AI And Machine Learning Provide Challenges And Opportunities For Data Center Architects

Meet the new challenge: AI and machine learning (AI+ML). The ability to share high-speed NVMe flash storage resources can no longer match the …

CEO and co-founder of Liqid Inc. Tech industry veteran with more than 20 years of experience.

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Gary Burchell

Pain drives the adoption of new IT solutions. The need for inexpensive shared storage for VMware virtualization drove the proliferation of storage area networks (SANs) — the massive data storage systems that are now a staple in modern data centers. High on-prem IT costs to run applications and store the massive amounts of data created and managed by SANs drove the adoption of cloud computing, enabling organizations to economically access applications and expensive, high-value resources such as storage to power native applications.

Meet the new challenge: AI and machine learning (AI+ML). The ability to share high-speed NVMe flash storage resources can no longer match the performance required to effectively calculate that data in real time for AI+ML operations. Graphics processing (GPU) resources that can calculate data three-dimensionally (i.e., visual computing), versus linear, transactional calculations of traditional CPUs, have been introduced into the data center ecosystem to improve data performance to meet the needs of AI+ML.

The numbers tell the story of this ongoing data center transformation very well. Recent earnings from GPU provider NVIDIA (a Liqid partner) show the company has posted 167% year-over-year revenue growth in its data center business with AI+ML and high-performance computing deployments driving growth across industry verticals. Furthermore, last year the analyst group Gartner predicted that through 2023, GPU adoption in the data center will grow much faster compared to PC gaming: 22.53% CAGR vs. 6.69%.

GPUs are high-value resources with the price tags to match. NVIDIA has again increased that value and thrown down the gauntlet for its data center competitors to pick up. The company’s new A100 Tensor Core GPU is faster than its previous generation of GPU by 20 times, making it among the fastest accelerators in any data center environment. NVIDIA sees the A100 as the “universal accelerator” for AI+ML operations, scientific research and cloud-based visual computing.

It’s easy to predict that those organizations seeking a competitive advantage in next-gen, AI-driven computing will eagerly deploy these devices in the largest quantities that budgets will allow. Again, the money tells the story well: Gartner anticipates that augmenting data center architectures with AI will create $2.9 trillion in business value in 2021.

A Wave Of Accelerator Innovation Drives AI Adoption

With GPUs increasingly becoming table stakes for competitive data center environments with diverse AI+ML workloads, it’s important to remember GPUs are by no means the only data accelerators evolving to meet the ever-increasing data requirements associated with AI+ML.

In addition to the performance advancements enabled by the A100, NVIDIA Mellanox is now producing the high-speed ConnectX-6 SmartNIC. The ConnectX delivers a powerful, secure 25/50 Gb/s ethernet controller. The device is designed to enable the most adaptive management of networked hardware possible, across the entire data center, via software.

And that is just from NVIDIA. Intel Optane memory technology uses software to give its Intel Core-based solid-state storage (SSD) products near-memory speeds. One of the most basic, bare-metal interface that connects disaggregated data center devices through the CPU, PCI-Express (PCIe), has recently been updated to PCI-Express 4.0., which offers twice the performance of its preceding specification. NVMe storage protocols provide marked performance improvements over legacy protocols such as SATA or SaaS for additional advancements in data speeds.

Tying It All Together: New Performance Requirements Call For New Architectures

While all of these new solutions are exciting for data center professionals, architecting them into existing environments and predicting rapidly changing performance requirements are urgently required. Traditional data center architectures leave GPU and other accelerator resources locked into configurations at the point of purchase. Without the ability to share these valuable resources in a networked enviornment, the result can be significant underutilization and waste.

Again using the example of the A100, multiple A100s to be aggregated in previously impossible volumes so users can share GPUs in a manner better capable of supporting the data needs of AI+ML applications.

Other organizations seek to better optimize resources through NVMe- and GPU-over Fabric (NVME-/GPU-oF) operations, which use software to aggregate the power of these resources via high-speed ethernet and infiniband networking fabrics in order to more widely distribute NVMe and GPU capabilities across distance and beyond traditional fixed configurations.

