Author: Rena Bhattacharyya

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.

Huawei’s Ascend 910 Chip and MindSpore Framework Underscore its Ability to Forge Ahead with AI, Despite Escalating Tensions with the U.S.

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

• Huawei announced the commercial launch of the Ascend 910, an AI chip optimized for model training, as well as MindSpore, a training and inference framework.

• The announcements come during escalating tensions between the U.S. and China, underscoring that Huawei will forge ahead in emerging technologies, with or without the U.S.

In the realm of AI, Huawei is readying itself to go head to head with global leaders, including Google and Amazon. The company’s recent commercial launches of an AI chip optimized for model training, as well as a training and inference framework, come hot on the heels of the unveiling of its internally developed operating system for mobile devices. The timing of the announcements is opportune; they come during a period of escalating tensions between the U.S. and China, serving to underscore that Huawei will forge ahead in emerging technologies, with or without the U.S. Continue reading “Huawei’s Ascend 910 Chip and MindSpore Framework Underscore its Ability to Forge Ahead with AI, Despite Escalating Tensions with the U.S.” →

HPE’s Acquisition of MapR Underscores That AI is All About Data

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

• 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” →

Tech Mahindra’s GAiA Platform Provides AI Marketplace and Model Lifecycle Management

by Rena Bhattacharyya, posted in Cloud Enable
R. Bhattacharyya

Summary Bullets:

• 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” →

Facial Recognition: A Lightning Rod for Societal Concerns in San Francisco

by Rena Bhattacharyya, posted in IT Leader
R. Bhattacharyya

Summary Bullets:

  • 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” →

AI and Ethics: The Waters are Murky, but Help is Available

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

• 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” →

At NASSCOM 2019, Executives Shared Best Practices for Addressing New Opportunities

by Rena Bhattacharyya, posted in IT Leader
R. Bhattacharyya

Summary Bullets:

  • 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” →

Operationalizing AI for Broader Adoption

by Rena Bhattacharyya, posted in IT Leader
R. Bhattacharyya

Summary Bullets:

  • 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” →

IBM Releases Images to Improve Facial Analytics Accuracy

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

• 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” →

Need a Ride? Call a Self-Driving Taxi!

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

  • Ford announced plans for self-driving taxis and delivery services; it expects to launch its fleet in Washington, D.C. in 2021.
  • Ford is one of many companies around the globe that is developing commercial autonomous vehicles.

Soon, if you need a ride to the airport, to the pub, or just around town to run errands, you’ll have another decision to make. Do you hop in a cab? Request an Uber? Or, perhaps… you take a self-driving taxi. What just a few years ago seemed like futuristic technology right out of a sci-fi movie will be here before you know it. Continue reading “Need a Ride? Call a Self-Driving Taxi!” →

Facial Recognition to Spark Lively Debate in 2019

by Rena Bhattacharyya, posted in Big Data
R. Bhattacharyya

Summary Bullets:

• Companies specializing in facial recognition raised sizable amounts of capital from investors in 2018.

• In the coming year, facial recognition will yield new use cases, but will also bring new ethical concerns to the forefront.

Facial recognition is a hot topic. During 2018, several companies active in image recognition, and specifically facial recognition, raised sizable amounts of capital. China-based Sensetime raised an additional $1 billion in September of 2018, bringing the company’s total funding to $2.6 billion. After its Series D funding in July 2018, Megvii’s Face++ had raised a total of $607 million.

During 2019, investment in companies pursing visual recognition and developing new applications for the technology will likely accelerate. Given recent trends, there is a strong possibility that much of this new funding will be flowing into China, which has been very public about its aspirations to lead the global AI arena. Continue reading “Facial Recognition to Spark Lively Debate in 2019” →