6 items tagged "trends "

  • 4 Trends That Are Driving Business Intelligence Demands

    IM Photo business intelligence fourMany organizations have sung the praises of business intelligence for years, but many of those firms were not actually realizing the full benefits of it. That picture is beginning to change, as advanced analytics tools and techniques mature.

    The result is that 2016 will definitely be the ‘year of action’ that many research firms have predicted when it comes to data analytics. That, at least, is the view of Shawn Rogers, chief research officer at Dell Statistica, who believes “we are at a tipping point with advanced analytics.”

    If Rogers sounds familiar, it may be due to his early connection to Information Management. Rogers was, in fact, the founder of Information Management when it was originally called DM Review Magazine. He is now in his second year as chief research officer for Dell Statistica. “Prior to that I was an industry analyst. I worked for Enterprise Management Associates and I covered the business intelligence, data warehousing and big data space.”

    Rogers believes there are a number of key trends driving business intelligence today that are making it more useful for a greater number of organizations.

    “The maturity in the market has helped everyone evolve to a much more agile and flexible approach to advanced analytics. I think there are four things that are driving that which make it exciting,” Rogers says.

    “One of them is the new sophistication of users,” Rogers notes “Users have become very comfortable with business intelligence. They want advanced insights into their business so they’re starting to look at advanced analytics as that next level of sophistication.”

    “They’re certainly not afraid of it. They want it to be more consumable. They want it to be easier to get to. And they want it to move as fast as they are. The users are certainly making a change in the market,” Rogers says.

    The market is also benefitting from new technologies that are enhancing the capabilities of advanced analytics.

    “It now functions in a way that the enterprise functions,” Rogers explains. “Now the technology allows advanced analytics on all of the data within your environment to work pretty much at the speed of the business.”

    Certainly not insignificant is the economic advantage of more competition from data analytics tool vendors.

    “There are all kinds of solutions out there that are less money. It has opened the door for a much wider group of companies to leverage the data in their enterprise and to leverage advanced analytics,” Rogers observes.

    “Lastly, the data is creating some fun pressure and opportunities. You have all these new data sources like social and things of that nature. But even more importantly we’re able to incorporate all of our data into our analysis,” Rogers says.

    “I know that when I was in the press and as an analyst I use to write a lot about the 80/20 rule of data in the enterprise – the 20 percent we could use and the 80 percent that was too difficult. Now with all these new technologies and their cost benefits we’re not ignoring this data. So we’re able to bring in what use to look like expensive and difficult to manage information, and we’re merging it with more traditional analytics.”

    “If you look at more sophisticated users, and economic advantage, and better technology, and new data, everything is changing,” Rogers says. “I think those four pieces are what are enabling advanced analytics to find a more critical home in the enterprise.”

    Finally, the other key trend driving the need for speed when it comes to analytics and business intelligence return on investment is where those investments are coming from. Increasingly they are not from IT, Rogers stresses.

    “I think there has been a big shift and most of the budgets now seem to be coming from the line of business – sales, marketing, finance, customer service. These are places where we’re seeing budgets fly with data-driven innovation,” Rogers says.

    “When you shift away from the technology side of innovation and move toward the business side, there is always that instant demand for action. I think that saturation of big data solutions, the saturation of analytics tools, and a shift from IT to the business stakeholder standpoint is creating the demand for action over just collecting data,” Rogers concludes.

    Source: Information Management

  • Business Intelligence Trends for 2017

    businessintelligence 5829945be5abcAnalyst and consulting firm, Business Application Research Centre (BARC), has come out with the top BI trends based on a survey carried out on 2800 BI professionals. Compared to last year, there were no significant changes in the ranking of the importance of BI trends, indicating that no major market shifts or disruptions are expected to impact this sector.
     
    With the growing advancement and disruptions in IT, the eight meta trends that influence and affect the strategies, investments and operations of enterprises, worldwide, are Digitalization, Consumerization, Agility, Security, Analytics, Cloud, Mobile and Artificial Intelligence. All these meta trends are major drivers for the growing demand for data management, business intelligence and analytics (BI). Their growth would also specify the trend for this industry.The top three trends out of 21 trends for 2017 were:
    • Data discovery and visualization,
    • Self-service BI and
    • Data quality and master data management
    • Data labs and data science, cloud BI and data as a product were the least important trends for 2017.
    Data discovery and visualization, along with predictive analytics, are some of the most desired BI functions that users want in a self-service mode. But the report suggested that organizations should also have an underlying tool and data governance framework to ensure control over data.
     
