In a world where we produce enough food to feed everyone, 811 million people still go to bed hungry each night; that's one in every 10 people worldwide. The COVID-19 pandemic, climate change, and complex social-economic factors make the situation even more dire. By contrast, space, satellite, and Artificial Intelligence (AI) technologies have radically transformed humanity's ability to observe and model Earth's systems. It's inevitable then that we pose the question: how can Earth observation (EO) and AI help those in need? To find an answer, the Φ-lab at the European Space Agency, together with the World Food Programme (WFP) Innovation Accelerator, are launching the new EO & AI for SDGs Innovation Programme.

Artificial intelligence is here for a long time in many forms and ways. In recent years significant progress has been made in some areas of AI. This doesn't mean that AI, in general, is evolving as fast, just those fields. And some of them are increasingly used for different domains of digital transformation. Instead of talking about artificial intelligence (AI), some describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing. Others focus on several real-life applications of artificial intelligence that often start with words such as "smart" (omnipresent in anything related to the Internet of Things and AI), "intelligent," "predictive" and, indeed, "cognitive," depending on the exact application – and vendor.

Global non-profit OceanMind uses AI to detect illegal and unregulated fishing which helps authorities protect ocean life and promote sustainability. The AI for Good movement founded by the UN ITU AI for Good Global Summit (#AI4G) is having reverberations into powerful responsibility. AI4G has more than 150 projects in their AI repository. I'm providing my perspective on these programs where I'm donating time to many of them, including Microsoft, and thus have deep insights. There is The Hague Summit for Accountability in the Digital Age (#I4ADA) November 6-7 2019, Peace Palace.

A World Food Programme convoy carries humanitarian aid to Aleppo, Syria. Getting food into conflict zones is a major hurdle -- and a topic of discussion at the WFP's Innovation Accelerator. A World Food Programme convoy carries humanitarian aid to Aleppo, Syria. Getting food into conflict zones is a major hurdle -- and a topic of discussion at the WFP's Innovation Accelerator. Let's figure out how to end hunger forever.

Although artificial intelligence (as a set of technologies, not in the sense of mimicking human intelligence) is here since a long time in many forms and ways, it's a term that quite some people, certainly IT vendors, don't like to use that much anymore – but artificial intelligence is real, for your business too. Instead of talking about artificial intelligence (AI) many describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing or focus on several real-life applications of artificial intelligence that often start with words such as "smart" (omni-present in anything related to the IoT as well), "intelligent", "predictive" and, indeed, "cognitive", depending on the exact application – and vendor. Despite the term issues, artificial intelligence is essential for and in, among others, information management, healthcare, life sciences, data analysis, digital transformation, security (cybersecurity and others), various consumer applications, next gen smart building technologies, FinTech, predictive maintenance, robotics and so much more. On top of that, AI is added to several other technologies, including IoT and big, as well as, small data analytics. There are many reasons why several vendors doubt using the term artificial intelligence for AI solutions/innovations and often package them in another term (trust us, we've been there). Artificial intelligence (AI) is a term that has somewhat of a negative connotation in general perception but also in the perception of technology leaders and firms.

For years many of us have been paying attention to the ways that several technological realities such as the Internet of Things, big data and artificial intelligence (AI) are impacting organizations across numerous industries, applications and areas. When we looked at the several technologies in the SMAC stack (social, mobile, analytics and cloud) or IDC's core 3rd platform technologies we looked at them separately but also in their combinations and interlinked value as they powered new next generation applications. It seemed pretty obvious that cloud services, big data/analytics, mobility (mobile devices, apps and broadband) and social (business) were fully intertwined ever since we started writing about that third platform, which IDC presented back in 2011. In that sense of intertwining the same goes for the second platform and its many technologies in areas such as local area networks, the client-server model, personal computers, the Internet and so forth. And in case we forgot that these technology-driven realities, as well as their real underlying technologies (there is no such things as one social business technology, mobile technology or even cloud technology) had little value and impact as such, Gartner reminded us that it was the convergence of mobile, social, cloud and information which enabled digital business through what the research firm called The Nexus of Forces.

