The early reporting on Canada's AI strategy. Carries the fingerprints of advice in the public consultation: -Cash for SME implementation -Subsidies for cloud/compute access especially Canadian suppliers -Keep-it-local data policies in some sectors but not others -Government as anchor customer for Canadian startups -Moonshot projects on A.I. in health, energy, ag, robotics, transport -Safety and Privacy Act upgrades. You can trace the lineage of these ideas to the expert submissions. The macro story? The macro story is there was a sharp dichotomy in the public consultations. A contradiction. 1) More AI: The experts submitted papers with all sorts of ideas for scaling up AI use in Canada, which is slower than a number of peer countries. 2) Less AI: the broader public? A big thumbs down for AI. The public comments were mega-negative, based on the thousands I analyzed.

Based on this report, it sounds like the majority of Canada's strategy aims at addressing point #1, with some moves aimed at public concerns in point #2. cbc.ca/news/politics/fe…

For context in the leadup to the release Canada's AI strategy, some useful references. 1) The annual state-of-AI report from Stanford. Shows how Canada, which punched far above its weight in developing much of the modern technology (reinforcement learning, semantic context, neural nets/backpropagation), is quite negative on the technology and relatively slow to commercialize: t.co/YgEiwv9ec0 2) Brookings report on AI sovereignty. Shows how no country can control its stack from A to Z. But all countries have certain advantages, including Canada on certain types of data. t.co/OOKDQslFHR 3) A deep dive on the state of Canadian AI. With a focus on sovereignty: t.co/URo5YAP196 4) The full dataset from the public consultations. With the expert ideas. And the public apprehension: t.co/vTP9mVmf5J