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Meh. Crashes come when there was no real business value. I use AI all day and I’m sure I’m not the only one.
There was a lot of business value during the dotcom boom and we still had a crash. The question is how many AI companies have strong fundamentals and will survive, vs the ones that have weak fundamentals and will die if/when the investment money dries up.
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> gpt5 has always been about making a "collection of models" work together and not about model++. No, it wasn’t. Have you read and listened to Altman’s hype around GPT-5 from a year ago? They changed the narration after the 4.1 flop, which they thought would be GPT-5, and it seems some people fell for it. > Capabilities ~90-110% of their top tier old models at 4-6x lower price Maybe they finally implemented the DeepS…
> No, it wasn’t. I replied below in this thread with the specific post, 6 months ago. > After that, a top goal for us is to unify o-series models and GPT-series models by creating systems that can use all our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks. > In both ChatGPT and our API, we will release GPT-5 as a system that integrates a lot of our technology,…
Obviously it's not.
What a bad article. I mean how biased can you be, to put the first big quote from someone who wrote a book called "The AI con". Come on! This feels like the "deepseek r1 is the death of nvda" of 6 months ago. Someone is making a play, and whoever wrote this article fell for it. gpt5 has always been about making a "collection of models" work together and not about model++. This was announced what, a year ago? And they…
> This was announced what, a year ago? Source? Others are calling out this as being incorrect, so a source would help people evaluate this claim. Personally I'm much more likely to believe that AI companies are moving the goalposts rather than making significant leaps forward.
After the crash, tech "industry leaders" will struggle to explain why/how they were conned into believing that intelligence was a simple database function with some probability and statistics sprinkled on top.
But who's to say humans are any different than simple databases with probability and statistics firing neurons?? /s
In engineering school, it was easy to spot the professors who taught this way. I avoided them like the plague.
The author isn't exactly a thought leader in the space, or really any space for that matter. Opinion worth nothing.
Never quite realized how much I disliked the term "Thought Leader" until I read it 5x in the comments responses of this thread.
As it happens LLMs work comparatively well with code. Is this because code does not refer (a lot) to the outside world and fits well to the workings of a statistical machine? In that case the LLMs output can also be be verified more easily by inspection through an expert, compiling, typechecking, linting and running. Although there might be hidden bugs that only show up later.
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Sounds more like you're helping Claude build a robot.
I have more hands and a larger context window. It's a collab(/s). But it's cool that I can do it more or less solely with that tool and not necessarily use Google or other resources(obviously for any source, from Google to the Encyclopedia Britannica, one must evaluate the quality of the information).
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"Thought leader" isn't an actual title (or at least it shouldn't be). In my mind, its simply someone who you recognize as having the expertise worth paying attention to.
It’s a title that is given to people to get them to present at junkets, a modern socially and legally acceptable way to bribe people. No one should take them seriously.
Meh. Crashes come when there was no real business value. I use AI all day and I’m sure I’m not the only one.
95 per cent of organisations are getting zero return from AI according to MIT - https://news.ycombinator.com/item?id=44956648 - August 2025 State of AI in Business 2025 [pdf] - https://news.ycombinator.com/item?id=44941374 - August 2025 https://web.archive.org/web/20250818145714/https://nanda.med... > Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of o…
https://venturebeat.com/ai/why-do-87-of-data-science-project...
A comment in a previous thread stuck with me said something like "AI is successful because nothing else interesting is happening". That rings true and I suspect the bubble won't burst until something else comes along to steal the show.
Meanwhile Claude is helping me build a robot and is also writing the code that runs its subsystems but okay. Sure, I could do it all myself(maybe?) but not nearly as quickly or in the interstitial moments of life.