Composable software makes it possible to share all of these resources in any volume required, in perfect balance with other high-performance hardware. Composability also allows for older accelerator devices already deployed to be seamlessly integrated with newer disaggrated hardware. As workload requirements change, all disaggregated high-performance accelerators can be adjusted to meet uneven data workload requirements, either on-demand or automated deployment.

In these ways and others, IT users will eventually be able to aggregate unlimited devices across ethernet in tandem with other accelerators. As the market matures, users will eventually be able to rent GPU resources as a service, just as the SAN enabled the movement of data to the cloud while simultaneously driving new opportunities to rent out the high-performance storage resources.

The evolving ecosystem that is developing to support and efficiently share high-value, next-gen accelerator resources will help solve huge problems and create significant opportunities across industry, government, and academia. It’s just that transformative. The leaders who emerge as change takes place at a rapid clip will need to be able to effectively and efficiently optimize and adapt to the changing data environment in order to meet the performance demand associated with AI+ML operations.


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Global Technology Leaders Adopt NVIDIA EGX Edge AI Platform to Infuse Intelligence at the Edge …

… to build and deploy healthcare, retail, logistics and smart cities solutions. … Rather than having 10,000 servers in one location, future enterprise data …

SANTA CLARA, Calif., Oct. 05, 2020 (GLOBE NEWSWIRE) — GTC–NVIDIA today announced widespread adoption of the NVIDIA EGX™ edge AI platform by the world’s leading tech companies, bringing a new wave of secure, GPU-accelerated software, services and servers to enterprise and edge data centers.

Hundreds of vision AI, 5G, CloudRAN, security and networking companies are teaming with major server manufacturers, including Dell Technologies, Inspur, Lenovo and Supermicro, as well as leading software infrastructure providers, including Canonical, Cloudera, Red Hat, SUSE and VMware, to leverage the NVIDIA EGX platform to help businesses bring AI to the edge.

The world’s largest industries — manufacturing, healthcare, retail, logistics, agriculture, telco, public safety and broadcast media — are able to benefit from the EGX platform to quickly and efficiently deploy AI at scale.

NVIDIA also announced that the EGX platform is expanding to combine the NVIDIA Ampere GPU and BlueField-2® DPU capabilities on a single PCIe card, giving enterprises a common platform to build secure, accelerated data centers. BlueField-2 DPUs include powerful Arm CPU cores that can be used to create a trusted enclave for AI inference models running on the GPU.

“Companies around the world will come to use AI to improve virtually every aspect of their business,” said Jensen Huang, founder and CEO of NVIDIA, who unveiled the news in his keynote at the GPU Technology Conference. “To support this massive shift, NVIDIA has created an accelerated computing platform that helps companies modernize their data centers and deploy AI anywhere.”

Optimized AI Software for Edge and Data Center

At the heart of the EGX platform is an optimized AI software stack available on NVIDIA NGC, a software catalog offering a range of industry-specific AI toolkits and pre-trained models to make it easier to build and deploy AI applications on NVIDIA-Certified systems.

NVIDIA AI application frameworks are used by leading AI software vendors such as Deep North, Everseen and Whiteboard Coordinator to build and deploy healthcare, retail, logistics and smart cities solutions.

NVIDIA vGPU software products and GPUDirect® RDMA technologies give NVIDIA GPUs the ability to send and receive data at full bandwidth to unlock the highest performance.

To help enterprises deploy AI at scale, NVIDIA is working with leading platform companies, including Canonical, Cloudera, Red Hat, SUSE and VMware, to enable their flagship virtualization, operating systems, Kubernetes and data analytics platforms are fully optimized for NVIDIA AI software when running in bare metal or virtualized environments.

Deploy and Manage EGX Servers Anywhere

Rather than having 10,000 servers in one location, future enterprise data centers will have one or more servers across 10,000 different locations, including inside office buildings, factories, warehouses, cell towers, schools, stores and banks.

To simplify and secure the deployment and management of AI applications and models on these servers at scale, NVIDIA announced an early access program for a new service called NVIDIA Fleet Command™. This hybrid cloud platform combines the security and real-time processing capabilities of edge computing with the remote management and ease of software-as-a-service.

