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.
From Google's purchase of Deepmind to Apple's purchase of VocalIQ, big deals in UK's intelligence technologies are booming. However, commercial innovations are only part of the story. Join Digital Catapult to meet SMEs, academics and investors working in this space. It's a fantastic opportunity to find out what the UK's leading academic and research organisations and businesses are doing and attending, you'll also gain exclusive insights into market opportunities, challenges and exciting advances.
As the world heads towards increased efficiency and productivity through disruptive technologies, some of them are revising themselves with enhanced attributes offering better services and effectiveness. Machine Intelligence is one such technology that has risen from the advancement and evolution of ubiquitous technologies – machine learning and artificial intelligence. Machine Intelligence is advanced computing that exists at the intersection of machine learning and artificial intelligence. It enables a machine to interact with its environment in an intelligent way. With the emergence of volumes and variety of data machine intelligence technologies have experienced a global resurgence.
When a select band of computer scientists met at Dartmouth College in Hanover, New Hampshire, in 1956 to begin work on a field they called'artificial intelligence', they were optimistic, to say the least. Their founding principle of developing machine intelligence was based on an assumption that human intelligence could itself be well characterized. They argued that: "Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it." Ask ten people to define human intelligence and you will get at least eleven answers. To a philosopher, intelligence is the absence of a lack of intelligence.
Lately, Artificial Intelligence and Machine Learning is a hot topic in the tech industry. Perhaps more than our daily lives Artificial Intelligence (AI) is impacting the business world more. There was about $300 million in venture capital invested in AI startups in 2014, a 300% increase than a year before (Bloomberg). AI is everywhere, from gaming stations to maintaining complex information at work. Computer Engineers and Scientists are working hard to impart intelligent behavior in the machines making them think and respond to real-time situations.