European Machine Intelligence Landscape


We @ProjectJunoAI are big fans of landscapes. That's why we've created a machine intelligence landscape focused entirely on Europe. Europe deserves a landscape of its own to highlight its talent and expertise. Until recently, its contribution to the innovation and commercialisation of machine intelligence technologies has been under-appreciated. We now see growing self-confidence borne of the success, and continued presence, of local acquired startups like VocalIQ, Swiftkey, Deepmind, Magic Pony Technology, and PredictionIO.

Machine Intelligence Lab


We are investigating practical ways in which we can support machine intelligence SMEs in the UK, especially around compute provision. This questionnaire is part of our research, and we really appreciate your input. Thank you very much for your participation.

Machine Intelligence 2.0 in charts and graphs


So are Apple, IBM, and Amazon. In fact, every major technology company is investing in machine intelligence to improve their existing products or to develop entirely new ones. This transformative technology is poised to affect just about every industry out there. VB Profiles partnered with Shivon Zilis to better understand its impact and to present the Machine Intelligence 2.0 landscape. Above: This chart is part of VB Profiles Machine Intelligence Series.

Why I'm Devoting My Life to Machine Learning

Huffington Post - Tech news and opinion

This is the shortest path I see towards machine intelligence: first, we develop ways to allow specialized AIs to manipulate formal concepts, write programs, run experiments, and at the same time develop mathematical intuition (even creativity) about the concepts they are manipulating. Then, we use our findings to develop an AI scientist that would assist us in AI research, as well as other fields. It would be a specialized superhuman artificial intelligence to be applied to scientific research. This would tremendously speed up the development of AI. At first we would apply it to solve well-scoped problems: for instance, developing agents to solve increasingly complex and open-ended games.

Flipboard on Flipboard


We've seen glimmers of this potential emerge in recent years. Mobile assistants get smarter all the time, from telling us when we need to leave for an appointment to encouraging us to take a walk if we've been sitting too long. Machine learning is speeding up deliveries and helping doctors diagnose diseases. Smart algorithms are stopping cybercriminals. Much of it would have been unimaginable ten years ago.