heart of the “Summit” supercomputer at o.k.Ridge national Laboratory and the sibling “Sierra” supercomputer at Lawrence Livermore national Laboratory are the main IBM machines americans are using to Do AI work. here is a agreeable looking agreeable start for a nascent trade and a platform that is comparatively unique to the AI crowd, however most likely now not so diverse for enterprise valued clientele which savor used vim iron of their database and software tiers for decades.

The preliminary PowerAI code from two years in the past began with models of the TensorFlow, Caffe, PyTorch, and Chainer desktop getting to know frameworks that huge Blue tuned up for its energy processors. The massive innovation with PowerAI is what's known as colossal model support, which makes exhaust of the coherency between Nvidia “Pascal” and “Volta” Tesla GPU accelerators and Power8 and Power9 processors within the IBM energy systems servers – enabled by means of NVLink ports on the energy processors and tweaks to the Linux kernel – to enable a agreeable deal greater neural network working towards fashions to be loaded into the equipment. every sole the PowerAI code is open source and disbursed as code or binaries, and to date best on vim processors. (We suspect IBM will depart agnostic on this ultimately, in view that Watson apparatus must race on the expansive public clouds, which with the exception now of the IBM Cloud, won't savor vim methods obtainable. (Nimbix, a professional in HPC and AI and a smaller public cloud, does present vigour iron and supports PowerAI, incidentally.)

below this, IBM has created a foundation called PowerAI enterprise, and here is no longer open supply and it is only attainable as piece of a subscription. PowerAI industry adds Message Passing Interface (MPI) extensions to the computer learning frameworks – what IBM calls dispensed deep discovering – as well as cluster virtualization and automatic hyper-parameter optimization techniques, embedded in its Spectrum Conductor for Spark (yes, that Spark, the in-reminiscence processing framework) device. IBM has moreover brought what it calls the deep gaining learning of savor an effect on module, which contains tools for managing data (equivalent to ETL extraction and visualization of datasets) and managing neural network models, together with wizards that indicate the route to most dependable exhaust facts and models. On prerogative of this stack, IBM’s first commercial AI utility that it is selling is called PowerAI imaginative and prescient, which can moreover be used to label photo and video information for training models and immediately train models (or augment latest fashions provided with the license).

So in any case of the alterations, here's what the unique Watson stack appears like:

As that you would be able to see, the Watson computing device discovering stack helps much more machine gaining learning of frameworks, specially the SnapML framework that got here out of IBM’s research lab in Zurich that's offering a major efficiency learning on vim iron compared to running frameworks enjoy Google’s TensorFlow. this is absolutely a greater complete stack for machine discovering, including Watson Studio for setting up fashions, the valuable Watson machine getting to know stack for training and deploying fashions in production inference, and now Watson OpenScale (it is mislabeled in the chart) to monitor and support enhance the accuracy of models according to how they're operating within the container as they infer issues.

For the second, there is no alternate in PowerAI enterprise licenses and pricing every sole the route through the primary quarter, however after that PowerAI enterprise will be introduced into the Watson stack to add the allotted GPU computer studying practicing and inference capabilities atop vim iron to that stack. So Watson, which every sole started out on Power7 machines taking piece in Jeopardy, is coming back home to Power9 with construction computer researching purposes within the commercial enterprise. They don't appear to be distinct if IBM will proffer similar dispensed laptop researching capabilities on non-vigor machines, however it appears doubtless it's consumers are looking to race the Watson stack on premises or in a public cloud, it's going to should. power systems will should stand by itself merits if that comes to flow, and given the benefits that Power9 chips savor in regards to compute, I/O and reminiscence bandwidth, and coherent memory throughout CPUs and GPUs, that can moreover now not be as tons of an influence as they might feel. The X86 architecture will must win by itself merits, too.

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IBM Watson V3 Application Development

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Building an IBM Watson bot with Node.js + Botkit | existent questions and Pass4sure dumps

Bots are fun and useful with unique businesses being built daily around bot interaction models. They recently launched their unique Team Messaging API — Glip - at Enterprise Connect and we’re excited to prove off more of the capabilities of the platform we’re structure at RingCentral, alongside with IBM Watson Bluemix and Botkit!

