bfeynman
Joined 652 karma
- bfeynmanWe are almost at state of being able to make the hedgefund name generator for the dozens of places doing same thing. Combinations of flow and whatever suffix {ly, drop, wise...} and boom its probably one of these wrappers.
- | Kinda surprised they didn’t run into model collapse problems
Not sure why you would expect this, all the models started doing this as its much more cost effective to get data for post training don't you remember the first grok release where many times it started replies "as a model trained by openai..."
- The quality is most definitely suspect for how much revenue it brings it and how poorly its allocated. MTA has been full of cronyism and corruption for years and the cycle of kickbacks. Yes, its a complicated service, however you cannot deny the lack of transparency and ineptitude leaves the service in a much worse place than it currently could be. People can understand price increases when it translates to service.
- I've rarely seen any non elementary use cases where just giving access to an MCP server just works, often times you need to update prompts to guide agents in system prompts or updated instructions. Unless you are primarily using MCP for remote environments (coding etc or to a persons desktop) the uses of it over normal tool calling doesn't seem to scale with complexity.
- Would think that blue origin and project kuiper launching for amazon that would put downward pressure on SpaceX, as they are about to have a huge amount of competition for starlink, as Amazon has massive distribution advantages - wouldn't be surprised introductory bundling with Prime etc...
- HBO has been around for way longer... HBO Go started in 2010.
- I mean - social engineering of humans takes many forms that can definitely include linguistics of persuasion etc... But the core thing to me fundamentally remains the same is the LLMs do not have symbolic reasoning, its just next token prediction, guardrails are implemented via repetition in fine tuning from manually curated examples, it does not have fundamental or internal structural reasoning understanding of "just dont do this"
- based on linkedin it looks like they took a failed company thats existed for a year "General agents" which had what just looked like a single browser agent and now have rebranded that.
- the need for more web search indices is indeed dire given landscape with agents and providers turning into walled gardens means that independent ones are definitely going to be needed, but just seems insurmountable when building actual index is so costly. Maybe just purely pareto efficient of serving 80% of requests or something is good enough.
- seems like you are misappropriating what canaries are useful and used for... they are designed to be lightweight and shallow... hence the name and whole analogy, canaries never were meant to determine if a mine was structurally unsafe etc
- Montessori is just an educational framework, I have no idea where you draw broad conclusion that the one or two things you looked at deemed it be "rigid" or little opportunity... Sounds like a random bad apple. There's a correlation between gifted children and montessori because it allows them to develop at their own pace which is often faster than that of traditional classrooms etc, it's not for everyone.
- The premise of this article is almost entirely wrong. The primary driver of overseas manufacturing was that labor and manufacturing costs in the US are higher. The part about USD is misconstrued, countries hold USD because of its stability, which we benefit from being able to essentially inflation as they all still have their own banks as well to regulate their monetary policy.
- not really sure how that differentiates since those things you mentioned are ancillary to main value. Also - browser base is insanely cheaper, but looking at the prices this doesn't look like a real company mainly just a way to have users in free tier (with toy level limits)
- you're missing that open ai and anthropic are finetuning their models for their coding agents, i.e. using rl and annotating datasets and optimizing for them with directly learnable parameters. Cursor is just able to use whatever foundational model apis are available (not sure if or when labs might give programmatic access to coding agents). I'm sure they are trying to train OSS models but those fall way short performance wise of proprietary ones.
- frontier labs do finetuning of their models for software dev using the terminal/cli driven style, annotating datasets to solve programming in this fashion, and fine tuning will almost always make for better performance. Cursor as mostly a wrapper is just using the underlying foundation models in their framework and orchestrating on top of that, as opposed to doing actual learnable objectives in training to make things better.
- I literally said that they have their own autocomplete models.
- not only that but the way that openai and claude have their own foundational models/agents trained to work via CLI, which will basically always be better than just cursors gpt wrapper approach.
- The reason is abundantly clear. Cursor was just a GPT wrapper with a nice UI/UX (which was very nice when it came out) it has some other models like autocomplete as well, but its still a wrapper. OpenAI and Anthropic build and train models specifically to work via CLI driven processes, which is why they are so much better now. Cursor is basically dead as I'm sure they realized they get much better performance with the CLI/agentic approach.
- Amtrak is not reasonable prices compared to trains in like any other part of the world, except some parts of UK. Other than booking extremely early you're looking at 150$ plus tickets.
- the demo video is literally just single thread tool calling to external sources. Indexing data is also a really complex problem more than just adding some elastic search to gmail which also you will find does not scale easily, if that's even what you're doing.