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I recently met with Dr. Nick Fuller, Vice President, Distributed Cloud, at IBM Research for a discussion about IBM’s long-range plans and strategy for artificial intelligence and machine learning at the edge.

Dr. Fuller is responsible for providing AI and platform–based innovation for enterprise digital transformation spanning edge computing and distributed cloud management. He is an IBM Master Inventor with over 75 patents and co-author of 75 technical publications. Dr. Fuller obtained his Bachelor of Science in Physics and Math from Morehouse College and his PhD in Applied Physics from Columbia University.

Edge In, not Cloud Out

In general, Dr. Fuller told me that IBM is focused on developing an "edge in" position versus a "cloud out" position with data, AI, and Kubernetes-based platform technologies to scale hub and spoke deployments of edge applications.

A hub plays the role of a central control plane used for orchestrating the deployment and management of edge applications in a number of connected spoke locations such as a factory floor or a retail branch, where data is generated or locally aggregated for processing.

“Cloud out” refers to the paradigm where cloud service providers are extending their cloud architecture out to edge locations. In contrast, “edge in” refers to a provider-agnostic architecture that is cloud-independent and treats the data-plane as a first-class citizen.

IBM's overall architectural principle is scalability, repeatability, and full stack solution management that allows everything to be managed using a single unified control plane.

IBM’s Red Hat platform and infrastructure strategy anchors the application stack with a unified, scalable, and managed OpenShift-based control plane equipped with a high-performance storage appliance and self-healing system capabilities (inclusive of semi-autonomous operations).

IBM’s strategy also includes several in-progress platform-level technologies for scalable data, AI/ML runtimes, accelerator libraries for Day-2 AI operations, and scalability for the enterprise.

It is an important to mention that IBM is designing its edge platforms with labor cost and technical workforce in mind. Data scientists with PhDs are in high demand, making them difficult to find and expensive to hire once you find them. IBM is designing its edge system capabilities and processes so that domain experts rather than PhDs can deploy new AI models and manage Day-2 operations.

Why edge is important

Advances in computing and storage have made it possible for AI to process mountains of accumulated data to provide solutions. By bringing AI closer to the source of data, edge computing is faster and more efficient than cloud. While Cloud data accounts for 60% of the world’s data today, vast amounts of new data is being created at the edge, including industrial applications, traffic cameras, and order management systems, all of which can be processed at the edge in a fast and timely manner.

Public cloud and edge computing differ in capacity, technology, and management. An advantage of edge is that data is processed and analyzed at / near its collection point at the edge. In the case of cloud, data must be transferred from a local device and into the cloud for analytics and then transferred back to the edge again. Moving data through the network consumes capacity and adds latency to the process. It’s easy to see why executing a transaction at the edge reduces latency and eliminates unnecessary load on the network.

Increased privacy is another benefit of processing data at the edge. Analyzing data where it originates limits the risk of a security breach. Most of the communications between the edge and the cloud is then confined to such things as reporting, data summaries, and AI models, without ever exposing the raw data.

IBM at the Edge

In our discussion, Dr. Fuller provided a few examples to illustrate how IBM plans to provide new and seamless edge solutions for existing enterprise problems.

Example #1 – McDonald’s drive-thru

Dr. Fuller’s first example centered around Quick Service Restaurant’s (QSR) problem of drive-thru order taking. Last year, IBM acquired an automated order-taking system from McDonald's. As part of the acquisition, IBM and McDonald's established a partnership to perfect voice ordering methods using AI. Drive-thru orders are a significant percentage of total QSR orders for McDonald's and other QSR chains.

McDonald's and other QSR restaurants would like every order to be processed as quickly and accurately as possible. For that reason, McDonald's conducted trials at ten Chicago restaurants using an edge-based AI ordering system with NLP (Natural Language Processing) to convert spoken orders into a digital format. It was found that AI had the potential to reduce ordering errors and processing time significantly. Since McDonald's sells almost 7 million hamburgers daily, shaving a minute or two off each order represents a significant opportunity to address labor shortages and increase customer satisfaction.

Example #2 – Boston Dynamics and Spot the agile mobile robot

According to an earlier IBM survey, many manufacturers have already implemented AI-driven robotics with autonomous decision-making capability. The study also indicated that over 80 percent of companies believe AI can help Strengthen future business operations. However, some companies expressed concern about the limited mobility of edge devices and sensors.

To develop a mobile edge solution, IBM teamed up with Boston Dynamics. The partnership created an agile mobile robot using IBM Research and IBM Sustainability Software AI technology. The device can analyze visual sensor readings in hazardous and challenging industrial environments such as manufacturing plants, warehouses, electrical grids, waste treatment plants and other hazardous environments. The value proposition that Boston Dynamics brought to the partnership was Spot the agile mobile robot, a walking, sensing, and actuation platform. Like all edge applications, the robot’s wireless mobility uses self-contained AI/ML that doesn’t require access to cloud data. It uses cameras to read analog devices, visually monitor fire extinguishers, and conduct a visual inspection of human workers to determine if required safety equipment is being worn.

IBM was able to show up to a 10X speedup by automating some manual tasks, such as converting the detection of a problem into an immediate work order in IBM Maximo to correct it. A fast automated response was not only more efficient, but it also improved the safety posture and risk management for these facilities. Similarly, some factories need to thermally monitor equipment to identify any unexpected hot spots that may show up over time, indicative of a potential failure.

IBM is working with National Grid, an energy company, to develop a mobile solution using Spot, the agile mobile robot, for image analysis of transformers and thermal connectors. As shown in the above graphic, Spot also monitored connectors on both flat surfaces and 3D surfaces. IBM was able to show that Spot could detect excessive heat build-up in small connectors, potentially avoiding unsafe conditions or costly outages. This AI/ML edge application can produce faster response times when an issue is detected, which is why IBM believes significant gains are possible by automating the entire process.

IBM market opportunities

Drive-thru orders and mobile robots are just a few examples of the millions of potential AI applications that exist at the edge and are driven by several billion connected devices.

Edge computing is an essential part of enterprise digital transformation. Enterprises seek ways to demonstrate the feasibility of solving business problems using AI/ML and analytics at the edge. However, once a proof of concept has been successfully demonstrated, it is a common problem for a company to struggle with scalability, data governance, and full-stack solution management.

Challenges with scaling

“Determining entry points for AI at the edge is not the difficult part,” Dr. Fuller said. “Scale is the real issue.”

Scaling edge models is complicated because there are so many edge locations with large amounts of diverse content and a high device density. Because large amounts of data are required for training, data gravity is a potential problem. Further, in many scenarios, vast amounts of data are generated quickly, leading to potential data storage and orchestration challenges. AI Models are also rarely "finished." Monitoring and retraining of models are necessary to keep up with changes the environment.

Through IBM Research, IBM is addressing the many challenges of building an all-encompassing edge architecture and horizontally scalable data and AI technologies. IBM has a wealth of edge capabilities and an architecture to create the appropriate platform for each application.

IBM AI entry points at the edge

IBM sees Edge Computing as a $200 billion market by 2025. Dr. Fuller and his organization have identified four key market entry points for developing and expanding IBM’s edge compute strategy. In order of size, IBM believes its priority edge markets to be intelligent factories (Industry 4.0), telcos, retail automation, and connected vehicles.

IBM and its Red Hat portfolio already have an established presence in each market segment, particularly in intelligent operations and telco. Red Hat is also active in the connected vehicles space.

Industry 4.0

There have been three prior industrial revolutions, beginning in the 1700s up to our current in-progress fourth revolution, Industry 4.0, that promotes a digital transformation.

Manufacturing is the fastest growing and the largest of IBM’s four entry markets. In this segment, AI at the edge can Strengthen quality control, production optimization, asset management, and supply chain logistics. IBM believes there are opportunities to achieve a 4x speed up in implementing edge-based AI solutions for manufacturing operations.

For its Industry 4.0 use case development, IBM, through product, development, research and consulting teams, is working with a major automotive OEM. The partnership has established the following joint objectives:

  • Increase automation and scalability across dozens of plants using 100s of AI / ML models. This client has already seen value in applying AI/ML models for manufacturing applications. IBM Research is helping with re-training models and implementing new ones in an edge environment to help scale even more efficiently. Edge offers faster inference and low latency, allowing AI to be deployed in a wider variety of manufacturing operations requiring instant solutions.
  • Dramatically reduce the time required to onboard new models. This will allow training and inference to be done faster and allow large models to be deployed much more quickly. The quicker an AI model can be deployed in production; the quicker the time-to-value and the return-on-investment (ROI).
  • Accelerate deployment of new inspections by reducing the labeling effort and iterations needed to produce a production-ready model via data summarization. Selecting small data sets for annotation means manually examining thousands of images, this is a time-consuming process that will result in - labeling of redundant data. Using ML-based automation for data summarization will accelerate the process and produce better model performance.
  • Enable Day-2 AI operations to help with data lifecycle automation and governance, model creation, reduce production errors, and provide detection of out-of-distribution data to help determine if a model’s inference is accurate. IBM believes this will allow models to be created faster without data scientists.

