Enterprise IT Watch Blog


July 2, 2018  7:05 AM

How AI is teaching robots to speak fluent human

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
Artificial intelligence, Robotics


Robotics image via FreeImages

By James Kobielus (@jameskobielus)

The only place where robots actually look like real human beings is in the movies. And that’s only because cinema artists have perfected the use of live actors, motion-capture technology, and computer-generated imagery. I seriously doubt that Steven Spielberg will live long enough to direct an actual android playing a fictional android.

However, we’re already beginning to hear robotic speech that is indistinguishable from what emanates naturally from the human vocal tract. That’s pretty much what Google’s new Duplex technology has been able to achieve. Though the vendor demonstrated it coming from its next-generation smartphone operating system rather than from a distant R2D2 relative, this new artificial intelligence (AI)-driven speech generation technology is clearly capable of being embedded in any device. So it probably won’t be long till robot manufacturers embed it in mechanisms that resemble sci-fi androids.

It’s only a matter of time before these “uncanny valley” robots speak fluent human, perhaps even more mellifluously than those of us who were born with the old-fashioned type of tongue. Or, as it was phrased in this recent article, many of us will start to regard the natural language processing (NLP) variety of AI as little more than a “chatbot in a robot suit.” Their robotic voices will echo across the uncanny valley as if they were coming from lips of flesh and blood.

Within our lifetimes, “robotic” will lose the connotation of conspicuously artificial, especially where their speaking voices are concerned. As robotic audio processing technology comes into our lives, it will create conversational user interfaces of amazing naturalness. Chatbots, now the subject of so much derision for their awkward speech, will become amazingly and automatically human with little or no training. And they will serve as auditory nerve centers of any physical robot that is built to interact with you and me.

Generative audio is one of AI’s hottest research frontiers. This technology can now render any computer-generated voice into one that truly sounds like it was produced in a human vocal tract. It can translate text to speech with astonishing naturalness. It can also compose music that feels like it expresses some authentic feeling deep in the soul of an actual human musician.

To resemble humans with uncanny precision, robots should be attuned to and be able to produce the full range of non-verbal utterances of which people are capable. In addition, they should be able to create and respond to music just like people do. And, going beyond voices and instruments, they must be able to manipulate sound-producing objects with full fidelity in the same meaningful, environmentally aware patterns that we normally associate with human agency.

For robots to truly embody the full sonic signature of flesh-and-blood humans, generative audio techniques will need to advance to the point where AI can help devices achieve near-perfect mastery of human behavior in each of the following tasks:

