Especially this 2nd half! Feels like the progress of AI has accelerated ten-fold. Likely due to the increased interest and investments being poured into the field. Competition drives innovation!

Historically speaking? No idea. Personally? Yes. This was the first year that so much progress took place even normal people I know that don't follow the industry were talking about it.

Yeah I was surprised to see that too

Although I agree with the sentiment, it's important to note that VC funding for AI startups is down ~50% this year compared to last year.

For me, yes. 2022 marks the first year that I use Artificial Intelligence as an integral part of my activities. I am using Midjourney to generate ideas, concept art and even finished pieces in my work. I am using GPT 3 to write essays, and come up with concepts.

This year is the first time I am using AI as an actual substitute of something that I would have previously ask a human (skilled and creative) coworker to do.

The field is increasingly dominated by established tech giants so there is less opportunity for start ups. The cost of entry is high. In addition, it’s a mistake to just focus on US companies. AI research is happening globally and China, in particular, is battling the U.S. for AI supremacy.

I think historically it will be remembered when AI starts to make impact for general populace. Random street people has not even heard about these advances which we have today. History always remembers big happenings so I would say the moment general populace start to really losing jobs will be the year which will be remembered. It might be some big catastrophe/event related to AI which marks the moment. Something which causes shock to whole world. Something like collapse of soviet union, 11/9, 2008 financial crisis etc. It has to be something big.

It will probably be known at the “Roaring 20’s” for AI

What's TTI and TTV?

Text to image and text to video

I would say that’s been the case since 2013 onwards. It all started with image recognition 9 years back.

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I wonder how AI in 2022 is compared to in 2017 and to 2012?

I think, as with a lot of new technologies, following years will upstage this year's progress so that in retrospect this year in particular feels less significant. Like the early days of the internet. The internet itself has been a major foundational technology, but most people probably don't remember the first year it was introduced as a time of great significance relative to what it became in the following years. If in several years time AI has revolutionised medical science and we all have AI assistants with humanlike intelligence, coding is obsolete and anyone can make a game just by telling the AI what to do, etc, most people will probably barely remember the days when people who playing around with basic image generators. Even now, the image generators I was using months ago that couldn't manage humans at all feel like a distant memory compared to what I can do now.

I wonder what AI 2023 will be …

I think GPT 4 will be the big push that will give even non technical people a use for AI in there day to day lives.

For me, AlphaGo vs Lee Sedol in spring 2016 felt like more of a turning point in a technological sense. But I can see how the whole AI art thing happening this year could be more significant for the general public.

Good point

The AI don't think so... yet.

indeed this year has been very eventful

2023 is going to be wild

You might be right. By the time 2030 kicks in, there will probably be a wide spread disruption of society like we saw in 1929-30.

Completely agree.

This year is when we get to start using AI tools directly and it feels like more and more tools are becoming available. It has also started taking more of my mind space and predicting where it will go.

I don't think yet, this year has been great but we haven't had a big mainstream jump yet, something like when the iphone first dropped.

This year's progress will seem slow in comparison to 2023.

I really think there is no comparison between those in that AI art is far more important. GO is extremely complex, but working out a huge number of deeply complicated heuristics for playing is a difficult, but easy to envision process.

In the course of a year encoding so much of humanity's cultural output that one can generate original expressions of art that are just as complex and creative as what is made by humans? Surely that is on a completely different level?

I'm interested to see what you think though, and for example, what you think about the results in, say, starcraft, in comparison to GO.

This

I was super fascinated with Dalle and Stable Diffusion, and told all my friends. To my surprise, several of them became quite obsessed with it! cool stuff

I agree. Technology is growing exponentially at such a fast rate now. New advancements and discoveries in computers, science and biological systems are being created literally every week which used to take span of months or years. Both exciting and scary to be honest

2012 is the start of the AI revolution. It simply took a decade for the effects to start being felt.

This only imply that you joined this sub in 2022.....or you are an artist.... If you are an old user in this sub, will you considering 2022 is the first big thing?

But I actually admit that AI art (and LLM) is a bigger thing than AlphaFold, imo, drawing pic is a more powerful ability than predict the protein struture. I just want to ask, what is the next ability that AI will obtain?

In 2020, about a half of guys in this sub is pessimism, and half of post is not talking about AI, so, I think in last two year, it is actually a turning point in this sub.

Maybe it was 2017, the year when "Attention is all you need" was published. This changed deep learning completely and everything we do today uses transformers.

Maybe state of the art foundation models are hard to do without deep pockets, but applications built on these models are 100x easier to make now than before. I mean, you just tell it what you want. That's lowering the entry barrier for the public. Everyone can get in on it.

Used to be necessary to collect a dataset, create a custom architecture, train many models, pick the best, iterate on the dataset, etc to get to the same results. The work of months or years compressed into a prompt. It's not just artists that are being automated, traditional ML engineers too.

The only solution for ML eng is to jump on top of GPT-3 and its family, no more work left to do at a lower level. I am talking from personal experience, 4 years old project with 5 engineers and 3 labellers was solved at first sight by GPT-3 with no tuning. Just ask it nicely, it's all you have to do now.

That's easy.

Neural nets before 2012 were small, weak and hard to train. But in 2012 we got a sudden jump in accuracy by 10% in image classification. In the next 2 years all ML researchers switched to neural nets and all papers were about them. This period lasted 5 years in total and scaled models from the size of an "ant" to that of a "human". Almost all fundamentals of neural nets were discovered during this time.

