Cisco is set to snap up CloudCherry, a Salt Lake City based Customer Experience Management (CEM) specialist that provides rich APIs, predictive analytics, and customer journey mapping with integrated sentiment analysis.
Cisco said the purchase of the firm, with the majority of its employees based in Bangalore, Indi, aligned with its strategy around the cognitive and collaborative contact center. This approach will see Cisco focusing on cloud analytics, artificial intelligence, and machine learning to boost agent productivity and confidence, enabling them to provide more personalized customer experiences.
Upon completion of the transaction, the CloudCherry team will join Cisco’s Contact Center Solutions business, led by vice president and general manager Vasili Triant.
“With CloudCherry, we’re augmenting our contact center portfolio with advanced analytics, rich customer journey mapping and sophisticated survey capabilities that all our customers can use,” said Triant.
“And with more than 17 integrated feedback channels available, CloudCherry can help us better understand and enrich the agent and employee experience as well! CloudCherry’s predictive analytics and journey-oriented solution helps companies understand the correlations between various factors that influence customer experience, ” he said.
“Predictive analytics help agents make journey modifications in real-time, such as up and cross-selling and enabling discounting or couponing to meet customer needs during the interaction, to improve first contact resolution and customer happiness,” Triant added.
In addition, Cisco said CloudCherry’s open API platform complemented its own open and cloud architecture approach, by simplifying how customer data is ingested from systems of records, transactional data, and other data sources.
“This enables our customers to fully leverage their business technology investments, while helping contact center agents close the feedback loop and improve customer loyalty and satisfaction,” said Triant.
The acquisition is expected to close in the first quarter of Cisco’s fiscal year 2020, subject to customary closing conditions and required approvals.
US big data analytics specialist Guavus and Mumbai-based mobile data network service provider Jio have struck a key partnership, aimed at boosting the customer experience for the telco provider through artificial intelligence driven analytics.
Under the collaboration, Guavus’ AI-based services will provide real-time customer experience analytics as well as predictive analytics to automate network troubleshooting, along with marketing insights to Jio.
According to Guavus, the partnership will allow Jio to offer a dramatically improved service to its customers while addressing critical service operations with intelligent automation.
“The rapid growth, range and affordability of Jio’s service offerings and their innovative use of AI and analytics is transformative for their customers and India,” said Anukool Lakhina, Guavus Founder and President.
Jio, which has some 300 million subscribers, has created a completely digital experience for its users – including data services on smartphones, home gigabit Internet, and a suite of media services and IoT devices for the home such as smart speakers and switches.
“Our networks generate 4 to 5 petabytes of data each day. If this data can be properly analyzed in real-time using big data analytics and predictive analytics techniques, we can both improve the health of our network through intelligent automation and offer multiple, customized personal services to our customers,” said Anish Shah, President of IT, Reliance Jio.
“Guavus’ solutions enable us to do this – we can make data-driven decisions that allow us to deliver a great experience to our customers while bringing intelligent automation to our operations.”
South African drone imagery and AI specialist Aerobotics has appointed disruption and innovation expert Stuart van der Veen as Chief Platform Officer.
Van der Veen will be based in the US, managing global partnerships in agriculture and affiliated industries. He joins Aerobotics from Nedbank Corporate and Investment Banking (CIB), where he was Head of Disruption and Innovation.
The appointment comes as part of Aerobotics’ plans for major expansion around the globe. Aerobotics, which is currently operating in 11 countries, said it is allocating significant resources focusing on the agriculture market in the United States, particularly California and Florida.
“This is the year of aerial imagery analytics, and we’d like to work with the world’s most forward and sustainable thinking organizations,” said van der Veen. “Agriculture is fast becoming a data driven industry. Engaging with precision farming and our technology means less damage to the environment, enhancing how resources like water are being used and contributing to food security around the world.”
According to Aerobotics, his career highlights included winning the Financial Times of London ‘The Banker Tech Projects Award for Fintech Partnerships,’ and bringing Silicon Valley’s Plug and Play Tech Centre to Africa for the first time .
At Nedbank, van der Veen created new market opportunities in strategic industries, including a financial services partnership with Aerobotics in agriculture. Together, they worked to better serve clients by garnering unique data-driven insights through tree crop aerial imagery analytics.
“I am proud and excited to join Aerobotics and help build on the incredible growth they have already been able to achieve,” said van der Veen. “Aerobotics’ technology and services are already providing farmers and the agriculture industry transformative information and insights, and I am excited to contribute to one of the best South African and global stories of our generation.”