  • Robotic mimicry: Vocalized language is one of the hallmarks of the human species. This is what Duplex has achieved, in terms of vocalizing with uncanny fidelity like some random human being, as opposed to mimicking the speech patterns of a specific individual. Within the Android mobile OS, Duplex enables Google Assistant to carry on natural-language phone conversations without betraying the fact that it’s a bot. Clearly, this innovation has triggered waves of concern about its potential to transform robo-calling into a tool for mass deception on an unprecedented scale. By relegating synthesized digital-assistant voices to history’s dustbin, Duplex has leapt over that uncanny valley clear to the other side. But for Duplex and equivalent speech generation technologies to become truly revolutionary, they will need to advance to the point where they have the flexibility to mimic any speaker in any dialect or language, and inject a believable quality of humanlike emotion into their delivery. This will, of course, require not just an underlying text-to-speech NLP technology of unprecedented sophistication, but also continual training of this technology from live or recorded speech samples from people in every linguistic community.
  • Robotic conversation: Language isn’t fully human unless it’s engaged in conversations. This is what the next version of Google Assistant has been built to do, but only in a very limited fashion. Rather than attempt to truly ace the Turing test, Google Assistant will be able to respond to questions with multiple subjects. It will also be able to continue conversations without having to constantly repeat the trigger phrase “Hey Google.” And, in league with Google Duplex and TensorFlow Extended, it will be able to carry on natural phone conversations, based on its ability to understand complex sentences, fast speech, long remarks, and speaker intent. But it won’t be able to engage in the back-and-forth of debate, argumentation, and engaged conversation at the same level as humans. For that, we’ll need technologies such as what IBM has built under its Project Debater. Though it’s still quite limited and not integrated with audio-speech recognition technology, this NLP-based AI program could conceivably win an argument, though it quite literally doesn’t know what it’s talking about. Instead, it was built and trained by IBM researchers from large repositories of textual human conversations of a topic-focused nature. The technology rapidly analyzes huge of amount of textual conversational records before constructing a a plausible argument on a specific topic. It constructs arguments as sequences of conversation-contextual statements that combine winning elements of previous human arguments.
  • Robotic musicianship: Music is very much a human language that robots can consume, produce, and engage around. This is what the growing range of generative music programs are able to do, using convolutional neural networks, NLP, and other AI tools to compose and perform music of various sorts with the occasional lyric. For example, Google Deepmind’s “WaveNet”  can generate convincing music-like recordings by training a deep learning model on audio recordings of human-performed classical piano pieces. Along these same lines, iZotope’s Neutron 2 uses AI to isolate individual instruments and voices in a recording, thereby facilitating AI-assisted remixing of those elements into a unique new recording-like object. However, these “source separation” capabilities are limited to relatively simple musical and vocal performances, and the challenges of isolating the vast range of instrumentals and vocals in recorded or live musical performances—such as in symphonic music–are still beyond the capabilities of even the best AI-based tools. But the potential of solutions that can do this is great, which explains why researchers such as Eriksholm—the R&D center for hearing aid manufacturer Oticon—are exploring use of sophisticated AI techniques such as convolutional recurrent neural networks to distinguish voices and other sounds in natural environments, with the hope that they could be generalizable to real-world musical contexts as well.
  • Robotic audio engineering: Humans inhabit a sonic cacophony that expresses the complexity of our lived and built experience as a social species. As an aspect of ambient engineering, audio can be sculpted into diverse forms and for myriad purposes. For example, acoustical engineering is a well-established discipline with applications in urban planning, architecture and interior design, facilities monitoring and management, noise-pollution mitigation, and other disciplines of that necessary to quality of life, privacy, and other societal concerns. Robotics could conceivably handle more of these functions through algorithmic tools in such areas as automated audio mastering and refinement (e.g., LANDR, which uses AI to automate setting of audio parameters). Along these lines, AI could also be used to build high-quality audio outputs from inputs gathered from low-quality microphones; to emulate analog audio where there are only digital audio inputs; to add binaural effects such as simulated stereo; to add reverb, echo, and doppler shifts to provide spatial heft to sound outputs; to apply selective noise cancellation, boosting, and multi-tracking to create an immersive audio tableaux.

However, robots won’t truly be able to perform these amazing feats autonomously until they can emulate humans’ organic audio-processing abilities at a fine-grained level. With that in mind, I took great interest in this recent blog in which AI engineer Daniel Rothmann outlines the layers of neuromorphic audio-processing needed to equip robots with ability to comprehend audio material with human-like sophistication.

What’s clear is that the technology needed to perfect humanlike robot audio capabilities is not entirely worked out by the AI community. In his article, Rothmann mapped out a framework for robotic audio processing that aligns roughly with the architecture of the human auditory system:

  • Response of the eardrum to the air pressure fluctuations that produce our perception of sounds (as captured through raw digital audio samples)
  • Representation of those fluctuations on the fluid-filled cochlea organs in our inner ears (as processed through gammatone filterbanks)
  • Persistence of those representations in the sensory memories associated with auditory information (as processed through dilated circular buffers)
  • encoding of those sensory memories in our central nervous system (as processed through long short term memory encoders)
  • processing of those neural encodings in the auditory cortexes of our brains (as processed through neuromorphic circuitry that can distill it all into valid cognitive, affective, sensory, and other meaningful patterns)

Teaching robots to speak fluent human will be no easy task. It is far more than a matter of building AI that is grounded in computational linguistics, machine translation, and situational awareness.

