Rena is a Director of Custom Research at Current Analysis, specializing in Delivery Management. She is responsible for ensuring the delivery of actionable recommendations and guidance to clients to assist them in formulating their market development and execution strategies. Her expertise is in telecommunications and IT services, including business networking , communications, data center, security, and business continuity services.
• AWS launched three initiatives designed to help customers explore quantum processing as well as develop quantum expertise and identify quantum applications
• Amazon Braket gives users the opportunity to experiment with quantum algorithms; the AWS Center for Quantum Computing promotes collaborative research and development; and the Quantum Solutions Lab will help identify use cases for the technology.
Although quantum computing is still in the early stages, and practical applications for it still need to be developed, there is no doubt that the technology’s impressive processing power holds the potential to have a major impact across vertical industries. It’s only a matter of time before the ability to create and deploy quantum solutions becomes a competitive differentiator, allowing some companies to better leverage the wealth of data they have collected to uncover new insights. But building proficiency in new technologies takes years and can be expensive; however, many experts argue that the time is right to start developing internal quantum expertise. With a technology that is just emerging, how and where should enterprises start?
The ‘democratization of analytics,’ essentially getting analytics tools and insights into the hands of the masses, is the next step forward in a world eager to leverage greater business intelligence.
Tableau is taking on the challenge by providing tools such as Explain Data and Ask Data, which are designed to make it easier for line-of-business users to extract insights from their data visualizations.
There is no doubt that the vast amounts of data being generated today contain a wealth of valuable information. But, unlocking the strategic insights contained within this treasure trove of material remains elusive to many. Sure, data scientists and data programmers have the tools to perform the analysis at their fingertips, but their techniques remain out of reach to many line-of-business users. Extracting insights from data and getting it into the hands of those outside of the IT department is a challenge. The ‘democratization of analytics,’ essentially getting analytics tools and insights into the hands of the masses, is the next step forward in a world eager to leverage greater business intelligence. Continue reading “Tableau Tackles the Challenge of ‘Democratizing Analytics’ by Offering New Tools”→
• Competition in the AI chipset space is heating up; new players are looking to join the fray and they are raising impressive amounts of capital.
• New vendors face stiff competition from tech heavyweights such as Nvidia, hyper-scale cloud providers such as Google and Amazon, and well-funded Chinese organizations.
Just as the market for AI platforms is heating up, so is competition in the AI chipset space. And it isn’t only the large well-established competitors such as Nvidia, Google, and Huawei vying for market share. New players are looking to join the fray as well, and they are raising impressive amounts of capital. Untether, a Toronto-based chip manufacturing start-up, announced in early November that it had raised $20 million in series A funding. The one year old company plans to release a chip designed for AI inference using near-memory design, reducing the distance data must travel, thereby moving data to processors at 2.5 petabits per second, which improves overall processing efficiency. Across the pond, Graphcore, a UK-based organization, has raised a substantial $200 million to develop its Intelligence Processing Units (IPUs), parallel processors designed for machine learning.
Organizations in banking, financial services, and insurance are more likely to prioritize current and future investment in AI than overall survey respondents.
AI-driven solutions can help the sector verify customer identification and assist with fraud detection as well as anti-money laundering and know-your-customer initiatives.
Banking, financial services, and insurance organizations are eager to leverage AI solutions such as chat bots, deep learning, and machine learning. According to GlobalData’s most recent IT Customer Insight survey, organizations in this sector are more likely to be prioritizing investment in AI technology than their counterparts across other vertical industries. As shown below, 63% of respondents in banking, financial services, and insurance currently prioritize investments in AI, compared to only 54% of companies across all vertical markets. Similarly, 64% of financial services, insurance, and banking organizations have prioritized AI for investment in the next two years, versus only 55% of overall survey respondents. Continue reading “Survey Results Indicate Strong Investment in AI by Banking, Financial Services, and Insurance Sectors”→
• Comcast Business is looking to move beyond its small and mid-sized business roots and expand into the large enterprise market.