But in 2017 we got the transformer, this led to unprecedented scaling jumps, from the size of a "human" to that of a "city". By 2020 we had GPT-3 and today, just 5 years later from transformer, we have multiple generalist models.

On a separate arc, reinforcement learning, we got the first breakthroughs in 2013 with Deep Q-Learning from DeepMind on Atari games and by 2015 we had AlphaGo. Learning from self play has been proven to be amazing. There is cross pollination between large language models and RL. Robots with GPT-3 strapped on top can do amazing things. GPT-3 trained in self-play like AlphaGo can improve its ability to solve problems. It can already solve competition level problems in math and code.

The next obvious step is a massive video model, both for video generation and for learning procedural knowledge - how to do things step by step. YouTube and other platforms are full of video, which is a multi-modal format of image, audio, voice and text captions. I expect these models to revolutionise robotics and desktop assistants (RPA), besides media generation.

Agree. I came here to say this. 2012, with Andrew Ng's effort to use a neural network on a large farm using CPUs for the compute to find cats in youtube video was the first "modern" AI attempt. As I recall all that compute, and their accuracy was like 60%. Vs YOLO which can run in real time on one GPU and find cats by breed.

That was the start. But 2022 does feel like something special. It might be the "knee" of the S curve - when things start to go exponential. Hard to say, due to the recession throttling the money flow into AI it may slow things down a little.

I first heard about the internet in early 1993 and it was a sudden change in perception like this year.

I don't think I knew the internet existed until I was a 10 year old in 1997. The 4th grade classroom computers had the internet and nobody knew wtf it was and ignored it in favor of Oregon Trail and Chip's Challenge.

I was five at the time, so admittedly I wasn't the most tech informed. The AOL days were my first experience with it.

we won’t look back on 2022 specifically, but it will definitely be thought as the beginning of the ai era. starting in 2020 more or less imo

Nope. I think the year is either 2023 or 2024, definitely not 2025.

If we consider "actual" AI as in AI in the real world, like, not living in some DARPA facility or someone's IP garden, like, population facing AI, then yes, dates I mention above for "AI revolution".

I think it's a good candidate. Timelines definitely shrunk a lot in 2022.

Other candidates are 2012 (start of deep learning), 2017 (transformer), 2020 (GPT-3) and 2023 (GPT-4 + other stuff).

2nd half looked more impressive, but actually, 1st half was much more impactful (Chinchilla, Gato, Minerva, AlphaCode).

2023 hopefully the year all of this becomes useful in day-to-day life
I'm really hopeful for Adept AI

no because finally the scientific community is starting to agree that there’s no intelligence in artificial intelligence.

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Well said

“Not a hotdog”

Agreed, AlphaGo was the turning point. GPT3/Dall-E are very good compared to previous machine approaches, but are nowhere near human level quality. As opposed to AlphaGo, better than the world's best in a field that we never really expected to beat top humans in.

That was later. This was kitty/no kitty.

The issue with something like StarCraft is that it's a real-time game and so you can get to superhuman levels of play just by being fast enough. I suspect that serious effort put into a GOFAI approach to StarCraft could produce an AI that can beat human players in general, not by making the AI smarter, but by making it just smart enough and leveraging its ridiculous micro advantage. For this reason, turn-based games are always a more meaningful testbed for intelligence.

On the other hand, Go has a problem in that it's a perfect-information game, which I suspect makes it easier for existing AI techniques to handle. StarCraft on the other hand has a fog-of-war where players must guess at (and remember) what other players are doing, and I suspect that games with limited information like that are a better test for real intelligence. The ideal game for testing intelligence would be a highly complex and nuanced turn-based game with a fog-of-war in place.

/imagine prompt: AI in 2023

> The issue with something like StarCraft is that it's a real-time game and so you can get to superhuman levels of play just by being fast enough.

AlphaStar limited the APM capable of the agent to prevent this.

I've been a casual viewer for about 5 years so I haven't been paying too much attention, but this is the first time I've ever seen anything like the rate of progress we're seeing now, breakthroughs are happening multiple times a month

I'll tell you the big thing I noticed: this is the year a lot of people regained hope for ai as up until the stable diffusion release, the meme was that these models would be forever gated by large corporations. SD changed all that and got the open source community hyped that we don't have to be controlled by our corporate overlords afterall and perhaps all of the biggest innovations in the future will come from open source.

I find it really interesting that the groundbreaking thing here wasn't DALLe or any corporate owned image AI but open source product. We should remember this and start to question how much patents and ownership really hinder our progress. For example 3D printers has basically stuck in time for 5 years and no notable progress has happened because big corporations are gatekeeping patents.

https://twitter.com/CathieDWood/status/1591562714299912192

> If inflation is unwinding, as we believe, then we could be heading back to the future, the Roaring Twenties, the last time several general purpose technologies evolved at the same time: telephone, electricity, and the internal combustion engine. The setup is remarkably similar!

>5:44 PM · Nov 12, 2022

Agree 100%. I'm ready for the SD of 3d printing to arrive.

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I think 2023 is when all the fun tests and games we play with AI finally start to turn into incredibly powerful and useful tools.

I feel like AI is today where the Automobile was in 1900.

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