Maximo Application Suite

IBM’s Maximo Application Suite plays an important part in implementing large manufacturers' current and future IBM edge solutions. Maximo is an integrated public or private cloud platform that uses AI, IoT, and analytics to optimize performance, extend asset lifecycles and reduce operational downtime and costs. IBM is working with several large manufacturing clients currently using Maximo to develop edge use cases, and even uses it within its own Manufacturing.

IBM has research underway to develop a more efficient method of handling life cycle management of large models that require immense amounts of data. Day 2 AI operations tasks can sometimes be more complex than initial model training, deployment, and scaling. Retraining at the edge is difficult because resources are typically limited.

Once a model is trained and deployed, it is important to monitor it for drift caused by changes in data distributions or anything that might cause a model to deviate from original requirements. Inaccuracies can adversely affect model ROI.

Day-2 AI Operations (retraining and scaling)

Day-2 AI operations consist of continual updates to AI models and applications to keep up with changes in data distributions, changes in the environment, a drop in model performance, availability of new data, and/or new regulations.

IBM recognizes the advantages of performing Day-2 AI Operations, which includes scaling and retraining at the edge. It appears that IBM is the only company with an architecture equipped to effectively handle Day-2 AI operations. That is a significant competitive advantage for IBM.

A company using an architecture that requires data to be moved from the edge back into the cloud for Day-2 related work will be unable to support many factory AI/ML applications because of the sheer number of AI/ML models to support (100s to 1000s).

“There is a huge proliferation of data at the edge that exists in multiple spokes,” Dr. Fuller said. "However, all that data isn’t needed to retrain a model. It is possible to cluster data into groups and then use sampling techniques to retrain the model. There is much value in federated learning from our point of view.”

Federated learning is a promising training solution being researched by IBM and others. It preserves privacy by using a collaboration of edge devices to train models without sharing the data with other entities. It is a good framework to use when resources are limited.

Dealing with limited resources at the edge is a challenge. IBM’s edge architecture accommodates the need to ensure resource budgets for AI applications are met, especially when deploying multiple applications and multiple models across edge locations. For that reason, IBM developed a method to deploy data and AI applications to scale Day-2 AI operations utilizing hub and spokes.

The graphic above shows the current status quo methods of performing Day-2 operations using centralized applications and a centralized data plane compared to the more efficient managed hub and spoke method with distributed applications and a distributed data plane. The hub allows it all to be managed from a single pane of glass.

Data Fabric Extensions to Hub and Spokes

IBM uses hub and spoke as a model to extend its data fabric. The model should not be thought of in the context of a traditional hub and spoke. IBM’s hub provides centralized capabilities to manage clusters and create multiples hubs that can be aggregated to a higher level. This architecture has four important data management capabilities.

  1. First, models running in unattended environments must be monitored. From an operational standpoint, detecting when a model’s effectiveness has significantly degraded and if corrective action is needed is critical.
  2. Secondly, in a hub and spoke model, data is being generated and collected in many locations creating a need for data life cycle management. Working with large enterprise clients, IBM is building unique capabilities to manage the data plane across the hub and spoke estate - optimized to meet data lifecycle, regulatory & compliance as well as local resource requirements. Automation determines which input data should be selected and labeled for retraining purposes and used to further Strengthen the model. Identification is also made for atypical data that is judged worthy of human attention.
  3. The third issue relates to AI pipeline compression and adaptation. As mentioned earlier, edge resources are limited and highly heterogeneous. While a cloud-based model might have a few hundred million parameters or more, edge models can’t afford such resource extravagance because of resource limitations. To reduce the edge compute footprint, model compression can reduce the number of parameters. As an example, it could be reduced from several hundred million to a few million.
  4. Lastly, suppose a scenario exists where data is produced at multiple spokes but cannot leave those spokes for compliance reasons. In that case, IBM Federated Learning allows learning across heterogeneous data in multiple spokes. Users can discover, curate, categorize and share data assets, data sets, analytical models, and their relationships with other organization members.

In addition to AI deployments, the hub and spoke architecture and the previously mentioned capabilities can be employed more generally to tackle challenges faced by many enterprises in consistently managing an abundance of devices within and across their enterprise locations. Management of the software delivery lifecycle or addressing security vulnerabilities across a vast estate are a case in point.

Multicloud and Edge platform

In the context of its strategy, IBM sees edge and distributed cloud as an extension of its hybrid cloud platform built around Red Hat OpenShift. One of the newer and more useful options created by the Red Hat development team is the Single Node OpenShift (SNO), a compact version of OpenShift that fits on a single server. It is suitable for addressing locations that are still servers but come in a single node, not clustered, deployment type.

For smaller footprints such as industrial PCs or computer vision boards (for example NVidia Jetson Xavier), Red Hat is working on a project which builds an even smaller version of OpenShift, called MicroShift, that provides full application deployment and Kubernetes management capabilities. It is packaged so that it can be used for edge device type deployments.

Overall, IBM and Red Hat have developed a full complement of options to address a large spectrum of deployments across different edge locations and footprints, ranging from containers to management of full-blown Kubernetes applications from MicroShift to OpenShift and IBM Edge Application Manager.

Much is still in the research stage. IBM's objective is to achieve greater consistency in terms of how locations and application lifecycle is managed.

First, Red Hat plans to introduce hierarchical layers of management with Red Hat Advanced Cluster Management (RHACM), to scale by two to three orders of magnitude the number of edge locations managed by this product. Additionally, securing edge locations is a major focus. Red Hat is continuously expanding platform security features, for example by recently including Integrity Measurement Architecture in Red Hat Enterprise Linux, or by adding Integrity Shield to protect policies in Red Hat Advanced Cluster Management (RHACM).

Red Hat is partnering with IBM Research to advance technologies that will permit it to protect platform integrity and the integrity of client workloads through the entire software supply chains. In addition, IBM Research is working with Red Hat on analytic capabilities to identify and remediate vulnerabilities and other security risks in code and configurations.

Telco network intelligence and slice management with AL/ML

Communication service providers (CSPs) such as telcos are key enablers of 5G at the edge. 5G benefits for these providers include:

  • Reduced operating costs
  • Improved efficiency
  • Increased distribution and density
  • Lower latency

The end-to-end 5G network comprises the Radio Access Network (RAN), transport, and core domains. Network slicing in 5G is an architecture that enables multiple virtual and independent end-to-end logical networks with different characteristics such as low latency or high bandwidth, to be supported on the same physical network. This is implemented using cloud-native technology enablers such as software defined networking (SDN), virtualization, and multi-access edge computing. Slicing offers necessary flexibility by allowing the creation of specific applications, unique services, and defined user groups or networks.

An important aspect of enabling AI at the edge requires IBM to provide CSPs with the capability to deploy and manage applications across various enterprise locations, possibly spanning multiple end-to-end network slices, using a single pane of glass.

5G network slicing and slice management

Network slices are an essential part of IBM's edge infrastructure that must be automated, orchestrated and optimized according to 5G standards. IBM’s strategy is to leverage AI/ML to efficiently manage, scale, and optimize the slice quality of service, measured in terms of bandwidth, latency, or other metrics.

5G and AI/ML at the edge also represent a significant opportunity for CSPs to move beyond traditional cellular services and capture new sources of revenue with new services.

Communications service providers need management and control of 5G network slicing enabled with AI-powered automation.

Dr. Fuller sees a variety of opportunities in this area. "When it comes to applying AI and ML on the network, you can detect things like intrusion detection and malicious actors," he said. "You can also determine the best way to route traffic to an end user. Automating 5G functions that run on the network using IBM network automation software also serves as an entry point.”

In IBM’s current telecom trial, IBM Research is spearheading the development of a range of capabilities targeted for the IBM Cloud Pak for Network Automation product using AI and automation to orchestrate, operate and optimize multivendor network functions and services that include:

  • End-to-end 5G network slice management with planning & design, automation & orchestration, and operations & assurance
  • Network Data and AI Function (NWDAF) that collects data for slice monitoring from 5G Core network functions, performs network analytics, and provides insights to authorized data consumers.
  • Improved operational efficiency and reduced cost

Future leverage of these capabilities by existing IBM Clients that use the Cloud Pak for Network Automation (e.g., DISH) can offer further differentiation for CSPs.

