101–110 of 127 posts
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By all means; I also work at a start-up. That doesn't mean that everyone here does, or is interested in doing so, or will have the necessary background. All I ask of you is to present information in the spirit of the XKCD 10,000: https://xkcd.com/1053/
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>There isn’t a single day where I don’t have to deal with software that’s broken but no one cares to fix Since when does this have anything to do with AI? Commercial/enterprise software has always been this way. If it's not going to cost the company in some measurable way issues can get ignored for years. This kind of stuff was occurring before the internet exists. It boomed with the massive growth of personal comput…
> Commercial/enterprise software has always been this way All software is this way. The only way something gets fixed is if someone decides it's a priority to fix it over all the other things they could be doing. Plenty of open source project have tons of issues. In both commercial and open source software they don't get fixed because the stack of things to do is larger than the amount of time there is to do them.
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Are they really? Is this one of those "just because people say so" beliefs? The countries adopting these the most are declining economies. It's places that are looking for something to do after there's no more oil left to drill up and export. You know where fossil fuel use is booming? Emerging (e.g., growing) economies. Future scarcity of such resources will only make them more valuable and more profitable. Yes, this…
Isn't it China that adopting renewable more rapidly than anywhere else and also has a booming economy? Although they're also investing in non-renewable energy sources. My understanding is that "green" investment portfolios which were intended as "ethics over return on investment" have actually outperformed petrochemical stocks for years now, and it's more ideology than economics that's preventing further investment (…
Renewable energy in the form of wind and solar are direct subsidies for the oil and gas industry. Wind and solar are intermittent and you have to build a proportional amount of natural gas power plants to maintain a stable grid. Every new PV farm creates demand for another natural gas power plant.
The IRA subsidies for renewables were extremely lucrative. That’s why you see renewable energy projects in Texas. Government money spends just as good as profits from oil and gas.
“Renewable” energy exists where the subsidies are, and in some rare niche cases like geothermal power in Iceland. Many of these wind farms won’t produce more energy than it took to create them.
More than anything, I want to get back the era when the users were the customers, not the product.
Very few people are willing to pay cash for the things that they currently pay for in attention and data.
I wonder about the world where, instead of investing in AI, everyone invested in API . Like, surfacing APIs, fostering interoperability... I don't want an AI agent, but I might be interested in an agent operating with fixed rules, and with a limited set of capabilities. Instead we're trying to train systems to move a mouse in a browser and praying it doesn't accidentally send 60 pairs of shoes to a random address in…
LLMs offer the single biggest advance in interoperability I've ever seen. We don't need to figure out the one true perfect design for standardized APIs for a given domain any more. Instead, we need to build APIs with just enough documentation (and/or one or two illustrative examples) that an LLM can help spit out the glue code needed to hook them together.
> ... we need to build APIs with just enough documentation (and/or one or two illustrative examples) that an LLM can help spit out the glue code needed to hook them together.
If a developer relies on client code generated by an LLM to use an API, how would they know if what was generated is a proper use of said API? Also, what about when lesser used API functionality should be used instead of more often used ones for a given use-case?
If the answer is "unit/integration tests certify the production code", then how would those be made if the developer is reliant upon LLM for code generation? By having an LLM generate the test suite?
And if the answer is "developers need to write tests themselves to verify the LLM generated code", then that implies the developer understands what correct and incorrect API usage is beforehand.
Which begs the question; why bother using an LLM to "spit out the glue code" other than as a way to save some keystrokes which have to be understood anyway?
Earlier quoted context omitted.
LLMs offer the single biggest advance in interoperability I've ever seen. We don't need to figure out the one true perfect design for standardized APIs for a given domain any more. Instead, we need to build APIs with just enough documentation (and/or one or two illustrative examples) that an LLM can help spit out the glue code needed to hook them together.
> LLMs offer the single biggest advance in interoperability I've ever seen. > ... we need to build APIs with just enough documentation (and/or one or two illustrative examples) that an LLM can help spit out the glue code needed to hook them together. If a developer relies on client code generated by an LLM to use an API, how would they know if what was generated is a proper use of said API? Also, what about when less…
This pattern works really well.
"other than as a way to save some keystrokes which have to be understood anyway?"
It's exactly that. You can save so many keystrokes this way.
>There isn’t a single day where I don’t have to deal with software that’s broken but no one cares to fix Since when does this have anything to do with AI? Commercial/enterprise software has always been this way. If it's not going to cost the company in some measurable way issues can get ignored for years. This kind of stuff was occurring before the internet exists. It boomed with the massive growth of personal comput…
Thought exercise: has any of the money Apple has spent integrating AI features produced as much customer good-will as fixing iOS text entry would? One reason for paying attention to quality is that if you don't, over time it tarnishes your brand and makes it easier for competitors to start cutting into your core business.
FaceID has proven pretty popular tools.
Investing 100 years of open-source Blender does not give them any fraction of monopoly.
Even if scientists present 100's of proposals for computation (optical, semiconductor,...) they will specifically invest in technologies that are hard to decentralize: growing monocrystalline ingots, reliant on dangerous chemicals, ... if there is no money in easily decentralizable processor manufacture, then it could easily be duplicated then proposals to pursue it would basically be equivalent to begging investors to become philantropists. Quite a naive position.
It's in the interest of the group to have quality software, manufacturing technologies, ... so the onus is on representatives of the group of taxpayers to invest in areas investors would prefer to see no investment in (even if someone else invests it). Perhaps those "representatives" are inept or malicious or both.
There is real value being created by creating interactive summaries of the human corpus. While it is taking time to unlock the value, it will definitely come.
>There isn’t a single day where I don’t have to deal with software that’s broken but no one cares to fix Since when does this have anything to do with AI? Commercial/enterprise software has always been this way. If it's not going to cost the company in some measurable way issues can get ignored for years. This kind of stuff was occurring before the internet exists. It boomed with the massive growth of personal comput…
Thought exercise: has any of the money Apple has spent integrating AI features produced as much customer good-will as fixing iOS text entry would? One reason for paying attention to quality is that if you don't, over time it tarnishes your brand and makes it easier for competitors to start cutting into your core business.