Application image via FreeImages
By James Kobielus (@jameskobielus)
Artificial intelligence (AI) is transforming practically every aspect of the application, analytics, data management, and IT infrastructure markets.
Increasingly, AI applications live in the cloud. As Wikibon found in our recent Big Data Analytics Trends and Forecast, the application industry’s transformation toward AI-first go-to-market models is well underway.
In this regard, here are the key trends that Wikibon sees disrupting the application market in the era of all-things AI:
- Old-line business analytics application vendors are losing momentum as the market migrates to comprehensive public cloud-based offerings that use AI to add value to data warehousing, data lakes, stream computing, in-memory cubes, real-time decision support, and other traditional enterprise applications.
- Established application vendors are migrating their solutions to public clouds that leverage the sophisticated AI APIs, libraries, and 24×7 managed services in those environments.
- Analytic app vendors are shifting their solution portfolios toward delivery of packaged AI applications that deliver fast industry or task-specific business outcomes.
- Application platforms are being architected for continued versionless feature evolution through continual refresh of the AI, metadata, rules, graphs, and other intelligent artifacts that have been deployed to the cloud edge.
- Application development tools are evolving toward a focus on building and orchestrating AI microservices in distributed environments, especially in mobility, robotics, sensor networks, and other edge scenarios.
- Big data catalogs are becoming the centerpiece of vendors’ data-lake platforms, enabling real-time curation, exploration, modeling, training, deployment, and governance of AI applications.
- AI-driven IT management tools are becoming commonplace, enabling 24×7 automated event monitoring, root-cause diagnostics, and predictive remediation of application, network, and system performance.
- More new enterprise application-development projects that come online involve building AI-driven smarts for deployment to mobile, embedded, and Internet of Things endpoints, as well as to massively parallel data centers, and domain-specific gateways.
- Increasingly, enterprises will be adopting AI-infused solutions as pre-built, pre-trained templatized cloud offerings that continuously and automatically adapt and tune themselves to deliver desired business outcomes.
For more depth on all of these trends, please check out the market study here.
Speech image via FreeImages
Thanks to AI, speech technology is now more than just speech-to-text dictation for note taking and documentation. But find out why enterprises may not be ready for the technology in this week’s roundup.
1. Ready for artificial intelligence in speech recognition? – Katherine Finnell (SearchUnifiedCommunications)
Artificial intelligence in speech recognition is transforming the technology, but are enterprises ready to employ these new tools within their operations?
2. EBay’s Elasticsearch hack consolidates Kubernetes monitoring – Beth Pariseau (SearchITOperations)
EBay made Kubernetes monitoring more flexible for developers and consistent for ops through modifications that are now part of Elastic’s Beats software.
3. IIC addresses industrial IoT security on endpoints – Sharon Shea (IoT Agenda)
In a new document, the Industrial Internet Consortium abridges IEC and NIST publications, offering clear, concise guidance to ensure IIoT security in connected plants.
4. Scrivito unveils serverless CMS product – Jesse Scardina (SearchContentManagement)
By building the CMS with ReactJS, Scrivito gained attraction with development community, according to an analyst.
5. Leaked report on AMD chips flaws raises ethical disclosure questions – Michael Heller (SearchSecurity)
Researchers announced AMD chip flaws without the coordinated disclosure procedure, and a leak of the research to a short seller has raised further suspicions about the process.
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Unified communications has evolved well beyond telephony. And as a result, new big-name vendors have infiltrated the UC market and will headline Enterprise Connect 2018. Find out who in this week’s roundup.
1. New vendors, trends crash Enterprise Connect 2018 party – Luke O’Neill (SearchUnifiedCommunications)
Slack and Facebook are making their first appearances at the unified communications conference. Plus, contact center technologies could take center stage at the show.
2. Why improving social media customer service is important – Jesse Scardina (SearchCRM)
By having a social media strategy in place, companies can quickly respond to customers’ concerns through social media.
3. SAP debuts consumption-based pricing model for SAP Cloud – Jim O’Donnell (SearchSAP)
SAP Cloud Platform is now available as a consumption-based model, an alternative to the subscription model. SAP also updated the SCP SDK for iOS and released two new mobile iOS apps.
4. Reprimand on healthcare and cloud computing spurs HIMSS debate – Scott Wallask (SearchHealthIT)
The benefits of the cloud are well-known, as is the healthcare industry’s wariness about moving patient data to the cloud. At the HIMSS conference, the deliberations expanded.
5. Terabit DDoS attack hits 1.7Tbps and experts expect higher – Michael Heller (SearchSecurity)
Five days after a record breaking terabit DDoS attack, a new 1.7Tbps DDoS attack was detected taking advantage of improperly secured memcached servers to launch a reflection attack.