It goes beyond words. Giving robots human fluency requires that we embody them with mastery over the full range of the human faculties for shaping the sonic environments in which we live.

July 2, 2018  7:01 AM

TechTarget’s weekly roundup (6/25 – 7/2)

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
Container, Data Science, Hadoop, Linkedin, Unified Communications


Social Media image via FreeImages

What do you think of the possibility that the LinkedIn Talent Insights analytics tool may increase poaching? Find out why the company is not shying away from this outcome in this week’s roundup.

1. Recruiting on LinkedIn adds analytics and pointed questions – Patrick Thibodeau (SearchHRSoftware)

LinkedIn is releasing an analytics platform at the end of the third quarter. The platform will allow users to quickly compare themselves to other firms.

2. Ex-Cisco exec Rowan Trollope promises to be different CEO at Five9 – Jonathan Dame (SearchUnifiedCommunications)

In May, UC and collaboration exec Rowan Trollope left Cisco for a nimbler Five9. As CEO of the contact center vendor, he promises to be more product-focused than his predecessor.

3. Building a data science pipeline: Benefits, cautions – George Lawton (SearchCIO)

A data science development pipeline is critical for digital business. But the sequence of the pipeline must be monitored closely to ensure the output reflects the business goal.

4. Container orchestration systems at risk by being web-accessible – Michael Heller (SearchSecurity)

Security researchers found tens of thousands of container orchestration systems accessible via the web, which in itself puts those dashboards at risk of attack.

5. Hadoop data lake architecture tests IT on data integration – Jack Vaughan (SearchDataManagement)

Hortonworks users talk about building Hadoop data lakes to support new applications — and the challenges their teams face on ingesting and refining data for end users.


June 25, 2018  7:47 AM

TechTarget’s weekly roundup (6/18 – 6/25)

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
cybersecurity, Healthcare, iot, Machine learning, Swift


Security image via FreeImages

Do you think the NSA holds any responsibility for its leaked exploits being repurposed? Why or why not? Check out why experts believe the NSA should not be held accountable for the damages in this week’s roundup.

1. PyRoMineIoT cryptojacker uses NSA exploit to spread – Michael Heller (SearchSecurity)

The latest malware threat based on the EternalRomance NSA exploit is PyRoMineIoT, a cryptojacker infecting IoT devices. But experts said the NSA shouldn’t be held responsible for the damages.

2. Mobile app machine learning imagines a bigger future with Swift – Kristen Gloss (SearchMobileComputing)

Swift has the potential to lead the way to easier implementation of mobile app machine learning. Discover new tools for creating AI models in Swift and their use cases.

3. AARP, startups partner to study digital healthcare technology – Makenzie Holland (SearchHealthIT)

Clinicians and groups like AARP view in-home digital technology as the future of healthcare and are studying different technologies to assist patients in the home.

4. Unchecked cloud IoT costs can quickly spiral upward – Trevor Jones (SearchCloudComputing)

IoT sensors can produce seemingly endless streams of data, so users must beware how much to send back to the cloud to avoid jaw-dropping monthly bills.

5. Herjavec: Cybersecurity investment now a priority for for CEOs, boards – Ben Cole (SearchCIO)

How did Robert Herjavec, CEO of a global IT security firm and star of NBC’s ‘Shark Tank,’ know cybersecurity was gaining traction? He started getting meetings with the C-suite.


June 18, 2018  8:06 AM

TechTarget’s weekly roundup (6/11 – 6/18)

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
Business Intelligence, Data Recovery, Databricks, Machine learning, salesforce, Security


North Korea image via FreeImages

How should the U.S. government address North Korean cyberattacks during summit negotiations? Find out why we should still be worried about North Korean hacking and cyberespionage in this week’s roundup.

