gbnwl

Is it really that confusing? Heart rate is correlated with oxygen consumption which is correlated with metabolic activity. The wearable would see the increased heart rate when a person is moving with a heavy backpack versus moving without one.

Now whether we can do that accurately with today’s wearables and without calibration to each individual is up in the air as far as I’m concerned. But it seems strange to me that you’re confused as to how we could even directionally infer these things.

The past two days have been awful as someone who uses Railway.

I like seige tanks

Reddit thread from about a month ago where creator introduced this: https://www.reddit.com/r/starcraft/comments/1wqdabw/i_made_t...

What people espousing these kinds of opinions really mean is “I’m not afraid of AI taking MY job”

This is a nit but his name is actually Erik Satie not Eric Satre.

It seems like the entire thought process you’re trying to sell hinges on the idea that OpenAI reported the attack first. Did you forget that it was actually HuggingFace that reported it first, and OpenAI only stepped forward latter?

It’s just a boring and unhelpful complaint that afaict largely serves to soothe the commenters ego rather than point at anything insightful that’s useful or predictive. Point me to your favorite “next token predictor” comment that was actually insightful or predictive. You have years of material to draw from.

I just prefer HN comments to be better reflections of reality. There is an unspoken expectation here that people here know what they’re talking about especially when it comes to technical matters. The rise of LLMs has given way to a HN branded populism that willingly denies reality as well. “Next token predictor” truthism is just so dumb and completely ignores the reality of what these tool are able to do. Smash that upvote button every time it feels good if you want but it’s just a meaningless take at this point. It won’t help you predict anything that’s coming.

Since we disagree on the present let’s informally do a “remind me 2 years” to this discussion and see what’s happened then.

Fair so let me be clear. I’m whining because the “next token predictor” reductionist point of view has been wrong and is only growing more wrong with time. Clearly these things can do things that actually matter. Do you disagree?

Are they useful or not? Will they continue changing the world or not? People who choose one way or the other for describing them typically fall on one side or the other in these questions imo. What do you think? Will these next token predictors change the world or not?

Every day I wake up and open HN.

“LLM has made legitimate mathematical discoveries” —> Wow the rate of progress is amazing. Highly upvoted.

“LLM does something not good” -> Does everyone else not realize LLMs are just dumb next token predictors? Highly upvoted.

So tired of this discourse and this site.

There are articles with far fewer upvotes and comments ranking higher on the front page right now, despite being the same age or older than this one. HNs opaque ranking system at it again.

Everyday? Which 10 problems were solved by mathematics grad students in the past 10 days?

OK I’ll grant that it’s not your obligation to be my search function (despite you making the wild assertion in the first place), so instead can you just point us to the latest grad student solved problem of this level that you know of?

I think the fundamental difference between our assumptions is you believe prompts to be optimized for tasks rather than model-task pairs. The only elaboration I can give you is empirical observations and model providers own guidance (as someone has already linked here). I'm pretty sure you probably have specific parts of your prompts that came about due to specific failure modes observed in your evals of running the task against first model. These vary across models in my experience, and it's always worth redoing this calibration process.

Experienced similar between 5.4-mini vs 5.6-luna in our own pipelines but after spending some time on prompt optimization and testing out various reasoning effort levels 5.6-luna was well worth it. Did you just replace model selection while keeping everything else in place or spend some time on evaling with newer prompts etc?

We can assume (outside of Ollama) that they meant the strongest model from each lab. If you limit yourself to just looking at the literal strings in the list, literally none of these are models. What model is "Deepseek" or "GPT"?

How is this any different than what we have already? We've had this ability for ages (6+ months, decades in the AI world), you can literally today easily prompt CC or Codex to use subagents to accomplish tasks and they'll do it well. My entire workflow is one top level orchestrator chat creating tickets to dispatch to subagents to implement, and other subagents to verify. Why is this being sold as a new thing? Have HN users never tried tried asking CC or Codex to use subagents?

As usual HN posters are hyper aware of other's credentials while ignoring that their BS in CS (if that) doesn't magically qualify them to assess everything in every domain.

"I'm a software engineer, I'm sure if I had the time to study Neuroscience, I'd figure out what all of these researchers failed to realize all these decades! I (alone) have the magic of critical and logical thinking"

Hm first Shazeer and now Jumper, DeepMind getting hollowed out this week.

Don't forget that the denominator (total number of outstanding shares) will be increased by this as well. So even if the market cap reacted exactly one to one like you're proposing the per share price wouldn't stay constant necessarily.

No they didn't, they predict they'll get that much. Also worth noting the prediction assumes running at MXFP4/FP8 quantization.

Frontier as in "Frontier Model" is a legitimate vocabulary term you should probably be aware of in 2026. It's not something the author made up or chose randomly, it's common parlance in the space.

Can you really look yourself in the mirror and say with a straight face that fundamentally nothing has changed about the relationship between the US and its allies? Do you really think Europeans will be quick to forgive the wrongs of this administration? They’ve lost faith in our political system and will, rightfully so, do everything in their power to disentangle with us. The problem with your theory is that they know even if Trump is replaced by someone closer to European social values, our electorate could just as easily completely reverse course in 4 years. It literally already happened. Bush never threatened to annex European territory with military force as far as I can tell. But I understand why in these chaotic times you’d want to gravitate towards hopeful fictions.

Probably a better way to phrase it would be keeping “pace“. Yes, they are still behind but by about the same amount as they always have, they aren’t drifting further behind. Like two marathon runners, one a a mile ahead, but both maintaining the same mile time.

I mean yes? Considering that we're here reading the news that they've agreed to this.

What exactly is the intuition behind taking something inherently linear like a sequence of 100 days and presenting it as a graph with no information given about the rationale or reasoning behind the edges.

The symbol is not the thing. The map is not the territory. Ceci n'est pas une pipe.

Of course the motivation makes sense on the surface. What I'm getting at is that the supply of capital vs the supply of potential "control of the future" plays feels incredibly imbalanced. Money seems to be so desperate to move into AI it's lost all prudence (the particular people and company mentioned in the OP nonwithstanding, maybe they do deserve 1B).

"not wanting to risk missing out" is essentially just FOMO right? "Smart" money has feels more like FOMO money these days. We literally have shoe companies savying they're going to pivot to AI and having their market cap increase in multiples as reward.