My understanding is that, if confirmed, this demonstrates that AI can find novel solutions. This is a strong counterpoint to generative-AI-is-strictly-limited-to-training-data.
I really enjoyed fantasy part of many small farmers. It felt rustic. However based on my understanding the modern world is moving towards megacorps and economies of scale.
Servicing is not done by Apple, it's 3rd party contractors. They have a rubric of possible issues from Apple and their profit margins are thin. I suspect contacting Apple support about Apple support issues would have resulted in a swift replacement of the item.
Will need to wait for real benchmarks, but based on OpenAI marketing Instant is their latency optimized offering. For voice interface, you don't actually need high tok/s because speech is slow, time to first token matters much more.
No, what he is saying is that benchmarks are static and there is tremendous reputational and financial pressure to make benchmark number go up. So you add specific problems to training data... The result is that the model is smarter, but the benchmarks overstate the progress. Sure there are problem sets designed to be secret, but keeping secrets is hard given the fraction of planetary resources we are dedicating to making the AI numbers go up.
I have two of my own comments to add to that. First one is that there is problem alignment at play. Specifically - the benchmarks are mostly self-contained problems with well defined solutions and specific prompt language, humans tasks are open ended with messy prompts and much steerage. Second is that it would be interesting to test older models on brand new benchmarks to see how those compare.
You can chain normalized quaternions to combine or diff transformations. For example you can subtract desired attitude quaternion from predicted attitude quaternion to get attitude error quaternion which you can then feed to control algs designed for driving that error to zero. This is even more important when multiple frames of reference are involved as quaternions can be used to transform between them.
Sure, and there are a ton of ways to shifting income around. For example selling a subsidiary in lower tax jurisdiction patents and then paying for their usage. Another example is Hollywood accounting where productions pay exorbitant rates for equipment and catering to affiliated companies. This inflates the costs so the movies end up unprofitable despite smashing box office.
It could be as simple as links. People drop links in the slack discussions, other people from Geolocated IP addresses (or same) click on them. Google analytics et. al. hovers a lot of data.