Row 59915

Row ID: 59915 | Dataset Entry | Axioma AXP Content Repository

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Self-driving cars are mostly this slow to get adopted due to regulations. There are definitely some rough edges in the tech, but even with those edges self-driving cars are better than most of human drivers. But fusion and fission have been "30 years until viable" for the past, like, 40+ years. We are making good progress on that front, but there are always unexpected hurdles pushing us back.

Generative AI, on the other hand, has made some *insane* progress in the past six years. I've been working with NLP for a while, and if you showed experts in 2017 ChatGPT-4 and asked when do they think it would be possible, the median answer would've been 2040 at best—probably closer to 2050. No one could've predicted that an architecture invented for translation would lead to the Holy Grail of Large Language Models. Are LLMs and LMMs still flawed? Absolutely. But I, and most people I know, were in awe when GPT-2 was revealed, and in outright horror from GPT-3 and beyond (Gato, Flamingo, etc.).

FieldValue
text Self-driving cars are mostly this slow to get adopted due to regulations. There are definitely some rough edges in the tech, but even with those edges self-driving cars are better than most of human drivers. But fusion and fission have been "30 years until viable" for the past, like, 40+ years. We are making good progress on that front, but there are always unexpected hurdles pushing us back. Generative AI, on the other hand, has made some *insane* progress in the past six years. I've been work…
label r/openai
dataType comment
communityName r/OpenAI
datetime 2024-05-23
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Raw Record

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  "text": "Self-driving cars are mostly this slow to get adopted due to regulations. There are definitely some rough edges in the tech, but even with those edges self-driving cars are better than most of human drivers. But fusion and fission have been \"30 years until viable\" for the past, like, 40+ years. We are making good progress on that front, but there are always unexpected hurdles pushing us back.\n\nGenerative AI, on the other hand, has made some *insane* progress in the past six years. I've been working with NLP for a while, and if you showed experts in 2017 ChatGPT-4 and asked when do they think it would be possible, the median answer would've been 2040 at best—probably closer to 2050. No one could've predicted that an architecture invented for translation would lead to the Holy Grail of Large Language Models. Are LLMs and LMMs still flawed? Absolutely. But I, and most people I know, were in awe when GPT-2 was revealed, and in outright horror from GPT-3 and beyond (Gato, Flamingo, etc.).",
  "label": "r/openai",
  "dataType": "comment",
  "communityName": "r/OpenAI",
  "datetime": "2024-05-23",
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}
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