5G radio access

Open radio access networks (O-RANs) are expected to significantly impact telco 5G wireless edge applications by allowing a greater variety of units to access the system. The O-RAN concept separates the DU (Distributed Units) and CU (Centralized Unit) from a Baseband Unit in 4G and connects them with open interfaces.

O-RAN system is more flexible. It uses AI to establish connections made via open interfaces that optimize the category of a device by analyzing information about its prior use. Like other edge models, the O-RAN architecture provides an opportunity for continuous monitoring, verification, analysis, and optimization of AI models.

The IBM-telco collaboration is expected to advance O-RAN interfaces and workflows. Areas currently under development are:

  • Multi-modal (RF level + network-level) analytics (AI/ML) for wireless communication with high-speed ingest of 5G data
  • Capability to learn patterns of metric and log data across CUs and DUs in RF analytics
  • Utilization of the antenna control plane to optimize throughput
  • Primitives for forecasting, anomaly detection and root cause analysis using ML
  • Opportunity of value-added functions for O-RAN

IBM Cloud and Infrastructure

The cornerstone for the delivery of IBM's edge solutions as a service is IBM Cloud Satellite. It presents a consistent cloud-ready, cloud-native operational view with OpenShift and IBM Cloud PaaS services at the edge. In addition, IBM integrated hardware and software Edge systems will provide RHACM - based management of the platform when clients or third parties have existing managed as a service models. It is essential to note that in either case this is done within a single control plane for hubs and spokes that helps optimize execution and management from any cloud to the edge in the hub and spoke model.

IBM's focus on “edge in” means it can provide the infrastructure through things like the example shown above for software defined storage for federated namespace data lake that surrounds other hyperscaler clouds. Additionally, IBM is exploring integrated full stack edge storage appliances based on hyperconverged infrastructure (HCI), such as the Spectrum Fusion HCI, for enterprise edge deployments.

As mentioned earlier, data gravity is one of the main driving factors of edge deployments. IBM has designed its infrastructure to meet those data gravity requirements, not just for the existing hub and spoke topology but also for a future spoke-to-spoke topology where peer-to-peer data sharing becomes imperative (as illustrated with the wealth of examples provided in this article).

Wrap up

Edge is a distributed computing model. One of its main advantages is that computing, and data storage and processing is close to where data is created. Without the need to move data to the cloud for processing, real-time application of analytics and AI capabilities provides immediate solutions and drives business value.

IBM’s goal is not to move the entirety of its cloud infrastructure to the edge. That has little value and would simply function as a hub to spoke model operating on actions and configurations dictated by the hub.

IBM’s architecture will provide the edge with autonomy to determine where data should reside and from where the control plane should be exercised.

Equally important, IBM foresees this architecture evolving into a decentralized model capable of edge-to-edge interactions. IBM has no firm designs for this as yet. However, the plan is to make the edge infrastructure and platform a first-class citizen instead of relying on the cloud to drive what happens at the edge.

Developing a complete and comprehensive AI/ML edge architecture - and in fact, an entire ecosystem - is a massive undertaking. IBM faces many known and unknown challenges that must be solved before it can achieve success.

However, IBM is one of the few companies with the necessary partners and the technical and financial resources to undertake and successfully implement a project of this magnitude and complexity.

It is reassuring that IBM has a plan and that its plan is sound.

Paul Smith-Goodson is Vice President and Principal Analyst for quantum computing, artificial intelligence and space at Moor Insights and Strategy. You can follow him on Twitter for more current information on quantum, AI, and space.

Note: Moor Insights & Strategy writers and editors may have contributed to this article.

Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movandi.

Mon, 08 Aug 2022 03:51:00 -0500 Paul Smith-Goodson en text/html https://www.forbes.com/sites/moorinsights/2022/08/08/ibm-research-rolls-out-a-comprehensive-ai-and-ml-edge-research-strategy-anchored-by-enterprise-partnerships-and-use-cases/
Killexams : How IBM Could Become A Digital Winner

Last week, after IBM’s report of positive quarterly earnings, CEO Arvind Krishna and CNBC’s Jim Cramer shared their frustration that IBM’s stock “got clobbered.” IBM’s stock price immediately fell by10%, while the S&P500 remained steady (Figure 1)

While a five-day stock price fluctuation is by itself meaningless, questions remain about the IBM’s longer-term picture. “These are great numbers,” declared Krishna.

“You gave solid revenue growth and solid earnings,” Cramer sympathized. “You far exceeded expectations. Maybe someone is changing the goal posts here?”

The Goal Posts To Become A Digital Winner

It is also possible that Krishna and Cramer missed where today’s goal posts are located. Strong quarterly numbers do not a digital winner make. They may induce the stock market to regard a firm as a valuable cash cow, like other remnants of the industrial era. But to become a digital winner, a firm must take the kind of steps that Satya Nadella took at Microsoft to become a digital winner: kill its dogs, commit to a mission of customer primacy, identify real growth opportunities, transform its culture, make empathy central, and unleash its agilists. (Figure 2)

Since becoming CEO, Nadella has been brilliantly successful at Microsoft, growing market capitalization by more than a trillion dollars.

Krishna’s Two Years As CEO

Krishna has been IBM CEO since April 2020. He began his career at IBM in 1990, and had been managing IBM’s cloud and research divisions since 2015. He was a principal architect of the Red Hat acquisition.

They are remarkable parallels between the careers of Krishna and Nadella.

· Both are Indian-American engineers, who were born in India.

· Both worked at the firm for several decades before they became CEOs.

· Prior to becoming CEOs, both were in charge of cloud computing.

Both inherited companies in trouble. Microsoft was stagnating after CEO Steve Ballmer, while IBM was also in rapid decline, after CEO Ginny Rometty: the once famous “Big Blue” had become known as a “Big Bruise.”

Although it is still early days in Krishna’s CEO tenure, IBM is under-performing the S&P500 since he took over (Figure 3).

More worrying is the fact that Krishna has not yet completed the steps that Nadella took in his first 27 months. (Figure 1).

1. Jettison Losing Baggage

Nadella wrote off the Nokia phone and declared that IBM would no longer sell its flagship Windows as a business. This freed up energy and resources to focus on creating winning businesses.

By contrast, Krishna has yet to jettison, IBM’s most distracting baggage:

· Commitment to maximizing shareholder value (MSV): For the two prior decades, IBM was the public champion of MSV, first under CEO Palmisano 2001-2011, and again under Rometty 2012-2020—a key reason behind IBM’s calamitous decline (Figure 2) Krishna has yet to explicitly renounce IBM’s MSV heritage.

· Top-down bureaucracy: The necessary accompaniment of MSV is top-down bureaucracy, which flourished under CEOs Palmisano and Rometty. Here too, bureaucratic processes must be explicitly eradicated, otherwise they become permanent weeds.

· The ‘Watson problem’: IBM’s famous computer, Watson, may have won ‘Jeopardy!’ but it continues to have problems in the business marketplace. In January 2022, IBM reported that it had sold Watson Health assets to an investment firm for around $1 billion, after acquisitions that had cost some $4 billion. Efforts to monetize Watson continue.

· Infrastructure Services: By spinning off its Cloud computing business as a publicly listed company (Kyndryl), IBM created nominal separation, but Kyndryl immediately lost 57% of its share value.

· Quantum Computing: IBM pours resources into research on quantum computing and touts its potential to revolutionize computing. However unsolved technical problems of “decoherence” and “entanglement” mean that any meaningful benefits are still some years away.

· Self-importance: Perhaps the heaviest baggage that IBM has yet to jettison is the over-confidence reflected in sales slogans like “no one ever got fired for hiring IBM”. The subtext is that firms “can leave IT to IBM” and that the safe choice for any CIO is to stick with IBM. It’s a status quo mindset—the opposite of the clients that IBM needs to attract.

2. Commit To A Clear Customer-Obsessed Mission

At the outset of his tenure as CEO of Microsoft, Nadella spent the first nine months getting consensus on a simple customer-driven mission statement.

Krishna did write at the end of the letter to staff on day one as CEO, and he added at the end:“Third, we all must be obsessed with continually delighting our clients. At every interaction, we must strive to offer them the best experience and value. The only way to lead in today’s ever-changing marketplace is to constantly innovate according to what our clients want and need.” This would have been more persuasive if it had come at the beginning of the letter, and if there had been stronger follow-up.

What is IBM’s mission? No clear answer appears from IBM’s own website. The best one gets from About IBM is the fuzzy do-gooder declaration: “IBMers believe in progress — that the application of intelligence, reason and science can Strengthen business, society and the human condition.” Customer primacy is not explicit, thereby running the risk that IBM’s 280,000 employees will assume that the noxious MSV goal is still in play.