    In 2016, BI was majorly used in the finance department followed by management and sales and there was a very slight variation in their usage rates in that last 3 years. But, there was a surge in BI usage in production and operations departments which grew from 20% in 2008 to 53% in 2016.
     
    "While BI has always been strong in sales and finance, production and operations departments have traditionally been more cautious about adopting it,” says Carsten Bange, CEO of BARC. “But with the general trend for using data to support decision-making, this has all changed. Technology for areas such as event processing and real-time data integration and visualization has become more widely available in recent years. Also, the wave of big data from the Internet of Things and the Industrial Internet has increased awareness and demand for analytics, and will likely continue to drive further BI usage in production and operations."
     
    Customer analysis was the #1 investment area for new BI projects with 40% respondents investing their BI budgets on customer behavior analysis and 32% on developing a unified view of customers.
    • “With areas such as accounting and finance more or less under control, companies are moving to other areas of the enterprise, in particular to gain a better understanding of customer, market and competitive dynamics,” said Carsten Bange.
    • Many BI trends in the past, have become critical BI components in the present.
    • Many organizations were also considering trends like collaboration and sensor data analysis as critical BI components. About 20% respondents were already using BI trends like collaboration and spatial/location analysis.
    • About 12% were using cloud BI and more were planning to employ it in the future. IBM's Watson and Salesforce's Einstein are gearing to meet this growth.
    • Only 10% of the respondents used social media analysis.
    • Sensor data analysis is also growing driven by the huge volumes of data generated by the millions of IoT devices being used by telecom, utilities and transportation industries. According to the survey, in 2017, the transport and telecoms industries would lead the leveraging of sensor data.
    The biggest new investments in BI are planned in the manufacturing and utilities industries in 2017.
     
    Source: readitquick.com, November 14, 2016
  • Internet of things (IoT) trends and realities: what to expect in 2017

    wat is iot of internet of things showcase 1472198180As part of our agenda of looking at the impact of technology and innovation on economic growth and development, we’ve written about the internet if things (IoT) for several years. In January 2013, we said:

    “‘Internet of things’ will have a huge impact on how businesses look at their business operations, efficiency and productivity – in the next few years it could actually help restore confidence after the global economic crisis, providing a leap forward in global productivity. Combine this with the need to interpret the huge number of data points that will be generated – the so-called ‘big-data – and automated business intelligence and reporting systems also become increasingly important. The next wave of innovation will therefore come around the internet of things, big data and business intelligence.”

    Fast forward to 2017, writing in the World Economic Forum blog, Dominic Gorecky and Detlef Zühlke of the German Research Centre for Artificial Intelligence (DFKI) say the internet of things (IoT) is already starting to affect environments of all kinds – homes, cities, travel, logistics, retail and medicine, to name just a few – and it will not stop at our factory gates, either.

    According to a recent estimation by McKinsey, the potential economic impact of IoT applications in 2025 is between US$ 3.9 and $11.1 trillion, of which $1.2 to $3.7 trillion is allotted to IoT applications within the factory environment. Also known as smart manufacturing, or Industrie 4.0 in Germany, these are fully networked manufacturing ecosystems driven by the IoT.

    Gorecky and Zühlke add that in smart manufacturing, where all ‘factory objects’ will be integrated into networks, traditional control hierarchy will be replaced by a decentralized self-organization of products, field devices and machines. Production processes have to become so flexible that even the smallest lot size can be produced cost-effectively and just in time to the customer’s individual demands. Customers are driving this development too, as they can design and order products at the click of a mouse. They can also expect products to be delivered within a few days – or even hours – and don’t want to wait weeks for goods to travel from far regions of the world where labor costs are lower.

    Despite this huge potential, the introduction of IoT technologies in the rather traditional domain of manufacturing will not happen abruptly: investment cycles are long, and robustness of processes and technologies outweigh the striving for innovation. Too many questions have to be answered first.

    As IoT technologies penetrate ever more deeply into our factories, down to the smallest piece of equipment, technology providers and factory planners must find solutions to four main problems:

    • How to assure the interoperability of systems
    • How to guarantee real-time control and predictability, when thousands of devices communicate at the same time
    • How to prevent disruptors, or competitors, taking control of highly networked production systems
    • How to determine the benefit or return on investment in IoT technologies.