1. North Korea hacking threat still looms despite summit – Rob Wright (SearchSecurity)

Despite a summit between President Trump and North Korean leader Kim Jong Un, the threat of North Korean hacking and cyberespionage still looms large, according to experts.

2. Databricks platform additions unify machine learning frameworks – Ed Burns (SearchEnterpriseAI)

Databricks’ new products take aim at simplifying machine learning integration — something that has become increasingly difficult, as the number of tools has multiplied.

3. Tableau acquisition of MIT AI startup aims at smarter BI software – Mark Labbe (SearchBusinessAnalytics)

Tableau acquires AI startup Empirical Systems in a plan to provide users with automated data modeling capabilities and enable broader BI and analytics applications.

4. Salesforce Interaction Studio unveiled at Connections 2018 – Jesse Scardina (SearchSalesforce)

At Salesforce Connections, Salesforce builds off its Google partnership announced at Dreamforce by releasing new integrations between Marketing Cloud and Google Analytics 360.

5. Iron Mountain data recovery adds ransomware protection – Paul Crocetti (SearchDisasterRecovery)

The isolated nature of Iron Mountain’s latest Iron Cloud offering is important to its battle against ransomware. The Virtual Cleanroom provides an offline recovery environment.


June 13, 2018  1:58 PM

Waiting for blockchain hype to subside and data platform incumbents to play their hands

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
Blockchain


Data image via FreeImages

By James Kobielus (@jameskobielus)

Blockchain isn’t snake oil, but it’s not exactly the panacea that we’re being led to believe.

Yes, many promising technologies got through this hype phase before mass adoption, but the blockchain mania seems to lack the center of gravity that old-timers like me used to call a “killer app.” In enterprise IT, there’s not even any consensus about where blockchain should sit in the stack of promising projects to explore. By some accounts, blockchain is gaining momentum among IT practitioners. But other observers have surveyed enterprise IT executives and found precious little enthusiasm for the technology.

No one doubts that blockchain has use cases for which it’s ideally suited and will be commercialized successfully. But if anybody’s making serious money from this open-source technology right now, it’s the hypesters. I couldn’t help noticing when the roguish John McAfee added blockchain hype to his revenue model. This recent interview revealed that he now charges $105,000 per tweet to promote different cryptocurrencies and has advised or worked with well over dozen startups in this space.

That’s why I couldn’t help laughing as I sifted through one outlandish McAfee assertion after another, such as:

  • “Every field of life is being enhanced, bettered, made cleaner, safer, more convenient and cheaper with cryptocurrency and the blockchain.”
  • “In five years, there will be nothing that’s not on the blockchain.”
  • “The people who understand there is no boss, central authority or central design will be making hundreds of millions of dollars, and everybody else will fail.”
  • “With the blockchain, you don’t have an idea. You simply get the people together and see what comes out.”

With that last statement, I felt like I was going to pass out, seeing as how McAfee seems to be advising us to switch off our critical minds when blockchain enters the conversation. This is the kind of exhortation where a tech evangelist starts to sound like a cult leader who wants our money along with our unquestioning devotion to the sacred cause. This collectivist “you simply get people together” tenet seems to be yet another page out of the crusading evangelists textbook. And the promise of one clique getting super-rich while “everybody else will fail” sums up the blockchain true believer’s saved-or-damned outlook very nicely.

It will be good in a few years’ time when blockchain mania is ancient history and we learn where this technology ends up in the current pantheon of next big things, including artificial intelligence, autonomous vehicles, intelligent robotics, augmented programming, edge computing. Wikibon finds a lot of innovation taking place in the intersections between blockchain and these emerging technologies, as well as in such established enterprise infrastructure as industrial IoT and identity management.

Regarding blockchain’s commercialization, I doubt that the getting-rich will be as speedy as McAfee wants to believe, due in parat to the very collectivism he calls out as necessary to the technology’s deployment.

