Apparently, there was only so much IP to steal
this post was submitted on 13 Nov 2024
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I hope it all burns.
Nice, looking forward to it! So much money and time wasted on pipe dreams and hype. We need to get back to some actually useful innovation.
Fingers crossed.
Yay
Seems to me the rationale is flawed. Even if it isn't strong or general AI, LLM based AI has found a lot of uses. I also don't recognize the claimed ignorance among people working with it, about the limitations of current AI models.
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Sigh I hope LLMs get dropped from the AI bandwagon because I do think they have some really cool use cases and love just running my little local models. Cut government spending like a madman, write the next great American novel, or eliminate actual jobs are not those use cases.
The tech priests of Mars were right; death to abominable intelligence.
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Oh nice, another Gary Marcus "AI hitting a wall post."
Like his "Deep Learning Is Hitting a Wall" post on March 10th, 2022.
Indeed, not much has changed in the world of deep learning between spring 2022 and now.
No new model releases.
No leaps beyond what was expected.
\s
Gary Marcus is like a reverse Cassandra.
Consistently wrong, and yet regularly listened to, amplified, and believed.
Theres no bracing for this, OpenAI CEO said the same thing like a year ago and people are still shovelling money at this dumpster fire today.
AI was 99% a fad. Besides OpenAI and Nvidia, none of the other corporations bullshitting about AI have made anything remotely useful using it.
Absolutely not true. Disclaimer, I do work for NVIDIA as a forward deployed AI Engineer/Solutions Architect—meaning I don’t build AI software internally for NVIDIA but I embed with their customers’ engineering teams to help them build their AI software and deploy and run their models on NVIDIA hardware and software. edit: any opinions stated are solely my own, N has a PR office to state any official company opinions.
To state this as simply as possible: I wouldn’t have a job if our customers weren’t seeing tremendous benefit from AI technology. The companies I work with typically are very sensitive to CapX and OpX costs of AI—they self-serve in private clouds. If it doesn’t help them make money (revenue growth) or save money (efficiency), then it’s gone—and so am I. I’ve seen it happen; entire engineering teams laid off because a technology just couldn’t be implemented in a cost-effective way.
LLMs are a small subset of AI and Accelerated-Compute workflows in general.
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I would say LLMs specifically are in that ball park. Things like machine vision have been boringly productive and relatively un hyped.
There's certainly some utility to LLMs, but it's hard to see through all the crazy over estimations and being shoved everywhere by grifters.
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