Enterprise big data and analytics cuts through the hype to make sense of data collection, storage, management, dissemination and discovery technologies, all employed collectively as a means of realizing corporate efficiencies and uncovering business opportunities.
• 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.
Just one short year after an internal reorganization to more fully meld artificial intelligence (AI) with data and analytics, IBM is back with a new, more accessible vision for IBM Watson.
This time around, the company isn’t focused on game shows or scientific discovery but instead on solving very basic, often human-centric challenges.
When it comes to chasing the market’s heated but somewhat unrequited love affair with AI, IBM has certainly done its part in terms of generating hype for its multi-billion dollar investment in IBM Watson. That hype, which has taken aim at some rather lofty goals such as identifying and diagnosing cancer, has not fully panned out, with some early adopters scaling back or halting operations altogether due to concerns over cost and efficacy. Continue reading “IBM Data and AI Forum: Say Hello to a More Accessible IBM Watson”→
• IBM is poised to grow its cloud services business by helping customers to accelerate their migration of mission-critical applications to the cloud.
• IBM brings a lot of value by helping customers remove complexities in their cloud migration; and avoiding vendor lock-in through an open source, hybrid cloud and multi-cloud strategy.
IBM held its annual analyst event – IBM Asia-Pacific 2019 Analyst Insights – in August 2019. The event was held in Singapore and coincided with THINK Singapore 2019, which was the first THINK event in the country. The THINK event helped IBM showcase its capabilities to customers in the country as it starts to ramp up customer engagement. Over the past few years, companies have experimented with AI and moved non-critical workloads to the cloud. IBM now advocates moving from experimentation to more substantial transformation to gain speed and scale. This will involve moving mission-critical applications (80% are still kept on-premises) to the cloud for scalability and agility. While this is ideal, to benefit from cloud-native features, enterprises need to deal with many layers of complexity ranging from regulations and compliance through to re-architecting legacy systems, security considerations, underlying infrastructure, and change management (people and processes). Continue reading “IBM Advocates Open, Hybrid, and Multi-Cloud in Helping Customers Transform their IT”→
• 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”→
Enterprises should be prepared to be ‘guinea pigs’ for large tech companies seeking to develop replicable AI solutions.
Off-the-shelf AI solutions for vertical and horizontal use cases are being offered by a growing number of providers.
One of the biggest challenges to adopting AI is knowing where to start. In theory, AI can be applied to any and all aspects of an organization’s day-to-day operations. Furthermore, even if AI enhances a particular part of a business’s operations, it does not necessarily mean that the value returned will be worth the investment. One of the biggest beasts in the telecoms technology world, Cisco, has acknowledged that it has not brought as many AI-enhanced solutions to the market as it anticipated because it is still developing the use cases for AI. Continue reading “Making Money from AI: Use Cases and Experimentation”→
Starting on September 1, 2019, Microsoft will begin onboarding new Office 365 users directly into Microsoft Teams, in essence removing the option for customers to run both Teams and the soon-to-be-retired Skype for Business Online.
Though somewhat extreme, this migration plan has been coming on for some time now, frankly ever since Microsoft introduced Microsoft Teams in 2017.
• Whilst AI can replace humans, it often works best when used to enhance what humans are doing.
• AI can deliver significant business benefits, but if implemented unsympathetically it can also cause disruption.
GlobalData’s research indicates that businesses understand that AI offers significant potential benefits in areas such as efficiency, R&D, and staff training, recruitment, and retention. The same research finds that enterprises also see potential pitfalls. Whilst the 5% of respondents in GlobalData’s survey who stated that AI is the ‘beginning of the end of the world’ may have had their tongues in their cheeks, a level of concern is not uncommon. Indeed, KPMG has referred to the concept of ‘Robocalypse Now’. It is also not unreasonable for employees to be worried that AI driven automation technologies will mean job losses because the adoption of those solutions usually does lead to headcount reductions. Continue reading “Humanizing AI: How to Automate in a Sympathetic Way”→
• Late last week AT&T and Samsung together cut the ribbon on a co-developed 5G Innovation Zone that had nothing at all to do with consumer 5G future opportunities.
• Rather, the new facility, housed within Samsung Austin Semiconductor’s Austin Texas fabrication plant, showcased several ways high speed cellular can both modernize and optimize manufacturing processes.
If you travel a few miles northeast of Austin, Texas, you’ll find among the gentle rolling hills an undistinguished 300-acre facility dedicated to the fabrication of semiconductors (aka computer chips) for networking, high performance computing, IoT, and of course mobile devices. And if you look carefully within the foyer of this 20+ year old foundry, you’ll find a somewhat unassuming highly rectangular room peppered with Ikea-styled demonstration tables and plain black monitors that when considered together scream out in all caps: “5G IS VERY REAL, RIGHT NOW!”