I teach English to Korean AI engineers so I am tangently in that industry.
It's not a super sexy high paying field. It's a grind in a dark room that leads most of the engineers into depression, eating disorders, and addiction.
That it’s smart. It works way better on trained models with controlled data sets.
With real world data it’s using on the web it can’t really discern good data so it’s kind of just an average idiot that spends way too much time on Facebook. It was probably ‘smarter’ in 2011 with Watson. We aren’t any closer to intelligence, we just have a more autonomous idiot with way more data to pull from and a lot more processing power.
That it’s smart. It works way better on trained models with controlled data sets.
With real world data it’s using on the web it can’t really discern good data so it’s kind of just an average idiot that spends way too much time on Facebook. It was probably ‘smarter’ in 2011 with Watson. We aren’t any closer to intelligence, we just have a more autonomous idiot with way more data to pull from and a lot more processing power.
I work in venture capital and I can tell you 99% of “AI” companies are not AI at all. Simple pdf scrapers are called AI. Simple VBA programs are called AI. It’s the most overused term ever.
I work in venture capital and I can tell you 99% of “AI” companies are not AI at all. Simple pdf scrapers are called AI. Simple VBA programs are called AI. It’s the most overused term ever.
A1 is literally destroying athletics with the wave light pacing and other technology being used to help people run times they shouldn't be able to run
It's not a super sexy high paying field. It's a grind in a dark room that leads most of the engineers into depression, eating disorders, and addiction.
I was a network engineer for 20 years, now retired. Oh, as rothbard said, it’s not exactly a glamorous job. It seems like making good money from home remoting into the little devices that run the internet is a cool job. You work at night, you work alone, and you deal with the most hideously boring data you can imagine. And when you report to the testing center to take your engineering exams, you look around the waiting room and see the most stressed out people in the world. I mean, people actually kill themselves for failing these exams.
The biggest misconception is that AI, AS IT IS NOW CONSTITUTED, will become sentient. What I mean is the large language models, the generative AI’s like ChatGPT, are actually beginning to reach the limits of the data they can learn (like literally, all the data in the entire world). They are now beginning to use simulated data and problems are developing with feedback loops of contaminated data.
OK, enough with the gobbledygook talk. Plain English time: It’s looking like generative AI is collapsing long before it reaches the sentience everyone was talking about.
But, hundreds of thousands of my IT peers have already lost their jobs due to this narrow AI being REALLY GOOD at very specific tasks. That’s only going to increase.
What no one is talking about is the growth of self-learning devices. Weird, strangely shaped robots that learn how to move and do things. The misconception here is these will just replace factory workers. Maybe initially, but, I think this is the vein of AI where true sentience may emerges. Little robots learning about the world just like we did, only, much, much faster.
I do Angel Projects with friends and peddle what works to Venture Capital and R&D divisions of big companies. AI is not artificial it's real electronic based intelligence. The big change from the 1960s/1970s Internet/Apollo days is that AI belongs to the world while 50 years ago the former came out of L.A./Frisco aerospace and defence industry. Today everyone can download the open source for python3, anaconda3, google, cuda, pytorch, tensorflow, stable studio, and so on. With open source there's AI projects at every tech company, college, and Starbucks in the world. Plus millions of zoom based projects spanning contributors across the globe.
I don't work in the field yet, but I fear that I will soon. I graduated top of my class in economics and stat, and then got my MBA and an advanced degree in pure math. I work as an analyst for a major REIT, but a lot of my time is figuring out how to automate my job. I see my role being done by a bot in fewer than 5 years. So then I will have to find a new job.
>> Tell us the biggest misconceptions about AI! <<
Misconception: AI is about machines exhibiting aspects of human intelligence. Truth: AI is a generic marketing term that covers a variety of machine learning technologies. It describes the field of computers doing things that require intelligence if done by humans. It explicitly isn't about machines exhibiting human intelligence - a subtle, but important, distinction.
Misconception: Machines are now exhibiting more signs of intelligence than in the past. Truth: When people talk about recent AI advances, they're typically referring to the movement of AI models from classification and prediction ("That meatbag bought a bed. Probably, he loves beds. Recommend him 148 more beds.") to the creation of content ("Write a biblical verse in the style of the King James bible explaining how to remove a peanut butter sandwich from a VCR."). So exhibiting a different type of machine intelligence rather than "more" intelligence. Another subtle, but important, difference.
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One key limitation going forward with AI will be our power grids. AI is eventually projected to require 5 times more electricity than we already are capable of producing. We will hit a wall with AI but it won't be the tech itself. It'll be the limits of our already strained power grids. And, at least in the US, governments don't seem to be in a huge hurry to create significant new generative sources of power. (Cue tired debates about nuclear, pollutive, and renewable but limited/flawed energy sources)
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