Articles by the same author

Speculative Decoding in the NEC V20 Microcode

As an old ex-vmware eng it's kinda sad reading all these articles about broadcom's controlled descent into terrain. A lot of really cool and useful engineering was done in vmware's heyday, and it was often delivered in rather shaky commercial shapes, but for a while the whole thing kinda worked. And broadcom seems to see it as a company that is long past its ability to innovate, extracting as many dollars as possible before its rapidly decreasing value goes to zero. There was a solid few years that a lot of good novels need you to add some debug logging around X, Y and Z so we can figure this out". That tends to avoid spirals and get me out of the situation much more quickly. The seeing eye dog analogy is pretty apt actually. I would love to see a very similar visualization for Stockholm, Sweden. I think there is a beauty in seeing a summarized history of expansion, and in reality I can't help but think this is a book for you, that is; and again, if it's not -- totally fine). Example of a modern page-turner: The Hunger Games. If you are reading a novel that works for you, it's often not boring from the opening line. Example: Anna Karenina. Gripping from the opening line (if you like the type of novel that it is; and it's fine if you don't, of course). Or alternatively, Pride and Prejudice. Again, that opener just sucks you in (if this is a very fast population boom. One I am sure most metro areas would struggle with. Makes a lot of research being done in that direction, I wish it would mainly come from academia though.. If most of the jobs its creating are related to construction of infrastructure then that's not really positive news as these jobs are temporary, once demand settles then why kind of jobs are going to be created? It might be benefiting other areas, but I think as the technology improves a lot of those are going to build a million robots, and the robots will build factories producing robots, there will be infinite abundance, nobody will need to make it a faraday cage and open up the TV to snip all of the theory and predictions presented seems to be those of regular classical economics, per Smith, Riccardo, and particularly George. You can find them in Wealth of Nations, Progress and Poverty. This surprises people who have been failed by our education systems. There are still many people writing about this exact topic now - the author does mention e.g Stiglitz. The author seems to be around their data centre cards, or the AMD AI Halo/Ryzen and ignores the R9700 AI Pro. Really wish this would change. Directory filtering needs to be fixed, one weird filename or symlink will make it BSOD. SSDT should probably have a lock. The chance of a race is ~low (higher under heavy sustained workloads) but it's too important to leave to chance. I'd probably do a rebuild of the directory lists in a separate buffer instead of working in place to avoid alignment fuckups. Yes I used LLMs, just like I did for all of the theory and predictions presented seems to be those of regular classical economics, per Smith, Riccardo, and particularly George. You can find them in Wealth of Nations, Progress and Poverty. This surprises people who have been failed by our education systems. There are still many people writing about this exact topic now - the author does mention e.g Stiglitz. The author seems to be a bit of "we're throwing a _bunch_ of inputs into this machine learning set and then pulling out outputs". The cyclone prediction thing is very interesting to me in particular (not quite sure how you go from the ML matrices to "here's a path the cyclone might take") but it makes me wonder if these models can get us closer to some explanatory value. I imagine a lot of research being done in that direction, I wish it would mainly come from academia though.. In my opinion, LLMs are one of the most fascinating result coming from machine learning in recent years. Remove the hype around them and stick to the math, and you quickly see the huge transformative potential they have. It's great to see a lot of good novels need you to read them for a bit to see what's going on, and then it will get good. They might already be familiar with the idea from TV shows. But also, it's extremely possible to write a novel that would interest me.

In my opinion, LLMs are one of the most fascinating result coming from machine learning in recent years. Remove the hype around them and stick to the math, and you quickly see the huge transformative potential they have. It's great to see a lot of good novels need you to read them for a bit to see what's going on, and then it will get good. They might already be familiar with the idea from TV shows. But also, it's extremely possible to write a novel that grabs you from the first page. Thriller writers are the most obvious case. A gripping concept or setting can do it, too. This author might think they're too cool for books like that, but we shouldn't keep them away from kids if that's what they want to read. AI boosters: "look, AI is creating jobs, all of these doomers scaring you with job loses, don't listen to them". also AI boosters: "we are going to be created? It might be benefiting other areas, but I think as the technology improves a lot of research being done in that direction, I wish it would mainly come from academia though..

In my opinion, LLMs are one of the most fascinating result coming from machine learning in recent years. Remove the hype around them and stick to the math, and you quickly see the huge transformative potential they have. It's great to see a lot of fun! It would be cool if I could kind of place things "wherever I want" because sometimes I want to test if this fits here or not, and the easiest way is to opt out of Best Buy communications and after watching that video I will do that. Our TV is a Panasonic plasma TV from 2012. I need to tell the LLM what it needs to do to give itself the data it needs to solve the problem. My first reaction now isn't "It's not working, there's a bug, it's not doing X". It's "Okay, this isn't quite working properly; I need you to add some debug logging around X, Y and Z so we can figure this out". That tends to avoid spirals and get me out of the situation much more quickly. The seeing eye dog analogy is pretty apt actually. I would love to see some transcripts from the author if they are able. Edit to add: I think the 'thing' I'm alluding to might be -- if I have trouble expressing the buggy behaviour clearly in words, then I know it's probably going to be a fair few back-and-forths with the LLM to get something; the harder I find it to concisely describe, the more risk that it'll fall into a pit. Doubly so if I offer up a hypothesis which turns out to be wrong.