The high barrier to entry prevents many companies from tapping into the full potential of machine learning. But what if you could make it more accessible?
We’re in the midst of a data explosion, with today’s enterprises amassing goldmines of information (25 quintillion bytes of data every day, according to some reports). But what exactly are they doing with this data? Considering the volume of data being collected is quickly becoming unmanageable, now is a good time to shift from manual machine learning to a cognitive approach. This enables businesses to better capitalize on their data and facilitate agile decision-making.

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The high barrier to entry prevents many companies from tapping into the full potential of machine learning. But what if you could make it more accessible?
We’re in the midst of a data explosion, with today’s enterprises amassing goldmines of information (25 quintillion bytes of data every day, according to some reports). But what exactly are they doing with this data? Considering the volume of data being collected is quickly becoming unmanageable, now is a good time to shift from manual machine learning to a cognitive approach. This enables businesses to better capitalize on their data and facilitate agile decision-making.

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I recently became a bionic man. I have one good ear and one bad ear as a result of flying around while suffering colds and flus over the years, and with only one good it makes it difficult to hear a conversation in a noisy room, so I went looking for a high tech digital solution.
For the last couple of years I have been watching the start-up, Doppler Labs, as they developed their earbuds that were purported to have great sound, but also to enhance hearing. This month after reading about their latest software release, I ordered a pair to try. There were three reasons I wanted to try Doppler Labs’ HearOne Wireless Smart Earbuds. First because their goal was to enhance hearing for a few hundred dollars, rather than for many thousands of dollars that the hearing aid industry charges, secondly, they were building artificial intelligence (AI) into their earbuds, and thirdly, I could listen to premium audio and talk on my phone with them.

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I recently became a bionic man. I have one good ear and one bad ear as a result of flying around while suffering colds and flus over the years, and with only one good it makes it difficult to hear a conversation in a noisy room, so I went looking for a high tech digital solution.
For the last couple of years I have been watching the start-up, Doppler Labs, as they developed their earbuds that were purported to have great sound, but also to enhance hearing. This month after reading about their latest software release, I ordered a pair to try. There were three reasons I wanted to try Doppler Labs’ HearOne Wireless Smart Earbuds. First because their goal was to enhance hearing for a few hundred dollars, rather than for many thousands of dollars that the hearing aid industry charges, secondly, they were building artificial intelligence (AI) into their earbuds, and thirdly, I could listen to premium audio and talk on my phone with them.

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In a recent survey, Sumo Logic surveyed 1,500 customers who employ cloud services such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). According to the survey, a quarter of the respondents have already deployed Docker containers and nearly as many (23 percent) are employing the AWS Lambda serverless computing framework.
It’s clear: serverless is here to stay. The adoption does come with some needed changes, within both application development and operations. That means serverless is also changing the way we leverage public clouds. Truth-be-told, many enterprise IT shops were so happy to get out of the management of physical servers within a data center that many limitations of the existing public IaaS clouds were forgiven. However, now that we’ve lived a few years with public IaaS clouds, developers and CloudOps pros are giving a huge thumbs down to the constant monitoring of servers, provisioned or not, that’s required to support the workloads.

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In preparation for General Data Protection Regulation (GDPR) compliance, a global 100 financial services organization embarked on a journey to assess its core information processing environments with the objective of identifying opportunities to strengthen its data privacy protection programs. This article focuses on the technology challenges, approach, and lessons learned for the centralized testing environment.

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Most technology leaders, contemporary and from the hardware era, are reshaping their businesses to do software. They hope to capture value from emerging technologies such as IoT, SDN, and AI. Ultimately, irrespective of the vertical, it is about deriving value from independent software applications participating in an ecosystem as one comprehensive solution. In his session at @ThingsExpo, Kausik Sridhar, founder and CTO of Pulzze Systems, discussed how given the magnitude of today’s application ecosystem, tweaking existing software to stitch various components together leads to sub-optimal solutions. This definitely deserves a re-think, and paves the way for a new breed of lightweight application servers that are micro-services and DevOps ready!

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Nordstrom is transforming the way that they do business and the cloud is the key to enabling speed and hyper personalized customer experiences. In his session at 21st Cloud Expo, Ken Schow, VP of Engineering at Nordstrom, discussed some of the key learnings and common pitfalls of large enterprises moving to the cloud. This includes strategies around choosing a cloud provider(s), architecture, and lessons learned. In addition, he covered some of the best practices for structured team migration and discussed ways to control cloud costs.

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«WineSOFT is a software company making proxy server software, which is widely used in the telecommunication industry or the content delivery networks or e-commerce,» explained Jonathan Ahn, COO of WineSOFT, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.

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The dynamic nature of the cloud means that change is a constant when it comes to modern cloud-based infrastructure. Delivering modern applications to end users, therefore, is a constantly shifting challenge. Delivery automation helps IT Ops teams ensure that apps are providing an optimal end user experience over hybrid-cloud and multi-cloud environments, no matter what the current state of the infrastructure is. To employ a delivery automation strategy that reflects your business rules, making real-time decisions based on a combination of real user monitoring, synthetic testing, APM, NGINX / local load balancers, and other data sources, is critical.

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