A step-by-step tutorial walking through the Github code is available here!

  • Two free RingCentral Developer accounts
  • A free IBM Bluemix Developer account
  • Creating a unique RC App

    Login to the RingCentral developer account to create a unique app. Click on “Create App” which will create your app and auto-create a unique sandbox account if you don’t already savor one.

    Create App

    Enter the application cognomen and description.

    Add Application Information

    There are two paths for progress on the RingCentral platform: making a private app which is just for your team, or a public app for public distribution through their App Gallery that others can use.

    Application and Authorization flow

    In the OAuth settings, originate positive the authorization selected is Glip. This authorization is required to build chatbots.

    OAuth Settings and Permissions

    Once the account has been created, you will be redirected to the dashboard. The App Key, App Secret, and the phone number will be used to play with the bot in the team. deliver it for the next step.

    App Credentials Botkit Setup

    Botkit is one of the most accepted open-source toolkits for structure bots, providing the essential structure blocks . Botkit supports multiple frameworks, but here they will be looking at Glip. Glip is currently in review process with Botkit but it can be install directly from Github. Bot can communicate with your team in three ways:

  • Incoming webhooks: is a simple route to post messages from external sources in Glip. e.g JIRA bots which post into your team when a unique ticket has been assigned to you.
  • Slash Command: are custom commands written by developers enjoy you. They start with a backslash (/) and act as a trigger event to accomplish some action. Slash commands are currently not available in Glip. They are scheduled to be available by nearby of year.
  • Real Time Messaging API: allows you to transmit and receive messages from a Glip user.
  • With some theory behind us, let’s start structure their sample application. This specimen will focus on getting post messages from a group or team in Glip and pass the message to IBM Watson to gather some personality insight.

    What are Personality Insights ?

    According to IBM, “Personality Insights extracts personality characteristics based on how a person writes. You can exhaust the service to match individuals to other individuals, opportunities, and products, or tailor their suffer with personalized messaging and recommendations. Characteristics comprehend the expansive 5 Personality Traits, Values, and Needs. At least 1200 words of input text are recommended when using this service.”

    As a first step, clone the sample application from Github. Now create a copy of the .env.template file and rename it to .env. The file should peruse something enjoy this:


    Then exhaust the below code to install every sole dependencies including botkit and watson-developer-cloud.

    npm install --save

    Now let’s connect Botkit with Glip using the following code snippet:

    "use strict";


    var Botkit= require('botkit'),os = require('os'),http = require('http'),request = require('request'),watson = require('watson-developer-cloud');

    var controller = Botkit.glipbot({debug: false,});

    var bot = controller.spawn({server: process.env.GLIP_SERVER,appKey: process.env.GLIP_APPKEY,appSecret: process.env.GLIP_APPSECRET,username: process.env.GLIP_USERNAME,password: process.env.GLIP_PASSWORD,extension: process.env.GLIP_EXTENSION,}).startRTM();

    controller.setupWebserver(process.env.port || 3000, function(err, webserver){webserver.get('/', role (req ,res) {res.send(':)');});

    controller.createWebhookEndpoints(webserver, bot);


    controller.hears(['watson'], 'message_received', role (bot, message) {

    bot.reply(message, "hi, this is watson, How can I benefit you ? ");});

    In the above example, when someone mentions “watson” the bot responds back with “Hi, this is watson. How can I benefit you?”.

    Now let’s originate the bot brilliant by integrating it with IBM Watson’s Personality Insights.

    IBM Watson

    IBM Watson offers AI and Machine Learning services through its Bluemix cloud platform. To pick up started quickly with Watson and Bluemix, you can create a free account.

    IBM Watson offers many services for AI and Machine Learning. For this example, they will exhaust the Personality Insights services. exhaust this document to setup and gather credentials for Personality Insights.

    Now update the .env file created above with the Personality Insights credentials.