    To compensate for technological uncertainty and financial risks, adequate pilot environments are needed. Here, smart manufacturing technologies and strategies can be implemented, evaluated and showcased for the first time. Smart manufacturing is a network paradigm affecting wide-ranging areas from automation to IT, from digital planning of a product to its recycling, and from smart sensors to business applications.

    There is no single-solution provider that can cover all of these aspects at once. So, for holistic solutions to emerge, there has to be a network of technology providers joining forces and competences to develop compatible solution blocks that fit the future requirements of technology users.

    As a result of all of this in a broader context beyond just manufacturing, Mike Krell, an analyst at Moor Insights & Strategy, says that 2017 will be another year of growth for the IoT — and potentially some contraction. IoT is still in its infancy in terms of dollars and deployments, and that can’t last much longer, before market frustration sets in. He says 2017 must become the year where the focus on real deployment and monetization of IoT systems, including both software and hardware.

    2017 will also be a year of contraction. There are way too many ‘platform’ and hardware providers trying to gain traction in the market. Small platform providers will either disappear or get swallowed up by ‘bigger fish’, and 2017 is likely to end with many fewer players than today. Hardware will continue to expand, but companies that only provide single or very narrow solutions will get swallowed up or disappear altogether, depending on the quality and security of their products.

    Writing in Forbes magazine, he says these are key things to watch for 2017 in IoT:

    • IoT semiconductor and sensor volumes will skyrocket. 2016 was a year of consolidation for IoT semiconductor makers. There was Broadcom and Avago (and then Broadcom jettisoning their IoT business to Cypress) and then Qualcomm swallowing up NXP (and the former Freescale in the process). Krells says that NXP is one of the best positioned IoT semi vendors, and if a deal with Qualcomm is completed, the combined company has the breadth of technologies and capacity to dominate the IoT market. ARM cores will continue to dominate IoT, and sensor manufacturers will continue to see volumes rise. He adds that 2017 may see more consolidation –Silicon Labs could grow bigger or be gobbled up.
    • The IoT platform shakeout will begin. The year started with lots of noise from new vendors with a definite slowing as 2016 came to a close. There are just too many vendors trying to push undifferentiated solutions.
    • Changes in ‘edge’ or ‘fog’ architectures will become critical to implement. The edge or the fog is the part of the network between the devices (where the data originates) and the cloud. Traditionally this had been a simple aggregation point or gateway, but that just won’t cut it for IoT. The massive amount of data generated by IoT devices will put strains on the network, requiring edge devices to get much smarter. Mainstream vendors such as Cisco Systems, Dell EMC and Hewlett Packard Enterprise recognize this and are pushing smarter IoT edge devices. These devices are, in simple terms, a combination of a server and gateway. With the increase in computation, storage and networking capabilities edge-based analytics will become a critical element in the success of IoT.
    • Telco and communication choices will continue to be messy. Telecom operators’ strategies and business models for generating revenues from IoT will continue to develop through 2017—and won’t be set by this time next year. For telcos, the battle will continue between NB-IoT and LTE-M based on region and monetization models through 2017. Infrastructure providers such as Ericsson and Huawei will increase in importance, with strong portfolios of IoT hardware and software solutions. Alternative LPWAN (lo power wide area network) technologies will become increasingly strong in niches where the bandwidth, capacity and security of 3GPP standards aren’t necessary (or cost affective). These include LoRa, Ingenu and Sigfox.
    • Regulation and standardization continue to come into focus but will evolve continuously. 2016 brought us a little closer to standards interoperability with the merger of OIC and the Allseen Alliance into the Open Connectivity Foundation. Other collaborations including ZigBee, Thread Group and Z-wave continue to move the market toward more cohesive and simpler solutions. However, there will still be a great amount of fragmentation and no clear-cut winners. Apple HomeKit and Google Weave will play a role, but how this fleshes out is anyone’s guess going into and coming out of 2017. On the regulatory front, expect to see more government interest in 2017, as IoT becomes more pervasive in smart cities, the public sector and energy.
    • Security gets its due. Security was finally taken seriously in 2016, largely because of real IoT hacks. The big denial-of-service attack in October, and the potential of a drone injecting a malicious virus via lights (from outside a building), caused great concern throughout the industry. With all the new vulnerable devices now being put into service, 2017 will see hackers continue to exploit IoT systems. Expect large scale breaches, as hackers look for newly connected devices in the energy and transportation areas.
    • Smart cities will lead the charge in IoT deployments. The awareness of what ‘smart city’ means has begun to come to the attention of residents. They value safety (smart lighting), convenience (transportation, parking) and potential cost savings (smart meters, on-demand trash pickup), and cities can deliver. Cities will continue to be strained by the need for money to support the deployment of sensors (to gather data) and the integration of citywide systems.
    • Smart home technology will become, smarter, more secure and easier to use. Amazon Echo and Google Home made great strides in 2016, both becoming more mainstream appliances in the home. However, networking bandwidth and connectivity between devices and systems is still a major problem for consumers. Networking continues to be painful. Streaming video rules the home entertainment market, and the need for increased bandwidth has put strains on home network bandwidth. Expect new announcements on mesh or mesh-like products with simpler network management in 2017. There continue to be too many applications and too many technologies to choose from to make it all work together seamlessly. Hopefully there will be some real advancements in interconnection in 2017.