Through a unified control plane, Fleet Command centralizes the management of servers spread across vast areas, including factories, hospitals, retail stores and even city streets. Fleet Command’s one-touch provisioning, over-the-air software updates, remote management and detailed monitoring dashboards make it easier for operational teams to reduce the burden of IT to get the most out of their AI applications and drive the highest operational efficiency.

Among the first companies provided early access to Fleet Command is KION Group, a leader in global supply chain solutions, which is using the NVIDIA EGX AI platform to develop AI applications for its intelligent warehouse systems, increasing the throughput and efficiency in retail distribution centers.

Additionally, Northwestern Memorial Hospital, the No. 1 hospital in Illinois and top 10 in the nation, is working with Whiteboard Coordinator to use Fleet Command for its IoT sensor platform, which includes computer vision, voice recognition and Bluetooth tracking capabilities inside its clinics and medical centers.

“Whiteboard Coordinator works with leading healthcare providers to organize their applications, servers and software deployments from anywhere at any time from the cloud,” said Andrew Gostine, MD, CEO of Whiteboard Coordinator. “We’re using NVIDIA Fleet Command to remotely deploy and securely manage a suite of healthcare AI applications across multiple hospital locations with a few clicks. That frees us to focus more on providing value to patients, instead of spending hours managing infrastructure.”

Availability

NVIDIA EGX systems are available for purchase through the NVIDIA qualified server catalog. Existing servers enabled for NVIDIA AI software are available from ASUS, Atos, Dell Technologies, Fujitsu, GIGABYTE, H3C, Inspur, Lenovo, Quanta/QCT and Supermicro.

The NVIDIA Fleet Command early access program is open to qualified customers.

About NVIDIA

NVIDIA’s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.

For further information, contact:

Kristin Uchiyama

NVIDIA Corporation

+1-408-313-0448

kuchiyama@nvidia.com

Certain statements in this press release including, but not limited to, statements as to: the benefits and impact of the NVIDIA EGX edge AI platform and its expansion to combine the NVIDIA Ampere GPU and BlueField-2 DPU capabilities on a single PCIe card, the NVIDIA Fleet Command service, NVIDIA vGPU software products and GPUDirect RDMA technologies; companies around the world coming to use AI to improve virtually every aspect of their business; NVIDIA working with leading platform companies to ensure full optimization for NVIDIA AI software; and future enterprise data centers having one or more servers across thousands of different locations are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

© 2020 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, BlueField, GPUDirect, NVIDIA EGX and NVIDIA-Certified Systems are trademarks and/or registered trademarks of NVIDIA Corporation and/or Mellanox Technologies in the U.S. and other countries. All other trademarks and copyrights are the property of their respective owners.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/3d959ded-0481-43e6-8dfe-44cbf54d9d3f

NVIDIA Unveils Jetson Nano 2GB: The Ultimate AI and Robotics Starter Kit for Students, Educators …

… industrial IoT, healthcare, smart cities and more. Additionally, with the performance and capability to run a diverse set of AI models and frameworks, …

SANTA CLARA, Calif., Oct. 05, 2020 (GLOBE NEWSWIRE) — GTC— NVIDIA today expanded the NVIDIA® Jetson™ AI at the Edge platform with an entry-level developer kit priced at just $59, opening the potential of AI and robotics to a new generation of students, educators and hobbyists.

The Jetson Nano 2GB Developer Kit is designed for teaching and learning AI by creating hands-on projects in such areas as robotics and intelligent IoT. To support the effort, NVIDIA also announced the availability of free online training and AI-certification programs, which will supplement the many open-source projects, how-tos and videos contributed by thousands of developers in the vibrant Jetson community.

“While today’s students and engineers are programming computers, in the near future they’ll be interacting with, and imparting AI to, robots,” said Deepu Talla, vice president and general manager of Edge Computing at NVIDIA. “The new Jetson Nano is the ultimate starter AI computer that allows hands-on learning and experimentation at an incredibly affordable price.”

Latest Offering in Jetson AI at the Edge Platform

The Jetson Nano 2GB Developer Kit is the latest offering in NVIDIA’s Jetson AI at the Edge platform, which ranges from entry-level AI devices to advanced platforms for fully autonomous machines.