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No technology is hotter at HIMSS 2018 than AI. Check out how the conference is showcasing vendors and users turning to AI and machine learning for clinical and business applications in this week’s roundup.
1. HIMSS 2018 focuses on AI in healthcare – Shaun Sutner (SearchHealthIT)
With AI in healthcare trending, the HIMSS conference is showcasing vendors and users turning to AI and machine learning for clinical and business applications; interoperability also is hot.
2. Hyperscale providers bet big on cloud AI – Trevor Jones (SearchCloudComputing)
AI cloud services have emerged as yet another battleground for the hyperscale providers, as they entice data scientists and developers to train their models on their platforms.
3. Zerto Virtual Replication reduces marketing firm’s RPO – Sonia Lelii (SearchDisasterRecovery)
Maritz needed a short RPO and flexible cloud provider options for its recovery process. Zerto replication protects applications to and from clouds and between multiple clouds.
4. New SAML vulnerabilitiy enables abuse of single sign-on – Rob Wright (SearchSecurity)
Duo Security discovered a new SAML flaw affecting several single sign-on vendors that allows attackers to fool SSO systems and log in as other users without their passwords.
5. IT priorities survey: CRM trends indicate move to the cloud – Don Fluckinger (SearchCRM)
Hybrid cloud and on-premises IT should remain the norm for years. But more respondents to TechTarget’s late 2017 survey indicate more cloud CRM and social media monitoring.
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What steps has your organization taken to be GDPR-compliant by the May 25 deadline? Find out how you can handle GDPR data breach notifications in this week’s roundup.
1. GDPR data breach notification is just one piece of EU privacy puzzle – Peter Loshin (SearchSecurity)
With the EU’s General Data Protection Regulation looming, Qualys’ Darron Gibbard discusses GDPR data breach notifications, and more with the EU’s new privacy law.
2. IT priorities 2018: Regs, big data, cloud loom larger for GRC pros – Ben Cole (SearchCIO)
Regulatory initiatives remain at the top of GRC pros’ lists of tech projects, according to TechTarget’s annual IT Priorities 2018 survey, but grab less attention than last year.
3. Android Enterprise Recommended touts quick security updates – Colin Steele (SearchMobileComputing)
Google’s new program certifies devices that meet minimum hardware requirements, provide regular Android security updates and offer a consistent management experience.
4. Xively buy broadens Google Cloud IoT tool utility – Trevor Jones (SearchCloudComputing)
The latest Google Cloud acquisition points to a doubling down on IoT, as the company tries to keep pace with AWS and Microsoft Azure in this emerging market.
5. New IBM storage products key on NAS, cloud, NVMe over Fabric – Carol Sliwa (SearchStorage)
IBM launches new and updated Spectrum software-defined storage products, including a new NAS option, and commits to broadened end-to-end NVMe over Fabrics support by the third quarter.
Security image via FreeImages
What do you think about these new reports regarding the Equifax breach? Are you worried about your data? Check out the new details surrounding the breach in this week’s roundup.
1. Equifax breach worsens, additional consumer data exposed – Madelyn Bacon (SearchSecurity)
The Equifax breach compromised even more consumer data, including tax identification numbers, than originally reported. But the credit rating agency didn’t disclose the update.
2. Zerto Virtual Replication dives deeper into multiple clouds – Sonia Lelii (SearchDisasterRecovery)
Zerto has added to its bidirectional Virtual Replication software with multi-cloud protection for data and applications stored in AWS, Microsoft Azure and IBM Cloud.
3. Neurala claims ‘lifelong deep neural nets’ don’t forget – Nicole Laskowski (SearchCIO)
Boston startup Neurala says it has developed deep neural networks that can learn on the fly. Neurala’s COO Heather Ames explains.
4. VMware Workspace One helps Western Digital organize 3,000 apps – Alyssa Provazza (SearchEnterpriseDesktop)
The application portal in VMware Workspace One allowed IT to streamline app delivery, and the product’s cloud-based model proved the right fit for administration.
5. ExtraHop intros Reveal(x) cybersecurity analytics software – Chuck Moozakis (SearchNetworking)
ExtraHop fortifies its packet capture platform with cybersecurity analytics software, Reveal(x); Mist introduces a virtual network assistant powered by artificial intelligence.
Clouds image via FreeImages
What is NetApp planning to accomplish in 2018? Find out why the company is going to narrow its priorities to fast-growth areas in this week’s roundup.
1. NetApp CEO Kurian narrows focus to flash, cloud – Garry Kranz (SearchStorage)
George Kurian became CEO of NetApp in 2015 to jump-start a push into cloud and flash storage. The vendor has bucked scant revenue growth with four straight solid quarters.
