This paper, a companion to "Problems in AI research and how the SP System may help to solve them", describes problems in AI research and how the "SP System" (described in sources detailed in the paper) may help to solve them. Most of these problems are described by leading researchers in AI in interviews with science writer Martin Ford, and reported by him in his book "Architects of Intelligence". Problems and their potential solutions that are described in this paper are: the need to rebalance research towards top-down strategies; how to minimise the risk of accidents with self-driving vehicles; the need for strong compositionality in the structure of knowledge; the challenges of commonsense reasoning and commonsense knowledge; establishing the key importance of information compression in AI research; establishing the importance of biological validity in AI research; whether knowledge in the brain is represented in 'distributed' or 'localist' form; the limited scope for adaptation of deep neural networks; and reasons are given for why the important subjects of motivations and emotions have not so far been considered. The evidence in this paper and its companion paper suggests that ***the SP System provides a firmer foundation for the development of artificial general intelligence than any alternative***.