Time for a New Era of Personalisation within the Travel Industry?


The travel market is currently undergoing a radical transformation. We've seen the growth of online travel agents whetting the appetite for bespoke holidays, with more options than you could ever explore. On the accommodation front, we can choose to stay in a hotel, a hostel, or experience life in someone's else's shoes via apps like Airbnb or CouchSurfing. Each booking implies an element of personalisation, and the explosion of'mix-and-match' services has only amplified the importance of catering for holidaymakers on a one-to-one level. A personalised, considered and tactical strategy for converting each purchase would be the natural reaction to what we're seeing, if only the market could deliver it.

Oracle talks customer experience at Modern CX 2019


These are the questions your firm should ask before going down the route of edge analytics and processing. Oracle presented its vision for customer experience this past week at its annual event for marketers, called Modern Customer Experience 2019, held in Las Vegas. Customer experience means the sum of all touchpoints a customer has with a brand. Because creating a great experience is easy to describe but difficult to execute well, let's dive into the challenge. Also: Oracle's Ellison: No way a'normal' person would move to AWS Think of the phases through which typical customers may pass as they research, buy, and use products or services.

The new Cloudera-Hortonworks Hadoop: 100 percent open source, 50 percent boring


These are the questions your firm should ask before going down the route of edge analytics and processing. Hadoop is the operating system for big data in the enterprise. So when Cloudera and Hortonworks, the two leading Hadoop distributions and vendors, merged, that was big news in and by itself. Last week's DataWorks Summit Europe was the first big public event for the new Cloudera after the merger, and it sure was not short of interesting news, both on the technology and the business front. That's the name the new company will go by, and there's a new-ish logo and branding to go with this too.

Blueforce Intelligent Edge Solutions for Sensitive Site Exploitation - Blueforce Development


Sensitive site exploitation (SSE) missions are often conducted far forward and without the luxuries of time and assured security. Analysis of site information has traditionally required network backhaul which has often proved elusive in electronic warfare-contested or space-contested operational environments. Even under ideal conditions, onsite forces face difficult challenges of making sense from, the volume, variety, and velocity of data encountered. Teams need to collect and triage quickly to exploit the most perishable information for immediate action and decide "what" and "to whom" to exfiltrate for offsite exploitation. For example, names and images, extracted from a device may correlate with bio-metric identification or with other wide ranges of sources, including RF detection, hyperspectral imagery, and/or gait from full motion video (FMV) analysis.

Ranking Tweets with TensorFlow


As a global, public communications platform, Twitter strives to keep users informed with relevant, healthy content. Originally, Twitter presented Tweets in reverse-chronological order. As the community became more connected, the amount of content in users' home timelines increased significantly. Users would follow hundreds of people on Twitter -- maybe thousands -- and when opening Twitter, they would miss some of their most important Tweets. To address this issue, we launched a "Ranked Timeline" which shows the most relevant Tweets at the top of the timeline -- ensuring users never miss their best Tweets. A year later we shared how machine learning powers the ranked timeline at scale.

A crash intro into AI-powered object detection - Picterra


Here the human intelligence in charge is telling the AI model to have a look at these sections of the image. At this stage, only the human knows what is in the selected spots --sheep on a background in full shadow, sheep on the grass, and sheep on the bare ground. Defining areas where you know there are not examples of your object of interest helps the algorithm by enabling it to understand what you are NOT looking for looks like. The AI model will use these sections of your image as counterexamples. It is particularly helpful to draw the attention of the algorithm to areas where you have objects that look similar to your object of interest, but which are not that for which you are looking.

AIs are being trained on racist data – and it's starting to show


Machine learning algorithms process vast quantities of data and spot correlations, trends and anomalies, at levels far beyond even the brightest human mind. But as human intelligence relies on accurate information, so too do machines. Algorithms need training data to learn from. This training data is created, selected, collated and annotated by humans. And therein lies the problem.

Six of the best 4k HDR TVs

The Guardian

Your current TV is showing its age. Its resolution is resolutely HD (so very 00s) and it doesn't even respond to voice commands, no matter how loud you bawl. Maybe the time has come to upgrade to something cutting edge. Connected smart TVs are now standard fare. With integrated streaming services, you can season binge from Netflix and Amazon Prime Video without the need for an additional set top box or dongle – or multiple remotes.

Digital economy will represent over half of Latin America's GDP by 2022


According to research by analyst house IDC, economic and political instability in Latin America, coupled with presidential elections hampered technology in the region last year, particularly in Brazil, Mexico and Colombia, which collectively represent 66 percent of the region's GDP. But this is all set to change in 2019, according to the analyst firm, as the region will join the global move towards digital transformation, with an accelerated pace in innovation and spending on digital assets. According to IDC Latin America, IT spending in Latin America between 2019 and 2022 should reach $380 billion. Some 54 percent of the companies polled by the firm said they will increase IT spending, and only 17 percent plan to spend less than in 2018. In 2019, what the analyst defines as "third platform" technologies - so mobility, cloud, big data and social media - will represent approximately half of Latin organizations' budgets and grow by 5 percent on average.

Intel hopes to clean up toxic speech in game chat with AI and machine learning


Anyone who has ventured into online gaming knows text chat can approach nuclear-waste-levels of toxicity. But what happens when it all shifts to voice-based chat in the future? Intel says it can help. Or at least, it hopes it can. The company said on Wednesday night it's working with Spirit AI on ways to use machine learning and artificial intelligence to reduce the acidic speech gamers often fall back on during intense gaming sessions.