    Initiate Personality Insights API using the snippet below:

    var watson = require('watson-developer-cloud'); var personality_insight = watson.personality_insights({username: process.env.WATSON_USERNAME,password: process.env.WATSON_PASSWORD,url: process.env.WATSON_URL,version: process.env.WATSON_VERSION});

    Now let’s integrate it to the chat-bot logic:

    controller.hears(['analyze'], 'message_received', role (bot,message) {bot.api.posts().get({groupId:}).then(function(history) {

    var messages = [];for(var i=0; i < history.records.length; i++){messages.push(history.records[i].text);}

    var corpus = messages.join("\n");

    personality_insight.profile({text: corpus,language: 'en'},function (err, response) {if(err){console.log('error:', err)}else{controller.startTask(bot, message, role (task, convo) {var top5 = response.personality;for (var c = 0; c < top5.length; c++) {

    convo.say('This channel has ' + Math.round(top5[c].percentile*100) + '% ' + top5[c].name);



    As you can see, when someone says “analyze”, it will gather the history of the post messages in the group and transmit it to Watson to analyze. Watson analyzes the post messages and responds back with the top 5 personality insights based on the post messages history as shown below.

    Personality Insight response from IBM Watson Conclusion

    The goal of the post has been to pick up developers started with structure bots in Glip with IBM Watson. Personality Insights is just one of the several API’s available in IBM Watson cloud. You could exhaust other APIs enjoy Tone Analyzer, Text to Speech, Conversation … etc. to build more advanced bots that are fun and interesting. The imagination is the limit!

    A step-by-step tutorial is moreover available here!

    Give it a try, and I more than welcome any kindly of feedback!

    Exploring the best ECM software for your company | existent questions and Pass4sure dumps

    Documents and the information they accommodate are the stuff of industry activities. Not surprisingly, the ECM marketplace continues to evolve to meet the ever-changing needs of competitive industry operations.

    Enteprise content management products reflect their roots. Some initiate as document management applications, intent on simply capturing final contour documents -- both difficult copy and electronic -- and providing a shared repository for storing, organizing, accessing and distributing the digital artifacts on demand. Other products focus on the complete content lifecycle -- creating and reviewing, while managing the multiple versions of a document, and then storing the published version within an authoritative repository. A third set of products considers the purpose of content to the transformation of digital industry and focuses on the content services associated with creating and managing industry documents.

    Selecting the best ECM software for a company depends on industry goals and objectives, organizational culture and measure operating procedures. Organizations savor a sweep of choices. Here's a snapshot of eight distinguished vendors to deem while making a buying decision.

    Alfresco Digital industry Platform channels content flows

    Alfresco provides ECM, industry process management (BPM) and records management (RM) capabilities to enterprises. The company's Digital industry Platform consists of three products: Alfresco Content Services, Alfresco Process Services and Alfresco Governance Services. This platform deploys either on premises or in the cloud running on AWS, depending on preferences.

    Alfresco combines open source tools with support services rather than turnkey applications. It provides technology partners with the structure blocks for delivering modular and scalable applications, designed around the needs of individual organizations.

    As an open source vendor, the company moreover delivers Alfresco Community Edition and Activiti, designed for developers who freely want to extend its ECM platform and BPM tool sets.

    Key capabilities of Alfresco Digital Platform include:

  • access controls for defining user and group permissions to manage document access;
  • checkout/check-in library services;
  • version controls to track changes and enable rollbacks;
  • content sharing for team collaboration;
  • document lifecycle management from creation to disposition;
  • RM that conforms to predefined industry standards;
  • document management stewardship for business-critical documents;
  • mobile content management to synchronize document access;
  • process management tools to streamline cross-company industry processes;
  • social media interfaces for YouTube, Facebook, Twitter, LinkedIn, Flickr and SlideShare; and
  • workflow to benefit developers, administrators and nontechnical industry users design and manage industry processes.
  • Alfresco maintains a network of systems integrators, independent software developers (ISVs), infrastructure providers and resellers that design and deliver the enterprise applications tailored to specific customer requirements.

    Box Platform delivers cloud-native content services for the extended enterprise

    Founded in 2005 and born as a cloud-native provider, Box has steadily transformed its initial file sync and share into an enterprise-grade content services platform. Box Platform provides a content hub for organizing, securing and sharing content across the extended enterprise. The platform becomes the repository of record where content is stored once, managed systematically and produced on claim to empower industry results.