Motorola Solutions has acquired VaaS, a data and image analytics company based in Livermore, California and Fort Worth, Texas, paying Motorola US$445 million in a combination of cash and equity.
VaaS, a “video analysis as a service” company, is billed as a primary global provider of data and image analytics for vehicle location. Its image capture and analysis platform, which features fixed and mobile license plate reader cameras driven by machine learning and artificial intelligence, provides vehicle location data to public safety and commercial customers.
The firm’s subsidiaries include Vigilant Solutions for law enforcement users and Digital Recognition Network (DRN) for commercial customers. The company’s 2019 revenues are expected to be approximately US$100 million.
According to Motorola Solutions, the acquisition’s research and development operations are based in Vietnam where it has more than 40 employees working in the specialised areas of software engineering, AI and data analytics.
“This acquisition expands Motorola Solutions’ data and analytics capabilities, complementing our public safety software and analytics suite and Avigilon video and analytics platform,” said Greg Brown, chairman and CEO, Motorola Solutions. “VaaS will enhance Motorola Solutions’ software portfolio with vehicle location information that can help first responders shorten response times, improve the speed and accuracy of investigations and create safer cities.”
VaaS’ platform enables controllable, audited data-sharing across multiple law enforcement agencies. Vehicle location information can help accelerate time to resolution and improve outcomes for public safety agencies, particularly when combined with police records. For example, law enforcement has used VaaS’ solutions to quickly apprehend dangerous suspects and find missing persons.
“We are very excited to be joining Motorola Solutions,” said Shawn Smith, co-founder of VaaS and president of Vigilant Solutions. “This acquisition enables us to continue to serve our existing customers and expand our footprint globally, while at the same time supporting a company with a commitment to innovation and growth, guided by a common purpose that aligns with our mission and culture: ‘To help people be their best in the moments that matter.’ It doesn’t get any better than that.”
“Our extensive license plate data and AI technology have opened new commercial applications of our products,” said Todd Hodnett, co-founder of VaaS and president of Digital Recognition Network. “We believe commercialisation of these new applications can be accelerated under the Motorola Solutions brand and reach, and we look forward to working together to grow and diversify our commercial business.”
License plate reading is a highly specialised practice that requires purpose-built cameras and analytics. VaaS’ fixed and mobile license plate reader cameras can capture and analyse license plate information, which differs greatly by state and country, even when vehicles are moving at high speeds or in low-visibility weather conditions.
VaaS will join Motorola Solutions’ Software Enterprise, the team responsible for creating the company’s integrated public safety software suite.
Commits RMB10 billion (A$2 billion) in R&D for 2019
OPPO will be investing RMB 10 billion (about A$1.97 billion) in research and development next year – a 150 per cent increase year-on-year – as it focuses on 5G, AI and IoT.
The Shenzhen-based handset maker also announced it will continue to ramp up investment on a yearly basis. The announcement was made at OPPO’s technology-focused ‘2018 OPPO Technology Exhibition’ in Shenzhen, China.
Embraces 5G technology
Since 2015, OPPO has been investing in R&D into the 5G standard. When 5G standards were frozen in December 2017, OPPO quickly invested in the development of 5G products, taking the lead in enabling the interoperability of 5G signalling and data links in August 2018. By October, OPPO had realised the first 5G smartphone connection.
“5G is a significant network upgrade, which will bring unprecedented speeds and applications to our mobile networks here in Australia,” said Michael Tran, managing director at OPPO Australia.
“In addition to striving to become the first manufacturer to launch 5G smartphones, OPPO’s exploration of application opportunities in the 5G+ era will ultimately determine the value of 5G.”
“OPPO will fully integrate 5G with applications and user insights, and continuously innovate to provide users with revolutionary, necessary, convenient and seamless mobile experiences,” added Tran.
Benefits of AI realised in the 5G era
To date, OPPO said it had applied AI technologies across a wide range of applications, including photography, facial recognition and fingerprint identification. In addition, AI has enabled OPPO to launch innovate features including an AI-powered beauty camera, 3D portrait lighting and intelligent recognition scenarios.
However, Tran said this only promised to be the start of what AI could make a reality.
“The benefits brought about by AI technologies will truly be realised when 5G launches in Australia. For OPPO, AI is both a capability and a mindset, meaning our development prospects for AI are very broad,” he said. “In the future, smartphones will be our intelligent personal assistants – and this is something OPPO will definitely enable.”
The rise of IoT sees OPPO expand to smart devices and homes
With OPPO’s commitment to becoming a leader in an era where 5G, AI and Internet of Things are broadly applied, the company is set to expand its product range to include smartwatches and smart home technologies, with its smartphones at the centre of a connected ecosystem.
