garlic_enjoyer

That hasn't been my experience, but I know what you mean. Claude in particular likes to point out "things you might not have considered" and I sometimes already have. But it tends to vindicates me more than it annoys.

I'm pretty early in my career, so I probably gain more from that sort of stuff than most people. The senior devs on my team tend to get the most frustrated with it and I think this behavior is a big part of why.

That just sounds like effective communication with emotional beings to me. I was taught in college to find points I agree with, acknowledge those, then move on to the parts I don't agree on. It makes the recipient feel good at first, which puts them in a frame of mind willing to accept criticism.

You even start your reply with "That's true but Claude has so many more forms of this." It's just a friendly way of speaking.

The quotes make it clear they meant a different meaning of alignment than how the term is typically used (alignment with each other, not with humans).

>Like any program, inference engines like vLLM or SGLang may contain exploitable bugs. Because the LLM controls the tokens passed to the inference engine, a malicious LLM could therefore emit a sequence of tokens that a poorly written inference engine mistakes for code or instructions to execute rather than data to return to the user.

They aren't talking about model providers. These are the tools you use with model weights locally (but you could set up remote infrastructure a la data center if you have the fundage).

>But anger is different from anxiety because anger needs to be directed somewhere. The feeling of anger suggests that somebody or something is doing something to you.

>Who are you going to be angry at and why are you angry in the first place?

The author is arguing that you should hone in on the underlying reasons behind emotions. It can be easy to conflate anger and anxiety. It's up to your agency to reflect on your emotions and how you act on them.

You can be angry, but you should name at what and why. Who is propagating the mindfulness movement? How is it affecting you? What can we do differently? Calling out "they" isn't a good answer.

I agree that it's marketing mumbo jumbo, but it's saying "we haven't added more features because more is better, we added them because they actually improve the longevity of the product."

If anything, that sentence tells me that they are insecure of their features being perceived as bullshit.

I was about to invest in Google, but your compelling observation has swayed me. Now it's obvious to me they are a dying company.

Exactly, positive details are almost always better than negative ones.

If you've ever seen the "generate a burger without pickles" conversations, it's clear that including the keyword "pickle" is causing them to show up. If you try "a burger with only [set of toppings]," you'll get far better results.

>AI is not so elegant, to make a comparison similar to Berry, as the humble, sterile Microsoft Word.

This is much like Berry drawing the line at a typewriter instead of a computer. To call a computer "sterile, untouched, factory made" and still use a typewriter is comical. Now let me tell you why etching into stone is the best medium.

People can have their preferences, but this kind of "I'm old fashioned and here's why that's better" posts are just nostalgia bait.

For papers that make grand claims, they usually have poignant limitations. In this paper, it's clear that the conclusion is extrapolated from a small set of observable information. That's usually the recipe for poor conclusions, and they are up front about where their findings sit.

That's not to say these findings aren't valuable though. Their blog post summary is just a bit more hype inducing than the underlying paper.

The way I feel about this is that the emergent properties of LLMs seem to reflect our own human faculties. Whether that's because we built them in our image or whether this is a common mode of consciousness is definitely outside the scope of this paper.

Assuming they have been transcribed, yes. The key idea that makes LLMs special is the attention mechanism. Maintaining attention over volumes of data is boring for most humans.

Also, to be pedantic, just taking about LLMs in this context is a tad reductive. There are many deep learning models involved in archival work that aren't language models.

I encourage you to read into this post for more context on what I mean: https://news.ycombinator.com/item?id=48675179

"There's nothing to apologize to. They're weights."

  - The Meat