It is supported by the NVIDIA JetPack™ SDK, which comes with NVIDIA container runtime and a full Linux software development environment. This allows developers to package their applications for Jetson with all its dependencies into a single container that is designed to work in any deployment. And it is powered by the same NVIDIA CUDA-X™ accelerated computing stack used to create breakthrough AI products in such fields as self-driving cars, industrial IoT, healthcare, smart cities and more.

Additionally, with the performance and capability to run a diverse set of AI models and frameworks, the Jetson Nano 2GB Developer Kit provides a scalable platform for learning and creating AI applications as they evolve.

Robust Ecosystem and Partner Support

The Jetson Nano 2GB Developer Kit has received strong endorsements from organizations, enterprises, educators and partners in the embedded computing ecosystem:

Jim McGregor, principal analyst at Tarias Research, said: “NVIDIA’s Jetson is driving the biggest revolution in industrial AIoT. With the new Jetson Nano 2GB, NVIDIA opens up AI learning and development to a broader audience, using the same software stack as its data center AI computing platform.”

Matthew Tarascio, vice president of Artificial Intelligence at Lockheed Martin, said: “Acquiring new technical skills with a hands-on approach to AI learning becomes critical as AIoT drives the demand for interconnected devices and increasingly complex industrial applications. We’ve used the NVIDIA Jetson platform as part of our ongoing efforts to train and prepare our global workforce for the AI revolution.”

Emilio Frazzoli, professor of Dynamic Systems and Control at ETH Zurich, said: “The Duckietown educational platform provides a hands-on, scaled down, accessible version of real-world autonomous systems. Integrating NVIDIA’s Jetson Nano power in Duckietown enables unprecedented, affordable access to state-of-the-art compute solutions for learning autonomy.”

Drew Farris, director of Analytics and AI Research at Booz Allen Hamilton, said: “At Booz Allen, we seek to empower people to change the world. We’re using NVIDIA Jetson to train new technical resources as AI becomes critical for enterprises and personnel leveraging AI to solve the most difficult global challenges.”

Christine Nguyen, STEM curriculum director at Boys & Girls Club of Western Pennsylvania, said: “We know how important it is to provide all students with opportunities to impact the future of technology. We’re excited to utilize the NVIDIA Jetson AI Specialist certification materials with our students as they work toward becoming leaders in the fields of AI and robotics.”

Availability

The Jetson Nano 2GB Developer Kit will be available at the end of the month for $59 through NVIDIA’s distribution channels.

About NVIDIA

NVIDIA’s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.

For further information, contact:

David Pinto

PR Manager

NVIDIA Corporation

+1-408-566-6950

dpinto@nvidia.com

Certain statements in this press release including, but not limited to, statements as to: the benefits, impact and availability of the Jetson Nano 2GB Developer Kit; today’s students and engineers interacting with and imparting AI to robots in the near future; Jetson being designed to work in any deployment; and NVIDIA’s Jetson driving the biggest revolution in industrial AIoT are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

© 2020 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, CUDA-X, JetPack, Jetson and Jetson Nano are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability, and specifications are subject to change without notice.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/551913ed-d603-4ff5-850e-df679bb3f4a2

AI in Manufacturing Market: Rockwell Automation Launching New AI module to Create Substantial …

According to Fortune Business Insights, its latest report, titled “Artificial Intelligence (AI) in Manufacturing Market Size, Share & COVID-19 Impact …

Pune, Oct. 05, 2020 (GLOBE NEWSWIRE) — The global AI in manufacturing market size is expected to rise owing to the increasing demand for collaborative robots and the growing semiconductor industry. According to Fortune Business Insights, its latest report, titled “Artificial Intelligence (AI) in Manufacturing Market Size, Share & COVID-19 Impact Analysis, By Offering (Hardware, Software, and Services), By Technology (Computer Vision, Machine Learning, Natural Language Processing, and Context Awareness), By Application (Process Control, Production Planning, Predictive Maintenance & Machinery Inspection, Logistics and Inventory Management, Quality Management, and Others), By Industry (Automotive, Medical Devices, Semiconductor &Electronics, Energy & Power, Heavy Metal & Machine Manufacturing, and Others), and Regional Forecast, 2020-2027.”, observes that the market will hit USD 9.89 Billion by 2027 while exhibiting a promising 24.2% CAGR between 2020 and 2027. This market is expected to witness substantial growth owing to the COVID-19 impact and hence the 2020-2027 CAGR is high/very high, as a large section of the industry would look to adopt AI in order to automate the operation with less human intervention.