It’s highly doubtful that greenfield blockchains will just waltz into existing industries and rapidly disrupt existing B2B practices to the advantage of some new class of competitors. If this scenario is realistic, then why, in the almost 10 years since blockchain sprang forth from the bowels of Bitcoin, have we seen no one seize this opportunity to disrupt market after market and get filthy rich in the process?

In a recent article, Deloitte discussed the pivotal role of B2B collectives and their stakeholders in building successful blockchains. “Generating the greatest value from blockchain will require organizations to collaborate with competitors, regulatory bodies, form or join consortia and partner with startups. For many organizations, this level of collaboration requires organizations to adopt new ways of working, both internally and externally….Standardisation will enable enterprises to share blockchain solutions more easily and collaborate on their development. CIOs can start to set the standards for this. For example, by working with external developer ecosystems, teams can begin to exchange ideas and key learnings with like-minded organizations…Data management and process standards already exist in many organizations and these same standards can be applied to blockchain.”

One factor slowing enterprise embrace of blockchain is the chicken-and-egg difficulty of finding tech personnel who have operational experience with the technology. As Gartner said in a recent study, “The challenge for CIOs is not just finding and retaining qualified engineers, but finding enough to accommodate growth in resources as blockchain developments grow. Qualified engineers may be cautious due to the historically libertarian and maverick nature of the blockchain developer community.”

Clearly, McAfee is one of many blockchain evangelists who are targeting that “libertarian and maverick” element with their breathless pitches. One might more accurately call it a “gold-rush mentality,” with that analogy an almost-perfect fit for a mania that’s sustained by waves of “miners” panning their “stakes” for a new “coin” that may turn out to be, for the most part, fool’s gold.

Ironically, another key libertarian cause—privacy protection—may also throw a wrench into adoption of blockchain into the business world. As I noted recently, the new General Data Protection Regulation  (GDPR) is making it very difficult to justify deploying blockchain’s “immutable distributed hyperledger” into any application that manages the personally identifiable information (PII) of European Union citizens. The sticking point is that blockchain’s unchangeable historical record conflicts with GDPR’s guarantee of a “right to be forgotten”—in other words, to request that your PII be permanently deleted from any database—including blockchains—in which it’s been persisted.

Even if blockchain’s money train is able to exploit lucrative opportunities that don’t conflict with GDPR and similar laws elsewhere, it may be derailed in the long run by the laws of capitalism. As it was with the hopefuls who flocked to northern California in the 19th century, the real money to be made from blockchain will accrue to merchants who supply the tools of the trade.

In that regard, we’re already seeing who those blockchain beneficiaries will likely be, and, no surprise, it’s the incumbent IT vendors. Wikibon has been seeing an acceleration in blockchain-related platform and tooling announcements from established enterprise IT solution providers, with a consistent emphasis on making this technology play well in enterprise cloud data infrastructures:

  • Amazon Web Services recently launched new preset templates for rapid creation, deployment and securing blockchains in the AWS cloud. Accessible through this get-started page, these templates make it easier for developers to create blockchains on either of two blockchain versions: Ethereum and Hyperledger Fabric. AWS’s templates create peer-to-peer blockchains in which each participant has access to a shared ledger where the immutable, independently verifiable transactions are recorded. Users can leverage managed, certified AWS CloudFormation templates to automate the deployment of Ethereum and Hyperledger Fabric frameworks as well as additional required components. The blockchains may be deployed on Amazon Elastic Container Service or ECS clusters, or directly on an EC2 instance running Docker. Blockchains are created in the user’s own Amazon Virtual Private Cloud, allowing use of their PC subnets and network Access Control Lists. Users of AWS-hosted blockchains can assign granular permissions using AWS Identity and Access Management to restrict which resources an ECS cluster or EC2 instance can access. The blockchain templates are free of additional charge to AWS customers, though they must still pay for the AWS resources needed to run their blockchains on AWS. They can create and deploy blockchain networks in any public AWS region.
  • IBM recently launched its Blockchain Platform, which offers the capability as a software-as-a-service on its public cloud service. As described in this IBM whitepaper, the service runs on the open-source Hyperledger blockchain version from the Linux Foundation. It includes intuitive tooling that helps IBM Cloud subscribers to accelerate development and operationalization of a distributed, scalable and high-performance blockchain. Developers use Integrated Hyperledger Composer to turn business concepts into application code optimized for running on the deployed blockchain. Policy-based governance tools simplify network activation and management tasks across distributed blockchains. IBM Cloud’s always-on operations enable 24×7, no-downtime updates to blockchain applications. IBM provides tools for users to easily migrate from blockchain proofs-of-concept all the way through to production on a secure, high-performance and fully scalable networks in IBM Cloud. IBM provides a visual tool for users to manage blockchain administration and governance, iterative development and basic service levels. Under an Enterprise Plan, IBM Cloud offers a secure environment and advanced service levels for production-grade deployment, application development and testing.
  • Microsoft recently announced the public preview of Azure Blockchain Workbench at its Build conference. Available in the Azure MarketplaceWorkbench is a low-code development tool that enables developers to create, refine and deploy blockchain apps rapidly with minimal coding. The tool provisions an end-to-end blockchain, infrastructure and application on Azure with a few clicks. It integrates the blockchain with all the Azure services needed to build a functioning application. It can associate blockchain identities with federated identity systems through Azure Active Directory for single sign-on, and for simplified identity management throughout a B2B blockchain consortium. It stores secrets and keys securely with Azure Key Vault. It ingests and manages the events required to trigger smart contracts using Service Bus and Event Grid. It synchronizes on-chain data with off-chain storage and databases to query attestations and visualize ledger activity more easily. It leverages Microsoft Flow and Logic Apps to enable easy integration of blockchain workflows with existing systems. And it extends blockchain capabilities with a REST-based API for client development and a message-based API for system-to-system integration.
  • Oracle unveiled its open-source blockchain platform-as-a-service offering last fall at its OpenWorld conference. Oracle Blockchain Cloud Service is a comprehensive cloud platform for building, deploying, integrating, updating, querying, transacting, securing, scaling, administering and monitoring blockchains. The service includes client-side software development kits for enrolling blockchain members, adding peer nodes, creating channels, deploying smart contracts, registering for events, running transactions and querying ledger data using Java and Node.js. It provides REST APIs for integrating with other systems via Oracle Integration Cloud, Oracle Digital Innovation Platform and NetSuite SuiteCloud Platform. Developers can build new blockchain transactional applications in Oracle Java, Application Container, Mobile, Application Builder, Integration or SOA Cloud Services. Provisioning an Oracle blockchain instance spins up a production-ready platform including all required infrastructure services and embedded resources, including compute, containers, storage, identity management and event streaming. Built on Hyperledger Fabric, Oracle’s service takes the features of that open-source platform and adds security, confidential permissions and transactional processing capabilities for building enterprise-grade blockchain applications.

As can be seen from these announcements, vendors of blockchain infrastructure solutions are going to market with approaches that have served them well with established platforms. As I discussed here, these include blockchain platforms as a service, blockchain deployment templates, blockchain domain accelerators, and blockchain ecosystem hubs.

My sense is that the most innovative blockchain startups will emerge from their incumbent-fostered ecosystems, with the most successful players being deeply rooted in established industries. The many technical limitations of blockchain—in terms of performance and scalability for transactional data applications—will keep it from dominating many core enterprise use cases.

The incumbent enterprise data platform vendors will dominate blockchains. They will do so by playing their hands in the area of hybrid clouds, in which blockchains will be one important new data thread in the tapestry but far from the only one.

In other words, there is no blockchain monoculture on the horizon for enterprise data professionals.


