As soon as Apple announced its plans to inject generative AI into the iPhone, it was as good as official: The technology is now all but unavoidable. Large language models will soon lurk on most of the world’s smartphones, generating images and text in messaging and email apps. AI has already colonized web search, appearing in Google and Bing. OpenAI, the $80 billion start-up that has partnered with Apple and Microsoft, feels ubiquitous; the auto-generated products of its ChatGPTs and DALL-Es are everywhere. And for a growing number of consumers, that’s a problem.
Rarely has a technology risen—or been forced—into prominence amid such controversy and consumer anxiety. Certainly, some Americans are excited about AI, though a majority said in a recent survey, for instance, that they are concerned AI will increase unemployment; in another, three out of four said they believe it will be abused to interfere with the upcoming presidential election. And many AI products have failed to impress. The launch of Google’s “AI Overview” was a disaster; the search giant’s new bot cheerfully told users to add glue to pizza and that potentially poisonous mushrooms were safe to eat. Meanwhile, OpenAI has been mired in scandal, incensing former employees with a controversial nondisclosure agreement and allegedly ripping off one of the world’s most famous actors for a voice-assistant product. Thus far, much of the resistance to the spread of AI has come from watchdog groups, concerned citizens, and creators worried about their livelihood. Now a consumer backlash to the technology has begun to unfold as well—so much so that a market has sprung up to capitalize on it.
Obligatory “fuck 99.9999% of all AI use-cases, the people who make them, and the techbros that push them.”
Except those things didn’t really solve any problems. Well, dotcom did, but that actually changed our society.
AI isn’t vaporware. A lot of it is premature (so maybe overblown right now) or just lies, but ChatGPT is 18 months old and look where it is. The core goal of AI is replacing human effort, which IS a problem wealthy people would very much like to solve and has a real monetary benefit whenever they can. It’s not going to just go away.
Can you trust whatever AI you use, implicitly? I already know the answer, but I really want to hear people say it. These AI hype men are seriously promising us capabilities that may appear down the road, without actually demonstrating use cases that are relevant today. “Some day it may do this, or that”. Enough already, it’s bullshit.
Yes? AI is a lot of things, and most have well-defined accuracy metrics that regularly exceed human performance. You’re likely already experiencing it as a mundane tool you don’t really think about.
If you’re referring specifically to generative AI, that’s still premature, but as I pointed out, the interactive chat form most people worry about is 18 months old and making shocking levels of performance gains. That’s not the perpetual “10 years away” it’s been for the last 50 years, that’s something that’s actually happening in the near term. Jobs are already being lost.
People are scared about AI taking over because they recognize it (rightfully) as a threat. That’s not because they’re worthless. If that were the case you’d have nothing to fear.
ChatGPT didn’t begin 18 months ago, the research that it originates from has been ongoing for years, how old is alexnet?
I’m referencing ChatGPT’s initial benchmarks to its capabilities to today. Observable improvements have been made in less than two years. Even if you just want to track time from the development of modern LLM transformers (All You Need is Attention/BERT), it’s still a short history with major gains (alexnet isn’t really meaningfully related). These haven’t been incremental changes on a slow and steady march to AI sometime in the scifi scale future.
AlexNet is related, it was the first use of consumer gpus to train neutral networks no?
No, not even remotely. And that’s kind of like citing “the first program to run on a CPU” as the start of development for any new algorithm.
As far as I can find out, there was only one use of GPUs prior to alexnet for CNN, and it certainty didn’t have the impact alexnet had. Besides, running this stuff on GPUs not CPUs is a relevant technological breakthrough, imagine how slow chayGPT would be running on a CPU. And it’s not at all as obvious as it seems, most weather forecasts still run on CPU clusters despite them being obvious targets for GPUs.
What? Alexnet wasn’t a breakthrough in that it used GPUs, it was a breakthrough for its depth and performance on image recognition benchmarks.
We knew GPUs could speed up neural networks in 2004. And I’m not sure that was even the first.
Okay, so some of the advances that chatGPT uses (consumer GPUs for training) are even older? 😁
Why stop there? The digital computer was introduced in 1942 and methods for solving linear equations were developed in the 1600s.