3. Focus On Major Growth Opportunities

At Microsoft, Nadella dismissed competing with Apple on phones or with Google on Search. He defined the two main areas of opportunity—mobility and the cloud.

Krishna has identified the Hybrid Cloud and AI as IBM’s main opportunities. Thus, Krishna wrote in his newsletter to staff on day one as CEO: “Hybrid cloud and AI are two dominant forces driving change for our clients and must have the maniacal focus of the entire company.”

However, both fields are now very crowded. IBM is now a tiny player in Cloud in comparison to Amazon, Microsoft, and Google. In conversations, Krishna portrays IBM as forging working partnerships with the big Cloud players, and “integrating their offerings in IBM’s hybrid Cloud.” One risk here is whether the big Cloud players will facilitate this. The other risk is that IBM will attract only lower-performing firms that use IBM as a crutch so that they can cling to familiar legacy programs.

4. Address Culture And The Importance Of Empathy Upfront

At Microsoft, Nadella addressed culture upfront, rejecting Microsoft’s notoriously confrontational culture, and set about instilling a collaborative customer-driven culture throughout the firm.

Although Krishna talks openly to the press, he has not, to my knowledge, frontally addressed the “top-down” “we know best” culture that prevailed in IBM under his predecessor CEOs. He has, to his credit, pledged “neutrality” with respect to the innovative, customer-centric Red Hat, rather than applying the “Blue washing” that the old IBM systematically applied to its acquisitions to bring them into line with IBM’s top-down culture, and is said to have honored its pledge—so far. But there is little indication that IBM is ready to adopt Red Hat’s innovative culture for itself. It is hard to see these two opposed cultures remain “neutral” forever. Given the size differential between IBM and Red Hat, the likely winner is easy to predict, unless Krishna makes a more determined effort to transform IBM’s culture.

5. Empower The Hidden Agilists

As in any large tech firm, when Nadella and Krishna took over their respective firms, there were large hidden armies of agilists waiting in the shadows but hamstrung by top-down bureaucracies. At Microsoft, Nadella’s commitment to “agile, agile, agile” combined with a growth mindset, enabled a fast start.. At IBM, if Krishna has any passion for Agile, it has not yet shared it widely.

Bottom Line

Although IBM has made progress under Krishna, it is not yet on a path to become a clear digital winner.

And read also:

Is Your Firm A Cash-Cow Or A Growth-Stock?

Why Companies Must Learn To Discuss The Undiscussable

Sun, 24 Jul 2022 23:19:00 -0500 Steve Denning en text/html https://www.forbes.com/sites/stevedenning/2022/07/25/how-ibm-could-become-a-digital-winner/
Killexams : IBM is ‘continuing to hire,’ senior exec says despite economic turbulence

RESEARCH TRIANGLE PARK – IBM and its Raleigh-based Red Hat group continue to hire even as layoffs or hiring freezes are becoming more commonplace across the tech sector, a senior Big Blue exec says.

“We’re always selective with our hiring and we’re constantly scanning the marketplace,” says Obed Louissaint, senior vice president of transformation and culture at IBM, in an interview with Human Resources Director. “We’re continuing to hire, and we’ll continue to monitor and pivot if circumstances require it. We’re continuing to build out and invest in critical skills our clients are needing. In our industry, areas around cloud, AI [artificial intelligence] and security continue to be in high demand.”

IBM and Red Hat both have job openings in the Triangle, as reported in WRAL TechWire’s weekly Jobs Report.

So too does Kyndryl, which was spun off from Big Blue but has a big operation built around former IBM operations in the Triangle.

But the latest numbers at Red Hat and IBM have fallen:

  • IBM: 3 job openings in RTP, according to the company’s career page, which is down from 24 openings two weeks ago.
  • Red Hat: 9 job openings in Raleigh, according to the company’s career page, down from 31 openings last week
  • Kyndryl: 120 job openings in RTP, according to the company’s career page

Read the full HRD interview at this site.

Job seekers: These 20 tech, life science firms are still recruiting across the Triangle

Triangle’s once hot employment market is cooling at some major jobs boards

Thu, 04 Aug 2022 23:49:00 -0500 en-US text/html https://wraltechwire.com/2022/08/05/ibm-is-continuing-to-hire-senior-exec-says-despite-economic-turbulence/
Killexams : IBM 'continuing to hire' ahead of recession

Read more: Safeguard Global CTO: Tech talent remains highly sought after

But IBM has always carved its own path. For example, the Armonk, NY-based company doesn’t use the term “Great Resignation,” at least internally. Of course, that doesn’t mean the tech giant isn’t aware of the nationwide talent shortage and the highly competitive labor market that’s resulted.

“This is a time to ensure we re-engage our population,” Louissaint says. “By nature of my title, my goal is to continue to transform and pivot our company toward being more growth-minded, transforming it directly through leadership: leadership development, getting people in the right jobs and ensuring we have the right succession plans.”

Like many companies since the COVID-19 pandemic, IBM has relied upon its business resource groups – its label for employee resource groups (ERGs) – to maintain and even boost retention. Traditionally, ERGs consist of employees who volunteer their time and effort to foster an inclusive workplace. Due to their motivations, needs and the general nature of ERG work, employees who lead these groups are more likely to be Black, Indigenous and People of Color (BIPOC) and oftentimes women. ERGs are a way for underrepresented groups to band together to recruit more talent like them into their companies and make sure that talent feels supported and gets promoted.

“It’s a lot easier to leave a company where you’ve only interacted with colleagues through a screen,” Louissaint says. “Our diversity groups and communities have gotten a lot stronger, which builds commitment to the company and community to each other. We’ve found that through our communities, business resource groups, open conversations and by democratizing leadership by using virtual technologies like Slack, the company has become smaller and the interactions are a lot more personal.”

A major contributor to the Great Resignation has been the push for workers to return to the office. While Apple and Google have ruffled feathers with requesting employees back for at least a couple days a week, Tesla went one step further by demanding employees head to the office five days a week, as if the COVID-19 pandemic never happened.

Ahead of the game, IBM was one of the first major tech firms to embrace remote work, with as much as 40% of its workforce at home during the 2000s. A shift came in 2017, but since the pandemic, only 20% of the company’s U.S. employees are in the office for three days a week or more, according to IBM CEO Arvind Krishna. In June, Krishna added that he doesn’t think the balance will ever get back to more than 60% of workers in the office.

“We’ve always been defined by flexibility, even prior to the pandemic that’s what we were known for and what differentiated us,” Louissaint says. “Continuing to double down on flexibility has been a value to us and to our people.”

IBM has also been defined by its eye toward the future, particularly when it comes to workforce development. Over the past decade, the tech giant has partnered with educational institutions, non-governmental organizations and other companies to discover and nurture talent from untapped pools and alternative channels. Last year, the company vowed to train 30 million individuals on technical skills by 2030.

“Our people crave learning and are highly curious,” Louissaint says, adding that the average IBM employee consumes about 88 hours of learning through its platform each year. Nearly all (95%) employees are on the platform in any given quarter.

“We’ve been building a strong learning environment where employees can build new skills and drive toward new jobs and experiences,” he says. “We also find that the individuals who consume the most learning are more likely to get promoted. It’s 30% more likely for a super learner to be promoted or switch jobs, so the incentive is continued growth and opportunity for advancement.”

Wed, 03 Aug 2022 16:00:00 -0500 en text/html https://www.hcamag.com/us/specialization/learning-development/ibm-continuing-to-hire-ahead-of-recession/415538
Killexams : The right and wrong way to use artificial intelligence

For decades, scientists have been giddy and citizens have been fearful of the power of computers. In 1965 Herbert Simon, a Nobel laureate in economics and also a winner of the Turing Award (considered “The Nobel Prize of computing”), predicted that “machines will be capable, within 20 years, of doing any work a man can do.” His misplaced faith in computers is hardly unique. Sixty-seven years later, we are still waiting for computers to become our slaves and masters.

Businesses have spent hundreds of billions of dollars on AI moonshots that have crashed and burned. IBM’s “Dr. Watson” was supposed to revolutionize health care and “eradicate cancer.” Eight years later, after burning through $15 billion with no demonstrable successes, IBM fired Dr. Watson.

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In 2016 Turing Award Winner Geoffrey Hinton advised that “We should stop training radiologists now. It’s just completely obvious that within five years, deep learning is going to do better than radiologists.” Six years later, the number of radiologists has gone up, not down. Researchers have spent billions of dollars working on thousands of radiology image-recognition algorithms that are not as good as human radiologists.