    Source: thenextsiliconvalley.com, January 8, 2016

  • The BI trends your business cannot neglect in the near future

    The BI trends your business cannot neglect in the near future

    According to the World Economic Forum’s Future of Jobs Report, the top five trends set to positively impact business growth through 2022 are (1) the increasing adoption of new technology, (2) the increasing availability of big data, (3) advances in mobile internet, (4) advances in AI, and (5) advances in cloud technology.

    This nexus of these and other trends, and their accelerated innovation and development (as an example, think of how fast we’ve gone from rotary phones to smartphones, to the dematerialization of other devices onto smartphones, and now to 5G), raises the imperative for organizations to focus their next-decade vision and investment strategy now.

    Consider these 2020 and beyond assertions for enterprise analytics and mobility from Ventana Research:

    • By 2020, analysis of streams of IoT event data will be a standard component of nearly all big data deployments.
    • By 2021, two-thirds of analytics processes will no longer simply discover what happened and why, they will also prescribe what should be done.
    • By 2022, one-half of organizations will re-examine the use of mobile devices and conclude the technology being used does not adequately address the needs of their workers, leading them to examine a new generation of mobile apps.

    And that’s just a start. In '10 Enterprise Analytics Trends to Watch in 2019', Ventana Research CEO Mark Smith notes that in addition to 5G, enterprise organizations’ mobility strategies must absolutely address accelerating technologies and capabilities, such as:

    • Device proximity features that can provide environmental context and suggest where to take action based on location.
    • Gestures and camera-based input that make it even easier and faster to engage with business applications.
    • Biometrics, from facial recognition to fingerprints, that enable significantly better device, data, and enterprise security.
    • High-quality device cameras that make it easy to capture, share, and use photos and videos and their data within business processes.
    • Augmented reality (AR) that enables the use of a mobile device’s camera to digitally interpose virtual objects to enhance work experiences.
    • Speech recognition and voice assistants on mobile devices that make it simpler for users to access information and act quickly.

    The future is here. Is your organization ready to take advantage of the accelerated innovation around enterprise analytics and mobility?

    Source: MicroStrategy

  • The most important BI trends for 2020

    The most important Business Intelligence trends for 2020

    Companies are in the midst of many profound changes: The amount of data available and the speed of producing new data has been increasing rapidly for years, and business models as well as process improvements increasingly rely on data and analytics.

    Against this backdrop, a key challenge is emerging: the efficient and, at the same time, innovative use of data is only possible when capabilities for, and the operationalization of, both analytics and data management are ensured. Many companies are already reaching their limits with a ‘the more data the better‘ approach and cannot fully leverage the benefits they expect due to a lack of data quality or analytical skills.

    In addition, there has been an increased focus on data protection since the GDPR came into effect in 2018. Amid a huge flood of information, companies will have to find ways to handle data in a way that not only complies with legal requirements, but also helps to improve processes and make day-to-day business easier.

    This year we asked 2,865 users, consultants and vendors for their views on the most important BI trends. The BARC BI Trend Monitor 2020 illustrates which trends are currently regarded as important in addressing these challenges by a broad group of BI and analytics professionals. Their responses provide a comprehensive picture of regional, company and industry specific differences and offer up-to-the-minute insights into developments in the BI market and the future of BI. Our long-term comparisons also show how trends in business intelligence have developed, making it possible to separate hype from stable trends.

    BARC’s BI Trend Monitor 2020 reflects on the business intelligence and data management trends currently driving the BI market from a user perspective.