Although artificial intelligence (as a set of technologies, not in the sense of mimicking human intelligence) is here since a long time in many forms and ways, it's a term that quite some people, certainly IT vendors, don't like to use that much anymore – but artificial intelligence is real, for your business too. Instead of talking about artificial intelligence (AI) many describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing or focus on several real-life applications of artificial intelligence that often start with words such as "smart" (omni-present in anything Internet of Things as well), "intelligent", "predictive" and, indeed, "cognitive", depending on the exact application – and vendor. Despite the term issues, artificial intelligence is essential for and in, among others, information management, medicine/healthcare, data analysis, digital transformation, security (cybersecurity and others), various consumer applications, scientific advances, FinTech, predictive systems and so much more. There are many reasons why several vendors doubt using the term artificial intelligence for AI solutions/innovations and often package them in another term (trust us, we've been there). Artificial intelligence (AI) is a term that has somewhat of a negative connotation in general perception but also in the perception of technology leaders and firms. One major issue is that artificial intelligence – which is really a broad concept/reality, covering many technologies and realities – has become like a thing we talk about and also seem to need to have an opinion/feeling about, with thanks to, among others, popular culture.

Although artificial intelligence (as a set of technologies, not in the sense of mimicking human intelligence) is here since a long time in many forms and ways, it's a term that quite some people, certainly IT vendors, don't like to use that much anymore – but artificial intelligence is real, for your business too. Instead of talking about artificial intelligence (AI) many describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing or focus on several real-life applications of artificial intelligence that often start with words such as "smart", "intelligent", "predictive" and, indeed, "cognitive", depending on the exact application – and vendor. Despite the term issues, artificial intelligence is essential for and in, among others, information management, medicine/healthcare, data analysis, digital transformation, security (cybersecurity and others), various consumer applications, scientific advances, FinTech, predictive systems and so much more. There are many reasons why several vendors doubt using the term artificial intelligence for AI solutions/innovations and often package them in another term (trust us, we've been there). Artificial intelligence (AI) is a term that has somewhat of a negative connotation in general perception but also in the perception of technology leaders and firms. One major issue is that artificial intelligence – which is really a broad concept/reality, covering many technologies and realities – has become like a thing we talk about and also seem to need to have an opinion/feeling about, with thanks to, among others, popular culture.

Although artificial intelligence (as a set of technologies, not in the sense of mimicking human intelligence) is here since a long time in many forms and ways, it's a term that quite some people, certainly IT vendors, don't like to use that much anymore – but artificial intelligence is real, for your business too. Instead of talking about artificial intelligence (AI) many describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing or focus on several real-life applications of artificial intelligence that often start with words such as "smart", "intelligent", "predictive" and, indeed, "cognitive", depending on the exact application – and vendor. Despite the term issues, artificial intelligence is essential for and in, among others, information management, medicine/healthcare, data analysis, digital transformation, security (cybersecurity and others), various consumer applications, scientific advances, FinTech, predictive systems and so much more. There are many reasons why several vendors doubt using the term artificial intelligence for AI solutions/innovations and often package them in another term (trust us, we've been there). Artificial intelligence (AI) is a term that has somewhat of a negative connotation in general perception but also in the perception of technology leaders and firms. One major issue is that artificial intelligence – which is really a broad concept/reality, covering many technologies and realities – has become like a thing we talk about and also seem to need to have an opinion/feeling about, with thanks to, among others, popular culture.

IDC released its 10 IT industry predictions for 2017 in a webcast with Frank Gens, IDC's senior vice president and chief analyst. The predictions covered many trends driving success today and in the future, from how the entire global economy will be re-shaped by digital transformation, the transition of all enterprises from being "digital immigrants" to being "digital natives," the scaling up of innovation accelerators, the emergence of "the 4thplatform" (a new set of technologies that will become mainstream in ten years), drastic changes in how enterprises connect to their customers, and the ecosystem becoming as important for business success as IP. Here are IDC's ten predictions: We will see a "deep core" transformation of what enterprises are all about and how they behave in the marketplace. By the end of 2017, revenue growth from information-based products will be twice that of the rest of the portfolio for a third of G2000 companies. By 2021, a third of CEOs and COOs of G2000 companies will have spent at least 5 years in a tech leadership role.