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Advancements in machine learning for machine learning

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Re: Advancements in machine learning for machine learning

#21

Post by greatpostman »

Der_Einzige wrote: post #17
greatpostman wrote: post #6

Earlier quoted context omitted.

I really don’t people will be programming like we do today in five years

They’re making fun of your typo, but you’re right. Pretty much every software job in 5 years will be an AI job. This rustles a lot of feathers, but ignoring the truth will only hurt your career. I think the era of big tech paying fat stacks to a rather larger number of technical staff will start to wane as well. Better hope you have top AI paper publications and deep experience with all parts of using LLMs/whatever f…

I give it two years. Salaries will drop like a rock.

Re: Advancements in machine learning for machine learning

#22

Post by educaysean »

m3kw9 wrote: post #19
RyanShook wrote: post #4

The pace that ML seems to be advancing right now is amazing. I don’t believe in the singularity but it’s changing software and then society in ways no one can predict.

I want to see it come out with a cure for a disease that is tough to cure first. Singularity itself is pointless unless it benefits humans which is mainly in health/lower suffering

I'd say advancement in mathematics, computer science, and heck, even art is far from "pointless". Why does it feel like goalposts get moved everytime there is a significant progress in AI?

Re: Advancements in machine learning for machine learning

#23

Post by kccqzy »

sbierwagen wrote: post #20
GreedClarifies wrote: post #9

How’s Gemini looking?

It is interesting how persistently dominant GPT-4 is: https://twitter.com/lmsysorg/status/1735729398672716114 Off the top of my head, I can think for at least five foundation models (Llama, Claude, Gemini, Falcon, Mistral) that are all trading blows, but GPT is still a head above them and has been for a year now. Transformer LLMs are simple enough that, demonstrably, anyone with a million bucks of GPU time can make o…

Their only special sauce is the first-mover advantage. Then it attracted users (data), brand recognition, talent and became a positive feedback cycle.

Re: Advancements in machine learning for machine learning

#24

Post by smabie »

SirMaster wrote: post #11
greatpostman wrote: post #6

Earlier quoted context omitted.

I really don’t people will be programming like we do today in five years

I don’t see why not. I like programming how I do now. I don’t plan to stop. People do lots of things manually that machines have been able to do for a long time.

And they generally get outcompeted sooner or latter.

All disciplines evolve over time and those who fail or refuse to keep up will be left behind.

Re: Advancements in machine learning for machine learning

#25

Post by tommychillfiger »

wait_a_minute wrote: post #8
RyanShook wrote: post #4

The pace that ML seems to be advancing right now is amazing. I don’t believe in the singularity but it’s changing software and then society in ways no one can predict.

This + FunSearch make it seem like Singularity is imminent. https://deepmind.google/discover/blog/funsearch-making-new-d...

At great risk of sounding completely ignorant, this approach is basically what I thought the point of machine learning was - cleverly using feedback loops to improve things automatically. The thing that sticks out to me as particularly cool about FunSearch is the use of programs as inputs/outputs and the fact that they managed to automate feedback.

I'm pretty naive in terms of granular understanding here as I am barely proficient in Python, to be clear, but when I daydream about things you could solve with machine learning/AI, this is the approach I always think of and I guess is how I thought it already worked. Load it up with the best information we have currently, define the desired results as clearly as possible, implement some form of automatic feedback, and let it run iteratively until it produces something better than what you had before.

Is this a case of "well no shit, but actually implementing that effectively is the hard part"? Is it being able to quickly apply it to a wide variety of problems? I guess I'm trying to understand whether this is a novel idea (and if so, what parts are novel), or if the idea has been around and it's a novel implementation.

Re: Advancements in machine learning for machine learning

#26

Post by euos »

greatpostman wrote: post #6
RyanShook wrote: post #4

The pace that ML seems to be advancing right now is amazing. I don’t believe in the singularity but it’s changing software and then society in ways no one can predict.

I really don’t people will be programming like we do today in five years

I’ve been programming since middle school. That would be 30 years. Nothing really changed much. C++ is incrementally more convenient but fundamentally the same. Code editors are same. Debugger are same. Shell is same.

I am certain in 30 years everything will still be the same.

Re: Advancements in machine learning for machine learning

#27

Post by flatline »

Der_Einzige wrote: post #17
greatpostman wrote: post #6

Earlier quoted context omitted.

I really don’t people will be programming like we do today in five years

They’re making fun of your typo, but you’re right. Pretty much every software job in 5 years will be an AI job. This rustles a lot of feathers, but ignoring the truth will only hurt your career. I think the era of big tech paying fat stacks to a rather larger number of technical staff will start to wane as well. Better hope you have top AI paper publications and deep experience with all parts of using LLMs/whatever f…

LLMs are cool and will continue to change society in ways we cannot readily predict, but they are not quite that cool. GPT3 has been around for a little bit now and the world has not ended or encountered a singularity. The models are expensive to run both in compute and expertise. They produce a lot of garbage.

I see the threat right now to low-paid writing gigs. I’m sure there’s a whole stratum of those they have wiped out, but I also know real live humans still doing that kind of work.

What developers may use in five years is a better version of Copilot trained on existing code bases. They will let developers do more in the time they have, not replace them. Open source software has not put us all out of jobs. I foresee the waning of Big Tech for other reasons.

Re: Advancements in machine learning for machine learning

#28

Post by impegh »

educaysean wrote: post #22
m3kw9 wrote: post #19

Earlier quoted context omitted.

I want to see it come out with a cure for a disease that is tough to cure first. Singularity itself is pointless unless it benefits humans which is mainly in health/lower suffering

I'd say advancement in mathematics, computer science, and heck, even art is far from "pointless". Why does it feel like goalposts get moved everytime there is a significant progress in AI?

I read this same empty “goalposts” lament multiples times a day when reading this website, and though I know what the words mean I’m confused what you all think they mean.

https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...

Is this just some performative grousing or do you really think what has been developed to date is “artificial intelligence”?

These comments all conveniently fail to define their author’s goalposts that apparently have been reached or surpassed. What were yours?

Re: Advancements in machine learning for machine learning

#29

Post by vitorgrs »

kccqzy wrote: post #23
sbierwagen wrote: post #20

Earlier quoted context omitted.

It is interesting how persistently dominant GPT-4 is: https://twitter.com/lmsysorg/status/1735729398672716114 Off the top of my head, I can think for at least five foundation models (Llama, Claude, Gemini, Falcon, Mistral) that are all trading blows, but GPT is still a head above them and has been for a year now. Transformer LLMs are simple enough that, demonstrably, anyone with a million bucks of GPU time can make o…

Their only special sauce is the first-mover advantage. Then it attracted users (data), brand recognition, talent and became a positive feedback cycle.

GPT4 was created before most feedback cycle. They had GPT4 ready before ChatGPT launch.

If I recall right, GPT4 got done in October. After that, it was RLHF and safety work (Bing starts using GPT4 publicly in February, a month earlier than official launch)

Re: Advancements in machine learning for machine learning

#30

Post by melagonster »

m3kw9 wrote: post #19
RyanShook wrote: post #4

The pace that ML seems to be advancing right now is amazing. I don’t believe in the singularity but it’s changing software and then society in ways no one can predict.

I want to see it come out with a cure for a disease that is tough to cure first. Singularity itself is pointless unless it benefits humans which is mainly in health/lower suffering

This is impossible, we can makesure that more possible scenario is that most of people lose job and starve. it is not sure whether we can reach to a society have UBI.
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