“We must continue to explore and innovate within this new connected era. In the future, OPPO will fully integrate technological innovation to develop smart devices and homes, with the smartphone at their core. Our priority is to develop and provide smart technologies to meet the increasing demands for connected devices in the age of the Internet of Things,” said Tran.
These are the droids you’re looking for: Tireless, uncomplaining, able to work 24 hours every day, responding instantly to threats against the Empire… or rather, threats against an enterprise, service provider, or telco.
We’re talking about artificial intelligence software, equipped with machine-learning algorithms, designed to work as part of a comprehensive security suite for the Security Operations Center (SOC).
“AI helps us go from hindsight to foresight,” says Vinod Peris, Senior Vice President at industry giant CA Technologies. “If you take things like malware detection, they used to be pattern-based. You were matching some patterns. Now, you’re trying to actually look at behaviors: behaviors of applications, behaviors of end-points.”
From matching patterns to looking at behavior to anomalies. “When you look at the SOC, there are certain areas where AI can help,” adds Slavik Markovich, CEO of security innovator Demisto.
“First of all identifying the needle from the haystack. That’s one of the easiest things you would do with AI, because AI is used a lot to take a lot of data and cluster it, and classify it, and try to find the outliers.”
Another application of AI, says Markovich, is to reduce the repetitive workload for security analysts. “Once an analyst identifies an alert, there are a lot of mundane tasks where you basically do the same thing over and over again, like get the reputation of a certain IP, check the provenance of a file, check logs, and all of those things.”
AI can do those tasks instead, in an adaptable day: “This is something AI is really good at, by looking at already-existing actions in the history and learning from them, and then feeding it back to the analyst whenever it’s needed.”
Greg Fitzgerald, CMO of security startup JASK, agrees about AI helping SOC analysts, and adds that algorithms can augment the decision-making process.
“For example, AI can correlate disparate alerts and events that may be happening in different locations or at different severity levels that a human may not even pay attention to,” he says. “So, AI captures all that, creates the linkages between those different alerts, and is able to aggregate those into things we actually call an insight.
“An insight is not the resolution that this is definitively happening,” explains Fitzgerald. “It’s a collection of the activity that now a human can use the subjective capability to determine ‘This is relevant for me and my organization at this time.’ ”
Key AI Technologies for the SOC
Researchers have developed dozens of AI technologies, algorithms, models, and learning techniques. Two of the most common used in the security field are machine learning and predictive analytics. Machine learning is a data-intensive technique that lets software progressively improve performance on specific tasks, particularly those involving classification of data, and predictions about future events. In the AI domain, predictive analytics is used to swiftly detect anomalies or new patterns in the data, and make recommendations based on those anomalies and patterns.
Demisto’s Markovich adds that security sometimes uses unguided deep learning, which is based on neural networks, as well as the guided techniques above. Deep learning, which mimics the way humans behave more than machine learning, can produce results similar to what a human SOC analyst would do. “You have deep learning, you have the guided learning; people are using all of that.”
At the end of the day, there’s a commonality: “Some software gets a lot of samples, and then based on various attributes classifies them,” explains Markovich. “Others look at lots and lots of events, and then try to correlate and find the right things to do. Companies like Demisto look at analysts’ intents and actions and derive the value from there.”
It’s all changing the world, says Sam Liang, CEO and Founder of AISense, a company focusing on using AI and speech recognition to create intelligent and contextually-aware mobile tools to enhance professional productivity. “You know, Marc Andreessen said software was eating the world, but now it’s actually that AI is eating the world.”
“All the major companies have got AI,” explains Liang, “AI is changing people’s lives in a lot of different perspectives in terms of, you know, speech recognition, image recognition, medical imaging. You can have AI to look at your MRI or x-ray to quickly detect a cancer.” Or to correlate data to detect a malware incursion or a hacker’s attack long before a human analyst would sense that something’s wrong, he adds.
Faster Time to Triage
JASK’s Fitzgerald agrees that AI is speeding up the detection of problematic events. “The biggest impact that AI is making in the SOC is faster time to triage, because in the end, that’s exactly what the human is trying to do. We see lots of reports that talk about, a compromise hasn’t been found for 100 days, or 150 days, or more.” AI is cutting that time-to-detections from months to minutes, he adds.
“It’s definitely in the detection,” comments Demisto’s Markovich. “When you look at detection, there’s a mass of events out there, and it’s almost impossible for a human to look at all of them. AI is doing a pretty decent job in highlighting what’s interesting.”