June 11, 2018  8:16 AM

TechTarget’s weekly roundup (6/4 – 6/11)

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
Data protection, Github, Google, Microsoft, Pega systems, SAP


Acquisition image via FreeImages

What are the pros and cons of Microsoft’s GitHub acquisition for IT pros? Check out what the deal could mean for the IT industry in this week’s roundup.

1. Microsoft-Github acquisition shakes up DevOps market – Beth Pariseau and Ed Scannell (SearchITOperations)

Microsoft’s $7.5 billion blockbuster deal for GitHub is a sea change for the IT market, as an enterprise software bellwether with legacy baggage snaps up an open source DevOps darling.

2. Catalogic Software teams up with Storware data protection – Paul Crocetti (SearchStorage)

Catalogic and Storware executives feel their companies complement each other. The two data protection vendors have a distribution agreement and are working in partnership.

3. Pega Infinity upgrades include marketing AI tools, blockchain support – Don Fluckinger (SearchCRM)

Pega Infinity adds new digital transformation tools for low-code app development, bot libraries and AI that can optimize apps and assist with marketing campaigns.

4. Research claims ‘widespread’ Google Groups misconfiguration troubles – Michael Heller (SearchSecurity)

Researchers from Kenna Security claim a Google Groups misconfiguration has exposed sensitive data for many organizations, but it is unclear just how widespread the issue might be.

5. C/4HANA suite gets qualified thumbs up at SAP Sapphire Now – Jim O’Donnell (SearchSAP)

SAP debuts its Salesforce challenger, C/4HANA, at Sapphire Now 2018. But users probably won’t implement it soon, and questions remain about SAP’s ability to redefine the CRM market.


June 4, 2018  8:39 AM

TechTarget’s weekly roundup (5/28 – 6/4)

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
Artificial intelligence, CIO, Network security, Pure Storage, Security


Retailer image via FreeImages

Securing the world’s largest private employer, with more than 2 million people worldwide and an ever-expanding IT environment, is a daunting challenge. Find out how Walmart’s CISO is taking that challenge on in this week’s roundup.

1. New Walmart ISO discusses protecting the world’s largest retailer – Kathleen Richards (SearchSecurity)

Walmart CISO Jerry Geisler talks about the retail giant’s evolving cloud strategy, vulnerability management and risks the company is focused on across its environments.

2. MIT CIO: What is digital culture, why it’s needed and how to get it – Linda Tucci (SearchCIO)

Creating a digital culture is essential in the age of information, but companies must not lose sight of their core values in the process. Two tech execs show how they’re doing it.

3. Developers set to build AI for Accessibility apps – Darryl Taft (SearchCloudComputing)

Developers will support Microsoft’s $25 million push to get software makers to build apps that benefit disabled individuals.

4. Cato’s network security feature on the hunt for threats – Jennifer English (SearchSDN)

Cato Networks added a network security feature that detects and identifies threats within customer networks. The capability is built into Cato’s SD-WAN platform, Cato Cloud.

5. Pure Storage cloud plan gets warm reception from end users – Garry Kranz (SearchStorage)

Pure Storage made new FlashArray and FlashBlade all-flash systems generally available this week, emphasizing their role in moving data seamlessly between local and cloud storage.


May 29, 2018  8:17 AM

TechTarget’s weekly roundup (5/21 – 5/28)

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
cybersecurity, Human Resources, Serverless computing, Slack


Security image via FreeImages

How should enterprises prepare for possible attacks from Iranian hackers? Find out how Iran’s state-sponsored cyber operation is different from other nation-states in this week’s roundup.

1. Recorded Future sheds light on Iranian hacking operations – Rob Wright (SearchSecurity)

Recorded Future’s Levi Gundert discusses how the Iranian government uses proxies and contractors to launch cyberattacks, and how its strategy presents challenges for the country.

2. In a serverless architecture age, infrastructure still matters – Trevor Jones (SearchCloudComputing)

Sorry, developers, but infrastructure still matters, even as serverless architectures and containers diminish its central role to build new applications.

