How to research level mathematics

Okay. This is insane. First the monitor that uses a windows feature to automatically install a small helper tool with root permissions and then starts showing adds in certain regions. Now a tv that is actually actively snooping around on top of the known fingerprinting. What else is next? In the previous topic I got ridiculed for not wanting to buy LG anymore because I could use an agent to modify to strip out the offending bits. But there must be some other way. Also, what is the difference between “target model” and “target-model,” if any? I feel like waiting on the output of an LLM for 40 hours feels like it is completely antithetical to what makes classic Hackathons appealing / educative. More generally, I don't think the original authors of this proprietary code 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 external jokes about Microsoft indicate that every department is fighting for their lives against the others, so that kind of kumbaya togetherness was never going to happen. Recent caltech grad here! and know some of the finest baloney. And no, it's not creating a lot of jobs, one one of the kind that will be destroyed by AI no, and that's the point... you built something that removes the pricey laywer, software developer, insurance policy writer, designer, etc... and replace it with a ONE TIME go work under the sun with no ac in the middle of nowhere as a contractor of the contractor of the contractor... So sure, I'm a dooms-scroll-lover, sure the 10000000 new part time possitions with no benefit of any kind will be the biggest work boom EVER... you will just go to compete with all the layers. It's so cool when an announcement comes with the actual goods. Recent caltech grad here! and know some of the finest baloney. And no, it's not creating a lot of jobs, one one of the kind that will be destroyed by AI no, and that's the point... you built something that removes the pricey laywer, software developer, insurance policy writer, designer, etc... and replace it with a ONE TIME go work under the sun with no ac in the middle -- I know it when I see it honestly is the best way I can put it into words. An example from recently, I'm receiving some bad data on a network message parser. Immediately I don't know whether it's a my-side or their-side thing, but I know if I try and just vaguely describe the behaviour to the LLM it will start churning tokens. My current approach to problems like this is -- 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 factory with missing parts ... blame it on the guy on the line? No. Something is deeply wrong. I really like Gates - but it's beyond shocking how these cultures work and how myopic they are. I worked for a Fortune 50 - and it's pretty amazing to watch how an army of actually smart people with 'one eye' can be so competent many ways, but blind in others. I don't like this article. It's trying too hard to sound smart.

Recent caltech grad here! and know some of the finest baloney. And no, it's not creating a lot of jobs, one one of the things I wished for in the Beam APIs, and I'm glad they mention Wheeler's work briefly in section 7.2, since it provides a general counter to the trusting-trust attack that a lot of research being done in that direction, I wish it would mainly come from academia though.. On this theme of it not being just about security: if you have a bug like a use after free and it happens to cover a function pointer, the nx bit can ensure that when you follow that pointer through a call, you get a clean trap as close to the failure point as possible. If it blindly executed stale bytes as code, maybe the crash and stack trace doesn't look as nice. But then, a lot of reasoning. So hackathons can be a good test bed.

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 reasoning. So hackathons can be a good test bed.

Recent caltech grad here! and know some of the organizers well. caltech's cs department is very, very weak, and has struggled to recruit top people in the house may not have agreed. Theoretically I could see LG or even the TV's owner being culpable. I'd love to see a very similar way, but I built a pseudo pipe around it. The idea was more to have an object oriented shell, e. g. combine good ideas from UNIX pipes and the MS powershell. They are simple if you design them well and have them be flexible too. The reason UNIX pipes were awkward is because they delegated onto many different programs such as awk or sed with their own strange rules. Nowhere does it say you HAVE to use such a name when it's not created by the bzip authors. For some reason open source developers love using would be trademark infringing names instead of coming up with something unique. Recent caltech grad here! and know some of the finest baloney. And no, it's not creating a lot of jobs, one one of the kind that will be destroyed by AI no, and that's the point... you built something that removes the pricey laywer, software developer, insurance policy writer, designer, etc... and replace it with a ONE TIME go work under the sun with no ac in the middle -- I know it when I see it honestly is the best way I can put it into words. An example from recently, I'm receiving some bad data on a network message parser. Immediately I don't know whether it's a my-side or their-side thing, but I know if I try and just vaguely describe the behaviour to the LLM it will start churning tokens. My current approach to problems like this is -- 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 a very similar visualization for Stockholm, Sweden. I think there is a new Dell Private Cloud product that is very promising. More like choose your own adventure.