# Key Points from #hplusroadmap IRC Discussion

• A discussion explored using neural networks for simulation as an alternative to full physical models or programmed simulations like GTA V, suggesting neural networks could provide better computational efficiency while maintaining capability.

• Participants proposed a hybrid simulation approach where detailed modeling (potentially down to atomic level) would be done once, but ongoing simulations would use varying levels of abstraction based on observer relevance, similar to human daydreaming.

• NVIDIA's approach to self-driving cars using full neural networks (rather than hard-coded rule sets used by Google) was cited as an example of modeling physics through learned inference.

• A technical method was shared for passing scalar parameters to convolutional neural networks by creating additional feature channels with wave patterns of varying amplitudes alongside RGB channels.

• Bryan Bishop shared a transcript of Elon Musk's "Making Humans a Multiplanetary Species" presentation, which was added to the DIY H+ Wiki (http://diyhpl.us/wiki/transcripts/spacex/elon-musk-making-humans-a-multiplanetary-species/).

• A paper on "Bootstrapping Lunar Industry" from the National Space Society journal was shared (http://www.nss.org/settlement/journal/NSSJOURNAL_BootstrappingLunarIndustry_2016.pdf), continuing the space colonization theme.

• New cloud computing resources for machine learning were discussed, including an Amazon EC2 instance type with 16 GPUs and Google's machine learning platform.