What about those self-driving vehicles, promised by many including Elon Musk in his 2016 boast that “I really consider autonomous driving a solved problem. I think we are probably less than two years away.” Six years later, the most advanced self-driving vehicles are arguably Waymos in San Francisco, which only operate between 10 p.m. and 6 a.m. on the least crowded roads and still have accidents and cause traffic tie-ups. They are a long way from successfully operating in downtown traffic during the middle of the day at a required 99.9999% level of proficiency.

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The list goes on. Zillow’s house-flipping misadventure lost billions of dollars trying to revolutionize home-buying before they shuttered it. Carvana’s car-flipping gambit still loses billions.

We have argued for years that we should be developing AI that makes people more productive instead of trying to replace people. Computers have wondrous memories, make calculations that are lightning-fast and error-free, and are tireless, but humans have the real-world experience, common sense, wisdom and critical thinking skills that computers lack. Together, they can do more than either could do on their own.

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Effective augmentation appears to be finally happening with medical images. A large-scale study just published in Lancet Digital Health is the first to directly compare AI cancer screening when used alone or to assist humans. The software comes from a German startup, Vara, whose AI is already used in more than 25% of Germany’s breast cancer screening centers.

Researchers from Vara, Essen University and the Memorial Sloan Kettering Cancer Center trained the algorithm on more than 367,000 mammograms, and then tested it on 82,851 mammograms that had been held back for that purpose.

In the first strategy, the algorithm was used alone to analyze the 82,851 mammograms. In the second strategy, the algorithm separated the mammograms into three groups: clearly cancer, clearly no cancer, and uncertain. The uncertain mammograms were then sent to board-certified radiologists who were given no information about the AI diagnosis.

Doctors and AI working together turned out to be better than either working alone. The AI pre-screening reduced the number of images the doctors examined by 37% while lowering the false-positive and false-negative rates by about a third compared to AI alone and by 14%-20% compared to doctors alone. Less work and better results!

As machine learning improves, the AI analysis of X-rays will no doubt become more efficient and accurate. There will come a time when AI can be trusted to work alone. However, that time is likely to be decades in the future and attempts to jump directly to that point are dangerous.

We are optimistic that the productivity of many workers can be improved by similar augmentation strategies — not to mention the fact that many of the tasks that computers excel at are dreadful drudgery; e.g., legal research, inventory control and statistical calculations. But far too many attempts to replace humans entirely have not only been an enormous waste of resources but have also undermined the credibility of AI research. The last thing we need is another AI winter where funding dries up, resources are diverted and the tremendous potential of these technologies are put on hold. We are optimistic that the accumulating failures of moonshots and successes of augmentation strategies will change the way that we think about AI.

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Funk is an independent technology consultant who previously taught at National University of Singapore, Hitotsubashi and Kobe Universities in Japan, and Penn State, where he taught courses on the economics of new technologies. Smith is the author of ”The AI Delusion” and co-author (with Jay Cordes) of ”The 9 Pitfalls of Data Science” and ”The Phantom Pattern Problem.”

Fri, 05 Aug 2022 21:00:00 -0500 en-US text/html https://www.nydailynews.com/opinion/ny-oped-the-right-and-wrong-way-to-use-artificial-intelligence-20220806-txybtmlcwfgddnfdozvynz5u64-story.html
Killexams : Colorado’s P-TECH Students Graduate Ready for Tech Careers (TNS) — Abraham Tinajero was an eighth grader when he saw a poster in his Longmont middle school’s library advertising a new program offering free college with a technology focus.

Interested, he talked to a counselor to learn more about P-TECH, an early college program where he could earn an associate’s degree along with his high school diploma. Liking the sound of the program, he enrolled in the inaugural P-TECH class as a freshman at Longmont’s Skyline High School.

“I really loved working on computers, even before P-TECH,” he said. “I was a hobbyist. P-TECH gave me a pathway.”


He worked with an IBM mentor and interned at the company for six weeks as a junior. After graduating in 2020 with his high school diploma and the promised associate’s degree in computer science from Front Range Community College, he was accepted to IBM’s yearlong, paid apprenticeship program.

IBM hired him as a cybersecurity analyst once he completed the apprenticeship.

“P-TECH has given me a great advantage,” he said. “Without it, I would have been questioning whether to go into college. Having a college degree at 18 is great to put on a resume.”


Stanley Litow, a former vice president of IBM, developed the P-TECH, or Pathways in Technology Early College High Schools, model. The first P-TECH school opened 11 years ago in Brooklyn, New York, in partnership with IBM.

Litow’s idea was to get more underrepresented young people into tech careers by giving them a direct path to college while in high school — and in turn create a pipeline of employees with the job skills businesses were starting to value over four-year college degrees.

The program, which includes mentors and internships provided by business partners, gives high school students up to six years to earn an associate's degree at no cost.

SKYLINE HIGH A PIONEER IN PROGRAM

In Colorado, St. Vrain Valley was among the first school districts chosen by the state to offer a P-TECH program after the Legislature passed a bill to provide funding — and the school district has embraced the program.

Colorado’s first P-TECH programs started in the fall of 2016 at three high schools, including Skyline High. Over the last six years, 17 more Colorado high schools have adopted P-TECH, for at total of 20. Three of those are in St. Vrain Valley, with a fourth planned to open in the fall of 2023 at Longmont High School.

Each St. Vrain Valley high school offers a different focus supported by different industry partners.

Skyline partners with IBM, with students earning an associate’s degree in Computer Information Systems from Front Range. Along with being the first, Skyline’s program is the largest, enrolling up to 55 new freshmen each year.

Programs at the other schools are capped at 35 students per grade.

Frederick High’s program, which started in the fall of 2019, has a bioscience focus, partners with Aims Community College and works with industry partners Agilent Technologies, Tolmar, KBI Biopharma, AGC Biologics and Corden Pharma.

Silver Creek High’s program started a year ago with a cybersecurity focus. The Longmont school partners with Front Range and works with industry partners Seagate, Cisco, PEAK Resources and Comcast.

The new program coming to Longmont High will focus on business.

District leaders point to Skyline High’s graduation statistics to illustrate the program’s success. At Skyline, 100 percent of students in the first three P-TECH graduating classes earned a high school diploma in four years.

For the 2020 Skyline P-TECH graduates, 24 of the 33, or about 70 percent, also earned associate’s degrees. For the 2021 graduating class, 30 of the 47 have associate’s degrees — with one year left for those students to complete the college requirements.

For the most latest 2022 graduates, who have two years left to complete the college requirements, 19 of 59 have associate’s degrees and another six are on track to earn their degrees by the end of the summer.

JUMPING AT AN OPPORTUNITY

Louise March, Skyline High’s P-TECH counselor, keeps in touch with the graduates, saying 27 are working part time or full time at IBM. About a third are continuing their education at a four year college. Of the 19 who graduated in 2022 with an associate’s degree, 17 are enrolling at a four year college, she said.

Two of those 2022 graduates are Anahi Sarmiento, who is headed to the University of Colorado Boulder’s Leeds School of Business, and Jose Ivarra, who will study computer science at Colorado State University.

“I’m the oldest out of three siblings,” Ivarra said. “When you hear that someone wants to give you free college in high school, you take it. I jumped at the opportunity.”

Sarmiento added that her parents, who are immigrants, are already working two jobs and don’t have extra money for college costs.

“P-TECH is pushing me forward,” she said. “I know my parents want me to have a better life, but I want them to have a better life, too. Going into high school, I kept that mentality that I would push myself to my full potential. It kept me motivated.”

While the program requires hard work, the two graduates said, they still enjoyed high school and had outside interests. Ivarra was a varsity football player who was named player of the year. Sarmiento took advantage of multiple opportunities, from helping elementary students learn robotics to working at the district’s Innovation Center.

Ivarra said he likes that P-TECH has the same high expectations for all students, no matter their backgrounds, and gives them support in any areas where they need help. Spanish is his first language and, while math came naturally, language arts was more challenging.

“It was tough for me to see all these classmates use all these big words, and I didn’t know them,” he said. “I just felt less. When I went into P-TECH, the teachers focus on you so much, checking on every single student.”

They said it’s OK to struggle or even fail. Ivarra said he failed a tough class during the pandemic, but was able to retake it and passed. Both credited March, their counselor, with providing unending support as they navigated high school and college classes.

“She’s always there for you,” Sarmiento said. “It’s hard to be on top of everything. You have someone to go to.”

Students also supported each other.

“You build bonds,” Ivarra said. “You’re all trying to figure out these classes. You grow together. It’s a bunch of people who want to succeed. The people that surround you in P-TECH, they push you to be better.”

SUPPORT SYSTEMS ARE KEY

P-TECH has no entrance requirements or prerequisite classes. You don’t need to be a top student, have taken advanced math or have a background in technology.

