This paper describes problems in AI research and how the SP System (described in sources referenced in the paper) may help to solve them. Most of the problems considered in the paper are described by leading researchers in AI in interviews with science writer Martin Ford, and reported by him in his book "Architects of Intelligence". These problems, each with potential solutions via SP, are: the divide between symbolic and non-symbolic kinds of knowledge and processing, and how the SP System may bridge the divide; the tendency of deep neural networks (DNNs) to make large and unexpected errors in recognition, something that does not happen with the SP System; in most AI research, unsupervised learning is regarded as a challenge, but unsupervised learning is central in how SP learns; in other AI research, generalisation, with under- and over-generalisation is seen as a problem, but it is a problem that has a coherent solution in the SP System; learning usable knowledge from a single exposure or experience is widely regarded as a problem, but it is a problem that is already solved in the SP System; transfer learning (incorporating old knowledge in new) is seen as an unsolved problem, but it is bedrock in how the SP System learns; there is clear potential for the SP System to solve problems that are prevalent in most AI systems: learning that is slow and greedy for large volumes of data and large computational resources; the SP System provides solutions to problems of transparency in DNNs, where it is difficult to interpret stored knowledge and how it is processed; although there have been successes with DNNs in the processing of natural language, the SP System has strengths in the representation and processing of natural languages which appear to be more in accord with how people process natural language, and these strengths in the SP System are well-integrated with other strengths of the system in aspects of intelligence; by contrast with DNNs, SP has strengths and potential in human-like probabilistic reasoning, and these are well integrated with strengths in other aspects of intelligence; unlike most DNNs, the SP System eliminates the problem of catastrophic forgetting (where new learning wipes out old learning); the SP System provides much of the generality across several aspects of AI which is missing from much research in AI. The strengths and potential of the SP System in comparison with alternatives suggest that {\em the SP System provides a relatively promising foundation for the development of artificial general intelligence}.