    Importance of Business Intelligence trends in 2020 (n=2,865)

    1. MD/MQ management. Importance (1-10 scale): 7.3
    2. Data discovery/visualization. Importance (1-10 scale): 6.9
    3. Establishing data-driven culture. Importance (1-10 scale): 6.9
    4. Data governance. Importance (1-10 scale): 6.8
    5. Self service BI. Importance (1-10 scale): 6.5
    6. Data prep. business users. Importance (1-10 scale): 6.3
    7. Data warehouse modernization. Importance (1-10 scale): 5.9 
    8. Agile BI development. Importance (1-10 scale): 5.8
    9. Real-time analytics. Importance (1-10 scale): 5.6
    10. Advanced analytics/ML/AI. Importance (1-10 scale): 5.5
    11. Big data analytics. Importance (1-10 scale): 5.5
    12. Integrated platforms BI/PM. Importance (1-10 scale): 5.2
    13. Embedded BI and analytics. Importance (1-10 scale): 5.1
    14. Data storytelling. Importance (1-10 scale): 5.1
    15. Mobile BI. Importance (1-10 scale): 5.1
    16. Analytics teams/data labs. Importance (1-10 scale): 5.0
    17. Using external/open data. Importance (1-10 scale): 4.9
    18. Cloud for data and analytics. Importance (1-10 scale): 4.9
    19. Data catalogs. Importance (1-10 scale): 4.2
    20. Process mining. Importance (1-10 scale): 4.1

    The most (and least) important BI trends in 2020

    We asked users, consultants and software vendors of BI and data management technology to give their personal rating of the importance of twenty trending topics that we presented to them.

    Data quality/master data management, data discovery/visualization and data-driven culture are the three topics BI practitioners identify as the most important trends in their work.

    At the other end of the spectrum, cloud for BI and analytics, data catalogs and process mining were voted as the least important of the twenty trends covered in BARC’s survey.

    What do these results tell us?

    While the two most important trends remained the same as last year with master data and data quality management in first position and data discovery in second, third spot is now occupied by establishing a data-driven culture. This trend, which was newly introduced last year and went straight into fifth place in the rankings, is seen as even more important this year. Self-service BI, on the other hand, went down to fifth place this year whereas data governance remains in fourth.

    All in all, these five top trends represent the foundation for organizations to manage their own data and make use of it. Furthermore, it demonstrates that organizations are aware of the relevance of high quality data and its effective use. These trends stand for underlying structures being changed: Organizations want to go beyond the collection of as much data as possible and actively use data to improve their business decisions. This is also supported by data warehouse modernization, which is once again in seventh place this year.

    Some trends have slightly increased in importance since last year (e.g., real-time analytics an integrated platforms for BI and PM). However, they all climbed just one rank with the exception of establishing a data-driven culture, which jumped two places. Therefore, no huge shift can be observed in terms of upward trends.

    The opposite is the case for downward trends: Mobile BI fell from twelfth to fifteenth place this year, continuing its downward trend that started in 2017. It seems as if the mobile application of BI functions is not seen as important anymore, either because it is available now or because requirements have shifted. Advanced analytics/machine learning/AI is ranked one place lower than last year (down from 9 to 10).

    More important than the difference of one rank however is the tendency behind this slight downward trend: In 2018, many hopes were based on new tools using machine learning and artificial intelligence so this topic might have been expected to rise. However, even if we refer to it as a stagnation in perceived importance rather than a 'real' downward trend, this result is surprising.

    Source: BI-Survey

  • Top artificial intelligence trends for 2020

    Top artificial intelligence trends for 2020

    Top AI trends for 2020 are increased automation to extend traditional RPA, deeper explainable AI with more natural language capacity, and better chips for AI on the edge.

    The AI trends 2020 landscape will be dominated by increasing automation, more explainable AI and natural language capabilities, better AI chips for AI on the edge, and more pairing of human workers with bots and other AI tools.

    AI trends 2020: increased automation

    In 2020, more organizations across many vertical industries will start automating their back-end processes with robotic process automation (RPA), or, if they are already using automation, increase the number of processes to automate.

    RPA is 'one of the areas where we are seeing the greatest amount of growth', said Mark Broome, chief data officer at Project Management Institute (PMI), a global nonprofit professional membership association for the project management profession.

