My company has hitched itself to the AI hype train, but they're talking about NLP and conversational UIs not data analysis.
This AI Boom Will Also Bust
81–90 of 320 posts
Re: This AI Boom Will Also Bust
#82I've read every comment in this thread and its filled mostly with peoples self congratulatory intellectual views. Nobody, not even Robin Hansen himself has given a good, detailed argument as to why the current progress in Machine learning will stop.
Re: This AI Boom Will Also Bust
#83Here's why the pipes metaphor is a bad one: we already are doing everything we can and ever will do with pipes. Pipes have been around for a really long time, we know what they are capable of, we've explored all of their uses. OTOH, the current progress in AI has enabled us to do things we couldn't do before and is pointing towards totally new applications. It's not about making existing functionality cheaper, or inc…
The interaction of a system of many small pipes to accomplish computation is an active area of research, and new improvements are used in devices pretty routinely. (Really, the behavior of networks of pipes in general is still pretty open, if you want instantaneous details rather than statistical averages.)
Along similar lines, HFLP systems and systems that require laminar flow to be effective are both more recent techniques that come out of a better understanding and engineering of pipes. HFLP upgrades are a current engineering change over very recent and modern high-pressure systems.
Re: This AI Boom Will Also Bust
#84Earlier quoted context omitted.
And before you do mundane data science on your structured data, you should figure out if there is a better way to get cleaner raw data, more data, as well as more accurate data. For example, I predict stereo vision algorithms will die out soon, including deep-learning-assisted stereo vision. It's useful for now but not something to build a business around. Better time-of-flight depth cameras will be here soon enough.…
ToF depth being single POV and depth infered from successive frames ?
No, that would also qualify as "AI algorithm wizardry" as dheera puts it. Instead it's just a hardware sensor that measures the time at which light arrives at each pixel. Knowing the speed of light you can calculate the depth of each pixel.
Re: This AI Boom Will Also Bust
#85When I was at Watson this is the first thing I told every customer: before you start with AI are you already doing the more mundane data science on your structured data? If not, you shouldn't go right away for the shiny object. This said I still believe the article is mistaken in its evaluation of potential impact (and its fuzzy metaphore of pipes). Unstructured or semi-structured or dirty data is much more prevalent…
So the basic criticism here is than Hanson, in suggesting firms clean up their data and then apply simple analytics to it, is defining away the problem that ML solves?
Re: This AI Boom Will Also Bust
#86The more I get into machine learning and deep learning it seems like there is an incredible amount of configuration to get some decent results. Cleaning and storing the data takes a long time. And then you need to figure out exactly what you want to predict. If you predict some feature with any sort of error in your process the entire results will be flawed. There are a few very nice applications of the AI techniques…
>" however most data sets don't fit well with machine learning"
Could you elaborate on why this is?
Re: This AI Boom Will Also Bust
#87The more I get into machine learning and deep learning it seems like there is an incredible amount of configuration to get some decent results. Cleaning and storing the data takes a long time. And then you need to figure out exactly what you want to predict. If you predict some feature with any sort of error in your process the entire results will be flawed. There are a few very nice applications of the AI techniques…
> In the real world, most things are in a maybe state rather than yes/no. Not to get too far afield, but I disagree with this on a certain philosophical level. All states are yes/no. All states of all things should result in a yes/no and be differentiable, with enough data. This doesn't speak to the practicality of that but as far as I can tell the theoretical potential is huge, almost infinite even.
Isn't this just shifting the ambiguity into your choice of state definitions, rather than the states themselves?
Re: This AI Boom Will Also Bust
#88[deleted]
Re: This AI Boom Will Also Bust
#89Ml comes in big in cleaning up the data and making recommendations on what to look at.
Re: This AI Boom Will Also Bust
#90When I was at Watson this is the first thing I told every customer: before you start with AI are you already doing the more mundane data science on your structured data? If not, you shouldn't go right away for the shiny object. This said I still believe the article is mistaken in its evaluation of potential impact (and its fuzzy metaphore of pipes). Unstructured or semi-structured or dirty data is much more prevalent…
And before you do mundane data science on your structured data, you should figure out if there is a better way to get cleaner raw data, more data, as well as more accurate data. For example, I predict stereo vision algorithms will die out soon, including deep-learning-assisted stereo vision. It's useful for now but not something to build a business around. Better time-of-flight depth cameras will be here soon enough.…
Stereo vision is obviously highly effective in biology as it has independently evolved a great many times. Time-of-flight may be poised for a renaissance, but it scales badly and is active, not passive. Stereo vision, and its big brother light fields, are far more general and are certainly not going to "die out".