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designer1one OP t1_j2ci3t6 wrote

It has been a wild year for generative AI! o_o For the Year 2023, I look forward to seeing exponential growth in various forms of text-to-x models (text-to-video, text-to-3D, text-to-audio, text-to-…). I also hope to see improvements in the factual grounding of large language models. Oh and there’s GPT-4.

What are some things you would like to see in AI progress for Year 2023?

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bluehands t1_j2cyz5r wrote

Your list of "text-to-X" highlights for me the need for "X-to-text". Captioning is nice but are names attached, is meaning extracted? (it maybe that I am just not aware of the state of the art)

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currentscurrents t1_j2czmdk wrote

Basically anything you can generate, you can also classify. Most of the image generators use CLIP for guidance, so if they can generate a sad face (and they can), CLIP can tell you whether or not a face is sad.

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cptkong t1_j2dhc41 wrote

I'm the most excited about AI code generation.

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ureepamuree t1_j2dkaci wrote

I'd recommend checking out the highly-cited papers on the topics of Meta Reinforcement Learning and Skill-based Reinforcement Learning, these two areas are chiefly focused around domain generalization.

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comparmentaliser t1_j2efyj9 wrote

Technical papers and models aside, this year marked a turning point in commercialisation and public access. The ease of access and quality also prompted some vigorous public debate about the ethics of generative art, the meaning of an ‘ai artist’, and the occasional debate about the future of film cinema.

I also think the general public have been blown away with the capabilities across imaging, writing and code, and there’s probably a few sectors and industries will be having a very hard think about their next move in the coming months.

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visarga t1_j2elbvk wrote

Please don't post articles that are not open to read.

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