    Citing a PMI report from summer 2019 that compiled survey data from 551 project managers, Broome said that now, some 21% of surveyed organizations have been affected by RPA. About 62% of those organizations expect RPA will have a moderate or high impact over the next few years.

    RPA is an older technology, organizations have used RPA for decades. It's starting to take off now, Broome said, partially because many enterprises are becoming aware of the technology.

    'It takes a long time for technologies to take hold, and it takes a while for people to even get trained on the technology', he said.

    Moreover, RPA is becoming more sophisticated, Broome said. Intelligent RPA or simply intelligent process automation (IPA), RPA infused with machine learning, is becoming popular, with major vendors such as Automation Anywhere and UiPath often touting their intelligent RPA products. With APIs and built-in capabilities, IPA enables users to more quickly and easily scale up their automation use cases or carry out more sophisticated tasks, such as automatically detecting objects on a screen, using technologies like optical character recognition (OCR) and natural language processing (NLP).

    Sheldon Fernandez, CEO of DarwinAI, an AI vendor focused on explainable AI, agreed that RPA platforms are becoming more sophisticated. More enterprises will start using RPA and IPA over the next few years, he said, but it will happen slowly.

    AI trends 2020: push toward explainable AI

    Even as AI and RPA become more sophisticated, there will be a bigger move toward more explainable AI.

    'You will see quite a bit of attention and technical work being done in the area of explainability across a number of verticals', Fernandez said.

    Users can expect two sets of effort behind explainable AI. First, vendors will make AI models more explainable for data scientists and technical users. Eventually, they will make models explainable to business users.

    Likely, technology vendors will move more to address problems of data bias as well, and to maintain more ethical AI practices.

    'As we head into 2020, we're seeing a debate emerge around the ethics and morality of AI that will grow into a highly contested topic in the coming year, as organizations seek new ways to remove bias in AI and establish ethical protocols in AI-driven decision-making', predicted Phani Nagarjuna, chief analytics officer at Sutherland, a process transformation vendor.

    AI trends 2020: natural language

    Furthermore, BI, analytics and AI platforms will likely get more natural language querying capabilities in 2020.

    NLP technology also will continue to evolve, predicted Sid Reddy, chief scientist and senior vice president at virtual assistant vendor Conversica.

    'Human language is complex, with hundreds of thousands of words, as well as constantly changing syntax, semantics and pragmatics and significant ambiguity that make understanding a challenge', Reddy said.

    'As part of the evolution of AI, NLP and deep learning will become very effective partners in processing and understanding language, as well as more clearly understanding its nuance and intent', he continued.

    Among the tech giants involved in AI, AWS for example, revealed Amazon Kendra in November 2019, an AI-driven search tool that will enable enterprise users to automatically index and search their business data. In 2020, enterprises can expect similar tools to be built into applications or sold as stand-alone products.

    More enterprises will deploy chatbots and conversational agents in 2020 as well, as the technology becomes cheaper, easier to deploy and more advanced. Organizations won't fully replace contact center employees with bots, however. Instead, they will pair human employees more effectively with bot workers, using bots to answer easy questions, while routing more difficult ones to their human counterparts.

    'There will be an increased emphasis in 2020 on human-machine collaboration', Fernandez said.

    AI trends 2020: better AI chips and AI at the edge

    To power all the enhanced machine learning and deep learning applications, better hardware is required. In 2020, enterprises can expect hardware that's specific to AI workloads, according to Fernandez.

    In the last few years, a number of vendors, including Intel and Google, released AI-specific chips and tensor processing units (TPUs). That will continue in 2020, as startups begin to enter the hardware space. Founded in 2016, the startup Cerebras, for example, unveiled a giant AI chip that made the news. The chip, the largest ever made, Cerebras claimed, is the size of a dinner plate and designed to power massive AI workloads. The vendor shipped some last year, with more expected to ship this year.

    While Cerebras may have created the largest chip in the world, 2020 will likely introduce smaller pieces of hardware as well, as more companies move to do AI at the edge.

    Max Versace, CEO and co-founder of neural network vendor Neurala, which specializes in AI technology for manufacturers, predicted that in 2020, many manufacturers will move toward the edge, and away from the cloud.

    'With AI and data becoming centralized, manufacturers are forced to pay massive fees to top cloud providers to access data that is keeping systems up and running', he said. 'As a result, new routes to training AI that can be deployed and refined at the edge will become more prevalent'.

    Author: Mark Labbe

    Source: TechTarget

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