With students starting the rigorous program with a wide range of skills, teachers and counselors said, they quickly figured out the program needed stronger support systems.

March said freshmen in the first P-TECH class struggled that first semester, prompting the creation of a guided study class. The every other day, hour-and-a-half class includes both study time and time to learn workplace skills, including writing a resume and interviewing. Teachers also offer tutoring twice a week after school.

“The guided study has become crucial to the success of the program,” March said.

Another way P-TECH provides extra support is through summer orientation programs for incoming freshmen.

At Skyline, ninth graders take a three-week bridge class — worth half a credit — that includes learning good study habits. They also meet IBM mentors and take a field trip to Front Range Community College.

“They get their college ID before they get their high school ID,” March said.

During a session in June, 15 IBM mentors helped the students program a Sphero robot to travel along different track configurations. Kathleen Schuster, who has volunteered as an IBM mentor since the P-TECH program started here, said she wants to “return some of the favors I got when I was younger.”

“Even this play stuff with the Spheros, it’s teaching them teamwork and a little computing,” she said. “Hopefully, through P-TECH, they will learn what it takes to work in a tech job.”

Incoming Skyline freshman Blake Baker said he found a passion for programming at Trail Ridge Middle and saw P-TECH as a way to capitalize on that passion.

“I really love that they give you options and a path,” he said.

Trail Ridge classmate Itzel Pereyra, another programming enthusiast, heard about P-TECH from her older brother.

“It’s really good for my future,” she said. “It’s an exciting moment, starting the program. It will just help you with everything.”

While some of the incoming ninth graders shared dreams of technology careers, others see P-TECH as a good foundation to pursue other dreams.

Skyline incoming ninth grader Marisol Sanchez wants to become a traveling nurse, demonstrating technology and new skills to other nurses. She added that the summer orientation sessions are a good introduction, helping calm the nerves that accompany combining high school and college.

“There’s a lot of team building,” she said. “It’s getting us all stronger together as a group and introducing everyone.”

THE SPARK OF MOTIVATION

Silver Creek’s June camp for incoming ninth graders included field trips to visit Cisco, Seagate, PEAK Resources, Comcast and Front Range Community College.

During the Front Range Community College field trip, the students heard from Front Range staff members before going on a scavenger hunt. Groups took photos to prove they completed tasks, snapping pictures of ceramic pieces near the art rooms, the most expensive tech product for sale in the bookstore and administrative offices across the street from the main building.

Emma Horton, an incoming freshman, took a cybersecurity class as a Flagstaff Academy eighth grader that hooked her on the idea of technology as a career.

“I’m really excited about the experience I will be getting in P-TECH,’ she said. “I’ve never been super motivated in school, but with something I’m really interested in, it becomes easier.”

Deb Craven, dean of instruction at Front Range’s Boulder County campus, promised the Silver Creek students that the college would support them. She also gave them some advice.

“You need to advocate and ask for help,” she said. “These two things are going to help you the most. Be present, be engaged, work together and lean on each other.”

Craven, who oversees Front Range’s P-TECH program partnership, said Front Range leaders toured the original P-TECH program in New York along with St. Vrain and IBM leaders in preparation for bringing P-TECH here.

“Having IBM as a partner as we started the program was really helpful,” she said.

When the program began, she said, freshmen took a more advanced technology class as their first college class. Now, she said, they start with a more fundamental class in the spring of their freshman year, learning how to build a computer.

“These guys have a chance to grow into the high school environment before we stick them in a college class,” she said.

Summer opportunities aren’t just for P-TECH’s freshmen. Along with summer internships, the schools and community colleges offer summer classes.

Silver Creek incoming 10th graders, for example, could take a personal financial literacy class at Silver Creek in the mornings and an introduction to cybersecurity class at the Innovation Center in the afternoons in June.

Over at Skyline, incoming 10th graders in P-TECH are getting paid to teach STEM lessons to elementary students while earning high school credit. Students in the fifth or sixth year of the program also had the option of taking computer science and algebra classes at Front Range.

EMBRACING THE CHALLENGE

And at Frederick, incoming juniors are taking an introduction to manufacturing class at the district's Career Elevation and Technology Center this month in preparation for an advanced manufacturing class they’re taking in the fall.

“This will give them a head start for the fall,” said instructor Chester Clark.

Incoming Frederick junior Destini Johnson said she’s not sure what she wants to do after high school, but believes the opportunities offered by P-TECH will prepare her for the future.

“I wanted to try something challenging, and getting a head start on college can only help,” she said. “It’s really incredible that I’m already halfway done with an associate’s degree and high school.”

IBM P-TECH program manager Tracy Knick, who has worked with the Skyline High program for three years, said it takes a strong commitment from all the partners — the school district, IBM and Front Range — to make the program work.

“It’s not an easy model,” she said. “When you say there are no entrance requirements, we all have to be OK with that and support the students to be successful.”

IBM hosted 60 St. Vrain interns this summer, while two Skyline students work as IBM “co-ops” — a national program — to assist with the P-TECH program.

The company hosts two to four formal events for the students each year to work on professional and technical skills, while IBM mentors provide tutoring in algebra. During the pandemic, IBM also paid for subscriptions to tutor.com so students could get immediate help while taking online classes.

“We want to get them truly workforce ready,” Knick said. “They’re not IBM-only skills we’re teaching. Even though they choose a pathway, they can really do anything.”

As the program continues to expand in the district, she said, her wish is for more businesses to recognize the value of P-TECH.

“These students have had intensive training on professional skills,” she said. “They have taken college classes enhanced with the same digital credentials that an IBM employee can learn. There should be a waiting list of employers for these really talented and skilled young professionals.”

©2022 the Daily Camera (Boulder, Colo.). Distributed by Tribune Content Agency, LLC.

Thu, 04 Aug 2022 02:41:00 -0500 en text/html https://www.govtech.com/education/k-12/colorados-p-tech-students-graduate-ready-for-tech-careers
Killexams : IBM Impact: Making a Lasting, Positive Impact in Business Ethics, Our Environment, and Communities

Northampton, MA --News Direct-- IBM

Recently, IBM launched IBM Impact, a new framework for the company's environmental, social, and governance (ESG) work that reflects how IBM aspires to create a more sustainable, equitable, and ethical future.

As detailed in the 2021 ESG report, IBM Impact comprises three pillars: Environmental Impact, Equitable Impact, and Ethical Impact. These values have been embedded in IBM's DNA as a company and have driven its work for its employees, clients, and other stakeholders across the world over the past century.

Get insights on how IBM is creating better pathways to conserve natural resources; creating spaces and opportunities for everyone by focusing on diversity, equity, and inclusivity; and creating innovations, policies and practices that prioritize ethics, trust, transparency, and above all – accountability:

ESG ContactSuzanne KlattDirector ESG Program & Strategy

Media ContactCarmen San SegundoGlobal Communications Director, CSR and Sustainability

Read the Report

View additional multimedia and more ESG storytelling from IBM on 3blmedia.com

View source version on newsdirect.com: https://newsdirect.com/news/ibm-impact-making-a-lasting-positive-impact-in-business-ethics-our-environment-and-communities-614234766

Thu, 14 Jul 2022 01:50:00 -0500 en-US text/html https://finance.yahoo.com/news/ibm-impact-making-lasting-positive-133006797.html
Killexams : The Quantum Decade: Canada’s foresight is paying off, says IBM Canada

“Quantum computing is no longer a futuristic concept," says Frank Attaie, IBM Canada’s general manager, technology

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For a country with a legacy of dominance in natural resource industries — forestry, mining, oil and gas and marine — it seems counterintuitive for it also to rank as a global leader in one of the most dynamic and complex computing technologies ever known, yet here we are.

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Canada recognized early on that quantum computing presents a staggering amount of potential across all facets of society, including the economy, medicine, climate change, academics, research, manufacturing and so much more. In fact, Canada is ranked fifth in total quantum science expenditures and first among G7 nations in per-capita spending on quantum research. The country has invested more than $1 billion in quantum science over the past decade and is investing $360 million more to launch a National Quantum Strategy to bolster quantum research, advance quantum-ready technologies and attract business and talent.

Frank Attaie, IBM Canada’s general manager, technology, says that Canada’s foresight is paying off: “Quantum computing is no longer a futuristic concept. The world has entered into the Quantum Decade, an era when Canadian enterprises are beginning to see quantum computing’s business value.” Over the last year, there have been unprecedented advances in hardware, software development and services that validate the technology’s momentum, creating an ecosystem that paves the way for further breakthroughs and helps prepare the market for the adoption of this revolutionary technology.

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In February, IBM announced — in partnership with the Government of Quebec — it will accelerate discovery in artificial intelligence, semiconductors, high-performance computing and quantum computing, including installation of the first IBM Quantum System One in Canada. What this could mean for science and research in the country is unprecedented, says Attaie.