The emergence of COVID-19 has brought the world to a standstill. We understand that this health crisis has brought an unprecedented impact on businesses across industries. However, this too shall pass. Rising support from governments and several companies can help in the fight against this highly contagious disease. There are some industries that are struggling and some are thriving. Overall, almost every sector is anticipated to be impacted by the pandemic.

We are taking continuous efforts to help your business sustain and grow during COVID-19 pandemics. Based on our experience and expertise, we will offer you an impact analysis of coronavirus outbreak across industries to help you prepare for the future.

Click here to get the short-term and long-term impact of COVID-19 on the AI in manufacturing Market.



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Artificial intelligence (AI) is believed to be a game-changing modern technology for the manufacturing industry. Adoption of AI in manufacturing provides multi-faceted benefits such as accurate and rapid data-driven decisions, minimizing of operational costs, optimizing several processes, and improving the overall experience of customer-satisfaction. In addition to this, AI can be easily embedded to the existing products and services offered by the companies to render them reliable, effective, and safe. For instance, in the automotive industry, AI-based technology such as computer vision is used to accurately detect obstructions to prevent road fatalities, while promoting safe driving.



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What does the Market Report Offer?

The market report offers an exhaustive study of several factors such as drivers, restraints, challenges, and opportunities that will affect the growth of the market in the forthcoming years. The report covers regional demographics that include qualitative and quantitative information about the regions that are further divided into nations that are contributing to the growth of the market between 2019 and 2026. Furthermore, the competitive landscape has been discussed in-depth that include information of several players operating in the market. Moreover, information on the adoption of strategies such as merger and acquisition, collaboration, partnerships, and joint ventures by the companies that will drive the growth of the market has been included during the projected horizon.

Drivers and Restraints:

Increasing Adoption of Cobots to Promote Growth

Emergence of automation and robotics has propelled the rise of collaborative robots (Cobots) across several manufacturing industries. Cobots are perceived as an essential addition to implement several industrial operations such as detecting failure scenarios, analyzing the result, and further taking appropriate action to resolve the issues. Increasing adoption of Cobots by the manufacturers is anticipated to drive the growth of the AI in manufacturing market during the forecast period. For instance, MVI Maskinfabrik, a Danish kitchen utility manufacturer, invested in Cobot to cater to the increasing demand for its several products. According to the company, the investment proved to be the right decision as it reduced 50% time required in the wielding process of its products. Furthermore, the total cost procured to buy Cobot was far more less than a wielding machine.



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Regional Analysis:

Increasing Investment for AI-based Platform in Asia-Pacific to Drive the Market

Among the regions, the market in Asia-Pacific that hit USD O.68 Billion in 2019 is expected to hold the highest global AI in manufacturing market revenue during the projected horizon. This is ascribable to factors such as increasing investment for AI-based platforms in countries such as India, China, and Japan in the region.

The market in Europe is expected to be the second-most leading region in the forthcoming years. Countries such as the UK investing a huge sum of about USD 1.3 Billion in developing AI technology will drive the market growth in the region. North America, on the other hand, will witness significant growth owing to increasing investment in R&D activities and growing number of startups for AI technology between 2020 and 2027.



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Competitive Landscape:

Rockwell Automation Introducing New AI Module to Augur Growth

In April 2019, Rockwell Automation, Inc. announced its launch of a new AI module, FactoryTalk Analytics LogixAI to enhance industrial production. The new AI module efficiently predicts analysis for precise decision making without interference from the data scientists. In addition to this, the module detects data anomalies, while alerting the workers to attain precise results. Major focus of the companies to provide AI-based solutions to strengthen market position will bode well for the growth of the market in the forthcoming years. Furthermore, amid the global pandemic, COVID-19, adoption of AI technology by the manufacturers will contribute to the market growth during the projected horizon.

