Machine Learning and DeweyDecimal Classification

September 22, 2019

AI is not a new technology and certainly not a new way of problem solving. Machine learning models have improved much in the last five years The concept of manual knowledge modelling in AI systems is almost gone Instead, we have introduced the data science concept into machine learning and AI; we let the system build its own knowledge model although carefully selecting the «learning material». AI methods gets widely available through open frameworks such as Tensorflow,Pytorch, gensim etc.

Spotlight

Affectiva

Affectiva is now a Smart Eye company. In June 2021 Smart Eye acquired Affectiva. We are merging the two companies to form a global AI powerhouse. Affectiva is on a mission to humanize technology. An MIT Media Lab spin-off, Affectiva created and defined the Emotion AI and Human Perception AI categories. Built on deep learning, computer vision, speech science and massive amounts of real-world data, Affectiva’s technology can detect nuanced human emotions, complex cognitive states, activities, interactions and objects people use. In automotive, Affectiva’s Interior Sensing AI is enabling leading car manufacturers, fleet managers and ridesharing companies to build next-generation mobility that understands the state of the driver, the cabin and the occupants in it. Affectiva’s technology is also used by 28 percent of the Fortune Global 500 companies to test consumer engagement with ads, videos and TV programming.

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Cloud SOS: Treating a case of cloud failure

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Your cloud-enabled future loomed bright. Major budgets were allocated. Agonising hours were spent herding stakeholders. You’re now using cloud, but your teams and the wider business aren’t reaping the expected benefits. Even with the best intentions, tech leaders are struggling to fill those skills gaps, particularly when it comes to cloud implementation, migration and net new deployments. As a result, the business is held back – from capitalising on the cloud’s potential to deliver value internally (boosting efficiency and agility) and externally (delivering products and services that boost revenue).

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The Expanding Universe of Low Code / No Code Platforms

whitePaper | June 30, 2022

Low code and no code (LCNC) development platforms expedite the creation of new applications with minimal or no coding requirements, as well as offer tools for non-programmers to create applications of their own. Low code development was introduced in the early 2000s to increase developer productivity. It uses a variety of approaches that automate and abstract application development activities, such as drag and drop editors, code generation, component assembly and model-driven development.

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Implementation Challenges to Three Pillars of America’s AI Strategy

whitePaper | December 23, 2022

The transformative potential of artificial intelligence (AI) is a kind of truism. Seeking to capture the benefits of the “Fourth Industrial Revolution” or “third wave of the digital revolution,” countries are prioritizing efforts to reorganize their public and private sectors, fund research and development (R&D), and establish structures and policies that unleash AI innovation.

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How MongoDB Provides Strategic Advantage in Financial Services

whitePaper | August 9, 2020

Even before the COVID-19 pandemic, the pace of change in the financial services industry was exhausting. The challenges just kept coming: from the 2008 financial crisis to a raft of fintech newcomers and established brands pivoting into the industry, a panoply of regulations and the looming threat of a recession — to name a few.

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Why Automation and AI Will Define the Future World of Work

whitePaper | June 16, 2022

As companies continue their digital transformation journey, it’s clear that automation and artificial intelligence (AI) are now a competitive imperative. Companies can no longer ignore the gains intelligent automation solutions deliver. Such solutions free up employees from repetitive tasks, making them available for more valuable work. Automation and AI tools also enable companies to harness the value of their own data for competitive advantage while automating its processing.

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ACCELERATE DEEP LEARNING WITH A MODERN DATA PLATFORM

whitePaper | February 17, 2022

Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data.

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Spotlight

Affectiva

Affectiva is now a Smart Eye company. In June 2021 Smart Eye acquired Affectiva. We are merging the two companies to form a global AI powerhouse. Affectiva is on a mission to humanize technology. An MIT Media Lab spin-off, Affectiva created and defined the Emotion AI and Human Perception AI categories. Built on deep learning, computer vision, speech science and massive amounts of real-world data, Affectiva’s technology can detect nuanced human emotions, complex cognitive states, activities, interactions and objects people use. In automotive, Affectiva’s Interior Sensing AI is enabling leading car manufacturers, fleet managers and ridesharing companies to build next-generation mobility that understands the state of the driver, the cabin and the occupants in it. Affectiva’s technology is also used by 28 percent of the Fortune Global 500 companies to test consumer engagement with ads, videos and TV programming.

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