    Box Platform supports multiple approaches to cloud content management, content sharing and collaboration. As a distributed platform, it is not limited to the checkout/check-in library services and hierarchical access controls of a centralized ECM repository.

    Box provides seamless connectivity to Microsoft Office apps, email attachment support for Outlook and Gmail and indigenous support for G Suite apps -- Google Docs, Sheets and Slides. Box features an integrated workflow product -- Box Relay -- that automates and standardizes document workflows within the repository.

    Box Platform is a consistent architecture for managing almost any nature of content on a big scale. Beyond text, numbers and images -- the close components of industry documents -- content types comprehend audio, video, 3D files and many other kinds of wealthy media artifacts. It features multiple methods for organizing and accessing content, including several that utilize machine learning technologies.

    Since its inception, Box Platform has excelled in metadata management. Metadata can be set within the Box web application or programmatically via APIs. Application developers can apply these APIs to develop purpose-built applications that deliver innovative digital experiences.

    Box Platform runs as a cloud-based service that the company hosts in various data centers, located in different geographies around the world. Box Zones enables enterprises to specify geographic locations for hosting to comply with data sovereignty requirements. Box supports multiple security, privacy, compliance and data protection standards, including GDPR, Health Insurance Portability and Accountability Act, Federal Risk and Authorization Management Program/Federal Information Security Management Act and industry-specific agreeable rehearse guidelines.

    Hyland OnBase adds ECM to core imaging and archiving capabilities

    Hyland Software released its first version of OnBase in 1991, in the PC and client/server computing era, as an application for banks to store fiscal reports directly on optical disks. The company has modernized its core product over the years, while continuing its focus on document capture, imaging and archiving capabilities.

    OnBase currently provides a sole database, code base and central repository for industry documents, so it is the best ECM software for a company looking for numerous places to store data. It encompasses five key components:

  • Capture for scanning difficult copy documents, capturing electronic documents and extracting germane metadata for indexing;
  • Store for securely storing files either in an on-premises repository or in Hyland Cloud -- the company currently maintains nine data centers around the world;
  • Access for managing access controls by people or processes;
  • Manage for applying workflow and BPM capabilities to electronic documents; and
  • Measure for providing reports and real-time views of industry data.
  • OnBase integrates with the latest versions of Microsoft Office and Outlook, SAP and AutoCAD.

    OnBase delivers a central content repository, linking stored documents to transactions in other enterprise applications, such as ERP, accounting and HR systems. It supports back-office processing, case management and information governance and can moreover manage content coming from transactional systems. Thus, auditors, reviewing invoices for an audit, can easily find supporting contracts and purchase orders, while working within their close industry systems.

    Capable of supporting organizations of any size, OnBase includes enhancements to meet the needs of specific plumb industries: healthcare, fiscal services, insurance, government and higher education.

    IBM Enterprise Content Management suite tailors content management capabilities to the enterprise

    With suffer in the ECM marketplace dating from the 1980s, IBM delivers a set of interrelated ECM products for managing unstructured industry information, while moreover protecting customers' investments in legacy systems.

    IBM Content Foundation is a fully functional content repository with enterprise-grade security, designed to store, organize and access every sole types of industry information. It can be deployed on premises, in the cloud or in a hybrid environment. Workgroups can access team spaces to collaborate on projects. Content Foundation supports basic enterprise search capabilities.

    IBM FileNet Content Manager extends the capabilities of the core repository and features tools for content lifecycle management, transactional content processing and content consolidation across the enterprise. It includes checkout/check-in library services and other document management capabilities. FileNet features compliance and governance tools for RM, as well as APIs for content-centric application development.

    IBM Watson Explorer delivers cognitive search and content analytics functionality, extending ECM search to comprehend intuitive and smart queries of document repositories within an enterprise.

    IBM Content Manager OnDemand provides access to published content collections, such as fiscal statements, insurance policies and other formal industry documents. OnDemand features its own high-performance repository to store and bear these content collections.