List of Key Companies Profiled in AI in Manufacturing Market:

    • Microsoft Corporation (United States)
    • Google LLC (United States)
    • IBM Corporation (United States)
    • Amazon.com Inc. (United States)
    • NVIDIA Corporation (United States)
    • Siemens AG (Germany)
    • GENERAL ELECTRIC (United States)
    • SAP SE (Germany)
    • Rockwell Automation, Inc. (United States)
    • Mitsubishi Electric Corporation (Japan)



Detailed Table of Content

  • Introduction
    • Definition, By Segment
    • Research Approach
    • Sources
  • Executive Summary
  • Market Dynamics
    • Drivers, Restraints and Opportunities
    • Emerging Trends
  • Key Insights
    • Macro and Micro Economic Indicators
    • Consolidated SWOT Analysis of Key Players
    • Porter’s Five Forces Analysis
  • Global AI in Manufacturing Market Analysis, Insights and Forecast, 2016-2027
    • Key Findings / Summary
    • Market Size Estimates and Forecasts
      • By Offering
        • Hardware
        • Software
        • Services
      • By Technology (Value)
        • Computer Vision
        • Machine Learning
        • Natural Language Processing
        • Context Awareness
      • By Application (Value)
        • Process Control
        • Production Planning
        • Predictive Maintenance & Machinery Inspection
        • Logistics and Inventory Management
        • Quality Management
        • Others
      • By Industry (Value)
        • Automotive
        • Medical Devices
        • Semiconductor & Electronics
        • Energy & Power
        • Heavy Metal & Machine Manufacturing
        • Others (Aerospace & Defense, Conglomerates, etc.,)
      • By Geography (Value)
        • North America
        • Europe
        • Asia Pacific
        • Middle East and Africa
        • Latin America

TOC Continued…!!!



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White House acknowledges Trump’s condition had been worse than revealed

As a legacy tech giant, Big Blue has struggled over the years to shed its … Palantir Technologies Inc.’s direct listing had everything –- and left some …

InvestorPlace

7 Artificial Intelligence Stocks to Buy for October

With so much death and economic destruction wrought by the novel coronavirus, it’s hard to find the silver lining. But if there is one on Wall Street, it’s the rise of artificial intelligence stocks. Yes, there is the profitability angle from machine learning and other relevant technology facilitates. But this crisis has been a crash course in the sector’s viability.

Hopefully, we won’t suffer a second wave like many European countries are experiencing because, you know, people can just get over themselves and wear a flipping mask in public. But even if we do succumb to a second round, eventually, this too shall pass. However, the return to some sense of normalcy will likely take time. Thus, we may depend on contactless platforms. Of course, this international emergency has provided an excellent arena for finetuning.

As well, it’s becoming clear that the scale and acceleration of our globalized economy is more than human brains can handle. Yes, we are the ultimate innovative species (as far as I know). However, machines can now play a major role in alleviating most if not one day all of our menial tasks. That frees us up for greater and more meaningful innovations, which is the underlying ethos of artificial intelligence stocks.InvestorPlace – Stock Market News, Stock Advice & Trading Tips

This isn’t just techno-babble gibberish. For instance, the food supply chain was put under enormous stress during the peak of Covid-19. Well before the pandemic, many retailers partnered with AI programmers to develop enhanced forecasting and planning infrastructure. Now, this need has accelerated due to the baptism of fire. Therefore, these diverse artificial intelligence stocks could enjoy upside throughout this year and beyond.

Apple (NASDAQ:AAPL)

Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL)

IBM (NYSE:IBM)

Nvidia (NASDAQ:NVDA)

Tencent (OTCMKTS:TCEHY)

Match Group (NASDAQ:MTCH)

Trade Desk (NASDAQ:TTD)

The 7 Top Robinhood Stocks for October

Finally, not everything about AI has to be so serious. Since we’re conducting our business and personal affairs increasingly online, almost anything that we can think of, including love and dating, can benefit from the integration of man and machine. Since this dynamic is well under way, here are the seven artificial intelligence stocks from which you can profit.