3. Federal HR wants to modernize cybersecurity recruiting, pay – Patrick Thibodeau (SearchHRSoftware)

The U.S. Dept. of Homeland Security wants to modernize recruitment and management of its cybersecurity workforce. It is asking vendors to explain how DHS can achieve its goals.

4. Pica8 wooing campus with white box network switch software – Chuck Moozakis (SearchNetworking)

Pica8 is rolling out new white box network switch software aimed at campus and branch-office deployments in a bid to build a new market.

5. Slack app integrations are made a two-way street – Jonathan Dame (SearchUnifiedCommunications)

Slack has designed a shortcut to convert Slack messages into content within business tools like Zendesk and Jira. The company said more than 90% of paid teams are using Slack app integrations.


May 21, 2018  8:09 AM

TechTarget’s weekly roundup (5/14 – 5/21)

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
Big Data, Data Analytics, DevOps, Google, Healthcare, IBM


Healthcare image via FreeImages

How effectively is your organization investing in health data analytics? Find out why investing in data is critical for healthcare organizations in this week’s roundup.

1. Healthcare data analytics success grows when IT advises execs – Dave Bernard (SearchHealthIT)

Educating healthcare executives about data analytics, and seeing that healthcare organizations invest in data, is critical, according to a panel of experts.

2. Google acquisition aims to simplify big data projects – Trevor Jones (SearchCloudComputing)

Google Cloud analytics tools are well-regarded for their technology, but not necessarily for their ease of use. Google’s acquisition of Cask Data could solve that shortcoming.

3. FBI: Business email compromise tops $676 million in losses – Kathleen Richards (SearchSecurity)

Verizon’s Data Breach Investigations Report indicates an increase in ransomware while the FBI’s Internet Crime Report shows a downward trend, with business email compromise on the rise.

4. Updated IBM storage products focus on cost savings and cloud – Carol Sliwa (SearchStorage)

IBM storage enhancements focus on data deduplication expansion, cloud-based Storage Insights, VM-based Spectrum NAS and Spectrum Virtualize for Public Cloud.

5. Serverless deployment lift enterprise DevOps velocity – Beth Pariseau (SearchITOperations)

Mainstream companies see mounting demand for serverless deployments for their new apps, but for existing apps, it’s another story.


May 14, 2018  8:25 AM

TechTarget’s weekly roundup (5/7 – 5/14)

Michael Tidmarsh Michael Tidmarsh Profile: Michael Tidmarsh
Artificial intelligence, Azure, Healthcare, Microsoft, Oracle


Artificial intelligence image via FreeImages

What’s your view of big tech’s investment in using artificial intelligence for good works? Check out how two organizations used AI for social good in this week’s roundup.

1. Artificial intelligence for social good: Big tech spins a new narrative – Nicole Laskowski (SearchCIO)

AI for social good is a thing. SAS touts research on tracking cheetah populations, Microsoft showcases work on precision farming at the Artificial Intelligence Conference.

2. Google, Fitbit, startups storm into healthcare AI – Shaun Sutner (SearchHealthIT)

Google is moving quickly into healthcare, forging alliances with Fitbit and selling AI services to smaller health IT vendors. Meanwhile, Fitbit is expanding into healthcare.

3. Azure IoT Edge tool set stirs AI into Microsoft’s cloud – Trevor Jones (SearchCloudComputing)

Microsoft extended more of its AI capabilities to connected devices to resolve some of the IoT shortcomings of the public cloud’s consolidated data center model.

4. Oracle Autonomous Database concept extended to PaaS, apps – George Lawton (SearchERP)

Having earlier laid the foundation with Oracle Autonomous Database, the vendor unveiled self-driving, self-repairing tools for application development, analytics and integration.

5. Microsoft patches Internet Explorer zero-day ‘Double Kill’ – Rob Wright (SearchSecurity)

Microsoft’s Patch Tuesday for May includes fixes for two zero-day vulnerabilities under attack, including an Internet Explorer exploit known as Double Kill.


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