2. Cisco: Cloud Computing workloads to skyrocket by 2021 – Chuck Moozakis (SearchNetworking)
By 2021, Cisco says, cloud computing workloads will make up the lion’s share of data center traffic as enterprises expand security, IoT and other activities in the cloud.
3. Avaya adds AI voice assistant to desk phones – Jonathan Dame (SearchUnifiedCommunications)
Avaya has created an AI voice assistant application for desk phones. AI voice assistant platforms could make mundane tasks easier for office workers.
4. Salesforce buys Attic Labs, adding to Quip capabilities – Jesse Scardina (SearchSalesforce)
Quip receives back-end capabilities with open source database after Salesforce purchase of Attic Labs.
5. IBM taps Mendix for low-code platform deal – Darryl K. Taft (SearchCloudApplications)
As the market to empower citizen app developers heats up, IBM and Mendix have joined forces to deliver low-code tools for the IBM Cloud.
Artificial Intelligence image via FreeImages
What do you see as the top challenges in developing an AI infrastructure for the enterprise? Find out why CIOs may have a tough time merging AI into their enterprise architectures in this week’s roundup.
1. CIOs need an AI infrastructure, but it won’t come easy – George Lawton (SearchCIO)
From picking vendors to upskilling staff, folding an AI infrastructure into enterprise architectures isn’t simple. Experts at the recent ReWork Deep Learning Summit zero in on the issues.
2. Office Depot says ‘no’ to Oracle ERP Cloud customizations – Patrick Thibodeau (SearchERP)
Office Depot believes it’s possible to run its HCM, EPM and supply chain on the Oracle ERP Cloud without customizations. The retailer says it will save money and headaches. Analysts agree.
3. IT monitoring, org discipline polish Nasdaq DevOps incident response – Beth Pariseau (SearchITOperations)
At Nasdaq, IT monitoring unified different teams’ views of infrastructure, but cultural blocking and tackling are equally important to improve incident response.
4. Microsoft rushes Spectre patch to disable Intel’s broken update – Michael Heller (SearchSecurity)
Microsoft was forced to release an out-of-band Spectre patch designed not to mitigate the vulnerability but to protect users from Intel’s broken fix.
5. SAP offers extra help on HR cloud migrations – Patrick Thibodeau (SearchHRSoftware)
SAP is trying to help on-premises HCM users make a case for moving to the cloud, as well as ease initial integration steps. But it may be hard for some European HR users to move.
Robotics image via FreeImages
By James Kobielus (@jameskobielus)
Artificial intelligence (AI) is the perfect laughingstock. Any phenomenon that takes itself as seriously as AI is just asking to be ridiculed.
What’s even funnier is when AI comes in humanoid form, as is the case with the smart robotics that are penetrating every aspect of our lives. As Bill Vorhies discussed in his recent column, robot fails can be comedic gold.
As the brains behind autonomous devices, AI can dampen the laughter only by helping devices master their assigned tasks so well and performing them so inconspicuously that we never give them a second thought. Where robotics are concerned, this involves the trial-and-error statistics-driven approach known as reinforcement learning (RL). Under this approach, the robot explores the full range of available actions—moving, grappling, voicing, etc.–that may or may not contribute to its achieving a desired outcome.
Depending on your point of view, humor is baked into RL’s intrinsically trial-and-error process. As a robot searches for the optimal sequence of actions to achieve its intended outcome, it will of necessity take more counterproductive actions than optimal paths. If you’re the developer who’s doing the training, this might be a long, frustrating, and tedious process. You may need to revise RL procedures and the robot’s algorithmic cognition countless times till you get it to work in a way that can be generalized to future scenarios of the type for which the mechanism is being trained.
This trial-and-error RL process may be humorous to observe in a laboratory setting. But when your AI-driven robot hasn’t been trained effectively and commits these errors in production environments, it may not be funny in the least. This is amply clear from the incidents that Vorhies cites. No one will tolerate robots that routinely smash into people, endanger passengers riding in autonomous vehicles, or order products online without their owners’ authorization.
If we can draw any lesson from these incidents, it’s that robotics developers will need to incorporate the following scenarios into their RL procedures before they release their AI-powered creations to the wider world:
- Geospatial awareness: Real-world operating environments can be very tricky for general-purpose robots to navigate successfully. The right RL could have helped the AI algorithms in this security robot learn the range of locomotion challenges in the indoor and outdoor environments where it was designed to patrol. Equipping the robot with a built-in video camera and thermal imaging wasn’t enough. No amount of trained AI could salvage it after it had rolled over into a public fountain.
