> a target release date of 2030 Don't get me wrong, I'm excited for a StarCraft shooter despite it not being StarCraft at all (I enjoy the universe). I wanted StarCraft: Ghost back in the day, and this feels like a taste of that dream. That said, targeting a release of 2030 is wild to me. Look at the Astra game dev hype that's hitting twitter right now. Yes it's all filtered to the best possible examples / yes people are not one shotting these things, but still it's very clear that LLMs are beginning to be very capable at game dev in a way that doesn't look/feel like ass. LLMs are going to become more capable over time. I think most of us can agree that eventually they'll be competitive with AAA developers given enough GPU cycles. I would argue that given rate of improvement, we're looking at that point coming in the next year or two. To emphasize this point, a year ago GPT-5 got released. This was the type of game it would make: https://youtu.be/yTHo7tMborY?t=324 This is the type of game Astra is making: https://youtu.be/GuO_Eo34C8E?t=348 It's just starting to be capable of making assets in blender / unreal. Given this rate of advancement, what is the state going to be like 4 years from now? It really feels a bit like the "travelling to distant stars" problem, where at some point it's faster to wait for better engines than to leave now. I worry that by the time this gets released, the market is going to be flooded with fully custom AAA games that are hyperniche. 4 years out is a long, long time to wait, and it's a longer time to bet on success / market dynamics.
I am a Lamport admirer. I gradually realized that Lamport is more of the godfather of distributed system than Hinton is to deep learning. Lamport is less prominent than Shannon is to information theory. Shannon is the closest to any title of "gold-like" figure to a scientific discipline of universal relevance in modern society. Lamport specifically revealed a philosophical connections between computer systems and physics, in the parallel of distributed consensus to relativity theory. To me, the enlightenment is that, the relations between events happening in a distributed system, is more fundamental than their absolute ordering, thus the central role of an "observer". I haven't really analyzed if this realization is from Lamport's papers, or my general reading and thinking, but I am moderately confident that general readings are heavily influenced by Lamport's papers, or can be traced back to be compatible with Lamport's thinking. I have not seriously study if this connection is valid in depth, which might be another pure amateur speculation of mine. One thing I think Lamport falls short is that his writing is not easy to read and understand. I unconciously feel that Lamport (and Dario from Anthropic) probably share a hidden sense of intellectual supriority grew from their own experience throughout their career. So their writing (and Dario's gospel) all share a unchangable sense of narration from their own delicate and graceful ideas, much less of faciliating the understanding to their audience. In this cateogry, Shannon is abosolutely superior in any measure, in his writing, ideas are so naturally presented, although the implications of the ideas remain elusive due to the inherent depth. Also, among the 3 prominent figures of modern AI: Hinton/Bengio are more like Shannon, Lecun is closer to Lamport. Enough random rambling. Lamport, as indicated by the outweight presence in this list, is no doubt the single most important scientist in distributed systems.
> I propose the following reconceptualization of the goal of a mathematics PhD: to become a world expert on some interesting, deep topic, and to be able to convey that interest and understanding to others. Part of operationalizing this might be a thesis, but the degree would be awarded primarily on the basis of a rigorous defense, in which the student explains the topic to their examiners until they are satisfied. I think this is a refreshingly forward looking idea and I agree with it 100%, especially the the "rigorous defense" part. That is a good measure of how well the topic has been researched and understood by the researcher. This is where the humans can be "in the loop". > How different would this look from current PhDs? I think students would still meet with an advisor, who might suggest a topic. That topic could be explored with AI assistance, or not, but the student would be responsible for understanding it; it might be much more open-ended and larger than the typical PhD is currently. Interesting point about "more open-ended" and "...larger than the typical PhD". I think the author has a point. Earlier, the bottleneck was the candidate's/researcher's understanding and knowledge. Now with AI tools, it is so much easier to zero in to relevant knowledge, get your questions answered quickly which might lead to understanding more quickly. For e.g., before the advent of public libraries and printing press, the knowledge was inaccessible and guarded. So that was the bottleneck. Then books became ubiquitous and the bottleneck to knowledge and understanding was people's motivation AND knowledge of WHAT books and topics to research. Then came the internet and free PDFs of books and research articles. Now, the bottleneck was still people's motivation and a mild version of what books and topics to research. I say "mild" because one can lookup articles and newsletters, and book reviews and come up with a list of reading. Now comes AI and it looks like the only bottleneck is people's motivation. I believe there was also a silent, yet potent, bottleneck all along which is also removed by AI: personal tutor/coach/teacher/professor etc. Let's say if I am reading a textbook on manifolds or some research paper and I have a question about a specific theorem or even a mathematical operator being used. Before AI my only way to get my questions answered was to read more books (PDFs or print), or ask on math exchange or math overflow and wait for someone to answer, or to ask a professor. This could take up to a week. Now all of that has been cut down to 1 hour or less with an interactive chatting session. !!!!! So....the only bottleneck is people's motivation! QED Exciting time!
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