If you spend time with the higher-tier (paid) reasoning models, you’ll see they already operate in ways that are effectively deductive (i.e., behaviorally indistinguishable) within the bounds of where they operate well. So not novel theorem proving. But give them scheduling constraints, warranty/return policies, travel planning, or system troubleshooting, and they’ll parse the conditions, decompose the problem, and run through intermediate steps until they land on the right conclusion. That’s not "just chained prediction". It’s structured reasoning that, in practice, outperforms what a lot of humans can do effectively.

When the domain is checkable (e.g., dates, constraints, algebraic rewrites, SAT-style logic), the outputs are effectively indistinguishable from human deduction. Outside those domains, yes it drifts into probabilistic inference or “reading between the lines.” But to dismiss it all as “not deduction at all” ignores how far beyond surface-level token prediction the good models already are. If you want to dismiss all that by saying “but it’s just prediction,” you’re basically saying deduction doesn’t count unless it’s done by a human. That’s just redefining words to try and win an Internet argument.

They do quite a bit more than that. There's a good bit of reasoning that comes into play and newer models (really beginning with o3 on the ChatGPT side) can do multi-step reasoning where it'll first determine what the user is actually seeking, then determine what it needs to provide that, then begin the process of response generation based on all of that.

This is not a surprise, just one more data point that LLMs fundamentally suck and cannot be trusted.

Huh? LLMs are not perfect and are not expert-level in every single thing ever. But that doesn't mean they suck. Nothing does everything. A great LLM can fail to produce a perfect original proof but still be excellent at helping people adjust the tone of their writing or understanding interactions with others or developing communication skills, developing coping skills, or learning new subjects quickly. I've used ChatGPT for everything from landscaping to plumbing successfully. Right now it's helping to guide my diet, tracking macros and suggesting strategies and recipes to remain on target.

LLMs are a tool with use cases where they work well and use cases where they don't. They actually have a very wide set of use cases. A hammer doesn't suck just because I can't use it to cut my grass. That's not a use case where it excels. But a hammer is a perfect tool for hammering nails into wood and it's pretty decent at putting holes in drywall. Let's not throw out LLMs just because they don't do everything everywhere perfectly at all times. They're a brand new novel tool that's suddenly been put into millions of peoples' hands. And it's been massively improved over the past few years to expand its usefulness. But it's still just a tool.

If I as china, first think I would do would make those factories nonoperational. Those factories are needed by the US, to combat china. China has their own chip fabs.

Its less that trump is in office, and more that he is being giving powers and almost unchallenged while most of the left complains about elon being hitler or other dumb tangents.

I swear they are letting trump consolidate power, because they "know" after his idiocy they have the election in the bag, and want that power themselves.

Most of the restaurants I go to don't even serve alcohol. Of course, I live in Utah, which is at the very bottom of the alcohol consumption per capita chart. Here restaurants all have normal fountain drinks, water, and then a wide array of specialty drinks, many of which are just normal sodas with some stuff added in.

Being a restaurant owner is hard. The margins on most food is slim. The margins on drinks (alcoholic or not), on the other hand, are ridiculous. There's a reason why sit down restaurants start you with something to drink, and why fast food places bundle sodas. To a very real extent these businesses make their money upselling you from drinking plain water.

While I do agree that we don't need as much as the protein industry claims, that ~50 g/day is minimum, and doesn't not take into account rebuilding, muscle growth, etc.

I would suggest people losing weight up their protein a bit to help prevent loss of muscle as well as people actively doing physical exercise where they want to get stronger.

Also the older you are, the more you need to maintain, and for people young and growing, need more too.

I'm trying to keep mine in the 60-75 range, if I get to going back to gym I will be eating more like 70-100 range.

"I've reduced it from 9,000 head to about 5,000 because I need less heads," Benioff said.

Fewer. Not less.

Not only that, but depending on where you work, there are tax implications for employers if buildings are empty more than X amount of time (if they own the real estate). The less people in a building, the more the taxes.

Wow, metaverse. What a uniquely tried-and-failed concept to be spending so much time on.

Stop posting AI slop. If you can't be bothered to do the work yourself and therefore be able to verify it's correct just don't post.

How embarassing for you.

You went from a plausible if naive viewpoint straight to an ad homineim attack when challenged. What a loser.

Yes, I'm positive. You seem to have a passing knowledge of this, but obviously not a complete one. None of thoe things you mentioned are capable of getting firmware and configuration from the manufacturer to program a new replacement module or update modules with new firmware. "Just replace all of your car's electronics with things that can be flashed with linux software" is not a reasonable or sane solution to anything. Again, more white noise nerd rage over linux and the state of how things actually work in the world, not limited to your parent's basement.

Because the solution I presented works 100% of the time. Ther rest of your post is just white noise nerd rage.