    IBM Content Navigator is an extensible, browser-based web client for accessing content stored within ECM repositories from both PCs and mobile devices.

    IBM Datacap provides high-speed scanning and optical character recognition (OCR) extraction to digitize difficult copy documents and store them within a repository.

    IBM industry Automation Workflow enables customers to resolve content and route industry documents through predefined steps in a industry process. The complete case is then stored within the repository, with plenary audit controls.

    Microsoft SharePoint as an extensible ECM platform

    Microsoft SharePoint is a many-sided and extensible ECM platform, designed to manage documents, webpages and other content types. Microsoft launched SharePoint in 2001 to benefit organizations create web portals and team spaces by enhancing Windows file shares and the capabilities of Office products. By 2007, Microsoft had extended SharePoint to comprehend key ECM capabilities: library services, access control lists (ACLs), metadata management, indexing, workflow and RM. Current platform versions, SharePoint 2016 and SharePoint 2019, comprehend integrated enterprise search capabilities and several features for team collaboration.

    Organizations configure SharePoint to solve a wide sweep of document management, content management and collaboration problems within an enterprise. Organizations deploy SharePoint to bear webpages for both employee-facing and customer-facing websites. SharePoint moreover delivers blogging and wiki functionality and supports several interfaces for sharing information with gregarious media platforms -- publicly through Facebook and LinkedIn, as well as privately through services such as Yammer.

    SharePoint runs both on premises and in the cloud. SharePoint Server is the on-premises package, delivering ECM, industry intelligence and enterprise search capabilities. Designed for organizations of every sole sizes, SharePoint Online hosts in the Microsoft Azure cloud and is typically bundled with Office 365 subscriptions. SharePoint moreover supports hybrid deployments where organizations benefit from the flexibility of the cloud, while maintaining on-premises security for sensitive content.

    Relying on Microsoft OneDrive for Business, SharePoint supports file sync-and-share capabilities with mobile devices. SharePoint 2019 includes a modern user experience, featuring responsive website design capabilities that peruse agreeable and scale appropriately on smartphones and tablets, as well as on full-screen web browsers.

    Finally, the SharePoint platform integrates with many enterprise applications and can manage unstructured industry documents, such as scanned invoices, bills of lading and material safety data sheets, for ERP and CRM applications. SharePoint APIs originate it facile to integrate with applications within the Microsoft ecosystem. SharePoint moreover supports Content Management Interoperability Services for direct integration with other ECM platforms.

    OpenText Content Suite Platform targets enterprise information management, governance and compliance

    OpenText Content Suite Platform, the company's stalwart ECM product, manages industry documents and other types of unstructured content within an organization. It supports plenary content lifecycle capabilities, from creation and capture, to archiving and disposition. Deployed either on premises or in the cloud, the platform delivers a unified, centralized enterprise information management environment, connecting people and processes across an extended enterprise.

    Designed for exhaust by big organizations, OpenText Content Suite Platform encompasses eight major components:

  • OpenText Content Server provides a central repository for managing industry documents and other kinds of content. It features enterprise-grade document management capabilities, including library services, multilayer security, access controls, content navigation, enterprise search and workflow. It includes a browser-based, responsive UI that can be customized by roles and projects and reconcile to device screen sizes. The repository moreover supports content sharing for team collaboration, as well as content reporting for tracking content usage.
  • OpenText Imaging Enterprise Scan supports content capture and OCR indexing from scanners and electronic documents, including faxes, email messages and other report formats.
  • OpenText Enterprise Connect enables users to continue to connect to Content Server directly from desktop applications, such as Microsoft Office and Adobe Acrobat.
  • OpenText Connected Workspaces provides templates and scripts for creating ECM-enabled industry applications. Workspaces incorporates industry information managed by external applications, such as SAP, SharePoint and Salesforce. Workspaces aggregates unstructured content, structured data, people and tasks to support a common industry function, such as a sales occasion or a project.
  • OpenText Records Management supports records classification and temperament schedules. It applies RM metadata, classifications and temperament tags to files stored within the repository. Record classifications map to retention schedules and remove records from the collection at the nearby of their lifecycle.
  • OpenText Archive headquarters utilizes RM to support rules-based, policy-driven archiving and content governance.
  • OpenText Tempo Box provides secure file sync-and-share capabilities with content stored on mobile devices, including remote wiping of mobile content stores.
  • OpenText Directory Services provides centralized enterprise directory services for user management.
  • OpenText provides a sweep of progress tools, so it is the best ECM to enable organizations to develop applications on top of Content Suite and integrate with other enterprise applications. Content Server supports RESTful APIs for integration with web-based services.