“What we do know,” continued Attaie, “is that the quantum challenge is too big for any one entity. As quantum moves from the lab to the real world, ecosystems are forming to support collaborative innovation and open-source development.” Potential ecosystems likely include a quantum computing technology partner, quantum computing developers and academic partners.

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A successful model of this is the membership of the Université de Sherbrooke in the IBM Quantum Network, a community of Fortune 500 companies, academic institutions, startups and national research labs working with IBM to advance quantum computing. Since the university joined the IBM Quantum Network as a Hub in 2020, other industry leaders such as Lockheed Martin Canada and CMC Microsystems have joined as Hub members. This is in addition to another 12 IBM Quantum Network start-ups and academic partners across the country, actively exploring quantum with our technology and scientists.  

Frank Attaie, IBM Canada’s general manager, technology. SUPPLIED
Frank Attaie, IBM Canada’s general manager, technology. SUPPLIED

The Quantum Decade needs a quantum workforce

“Innovation alone cannot unlock the full potential of quantum computing,” said Attaie. “We need the people and skills to do so.” Estimates indicate there are only about 3,000 skilled quantum workers in the market today, a base that needs to dramatically increase to exploit the full potential of quantum this decade and beyond. And while Canada’s foresight into the future of quantum has helped prime the sector with extraordinary levels of expertise, the growth of the industry will need much, much more, says Attaie.

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“For Canada to be quantum ready, industry needs to engage critical constituencies, from domain experts to students, to enable quantum computing skills to blossom.” These include quantum developer certification, as well as bootcamp-like educational programs and investments in educator training that empower a diverse workforce.

The decade ahead — enterprises will see the payoff of quantum

While the power and capacity of quantum is clear, how the Quantum Decade will unfold is not. How will governments implement quantum computing as part of their economic growth strategies? What novel use cases will researchers uncover and put into play?

Attaie agrees there are many unknowns as to how the Quantum Decade will evolve but is confident its end will look nothing like the beginning. “We will be working with quantum processors with thousands of qubits, we will have a whole workforce with years of experience, and enterprises will have seen the payoff of quantum,” said Attaie. “Make no mistake, quantum computing is a whole new paradigm. Every technology leader should be actively building quantum into their plans so that they’re ready for its rapid evolution over the next decade.”

This story was provided by IBM Canada for commercial purposes.

Fri, 05 Aug 2022 05:14:00 -0500 en-CA text/html https://ottawacitizen.com/sponsored/news-sponsored/the-quantum-decade-canadas-foresight-is-paying-off-says-ibm-canada
Killexams : Texas Pacific and IBM have been highlighted as Zacks Bull and Bear of the Day

For Immediate Release

Chicago, IL – July 25, 2022 – Zacks Equity Research shares Texas Pacific Land TPL as the Bull of the Day and International Business Machines IBM as the Bear of the Day. In addition, Zacks Equity Research provides analysis on The Boeing Company BA, L3Harris Technologies LHX and Spire Global, Inc. SPIR.

Here is a synopsis of all five stocks:

Bull of the Day:

Texas Pacific Land is a Zacks Rank #1 (Strong Buy) that is landowners principally in the State of Texas. The Company generates revenue from pipeline, power line and utility easements, commercial leases, material sales and seismic and temporary permits related to land uses including midstream infrastructure projects and hydrocarbon processing facilities.

The stock took off in late 2020 and into 2021, moving from $400 to $1770. From there, the stock saw a slow descent, back under the $1000 level earlier this year.

But investors have been buying the stock since those bottoms in Q1. The stock is back at all time highs and should be watched for buying opportunities.

More About TPL

The company describes itself as a "Pure play in the Permian Basin." Texas Pacific Land was founded in 1888 and is headquartered in Dallas, Texas. It employs about 100 people and has a market cap of $13.5 billion.

TPL engages in the land and resource management, and water services and operations businesses.

The company's Land and Resource Management segment manages approximately 880,000 acres of land in 19 counties in the western part of Texas. It rents this land out to oil and gas producers that pay fees for use of that land.

Texas Pacific also has a Water Services and Operations segment that provides full-service water offerings.

The stock has a Zacks Style Score of "B" in Momentum and "C" in Growth. However, it has a "F" in Value, due to the high Forward PE of 28. While the PE is high, investors value the free cash flow more, which has been high due to higher energy prices.

Q1 Earnings

On May 4th, TPL reported an 8% EPS miss for Q1. While the company missed the estimates, the year over year numbers came in almost double from last year.

For earnings, the company saw $12.64 v the $6.45 last year. And for revenues, $147.M vs the $84.2M last year.

The company raised their dividend 9.1% and boosted their special dividend to $20 a share.

Here are some comments from management on the special dividend and the quarter:

"With tailwinds of favorable commodity prices, strong production, and a debt-free balance sheet, we're pleased to announce a $20 per share special dividend as our shareholders reap the windfall of supportive underlying fundamentals."

The company added that the dividend is on top of their $100 million share repurchase program and they will continue to return capital back to shareholders.

Estimates Rising

Analysts are getting excited about the upcoming quarters and raising estimates across all time frames.

Over the last month, estimates for the current quarter have gone from $15.10 to $15.84, a move of 5%. For the current year, we have seen a move of 3.5% higher, with estimates moving from $60.73 to $62.91.

Next year's estimates are also moving higher. Over the last 60 days, estimates have gone from $67.26 to $70.60, or 5%.

Strength in a Weak Market

TPL has not only been a great place to hide, it has been very rewarding. The stock is up almost 50% so far in 2022 and over 120% since the beginning over 2020.

In addition to the appreciation, investors are being rewarded with a small annual dividend and of course, the large special dividend. Investors should expect more special dividends in the future, due to the free cash flow that is being generated from high energy prices.

The Technical Take

The stock is trading at all-time highs so instead of chasing it, investors might want to be patient and look for pullbacks.

The 21-day moving average is at $1600, while the 50-day is at $1550. The 200-day MA is all the way down at $1330 and not likely to hit anytime soon.

Looking at the Fibonacci levels, the pullback earlier this year came down into the 61.8% retracement at $930 and held. Investors looking for upside targets could target the -23.6% level at $2075.

In Summary

When markets are weak, investors should look for relative strength. Not only is TPL relatively strong, but the stock has taken off to all-time highs. This is a very positive sign for investors and when market sentiment improves, the stock could really get going.

Investors should watch energy prices when owning a name like this. A large drop in oil and natural gas could destroy the narrative.

Bear of the Day:

International Business Machines is a Zacks Rank #5 (Strong Sell) provides advanced information technology solutions, computer systems, quantum computing and super computing solutions, enterprise software, storage systems and microelectronics.

"Big Blue" has struggled over the last decade, so they have tried to adjust and pivot to the cloud. Their acquisition of Red Hat helped this idea, but a latest earnings report has disappointed investors.

The stock is now trending lower and looks like it might challenge 2022 lows.

About the Company

IBM is headquartered in Armonk, New York. The company was incorporated in 1911 and employs over 280,000 people.

The company operates through four business segments: Software, Consulting, Infrastructure, and Financing.

IBM is valued at $114 billion and has a Forward PE of 13. The stock holds a Zacks Style Score of "C" in Value, "B" in Growth and "B" in Momentum. The stock pays a dividend of 5%.

Q2 Earnings

The company reported EPS last week, seeing Q2 at $2.31 versus the $2.29 expected. Revenues came in at $15.5B versus $15.1B. IBM affirmed FY22 at the high end of its mid-single digit model, but narrowed the FY22 FCF to $10B from $10-10.5B.

Margins were down year over year, from 55.2% to 53.4%. While software, consulting and infrastructure revenues were all higher year over year.

Here are some comments from CEO Arvind Krishna:

"In the quarter we delivered good revenue performance with balanced growth across our geographies, driven by client demand for our hybrid cloud and AI offerings. The IBM team executed our strategy well."

Estimates

Analysts are already starting to drop estimates as a result of the earnings report.

After stabilizing over the last few months, estimates have fallen off a cliff over the last 7 days. For the current quarter, estimates have fallen from $2.57 to 2.07, or 20%.

Things look to Strengthen next quarter, but we see estimates tracking lower again for next year. Over the last 60 days, numbers have been lowered from $10.81 to $10.26, or 5%.

Technical Take

The stock was holding up well before earnings, as it was seeing support at the 50-day moving average. But IBM is now trading under all its moving averages after the earnings report, slicing right through the 200-day at $130.50.

The lows of the year are just under $120. These should be taken out if the momentum continues and the bears could possibly target the 2021 lows around $113.

