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Guidelines for AI procurement

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Artificial Intelligence is a technology that has the potential to greatly improve our public services by reducing costs, enhancing quality, and freeing up valuable time of frontline staff. Recognising this, the UK Government published the Data Ethics Framework and A Guide to using AI in the Public Sector to enable public bodies to adopt AI systems in a way that works for everyone in society. These new procurement guidelines will help inform and empower buyers in the public sector, helping them to evaluate suppliers, then confidently and responsibly procure AI technologies for the benefit of citizens.


Artificial Intelligence and the Integrated Review: The Need for Strategic Prioritisation

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The government's Integrated Review comes at a time of considerable technological change. The UK has entered a'Fourth Industrial Revolution' (4IR), which promises to'fundamentally alter the way we live, work, and relate to one another'. This new era will be characterised by scientific breakthroughs in fields such as the Internet of Things, Blockchain, quantum computing, fifth-generation wireless technologies (5G), robotics, and artificial intelligence (AI), which together are expected to deliver transformational changes across almost every sector of the economy. Of particular note are recent developments in AI, specifically advances in the sub-field of machine learning. Progress over the last decade has been driven by an exponential growth in computing power, coupled with increased availability of vast datasets with which to train machine learning algorithms.


Why SMEs should embrace machine learning

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RECENT technological advancements have placed artificial intelligence (AI) along with its subfield of machine learning (ML), at the forefront of transforming small and medium-sized enterprises (SMEs) digitally. Some SMEs are starting to tap into ML to shape their business processes and decision-making with the ultimate aim of raising profitability through revenue improvement, cost reduction and new sources of value creation. ML is seen as a continuation of the concepts around predictive analytics. However, a key difference in ML is that it uses mathematical algorithms to train computers in the processing and analysing of large amounts of data, allowing them to produce rules, identify patterns and generate classification predictions. It is important to note that computers automatically learn without human intervention or being explicitly programmed.


Adoption of AI and Blockchain at HHS: Interview with Jose Arrieta, US Department of Health & Human Services (HHS)

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Many governments worldwide are looking at using Artificial Intelligence (AI) and other cognitive technologies as part of making their operations more efficient, better serving their citizens, and increasing the range of ways they can meet their missions. It's no surprise then that the US Government and forward thinking leadership is making investments into AI technologies. Additionally, some agencies such as the US Department of Health & Human Services (HHS) are also seeing how other emerging technologies such as blockchain can help. Jose Arrieta, the CIO at the US Department of Health & Human Services (HHS), interviewed on a recent AI Today podcast episode while he was the associate Deputy Assistant Secretary for Acquisition at HHS is one such leader who sees how AI and blockchain can have a big impact at the agency. He became a program manager to build IT systems to use machine learning to analyze biographical information about people.


Public Sector Innovation Conference: Chair's Blog

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Like'digital transformation', innovation is an over-used and under-examined term. This applies within business generally, but more especially within the public sector, where there are limits to the amount of disruption and risk that it is considered acceptable to carry within the public domain. Further, a range of questions arises when government'innovates'. These include building the culture and incentives for innovation; understanding what innovation in the digital era is actually about (clue: it's not simply about having a new idea); handling the public-private sector relationship differently; scaling innovations; and handling the politics that inevitably surround changes of almost any kind to public services. The opportunity to chair the second Public Sector Innovation Conference on 25 February was a great opportunity to reflect on these, and many of the other tensions and opportunities that surround ongoing modernisation of public services, and benefit from a really high-quality speaker lineup.


6 European cities seek carbon emission-cut with AI

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Six European cities – Helsinki, Amsterdam, Copenhagen, Paris, Stavanger, and Tallinn – join forces in a new project named AI4Cities. The project challenges enterprises, researchers and others to develop solutions utilising artificial intelligence (AI) to generate cuts to carbon dioxide emissions, said the City of Helsinki in a press release. Helsinki emphasises utilisation of data and AI in its digitalisation programme to achieve the city's climate goals. The participating cities' respective programmes to cut carbon dioxide emissions emphasise emissions from transport and housing. Consequently, the AI4Cities Project focuses on emissions generated from transport and traffic as well as the energy consumption by buildings.


2020 AI Trends: Here's Why People Actually Want More Machines In The Workplace

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Artificial intelligence (AI) and machine learning will be everywhere, and we will learn to love them for all the right reasons. Let's begin with the big picture. Gartner analysts said that AI -- with a particular emphasis on machine learning -- will eventually infiltrate just about every existing technology. IDC predicted companies will invest over $265 billion worldwide in new intelligence technologies by 2023. Slightly further out, IDC researchers predicted that AI will be inescapable by 2025.


Six European cities tap AI to cut carbon emissions

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Helsinki, Amsterdam, Copenhagen, Paris Region, Stavanger and Tallinn will challenge companies to develop energy and mobility solutions using artificial intelligence (AI) as well as 5G, Internet of Things (IoT) and other related technologies. The initiative is part of AI4Cities, a three-year EU-funded project bringing together European cities looking for AI solutions to reduce their greenhouse gas emissions and meet climate commitments. The cities and regions will go through a pre-commercial procurement (PCP) process, which allows them to steer the development of new solutions directly towards their needs. Once they have defined their requirements, the cities will challenge start-ups, SMEs and larger companies to design solutions applying the use of AI and other technologies. Total funding of €4.6 million will be divided among the selected suppliers throughout the whole PCP process.


2020 AI Trends: More Machines in the Workplace SAP News

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Artificial intelligence (AI) and machine learning will soon be everywhere, and we will learn to love them for all the right reasons. That is my prediction after seeing the latest research about these fast-evolving technologies. Begin with the big picture: Gartner analysts said that AI -- with a particular emphasis on machine learning -- will eventually infiltrate just about every existing technology. IDC predicted companies will invest over $265 billion worldwide in new intelligence technologies by 2023. Slightly further out, IDC researchers predicted that AI will be inescapable by 2025.


Houston startup uses artificial intelligence to bring its clients better business forecasting calculations

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The business applications of artificial intelligence are boundless. Tony Nash realized AI's potential in an underserved niche. His startup, Complete Intelligence, uses AI to focus on decision support, which looks at the data and behavior of costs and prices within a global ecosystem in a global environment to help top-tier companies make better business decisions. "The problem that were solving is companies don't predict their costs and revenues very well," says Nash, the CEO and founder of Complete Intelligence. "There are really high error rates in company costs and revenue forecasts and so what we've done is built a globally integrated artificial intelligence platform that can help people predict their costs and their revenues with a very low error rate."