    OpenText Documentum manages documents within the enterprise

    OpenText Documentum is an ECM platform for managing industry documents across the extended enterprise. Acquired from Dell EMC in January 2017, it is a highly scalable, fault-tolerant platform. It is the best ECM software for big enterprises with extensive document collections, such as engineering design documents or unique drug applications, that reckon on Documentum to support essential industry operations.

    The Documentum platform includes multiple key components:

  • At its core, Documentum ECM is a shared central repository for securely storing and managing different types of industry documents.
  • Documentum xCP is a progress platform that includes a wealthy set of BPM tools, designed to benefit companies automate high-volume, information-intensive processes, such as case management.
  • Running within a web browser, Documentum D2 provides the UI capabilities for accessing enterprise content stored within the shared repository.
  • The Documentum platform integrates with additional components that address particular industry requirements:

  • Captiva is a set of ECM tools that automate document captureand transform information for content management systems, classifying data for subsequent industry processing.
  • Document Sciences provides tools for producing high-volume personalized documents, such as insurance policies.
  • Syncplicity provides secure file synchronization and sharing capabilities to mobile devices.
  • Documentum provides multilanguage support and localization, perhaps making it the best ECM software for globally distributed content management environments. It includes content analytics capabilities to automatically extract metadata and classify content. It offers federated search capabilities to retrieve documents from multiple repositories. The Documentum ECM tools suite supports both proprietary and open source APIs to deliver customized enterprise application environments.

    Oracle WebCenter Content delivers a scalable ECM application

    Many companies find Oracle WebCenter Content as the best ECM software for managing unstructured content across the entire content lifecycle. Oracle WebCenter Content helps enterprises simplify their enterprise application infrastructure by managing industry documents and other content types through a single, consistent application.

    Through Oracle WebCenter Content, businesses overcome information silos where disparate applications manage the content. Companies can enhance their productivity and optimize content distribution, consolidating ECM into a sole application.

    Oracle WebCenter Content features an extensive set of ECM capabilities, including:

  • full library services, including checkout/check-in and version management;
  • ACLs to determine the security and permissions for editing and viewing content;
  • while stored in indigenous formats, document conversion on the Fly to other formats, including HTML conversion for web publishing;
  • scanning documents and then utilizing Oracle's OCR tools to bear machine-readable text;
  • tailoring to bear context-specific metadata for content classification;
  • For Microsoft Office users, checking documents into and out of the central repository directly from their desktop applications;
  • mobile apps that originate managed content accessible on smartphones and tablets;
  • document retention and lifecycle management, including support for DoD 5015.2-STD v3, a federal RM standard; and
  • embedded workflows to streamline cross-company industry processes.
  • Using prepackaged adapters, Oracle WebCenter Content integrates with many accepted enterprise applications, including PeopleSoft, Siebel, JD Edwards, Primavera, Microsoft SharePoint and Office 365.

    NVIDIA Delivers Massive Performance Leap for deep Learning, HPC Applications With NVIDIA Tesla P100 Accelerators | existent questions and Pass4sure dumps

    Five Architectural Breakthroughs Enable Servers to Deliver Over 12x Greater Performance Than Previous Architecture

    SAN JOSE, CA--(Marketwired - Apr 5, 2016) - GPU Technology Conference -- NVIDIA (NASDAQ: NVDA) today introduced the NVIDIA® Tesla® P100 GPU, the most advanced hyperscale data headquarters accelerator ever built.