- Collision avoidance: Robots can be a hazard as much as a helpmate in many real-world environments. This is obvious with autonomous vehicles, but it’s just as disturbing for retail, office, residential, and other environments in which people might let their guard down. As demonstrated in the cited article, there’s every reason for society to build AI-driven safeguards into everyday robots so that toddlers, the disabled, and the rest of us have no need to fear that they’ll crash into us when we least expect it. Collision avoidance—a prime RL challenge—should be a standard, highly accurate algorithm in every robot. Very likely, laws and regulators will demand this in most jurisdictions before long.
- Authenticated agency: Robots are increasingly becoming the physical manifestations of digital agents in every aspect of our lives. The smart speakers mentioned in the cited article should have been trained to refrain from placing orders for what they mistakenly interpreted as voice-activated purchase requests, but which in fact came from a small child without parental authorization. Though this could have been handled through multifactor authentication rather than through algorithmic training, it’s clear that voice-activated robots in many environmental scenarios may need to step through complex algorithms when deciding what multifactor methods to use for strong authentication and delegated permissioning. Conceivably, RL might be used to help robots more rapidly identify the most appropriate authentication, authorization, and delegation procedures to use in environments where they serve as agents for many people trying to accomplish a diverse, dynamic range of tasks.
- Defensive maneuvering: Robots are objects that must survive both deliberate and accidental assaults that other entities—such as human beings–may inflict on them. The AI algorithms in this driverless shuttle bus should have been trained to take some sort of evasive action—such as veering a few feet in the opposite direction–to avoid the semi that inadvertently backed up into it. Defensive maneuvering will become critical for robots that are deployed into transportation, public safety, and military roles. It’s also an essential capability for robotic devices to fend off the general mischief and vandalism that is certainly going to target them wherever they’re deployed.
- Collaborative orchestration: Robots are increasingly deployed as orchestrated ensembles rather than isolated helpmates. The AI algorithms in warehouse robots in the cited article should have been trained to work harmoniously both with each other and with the many people employed in those environments. Given the huge range of potential interaction scenarios, this is a tough challenge for RL. But it’s an essential capability that society will be demanding from swarming devices of all sorts, including the drones that patrol our skies, deliver our goods, and explore environments that are too dangerous for humans to enter.
- Cultural sensitivity: Robots must respect people in keeping with the norms of civilized society. That includes, as noted in this article, making sure that robots’ face recognition algorithms don’t make discriminatory, demeaning, or otherwise insensitive inferences about the human beings they encounter. This will become even more critical as we deploy robots into highly social setting where they must be trained not to offend people by, for example, using an inaccurate gender-based salutation to refer to a transgender person. These kinds of distinctions can be highly tricky for actual humans to make on the fly, but that only heightens the need for RL to train AI-driven entities to avoid automated faux pas.
Controlled trial-and-error is how most robotics, edge computing, and self-driving vehicle solutions will acquire and evolve their AI smarts. To the extent that you’re capturing an AI-driven device’s RL training on video, it could prove to be the perfect “blooper reel” to show later on when your creation is a smashing success. For regulatory compliance and legal discovery purposes, this video may also help you prove that you’ve RL-trained your device in every relevant scenario, be it actual or simulated.
In the near future, a video audit log of your RL process may become required for passing muster with stakeholders who require certifications that your creations meet all reasonable “AI safety” criteria. Considering the life-or-death scenarios in which the robots of the future will serve us, this is no laughing matter.
Virtual Desktop image via FreeImages
What effects have you seen from patching Meltdown and Spectre? Find out why the patches will hit XenApp especially hard in this week’s roundup.
1. Meltdown and Spectre patches hit XenApp performance especially hard – Alyssa Provazza (SearchVirtualDesktop)
Organizations with VDI and RDSH will likely take a performance hit after patching Meltdown and Spectre, according to test results from Lakeside Software.
2. Pure Storage FlashStack is recycler’s renewable resource – Garry Kranz (SearchStorage)
Food waste recycler Valley Proteins chose Pure Storage’s all-flash converged infrastructure to replace Dell EMC VNX-Cisco UCS for 24 TB of usable storage with Cohesity backup.
3. Salesforce Trailhead gets social boost for admins, developers – Jessica Sirkin (SearchSalesforce)
Salesforce might not own LinkedIn, but it’s creating a similar online social network of certified professionals via Trailhead, complete with vanity URLs and more detailed profiles.
4. Intel Meltdown patches pulled with little explanation – Michael Heller (SearchSecurity)
Intel claims it has determined why the Spectre and Meltdown patches caused issues on some chips. The vendor is working on a fix and suggests users don’t patch for now.
5. Cisco HyperFlex system upgrade targets hybrid cloud – Antone Gonsalves (SearchNetworking)
The Cisco HyperFlex system is now available with AppDynamics, CloudCenter and other software for managing hybrid cloud applications. The new all-in-one system scales to 64 nodes.