The field of AI has changed significantly in the past couple of years and will likely continue to do so. Driven by a desire to expose our students to relevant and modern materials, we conducted two surveys, one of AI instructors and one of AI practitioners. The surveys were aimed at gathering infor-mation about the current state of the art of introducing AI as well as gathering input from practitioners in the field on techniques used in practice. In this paper, we present and briefly discuss the responses to those two surveys.

Associative memories based on DNA-affinity have been proposed based in L. M. Adleman (1994) and E. Baum (1995). Previously, we have quantified the quality of retrieval of genomic information in simulation as stated in M. Garzon et al. (2003). Here, the ability of two types of DNA-based memories to store abiotic data and retrieve semantic information is evaluated for soundness and compared to state-of-the-art symbolic methods available, such as LSA (latent semantic analysis) of T. K. Landauer et al. Their ability is poor when performed without a proper compaction procedure. However, when the corpus is summarized through a selection protocol based on PCR or a training procedure on J. Chen et al. (2004) to extract useful information, their performance is much closer to that of LSA, according to human expert ratings. These results are expected to improve and scale up when actual DNA molecules are employed in real test tubes, currently a feasible goal.