    The latest addition to the NVIDIA Tesla Accelerated Computing Platform, the Tesla P100 enables a unique class of servers that can deliver the performance of hundreds of CPU server nodes. Today's data centers -- vast network infrastructures with numerous interconnected commodity CPU servers -- process big numbers of transactional workloads, such as web services. But they are inefficient at next-generation ersatz intelligence and scientific applications, which require ultra-efficient, lightning-fast server nodes.

    Based on the unique NVIDIA Pascal™ GPU architecture with five breakthrough technologies, the Tesla P100 delivers unmatched performance and efficiency to power the most computationally demanding applications.

    "Our greatest scientific and technical challenges -- finding cures for cancer, understanding climate change, structure brilliant machines -- require a near-infinite amount of computing performance," said Jen-Hsun Huang, CEO and co-founder, NVIDIA. "We designed the Pascal GPU architecture from the ground up with innovation at every level. It represents a massive leap forward in computing performance and efficiency, and will benefit some of the smartest minds drive tomorrow's advances."

    Dr. John Kelly III, senior vice president, Cognitive Solutions and IBM Research, said: "As they enter this unique era of computing, entirely unique approaches to the underlying technologies will be required to fully realize the benefits of AI and cognitive. The combination of NVIDIA GPUs and OpenPOWER technology is already accelerating Watson's learning of unique skills. Together, IBM's Power architecture and NVIDIA's Pascal architecture with NVLink will further accelerate cognitive workload performance and further the ersatz intelligence industry."

    Five Architectural Breakthroughs The Tesla P100 delivers its unprecedented performance, scalability and programming efficiency based on five breakthroughs:

  • NVIDIA Pascal architecture for exponential performance leap -- A Pascal-based Tesla P100 solution delivers over a 12x augment in neural network training performance compared with a previous-generation NVIDIA Maxwell™-based solution.
  • NVIDIA NVLink for maximum application scalability -- The NVIDIA NVLink™ high-speed GPU interconnect scales applications across multiple GPUs, delivering a 5x acceleration in bandwidth compared to today's best-in-class solution1. Up to eight Tesla P100 GPUs can be interconnected with NVLink to maximize application performance in a sole node, and IBM has implemented NVLink on its POWER8 CPUs for enjoy a glitter CPU-to-GPU communication.
  • 16nm FinFET for unprecedented energy efficiency -- With 15.3 billion transistors built on 16 nanometer FinFET fabrication technology, the Pascal GPU is the world's largest FinFET chip ever built2. It is engineered to deliver the fastest performance and best energy efficiency for workloads with near-infinite computing needs.
  • CoWoS with HBM2 for expansive data workloads -- The Pascal architecture unifies processor and data into a sole package to deliver unprecedented compute efficiency. An innovative approach to memory design, Chip on Wafer on Substrate (CoWoS) with HBM2, provides a 3x boost in memory bandwidth performance, or 720GB/sec, compared to the Maxwell architecture.
  • New AI algorithms for peak performance -- unique half-precision instructions deliver more than 21 teraflops of peak performance for deep learning.
  • The Tesla P100 GPU accelerator delivers a unique level of performance for a sweep of HPC and deep learning applications, including the AMBER molecular dynamics code, which runs faster on a sole server node with Tesla P100 GPUs than on 48 dual-socket CPU server nodes3. Training the accepted AlexNet deep neural network would occupy 250 dual-socket CPU server nodes to match the performance of eight Tesla P100 GPUs4. And the widely used weather forecasting application, COSMO, runs faster on eight Tesla P100 GPUs than on 27 dual-socket CPU servers5.

    The first accelerator to deliver more than 5 and 10 teraflops of double-precision and single-precision performance, respectively, the Tesla P100 provides a giant leap in processing capabilities and time-to-discovery for research across a broad spectrum of domains.

    Updates to the NVIDIA SDKNVIDIA moreover announced a host of updates to the NVIDIA SDK, the world's most powerful progress platform for GPU computing.

    These updates comprehend NVIDIA CUDA® 8. The latest version of NVIDIA's parallel computing platform gives developers direct access to powerful unique Pascal features, including unified memory and NVLink. moreover included in this release is a unique graph analytics library -- nvGRAPH -- which can be used for robotic path planning, cyber security and logistics analysis, expanding the application of GPU acceleration into the realm of expansive data analytics.

