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Playing With CrowdStrike Machine Learning Detection

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Recently one of my clients received a well-performed phishing attack with an "invoice", that like a lot of attachments was malware. Everything seemed to be legit except that the invoice ended in one of my honeypot inboxes. I usually deploy some email addresses, not in use active use by the company, that I monitor in order to catch attacks. The malware seems to be a trojan focused on stealing information. Furthermore being a fresh sample at the beginning is was only detected by six detection engines in VirusTotal, right now it detected by 18 over the 60 available on VirusTotal.


[Experiment] How AI is Changing the Way We Optimize at Unbounce

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When I first encountered A/B testing, I immediately wanted to become the type of marketer who tested everything. The idea sounded fun to me. Like being a mad scientist running experiments to prove when my work was actually "working." Turns out though, there's always a long list of other things to do first… blog posts to write, campaigns to launch, and don't get me started on the meetings! A lot of marketers are just too darned busy to follow up and optimize the stuff they've already shipped.


The AI-Improved CX

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In 1990, a fellow chess player and I attended one of Gary Kasparov's several matches in New York City. Kasparov had become the youngest ever World Chess Champion in 1985, at the age of 22. In 1997, Kasparov also became the first World Chess Champion to be defeated by a computer, losing to IBM's Deep Blue in a stunning six-game match. Computers have become so good at chess that phones are now banned at chess tournaments, and players are very carefully monitored for any sort of digital activity or connection. Today, however, there is a new kind of chess becoming competitively dominant. Called "Advanced Chess," or more colloquially "Centaur Chess," it involves teaming human beings with computers, and it has been actively supported by Kasparov.


Artificial Intelligence: Expert warns of 'potential disaster' of AI bias

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He said: "It was a preventative health care system or model so it was built with all the good intentions, so was not to deny health care insurance to people. "But it was really for existing members to see if the company could target preventative health care practices to them. "Now, we all know that it's very biased because if you are black, and you have similar healthcare conditions as someone who is white, then unfortunately in the US, black people have less access to health care, so less is being spent on curing them from that disease. "So and that led to large amounts of bias and it was not something that couldn't be fixed." And the AI expert has warned how the bias inherent within AI can most likely never be eradicated.


Designing for AI: Trust

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At IBM, we're building software solutions that help our users make smarter decisions faster. In the world of data and artificial intelligence (AI), it all comes down to designing products our users can trust enough to help them make those important decisions. This focus on trust goes beyond data security and validation, it's about helping our users understand their data, providing relevant recommendations when they need it, and empowering them to create solutions they can be confident in. As we designed our end to end AI platform IBM Cloud Pak for Data, as well as a diverse set of AI offerings and solutions in our IBM Watson portfolio, we focused on the following 8 principles for establishing trust within AI experiences. At IBM, we believe that good design does not sacrifice transparency and that imperceptible AI is not ethical AI.


IBM secures fifth consecutive year of AI Software Platform market share leadership, says new IDC report - Journey to AI Blog

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For the fifth consecutive year, IDC ranked IBM the #1 market share leader in AI software platforms for 2019. In the IDC report, Worldwide AI Software Platforms Market Shares, 2019: The Battle Has Begun (doc #US46652020, July 2020), IDC valued the AI software platform market at USD 3.5 billion in 2019, a near-30% increase over the prior year. And despite a crowded landscape of competitors, IDC finds IBM leading the field among the largest AI platform players with an 8.8% share. While COVID-19 forces companies worldwide to reconsider business as usual, the accolades can wait; there's no time for a victory lap when work remains to accelerate the COVID-19 economic recovery with Data and AI. With IBM Watson positioned as the business world's first choice in AI software platforms, four competitive differentiators distinguish it from the competition.


An Open-Source Challenger to Popular Virtual Assistants

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Stanford researchers hope their open virtual assistant Almond can increase competition and better protect privacy.


The Rise of the Transformers

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Rise of the Transformers with Self-Attention Mechanism  The intention of this article is to continue in answering the questions that my friends April Rudin, Tripp Braden, Danielle Guzman and Richard Foster-Fletcher asked about the future of AI. Furthermore Irene Iyakovet interview with me about how


Use cases for AI while remote working - Information Age

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As organisations worldwide have had to shift to working remotely, technological measures have had to be taken in order to maintain operations. Keeping networks secure while employees use remote devices and home WiFi, continuing to collaborate on tasks and managing progress are among the challenges that have emerged while remote working, but AI has been able to aid effective collaboration. With this in mind, we take a look at some particular use cases for AI within work from home (WFH) practices. A digital skills gap proves to be a prolonged issue, but Paul Clough, head of data science at Peak Indicators, believes that AI can help to nurture skillsets within data science. With this year's National Coding Week launching today, we explore what to consider when looking to close the skills gap across the UK.


How AI can Change the Future of Telemedicine

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Artificial Intelligence and telemedicine are no more diverse. It has helped the digital health industry to emerge high from the scratch. This article outlines the various work areas of telemedicine and how Artificial Intelligence can change the life of healthcare systems even with challenges over the years. When in 1955, John McCarthy came up with the name "Artificial Intelligence" who had thought one day we would be diagnosing our health through the internet to distant locations? It was a dream by then, but not anymore.