Still, Markovich points out, AI can’t do the job alone. “We’re not in a place where you can take the human out of the equation. AI can need to highlight the right stuff, but then allow the human to actually look at it, interact with it, and decide if it’s a real incident or a false positive.”
“AI will help in reducing the time to triage,” says CA’s Peris. “If you have a SOC issue, the first thing people do is, they get on a call and they try to figure out what’s the root cause and go through the analysis. With AI, you could have this at your fingertips, hopefully even before that issue happens.”
Peris adds that AI will play multiple roles in protecting networks, applications – and people. “Facebook recently had to put in place a system that could look at, and prevent, fake news. They hired 10,000 people for this. This is obviously just a quick reaction. What AI will eventually do is allow machines to do that first level of analysis, so it will cut down the number of people that you need.” And perhaps do the job more accurately, with a more consistent set of rules.
What’s Next for AI in Security?
CA’s Peris sees a bright future for end-point behavioral analytics. “If somebody steals your password, unless they know exactly your access patterns, your system can detect that it’s not you through behavioral analytics. Similarly, you can do the same thing for applications. If you knew the application’s behavior, and let’s say we as application developers gave you a signature of the application’s behavior, you could factor that into figuring out when an application is compromised. “
“More optimization,” says Demisto’s Markovich. “You’ll see a lot of faster algorithms, maybe more accuracy, fewer false positives. The big bet is actually in unsupervised learning, that is, deep learning. Throw the bunch of events on enough computing power to let AI learn by itself. That will eventually get to a place where AI can actually identify the real positives and not false positives.” This level of deep learning might be 20 years away, says Markovich, but “that would be the real game-changer.”
Fitzgerald from JASK believes that “AI for SOC will expand beyond just the analytics of the alerts, and the logs, and the information that’s being ingested” and head into the ability to respond without human supervision. “To date, most things are still provided to what’s called a playbook, or something that allows a human to start taking physical action.”
“In the next couple of years, the SOC analyst will start to trust the decisions that are being made,” adds Fitzgerald, “and allow AI to automatically make the configurations that rectify the situation without the analyst’s involvement, but with the analyst’s supervision.”
In other words, soon we’ll let AI determine if those really are the droids you’re looking for, in an Empire far, far away.
Communication service providers such as AT&T, Comcast, Orange, and Verizon are actively advancing the growth of smart home adoption by building connecte home offerings alongside their investments and deployments of broadband and video services.
However, more recently most telcos have been outperformed by aggressive competition and are now at a crucial stage: they must either accelerate their UnTelco strategies – activities they should pursue beyond their traditional offerings to foster revenue growth – in smart homes to take back the ownership of the home or risk being relegated as marginal players.
Some key facts:
The impact of artificial intelligence on regional telecommunications, higher education and the urban environment will be the focus of a new research group launched today as part of a new five-year alliance between Optus Business and Curtin University.
The five-year alliance will develop an AI research group and will combine key synergies between Curtin’s excellent research, teaching and learning capabilities, and the Optus’ market-leading technology and infrastructure capabilities.
An Optus Chair in Artificial Intelligence and three Optus Research Fellows will be appointed to focus on applying artificial intelligence technologies in areas such as regional telecommunications, improving higher education student outcomes and the urban environment, as well as funding for PhD scholarships and student projects.
“CSPs are being threatened in a market increasingly driven by the likes of Google and Amazon with a range of products and services from AI-powered smart home voice control smart speakers to security solutions,” said Abi Research senior analyst Pablo Tomasi. “But things are changing and CSPs are accelerating their strategies for the smart home. Telefonica with Aura, Orange with Djingo, and SK Telecom with Nugu lead the way of CSPs developing AI assistants to support their smart home play.”
“Now is the time for CSPs to be more aggressive in tying the usage of their AI assistants to their other connected and smart home offerings,” he added.
ABI noted that CSPs have assets all around the connected home from providing connectivity, creating content and delivering video, to specific applications such as monitored security and as such, they have a wider reach than any other competitor.
“CSPs should use this mix of essential – e.g., broadband connectivity – and value-added services such as monitored security to tailor a strategy fine-tuned to customers’ needs and regional dynamics. “CSPs should not impose their legacy fixed-line business model to the smart home,” he said, admiringated.
“The smart home is core to CSPs’ future and it is a real test to assess how far CSPs have developed their business beyond their telco heritage and how they can adapt their bundling business to market condition, experiment with innovation, and compete head-to-head with webscale players,” concluded Cave.