• As part of its vision to serve large enterprise customers, Comcast is looking towards international expansion and to grow its product portfolio.
On September 4th and 5th, 2019, Comcast Business hosted industry analysts at the newly opened Comcast Technology Center and Four Seasons hotel in Philadelphia. During the conference, Comcast outlined its Enterprise 2.0 strategy that will drive its agenda over the next year, highlighted its plans for leveraging recent acquisitions, and detailed its launch of two new security-related solutions. It plans to build on the success it has already seen in the business market, which includes revenue growth of 10.8% of 2018 (which compared to 2017), a base of 2.3 million business customers, and a team of over 10,000 employees dedicated to business services. Continue reading “Comcast Business Details New Enterprise 2.0 Strategy During Analyst Conference”→
A draft research paper leaked the news that Google had achieved quantum supremacy.
The accomplishment reinforces Google’s position as a thought leader in the realm of high-performance computing.
Last week, a draft research paper appeared and then was immediately removed, apparently leaking the news that Google had achieved quantum supremacy, meaning it had performed calculations that today’s high-speed computers could not accomplish in a reasonable amount of time. Purportedly, Google’s Sycamore quantum processor, utilizing 53-qubits, performed calculations in 200 seconds that would have taken traditional supercomputers over 10,000 years to complete. The power and future potential of such an achievement are awe-inspiring, even if there are no practical applications today. Continue reading “Google Solidifies Position as a Trailblazer in High-Performance Computing with Purported Achievement of Quantum Supremacy”→
• HPE announced plans to acquire MapR, augmenting its data analytics portfolio with proprietary file system technology.
• HPE’s purchase reinforces the message that to derive true value from an artificial intelligence (AI) implementation, enterprises need to master the basics of data management.
Life isn’t always as it seems, and the same can be said of AI. Sure, the sexy parts of AI are the platforms, the algorithms, the APIs, and the use cases. We are enamored with the natural language processing capabilities, the predictive maintenance, the improved decision making, and the ability to provide a more personalized customer experience. But there is also the intrigue. The seedy underbelly of AI is comprised of the ethical concerns that reveal the potential dark sides of the technology. What if models result in unfair bias against a specific gender or race? What about privacy concerns? What if it’s used for destructive rather than constructive purposes? Continue reading “HPE’s Acquisition of MapR Underscores That AI is All About Data”→
• GAiA can be deployed on Google, AWS, or Azure clouds, or in a private cloud, on-premises data center, or in a bare metal environment.
• Customers can go to the GAiA public marketplace and download models developed by Tech Mahindra and others, and retune and retrain them for their own use.
Leveraging artificial intelligence to obtain better insights, make more informed predictions, and improve operations is a top priority for most mid-sized and large organizations. However, the process can be daunting. Developing models is time-consuming and skilled resources are scarce and expensive, leaving many organizations in search of solutions that will help them streamline the process. AI platforms strive to do just that by providing a comprehensive environment for developing, training, testing, sharing, deploying, and managing AI models. Continue reading “Tech Mahindra’s GAiA Platform Provides AI Marketplace and Model Lifecycle Management”→
San Francisco’s ban on the use of facial recognition technology by municipal agencies is noteworthy given the city’s high-tech affiliation and AI’s potential applications in public safety.
The safety-enhancing benefits of facial recognition are not resonating; instead, the technology has become a lightning rod for societal concerns related to privacy and inequality.
San Francisco is set to become the first major U.S. city to ban the use the facial recognition technology by municipal agencies. On Tuesday, the San Francisco Board of Supervisors voted in favor of the ‘Stop Secret Surveillance Ordinance,’ outlawing the use of the AI-based technology by city departments. The move is particularly noteworthy because it originates in a part of the U.S. otherwise known for embracing high tech and because it restricts the use of artificial intelligence for public safety, widely considered a top use case for facial recognition technology. However, San Francisco isn’t the only city evaluating restrictions on facial recognition; the issue is top of mind among lawmakers in many regions. Continue reading “Facial Recognition: A Lightning Rod for Societal Concerns in San Francisco”→