Apple (AAPL)

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As the manufacturer of the now-iconic iPhone, Apple is more well known as a consumer electronics behemoth rather than an investment into artificial intelligence stocks. Certainly, the company can bank simply on the power of its globally recognized brand. However, what makes AAPL stock special is that management refuses to be satisfied with its prior accomplishments.

As evidence, consider Apple’s foray into electric vehicles. At one point, rumors circulated that hundreds of people were developing a car, one that could possibly compete with Tesla (NASDAQ:TSLA). Nowadays, it appears that the consumer tech firm is focusing on developing software for self-driving cars. If that’s the case, such a course would require significant innovations in AI, particularly machine learning.

Theoretically, Apple has a lot of practice in this arena thanks to its wealth of consumer data. In addition, the company has forged consumer friendly applications, such as palm rejection technology. This nifty development allows the iPad to recognize the difference between a deliberate input with the Apple Pencil versus accidental contact with a part of the hand.

Undoubtedly, most investors will buy AAPL stock for its ever-popular smart devices. However, those who are interested in artificial intelligence stocks should also give it serious consideration.

Alphabet (GOOG, GOOGL)

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Whenever anyone talks about artificial intelligence stocks, Alphabet is one of the top names that’s mentioned and for good reason. Essentially, Alphabet’s Google owns the internet. As of July 2020, Google dominated desktop search engines with an 87% global market share. With figures like that, you’re bound to have a wealth of consumer data that other organizations can only dream about.

And with search dominance comes its web advertisement-driven revenue channels. Corporations spend billions buying up Google ads because that’s where the people are. In turn, Alphabet has gotten quite adept at utilizing its AI infrastructure to fine-tune what consumers want and just as importantly, when they want it. Additionally, thanks to its YouTube platform, Alphabet has years of valuable experience understanding and predicting consumer behavior.

Therefore, while GOOGL stock is often the target of social and political criticism, I don’t see the internet giant going anywhere but up over a long-term horizon.

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Plus, what really makes Alphabet stand out is its penchant for relevant acquisitions. For example, its DeepMind subsidiary specializes in traffic prediction algorithms. That’s not just important for everyday convenience but also as a framework for smart city infrastructures. Therefore, if you want more AI in your portfolio, go get some GOOGL stock.

IBM (IBM)

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Although artificial intelligence stocks represent one of the hottest segments on Wall Street, individual names tend to be well-known entities. As such, they’re not exactly what you would call undervalued as they typically have already garnered much investor sentiment.

Well, IBM doesn’t have that problem. As a legacy tech giant, Big Blue has struggled over the years to shed its image of yesteryear innovations. Instead, management has pivoted to many relevant markets, including cloud computing and cybersecurity. However, IBM stock is frustrating, even in this year where it’s down 10% while other tech firms are up big.

Nevertheless, if you want to go against the grain with your artificial intelligence stocks, IBM offers the patient investor potentially significant upside. As you know, with its AI platform Watson, Big Blue has been helping multiple enterprises and industries maximize their efficiency. One particular area that I’m intrigued in is healthcare.

With the novel coronavirus having disrupted this sector, there’s never been a more critical time for improved efficiencies. Here, IBM could make a conspicuously positive impact, reducing administrative friction so that medical professionals can spend less time on paperwork and more time helping patients. Having learned tough lessons from the new normal, the pandemic could help IBM stock regain its footing.

Nvidia (NVDA)

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When you hear the brand Nvidia, most likely what comes to mind first is video games. And that’s not a bad thing, believe me. Before the pandemic, video games, especially the rise of eSports, helped drive the bullish case for NVDA stock. During the lockdowns and the new normal, this entertainment platform helped while away the hours when other options were off the table.

Despite its dominance in gaming, Nvidia would like to let you know that it’s one of the leaders in artificial intelligence stocks as well. The company’s partnership with Walmart (NYSE:WMT) illustrates this relationship perfectly. As a big-box retailer, Walmart must make critical decisions all the time about their inventory: how much to buy, when to ship them out and to which stores, among countless other concerns.

