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Generative AI is excellent at churning out prose good enough for targeted scams, fake news and search engine optimization, and there is plenty of commercial val

Generative AI is excellent at churning out prose good enough for targeted scams, fake news and search engine optimization, and there is plenty of commercial value in all three of those. However, none of those three will transform humanity as we know it, they'll just make life a bit worse for everybody.

seanhunter 3y ago
It's also really excellent at a bunch of other things. For example I am currently doing self-directed study in maths. It turns out chatgpt is very good at explaining lots of things if you prompt correctly. You need to check things yourself and be on the lookout for plausible but wrong explanations, but it's like having a patient pure maths friend to work on things with - your friend won't get everything right either after all. Something with real commercial potential is what microsoft released (I think today) [1] which is a sort of wizard thing that accellerates various azure gpt-powered standard deployments that do things like set up private ephemeral instances that connect to your enterprise data sources behind your firewall. This has enormous potential given how difficult it is in most large enterprises to actually join data sources together, find basic information etc. Think of an automated helpdesk that can draw on all of the stuff in all of the various disjointed systems in most big companies. That has the potential to be quite transformative to the workplace for a lot of people. In general I think this bar of "transforming humanity" is just arbitrary and way too high for any technology. You could look at the map on your phone and say "that's all very well but will it transform humanity?" well no. It won't make toast either, but it's quite useful sometimes. Just as overinflated expectations and hype are unhelpful I think it's easy to be cynical and miss important tech developments just because we impose arbitrary standards on them that other technologies didn't have to meet on their way to adoption. [1] https://github.com/microsoft/azurechatgpt https://github.com/microsoft/azurechatgpt
- seanhunter 3y ago
  Here's an example of this kind of self-study chat btw (so you can see the pros and cons) https://chat.openai.com/share/d1428952-84e6-42be-9e0a-2ce62b132068 https://chat.openai.com/share/d1428952-84e6-42be-9e0a-2ce62b... It's interesting that in the final matrix example it somehow messed up the Latex by forgetting to put \begin{bmatrix} at the front which is why the formatting goes bonkers. It's also kind of cheesy that it chose a diagonal matrix rather than having to find the roots of the characteristic polynomial but any case you get the idea hopefully and can see how this would be helpful when you're trying to learn this stuff yourself? I'm certainly finding it great as I work through textbooks etc to chat through concepts in this way to check my understanding and drill into things.
- mark_l_watson 3y ago
  I also have had positive experiences in studying or learning with ChatGPT. For example, I am not a very good Haskell programmer but I am enthusiastic. I was looking at some of my old code that I hadn’t looked at in years. Honestly, I was a bit confused by my old code so I pasted it into ChatGPT and had it explain it. ChatGPT gave a great summary and explained the library calls I was making. All in all, in less than 2 minutes my head was back in my old code.

seanhunter 3y ago

It's also really excellent at a bunch of other things. For example I am currently doing self-directed study in maths. It turns out chatgpt is very good at explaining lots of things if you prompt correctly. You need to check things yourself and be on the lookout for plausible but wrong explanations, but it's like having a patient pure maths friend to work on things with - your friend won't get everything right either after all. Something with real commercial potential is what microsoft released (I think today) [1] which is a sort of wizard thing that accellerates various azure gpt-powered standard deployments that do things like set up private ephemeral instances that connect to your enterprise data sources behind your firewall. This has enormous potential given how difficult it is in most large enterprises to actually join data sources together, find basic information etc. Think of an automated helpdesk that can draw on all of the stuff in all of the various disjointed systems in most big companies. That has the potential to be quite transformative to the workplace for a lot of people. In general I think this bar of "transforming humanity" is just arbitrary and way too high for any technology. You could look at the map on your phone and say "that's all very well but will it transform humanity?" well no. It won't make toast either, but it's quite useful sometimes. Just as overinflated expectations and hype are unhelpful I think it's easy to be cynical and miss important tech developments just because we impose arbitrary standards on them that other technologies didn't have to meet on their way to adoption. [1] https://github.com/microsoft/azurechatgpt https://github.com/microsoft/azurechatgpt

seanhunter 3y ago
Here's an example of this kind of self-study chat btw (so you can see the pros and cons) https://chat.openai.com/share/d1428952-84e6-42be-9e0a-2ce62b132068 https://chat.openai.com/share/d1428952-84e6-42be-9e0a-2ce62b... It's interesting that in the final matrix example it somehow messed up the Latex by forgetting to put \begin{bmatrix} at the front which is why the formatting goes bonkers. It's also kind of cheesy that it chose a diagonal matrix rather than having to find the roots of the characteristic polynomial but any case you get the idea hopefully and can see how this would be helpful when you're trying to learn this stuff yourself? I'm certainly finding it great as I work through textbooks etc to chat through concepts in this way to check my understanding and drill into things.
mark_l_watson 3y ago
I also have had positive experiences in studying or learning with ChatGPT. For example, I am not a very good Haskell programmer but I am enthusiastic. I was looking at some of my old code that I hadn’t looked at in years. Honestly, I was a bit confused by my old code so I pasted it into ChatGPT and had it explain it. ChatGPT gave a great summary and explained the library calls I was making. All in all, in less than 2 minutes my head was back in my old code.