Looking at Fibonacci levels, a 61.8% retracement drawn from May lows to June highs was holding at $133. However, this support was broken and bears should target the 161.8% extension at $113. This lines up with that 2021 low support.

In Summary

While big blue had some positive aspects to the quarter, investors were disappointed overall. The stock fell over 8% after earnings and looks like it could take out 2022 lows on any market weakness.

The stock pays a nice dividend, but with cash flow being taken down, investors might start to lose faith in that payout.

Additional content:

Will Abnormal Costs Hurt Boeing (BA) on Q2 Earnings?

Increased 737 delivery figures are expected to have boosted The Boeing Company's commercial business in the second quarter. However, second-quarter 2022 results, scheduled for release on Jul 27, are projected to reflect the impacts of abnormal costs related to the 777-9 program, on the bottom-line front.

Click here to know how the company's overall Q2 performance is expected to have been.

Solid 737 Max Deliveries to Boost Growth

Thanks to steadily recovering air traffic, improved delivery figures for Boeing's 737 jets, a trend we have been witnessing in the past couple of quarters, were observed in the second quarter of 2022 as well. Notably, the aerospace giant delivered 103 737 jets in the soon-to-be-reported quarter, reflecting quite a solid improvement of 106% from 50 units delivered in the year-ago quarter.

In fact, such significant delivery figures of 737 primarily drove a significant surge of 53.2% in the company's overall commercial deliveries. This, in turn, must have contributed to Boeing Commercial Airplane (BCA) business segment revenues in the soon-to-be-reported quarter.

The Boeing Company price-eps-surprise | The Boeing Company Quote

However, the aerospace giant was unable to deliver any of its 787 Dreamliner jets in the second quarter of 2022, owing to production quality issues related to the program. This might have partially impacted the top-line performance of the BCA segment.

Currently, the Zacks Consensus Estimate for Boeing's commercial business segment's revenues, pegged at $6,491 million, indicates a solid 7.9% improvement from the year-ago quarter's reported figure.

Earnings Expectation

On the cost front, delivery delays concerning the 787 performance issue are likely to have had an impact on BCA's operating profit, thereby hurting its quarterly earnings. Also, the production pause for the 777-9 program is projected to result in approximately $1.5 billion of abnormal costs beginning in the second quarter, which in turn must have weighed on this unit's bottom line.

However, improvements in commercial airplanes' financial performance due to increasing 737 MAX deliveries and consistent efforts by the BCA team to manage costs through business transformation activities must have contributed to this unit's bottom-line growth in the first quarter.

Further, we expect to witness a steady improvement in the company's expenses in relation to the storage of the 737 aircraft as jets stored so long in the inventory are gradually getting delivered.

So, the effect of the aforementioned factors on the overall second-quarter earnings performance of the BCA segment seems to have been mixed.

Currently, the Zacks Consensus Estimate for Boeing's commercial business segment's bottom line, pegged at a loss of $158 million, indicates an improvement from the year-ago quarter's reported figure of a loss of $472 million.

What the Zacks Model Unveils

Our proven model does not conclusively predict an earnings beat for Boeing this time around. The combination of a positive Earnings ESP and a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 (Hold) increases the chances of an earnings beat. This is not the case here.

Boeing has an Earnings ESP of -62.40% and a Zacks Rank #3. You can uncover the best stocks to buy or sell before they're reported with our Earnings ESP Filter.

Stocks to Consider

Here are a couple defense companies you may want to consider as these have the right combination of elements to post an earnings beat this season:

L3Harris Technologies: It is scheduled to release its second-quarter results on Jul 28. LHX holds a Zacks Rank #3 and has an Earnings ESP of +1.01%. You can see the complete list of today's Zacks #1 Rank stocks here.

LHX delivered a four-quarter average earnings surprise of 2.32%. The Zacks Consensus Estimate for L3Harris' second-quarter earnings, pegged at $3.16, has moved up 0.3% over the past seven days.

Spire Global, Inc. has an Earnings ESP of +9.43% and a Zacks Rank #3.

Spire delivered an earnings surprise of 7.7% in the last reported quarter. The Zacks Consensus Estimate for Spire's second-quarter sales is pegged at $18.93 billion.

Stay on top of upcoming earnings announcements with the Zacks Earnings Calendar.

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Past performance is no certain of future results. Inherent in any investment is the potential for loss. This material is being provided for informational purposes only and nothing herein constitutes investment, legal, accounting or tax advice, or a recommendation to buy, sell or hold a security. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. It should not be assumed that any investments in securities, companies, sectors or markets identified and described were or will be profitable. All information is current as of the date of herein and is subject to change without notice. Any views or opinions expressed may not reflect those of the firm as a whole. Zacks Investment Research does not engage in investment banking, market making or asset management activities of any securities. These returns are from hypothetical portfolios consisting of stocks with Zacks Rank = 1 that were rebalanced monthly with zero transaction costs. These are not the returns of real portfolios of stocks. The S&P 500 is an unmanaged index. Visit https://www.zacks.com/performance for information about the performance numbers displayed in this press release.


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Killexams : Astadia Publishes Mainframe to Cloud Reference Architecture Series

Press release content from Business Wire. The AP news staff was not involved in its creation.

BOSTON--(BUSINESS WIRE)--Aug 3, 2022--

Astadia is pleased to announce the release of a new series of Mainframe-to-Cloud reference architecture guides. The documents cover how to refactor IBM mainframes applications to Microsoft Azure, Amazon Web Services (AWS), Google Cloud, and Oracle Cloud Infrastructure (OCI). The documents offer a deep dive into the migration process to all major target cloud platforms using Astadia’s FastTrack software platform and methodology.

As enterprises and government agencies are under pressure to modernize their IT environments and make them more agile, scalable and cost-efficient, refactoring mainframe applications in the cloud is recognized as one of the most efficient and fastest modernization solutions. By making the guides available, Astadia equips business and IT professionals with a step-by-step approach on how to refactor mission-critical business systems and benefit from highly automated code transformation, data conversion and testing to reduce costs, risks and timeframes in mainframe migration projects.

“Understanding all aspects of legacy application modernization and having access to the most performant solutions is crucial to accelerating digital transformation,” said Scott G. Silk, Chairman and CEO. “More and more organizations are choosing to refactor mainframe applications to the cloud. These guides are meant to assist their teams in transitioning fast and safely by benefiting from Astadia’s expertise, software tools, partnerships, and technology coverage in mainframe-to-cloud migrations,” said Mr. Silk.

The new guides are part of Astadia’s free Mainframe-to-Cloud Modernization series, an ample collection of guides covering various mainframe migration options, technologies, and cloud platforms. The series covers IBM (NYSE:IBM) Mainframes.

In addition to the reference architecture diagrams, these comprehensive guides include various techniques and methodologies that may be used in forming a complete and effective Legacy Modernization plan. The documents analyze the important role of the mainframe platform, and how to preserve previous investments in information systems when transitioning to the cloud.

In each of the IBM Mainframe Reference Architecture white papers, readers will explore:

  • Benefits, approaches, and challenges of mainframe modernization
  • Understanding typical IBM Mainframe Architecture
  • An overview of Azure/AWS/Google Cloud/Oracle Cloud
  • Detailed diagrams of IBM mappings to Azure/AWS/ Google Cloud/Oracle Cloud
  • How to ensure project success in mainframe modernization

The guides are available for get here:

To access more mainframe modernization resources, visit the Astadia learning center on www.astadia.com.

About Astadia

Astadia is the market-leading software-enabled mainframe migration company, specializing in moving IBM and Unisys mainframe applications and databases to distributed and cloud platforms in unprecedented timeframes. With more than 30 years of experience, and over 300 mainframe migrations completed, enterprises and government organizations choose Astadia for its deep expertise, range of technologies, and the ability to automate complex migrations, as well as testing at scale. Learn more on www.astadia.com.

View source version on businesswire.com:https://www.businesswire.com/news/home/20220803005031/en/

CONTACT: Wilson Rains, Chief Revenue Officer

Wilson.Rains@astadia.com

+1.877.727.8234

KEYWORD: UNITED STATES NORTH AMERICA MASSACHUSETTS

INDUSTRY KEYWORD: DATA MANAGEMENT TECHNOLOGY OTHER TECHNOLOGY SOFTWARE NETWORKS INTERNET

SOURCE: Astadia

Copyright Business Wire 2022.

PUB: 08/03/2022 10:00 AM/DISC: 08/03/2022 10:02 AM

http://www.businesswire.com/news/home/20220803005031/en

Wed, 03 Aug 2022 02:02:00 -0500 en text/html https://apnews.com/press-release/BusinessWire/technology-f50b643965d24115b2c526c8f96321a6
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