Fortunately, Walmart has advanced data analytics software that references back decades of data for hundreds of millions of products. But all that data processing requires sophisticated hardware – otherwise, you’re not going anywhere. That’s where Nvidia comes in with its graphics processors. Sure, they’re best known for their gaming applications, but they can do so much more.

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Not surprisingly, NVDA stock has significant links to other burgeoning industries, such as self-driving technologies and the blockchain. Therefore, you’ll want to keep this on your short list of artificial intelligence stocks to buy.

Tencent (TCEHY)

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Taking aside the politics, if you want to broaden your portfolio of artificial intelligence stocks, you should look at China. Companies like Tencent really are in an enviable position. For one, Tencent’s home market has blossomed into a technological powerhouse. Second, China’s massive population means ample room for growth, increased connectivity and the biggest data goldmine.

Further, Tencent has wide-reaching ambitions regarding its AI initiatives. As an internet content and social media network provider, the company is finetuning personalized advertisements and suggestions for its millions of users. In addition, Tencent is pursuing more serious endeavors, such as medical AI applications. Here, the idea is to use technology to help physicians detect and prevent the spread of disease.

With the coronavirus having originated from China – as President Trump reminds us every day – this application seems very relevant for TCEHY stock.

Of course, nothing can be divorced from politics these days and so it is with Tencent. As the owner of WeChat, the messaging/payments app has come under fire from the Trump administration. And that might mean TCEHY stock is on shaky ground, at least until we figure out who will run our nation on Nov. 3. Still, the opportunity for upside is tantalizing because of the aforementioned attributes of the home market.

Match Group (MTCH)

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Invariably, analyses of artificial intelligence stocks typically involve high-scale solutions. Over this list, we’ve covered the impact that AI can have on our purchasing decisions, interactions with machines, forecasting inventory demand and improving health outcomes. But AI doesn’t have to be so serious. Instead, it can help with that age-old longing for love.

That’s right, for those of who want to give Cupid an assist, online dating apps, such as those under the Match Group umbrella, may help accelerate your search for a soulmate. But what if Cupid needs help too? Increasingly, the mythical god has turned to artificial intelligence to help provide appropriate matchups.

In a way, this is the probably the most ingenious use of AI. By now, many of these dating sites and apps have collected an enormous amount of behavioral data. That’s also due to the stigma of online dating fading away. Plus, with the novel coronavirus disrupting offline dating, Match is one of the viable places to go. That right there is a great reason to consider MTCH stock.

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Better yet, Match is wising up to the power of AI to promote a safe dating environment. The company invested in Noonlight to provide safety features such as location tracking in case a meetup goes awry. That’s smart thinking, which should separate MTCH stock from other social networking investments.

Trade Desk (TTD)

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Well before the pandemic, the cord-cutting phenomenon was placing increased pressure on traditional cable TV providers. With the advent of connected TV and streaming services, these innovations sparked never-before-seen capabilities, such as on-demand viewing. Instead of people revolving their lives around content scheduling (as in linear TV), the new generation of entertainment adapted to the individual.

Following the coronavirus impact, the pressure to cut the cord intensified for many households. This was especially true during the early days of the crisis, when new content offerings were thin but the bills kept piling up. But pandemic or not, streaming and connected TV is here to stay. And that makes Trade Desk a relevant idea among artificial intelligence stocks.

Primarily, the company utilizes AI algorithms to maximize advertisers return for their connected TV dollars. That’s much easier now because Trade Desk has access to a wealth of viewership data. As a result, it’s able to pinpoint which advertising strategies will work best, bolstering the narrative for TTD stock.

Further, with live sports returning, Trade Desk may have an opportunity to evangelize its services. Because of the added cord-cutting pressures, the live sports streaming audience has probably increased significantly. That plays into the hands of TTD stock, where the underlying company can help advertisers plan for the possibility of games that go into overtime, which will likely feature a substantial uptick in engaged viewers.

On the date of publication, Josh Enomoto did not have (either directly or indirectly) any positions in the securities mentioned in this article.

A former senior business analyst for Sony Electronics, Josh Enomoto has helped broker major contracts with Fortune Global 500 companies. Over the past several years, he has delivered unique, critical insights for the investment markets, as well as various other industries including legal, construction management, and healthcare.

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