I never said it discovered new mathematics (edit: yet), I implied it can reason. This is clear example of reasoning to solve a problem

You need to dig deeper of how that "reasoning" works, but you got misled if you think it does what you say it does.

You can also use 9/11 + GWOT in place of the dotcom bubble, for 'society reshaping disaster crisis'

So uh, silly me, living in the disaster hypercapitalism ers, being so normalized to utterly.world redefining chaos at every level, so.often, that i have lost count.

This comment really exemplifies the ignorance around AI. It's not fancy autocorrect, it's fancy autocomplete.

You do realise that everyone actually educated in statistical modeling knows that you have no idea what you're talking about, right?

As programmer. It’s helping my productivity. And look I am SDET in theory I will be the first to go, and I tried to make an agent doing most of my job, but it always things to correct.

But programming requires a lot of boilerplate code, using an agent to make boilerplate files so I can correct and adjust is speeding up a lot what I do.

I don’t think I can replaced so far, but my team is not looking to expand the team right now because we are doing more work.

Can you elaborate? How is this not reasoning? Define reasoning to me

Deep research independently discovers, reasons about, and consolidates insights from across the web. To accomplish this, it was trained on real-world tasks requiring browser and Python tool use, using the same reinforcement learning methods behind OpenAI o1, our first reasoning model. While o1 demonstrates impressive capabilities in coding, math, and other technical domains, many real-world challenges demand extensive context and information gathering from diverse online sources. Deep research builds on these reasoning capabilities to bridge that gap, allowing it to take on the types of problems people face in work and everyday life.

Note that I'm not one of the people talking about it on X, I don't know who they are. I just linked it with a simple "this looks like reasoning to me".

(openai.com)

Surprise, surprise, motherfxxxers. Now you'll have to re-hire most of the people you ditched. AND become humble. What a nightmare!

nope, they will be hiring outsourced employees instead, AI=ALWAYS indians. on the very same post on reddit, they already said that is happening already. its going to get worst.

the ceo and csuites did, they hyped all up and was excited for its innovation.

That is more American focused though. Sure I heard about 9/11 but I was 8 and didn't really care because I wanted to go play outside.

yup, i was looking some terms, or conditions up, it was USING stuff froma blog, and sites that just stole from other sites.

We had that recently. 10% redundant and pay freeze because we were not profitable enough. Guess what, morale tanked and they only slightly improved it by giving everyone +10 days holiday.

they will rehire, but it will be outsourced for lower wages, at least thats what the same posts on reddit of the same article is discussing.

It's fancy autoincorrect

While that contains the word "reasoning" that does not make it such. If this is about the new "reasoning" capabilities of the new LLMS. It was if I recall correctly, found our that it's not actually reasoning, just doing a fancy footwork appear as if it was reasoning, just like it's doing fancy dice rolling to appear to be talking like a human being.

As in, if you just change the underlying numbers and names on a test, the models will fail more often, even though the logic of the problem stays the same. This means, it's not actually "reasoning", it's just applying another pattern.

With the current technology we've gone so far into this brute forcing the appearance of intelligence that it is becoming quite the challenge in diagnosing what the model is even truly doing now. I personally doubt that the current approach, which is decades old and ultimately quite simple, is a viable way forwards. At least with our current computer technology, I suspect we'll need a breakthrough of some kind.

But besides the more powerful video cards, the basic principles of the current AI craze are the same as they were in the 70s or so when they tried the connectionist approach with hardware that could not parallel process, and had only datasets made by hand and not with stolen content. So, we're just using the same approach as we were before we tried to do "handcrafted" AI with LISP machines in the 80s. Which failed. I doubt this earlier and (very) inefficient approach can solve the problem, ultimately. If this keeps on going, we'll get pretty convincing results, but I seriously doubt we'll get proper reasoning with this current approach.

Either spell the word properly, or use something else, what the fuck are you doing? Don't just glibly strait-jacket language, you're part of the ongoing decline of the internet with this bullshit.

They can't reason. LLMs, the tech all the latest and greatest still are, like GPT5 or whatever generate output by taking every previous token (simplified) and using them to generate the most likely next token. Thanks to their training this results in pretty good human looking language among other things like somewhat effective code output (thanks to sites like stack overflow being included in the training data).

Generating images works essentially the same way but is more easily described as reverse jpg compression. You think I'm joking? No really they start out with static and then transform the static using a bunch of wave functions they came up with during training. LLMs and the image generation stuff is equally able to reason, that being not at all whatsoever

Investors and executives still show strong interest in AI, hoping that ongoing advances will close these gaps. But the short-term outlook points to slower progress than many expected.

Doesn't sound like that's gonna happen in the near future