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.
• 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”→
• Many organizations need help navigating ethical issues related to artificial intelligence (AI), such as privacy laws, unintentional bias, and lack of model transparency, but don’t know where to begin.
• Enterprises can benefit from working with a partner that helps them consider the ethical implications of their AI deployments, but they should keep in mind that issues aren’t static and can evolve over time.
Organizations are eager to enjoy the benefits that AI can bring to them – whether enhanced productivity, or new revenue-generating or enhanced customer experience opportunities. But many are unclear about how to navigate the murky waters of AI and ethics. Changing regulations and privacy laws, concerns over unintentional bias in training data, lack of transparency in AI models, and the dearth of experience with new use cases are difficult challenges to address. Enterprises want to ensure that their adoption of the technology doesn’t cross ethical boundaries, but often don’t know where to begin. Thankfully, the topic is being increasingly addressed by IT services providers. Many organizations, from IBM to Capgemini to Atos are touting that they help their customers implement AI while also considering the ethical implications of their deployment. Continue reading “AI and Ethics: The Waters are Murky, but Help is Available”→
IT services players must change their ways to be more effective partners to their clients.
At the NASSCOM Technology & Leadership Forum (NTLF) 2019, held in Mumbai, India in late February, Indian and international industry leaders shared best practices for managing AI’s impact on staff, reskilling teams, developing deeper customer relationships, and cultivating a culture that embraces change.
It’s not only about finding the right technology, curating large amounts of data, or identifying the best use cases. Successful AI depends on changing business processes. We often focus on the change that needs to take place at the enterprise, but what about the changes that IT services providers need to make in order to better serve their customers? IT services players must also change their ways to be more effective partners to their clients. Continue reading “At NASSCOM 2019, Executives Shared Best Practices for Addressing New Opportunities”→
A shortage of skilled AI professionals is one of the biggest hurdles to broader AI adoption by enterprises.
Salesforce is embedding its solutions with Einstein-powered AI to make the technology more accessible to non-data scientists.
Businesses need artificial intelligence (AI) solutions that can be easily adopted and manipulated by line-of-business users. Although many organizations are eager to adopt AI, they are often held back by a lack of access to data scientists that can curate data and develop AI models that address their specific needs. This skills shortage is one of the top hurdles facing organizations when it comes to operationalizing AI. And it is precisely this challenge that Salesforce is looking to address by embedding its solutions with Einstein-powered AI. Continue reading “Operationalizing AI for Broader Adoption”→
• Concerns over the accuracy of facial analytics have prompted IBM to release a dataset of over one million facial images, including facial coding, that can be used to train facial analytics software.
• Improving the results of facial analytics will bolster public confidence in the technology, promoting adoption by enterprises.
IBM has released a dataset of over one million facial images to the global research community to combat bias in facial recognition software. The announcement comes after researchers from MIT and the University of Toronto made claims that a well-known competitor’s product misclassified women at a higher rate than men, with error rates for darker-skinned women far surpassing error rates for lighter-skinned women. With women accounting for roughly half of the world’s population, inaccuracies in their classification present a serious threat to facial recognition adoption. Continue reading “IBM Releases Images to Improve Facial Analytics Accuracy”→