Why We Need Ethical AI: 5 Initiatives to Ensure Ethics in AI

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Artificial intelligence (AI) has already had a profound impact on business and society. Applied AI and machine learning (ML) are creating safer workplaces, more accurate health diagnoses and better access to information for global citizens. The Fourth Industrial Revolution will represent a new era of partnership between humans and AI, with potentially positive global impact. AI advancements can help society solve problems of income inequality and food insecurity to create a more "inclusive, human-centred future" according to the World Economic Forum (WEF). There is nearly limitless potential to AI innovation, which is both positive and frightening.


AI applications for social good Tryolabs Blog

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Artificial intelligence is gaining traction in areas of social responsibility. From climate change to social polarization to epidemics, humankind has been seeking new solutions to old but persistent problems. From a technological point of view, the amount of daily data produced in the digital universe now allows for state-of-the-art approaches, which may lead to innovative solutions in these underserved areas. AI for social good turned into a reality for us at Tryolabs after we collaborated with an NGO to improve upon how African lions are tracked, which helps with species preservation. We will go into more detail on that timely case, especially as wildlife conservation faces the immense challenges posed by devastating megafires threatening the lives of millions of animals in historic ways.


2020 Predictions for the Future of Work

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It will be quite a year in 2020 for digital workplace and employee experience, as a number of important emerging trends shift the landscape. Some long-standing issues will also reach a tipping point for many organizations. I recently laid out the reasons for this in considerable detail. These issues are now consistently a significant challenge for many organizations to deliver well on either digital workplace or employee experience, two closely related concepts. While these issues can't entirely be overcome this year for most organizations, it's safe to say that understanding them and tackling them proactively will product the better result.


Challenges Of Implementing Natural Language Processing

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The process includes several activities such as pre-processing, tokenisation, normalisation, correction of typographical errors, Named Entity Reorganization (NER), and dependency parsing. To attain high-quality models, NLP performs an in-depth analysis of user inputs like lexical analysis, syntactic analysis, semantic analysis, discourse integration, and pragmatic analysis, etc. The main challenge is information overload, which poses a big problem to access a specific, important piece of information from vast datasets. Semantic and context understanding is essential as well as challenging for summarisation systems due to quality and usability issues. Also, identifying the context of interaction among entities and objects is a crucial task, especially with high dimensional, heterogeneous, complex and poor-quality data.


AI for Classes 3-6

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Artificial Intelligence seems to be everywhere. Experts claim AI is the Next Industrial Revolution bringing in changes as Electricity did decades back. With every massive change it's important that children are provided the right education to become ready. At WiselyWise we have been researching and working on the right Curriculum for School students. We wanted to ensure the content and intensity is appropriate for different age groups.


Not bot, not beast: scientists create first ever living, programmable organism

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A remarkable combination of artificial intelligence (AI) and biology has produced the world's first "living robots". This week, a research team of roboticists and scientists published their recipe for making a new lifeform called xenobots from stem cells. The term "xeno" comes from the frog cells (Xenopus laevis) used to make them. One of the researchers described the creation as "neither a traditional robot nor a known species of animal", but a "new class of artifact: a living, programmable organism". Xenobots are less than 1mm long and made of 500-1000 living cells.


How Industries are Using AI to Improve Their Efficiency

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Companies are having a much easier time collecting data with the aid of analytics tools that can be incorporated easily in most of the consumer-facing products and services. Experts estimate that by 2020, each individual with general 1.7 megabytes per second, which makes up to 146 gigabytes per day. However, data collection is only a part of it, and the challenge lies in extracting meaningful intelligence out of them, and this is where development in the artificial intelligence (AI) field has started to change that. The AI industry has been attracting much attention from investors and customers for a decade and more. Nonetheless, understanding what artificial intelligence is capable of doing can be a tricky affair if we aren't familiar with the fundamentals of it.


MIT professors sound alarm on US falling behind on AI

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The U.S. is locked in a race when it comes to advanced technology like artificial intelligence and machine learning – chiefly against China. Speaking about technological progress from the World Economic Forum in Davos, Switzerland, MIT Sloan's Erik Brynjolfsson and Andrew McAfee pointed out how inextricably linked the AI race is with immigration policies and government investment – and particularly the red tape that hinders smart people from coming to the U.S. AI and machine learning are thought of technologies that will fundamentally reshape productivity and growth. Companies from around the world from Amazon to Google as well as more mundane companies in manufacturing are employing these technologies. According to Accenture, within five years AI will drive "significant innovation" and "unleash new levels of human productivity and creativity." Brynjolfsson said the U.S. is still the leader in developing these modern technologies -- and commercializing them.



The United States of Artificial Intelligence

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The most well-funded US artificial intelligence startup is Nuro, with just over $1B in disclosed equity funding, including a $940M Series B from SoftBank in February 2019. The California-based startup is developing autonomous vehicles, with a focus on last-mile delivery. Nuro is followed by New York's UiPath ($1B in disclosed equity funding) and Illinois' Avant ($655M). There are 9 unicorn startups on our map: robotic process automation vendor UiPath ($7.1B valuation), autonomous vehicles software provider Argo AI ($7B), agtech startup Indigo Agriculture ($3.5B), Nuro ($2.7B), alternative lending startup Avant ($1.9B), AI-powered predictive sales platform InsideSales.com The startup with the least funding on the list is Rhode Island's The Innovation Scout, a SaaS platform that connects enterprises with startups, accelerators, and more.