    NVIDIA moreover announced cuDNN version 5, a GPU-accelerated library of primitives for deep neural networks. cuDNN 5 includes Pascal GPU support; acceleration of recurrent neural networks, which are used for video and other sequential data; and additional enhancements used in medical, oil and gas, and other industries. cuDNN accelerates leading deep learning frameworks, including Google's TensorFlow, UC Berkeley's Caffe, University of Montreal's Theano and NYU's Torch. These, in turn, power deep learning solutions used by Amazon, Facebook, Google and others.

    Tesla P100 Specifications Specifications of the Tesla P100 GPU accelerator include:

  • 5.3 teraflops double-precision performance, 10.6 teraflops single-precision performance and 21.2 teraflops half-precision performance with NVIDIA GPU BOOST™ technology
  • 160GB/sec bi-directional interconnect bandwidth with NVIDIA NVLink
  • 16GB of CoWoS HBM2 stacked memory
  • 720GB/sec memory bandwidth with CoWoS HBM2 stacked memory
  • Enhanced programmability with page migration engine and unified memory
  • ECC protection for increased reliability
  • Server-optimized for highest data headquarters throughput and reliability
  • Availability universal availability for the Pascal-based NVIDIA Tesla P100 GPU accelerator in the unique NVIDIA DGX-1™ deep learning system is in June. It is moreover expected to be available birth in early 2017 from leading server manufacturers.

    Supporting Resources

    Keep Current on NVIDIA Subscribe to the NVIDIA blog, follow us on Facebook, Google+, Twitter, LinkedIn and Instagram, and view NVIDIA videos on YouTube and images on Flickr.

    About NVIDIA NVIDIA (NASDAQ: NVDA) is a computer technology company that has pioneered GPU-accelerated computing. It targets the world's the most demanding users -- gamers, designers and scientists -- with products, services and software that power Amazing experiences in virtual reality, ersatz intelligence, professional visualization and autonomous cars. More information at

    (1) NVLink delivers 160GB/sec of bi-directional interconnect bandwidth, compared to PCIe x16 Gen3 that delivers 31.5GB/sec of bi-directional bandwidth. (2) NVIDIA Tesla P100 GPU has 15.3 billion 16nm FinFET transistors.(3) CPU system: 48 nodes, each node with 2x Intel E5-2680v3 12 core, 128GB DDR4, FDR IB interconnect. GPU system: sole node, 2x Intel E5-2698 v3 16 core, 512GB DDR4, 4x Tesla P100, NVLink interconnect.(4) Compared to Caffe/AlexNet time to train ILSVRC-2012 dataset on cluster of two-socket Intel Xeon E5-2697 v3 processor-based systems with InfiniBand interconnect. 250-node performance estimated using source: CPU system: 2x Intel E5-2698 v3 16 core, 256GB DDR4. GPU system: sole node, 2x Intel E5-2698 v3 16 core, 512GB DDR4, 8x Tesla P100, NVLink interconnect.

    Certain statements in this press release including, but not limited to, statements as to: the impact, performance, benefits and availability of the NVIDIA Tesla P100 GPU, the NVIDIA SDK and NVIDIA DGX-1 deep learning system are forward-looking statements that are theme to risks and uncertainties that could judgement results to be materially different than expectations. distinguished factors that could judgement actual results to vary materially include: global economic conditions; their reliance on third parties to manufacture, assemble, package and test their products; the repercussion of technological progress and competition; progress of unique products and technologies or enhancements to their existing product and technologies; market acceptance of their products or their partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of their products or technologies when integrated into systems; as well as other factors circumstantial from time to time in the reports NVIDIA files with the Securities and Exchange Commission, or SEC, including its contour 10-K for the fiscal year ended January 31, 2016. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and talk only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

    © 2016 NVIDIA Corporation. every sole rights reserved. NVIDIA, the NVIDIA logo, Tesla, Pascal, Maxwell, NVIDIA NVLink, CUDA, NVIDIA GPU BOOST, and DGX-1 are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are theme to change without notice.

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    AICPA [2 Certification Exam(s) ]
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