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Don't have anything relevant to say except to make a fun note that we can change your second sentence, keeping it correct, while increasing its ambiguity. If we

Don't have anything relevant to say except to make a fun note that we can change your second sentence, keeping it correct, while increasing its ambiguity. If we restate it as: Are they talking about basically getting the most out of the current ML type systems? Since Deep learning is a subset of machine learning, the sentence retains correctness but there are now two equally valid interpretations. Okay, I do have something relevant to say. I don't see what advantage there is in raw sensory data streams, models can be trained off-line to operate on sensor streams just fine. What we actually want are systems that learn adaptively and on-line. To do that well, they'd need to also be data efficient.

resu_nimda 9y ago
models can be trained off-line to operate on sensor streams just fine. I mentioned this in another comment, but I don't know that we can train these models just fine, a human can get a lot more information out of an audiovisual stream than a rudimentary transcription of recognized speech, objects and/or text. If we make these models more sophisticated to capture more information (e.g. body language, tone, context), we have to decide how that information is structured and communicated to the "higher level meaning interpretation" stage. No matter what, their output is going to be more rigidly structured and will contain less information than the raw stream. The extent to which the sensory processing model captures the human-recognizable information in the stream is the extent to which you have created an intelligent system. There is some form of this structuring and reducing happening inside our brains, but we will never get machines to do that if we continue curating structured data sets. We, the researchers, are using our human intelligence to process raw sensory data and put it into a nice format for the AI. They need to be able to do that themselves.
- IanCal 9y ago
  > we have to decide how that information is structured and communicated to the "higher level meaning interpretation" stage. Do we? I'm not convinced. I've joined different sensory inputs before and just glommed together the top of two nets, I didn't have to create any of my own representations. > but we will never get machines to do that if we continue curating structured data sets Curated datasets are important though. Want your machine to understand more about the world around it? Then you need high quality inputs in formats you can load in. These data also need to be licensed correctly. > They need to be able to do that themselves. We don't chuck kids out into the wilderness and expect them to come back as a useful member of society. We have a huge range of inputs specifically curated to help (from toys and shows to school curricula). Later on with specialisation we pay for extremely carefully selected data, presented in a specific order! Creating high quality datasets is vital for really anything from niche specialist systems to large general ones.

resu_nimda 9y ago

models can be trained off-line to operate on sensor streams just fine. I mentioned this in another comment, but I don't know that we can train these models just fine, a human can get a lot more information out of an audiovisual stream than a rudimentary transcription of recognized speech, objects and/or text. If we make these models more sophisticated to capture more information (e.g. body language, tone, context), we have to decide how that information is structured and communicated to the "higher level meaning interpretation" stage. No matter what, their output is going to be more rigidly structured and will contain less information than the raw stream. The extent to which the sensory processing model captures the human-recognizable information in the stream is the extent to which you have created an intelligent system. There is some form of this structuring and reducing happening inside our brains, but we will never get machines to do that if we continue curating structured data sets. We, the researchers, are using our human intelligence to process raw sensory data and put it into a nice format for the AI. They need to be able to do that themselves.

IanCal 9y ago
> we have to decide how that information is structured and communicated to the "higher level meaning interpretation" stage. Do we? I'm not convinced. I've joined different sensory inputs before and just glommed together the top of two nets, I didn't have to create any of my own representations. > but we will never get machines to do that if we continue curating structured data sets Curated datasets are important though. Want your machine to understand more about the world around it? Then you need high quality inputs in formats you can load in. These data also need to be licensed correctly. > They need to be able to do that themselves. We don't chuck kids out into the wilderness and expect them to come back as a useful member of society. We have a huge range of inputs specifically curated to help (from toys and shows to school curricula). Later on with specialisation we pay for extremely carefully selected data, presented in a specific order! Creating high quality datasets is vital for really anything from niche specialist systems to large general ones.