767 karma · joined April 28, 2021
Don't want to sign up to one multinational behemoth? Well, your choice is to sign up to one other multinational behemoth.
Also, many exisiting sentiment analysis tools have a lot of research behind them that can be referenced when interpreting the results (known confounds etc). I don't think there is yet an equivalent for the LLM approach
If so, building this could be quite complex depending on the domain. In the legal field even one simple word that is changed can have large consequences.
A person 'doing boring things' isn't necessarily a bored person. The experience of being bored is entirely subjective. One person staring at paint dry could be driven insane but another could be meditating upon the physical experience of the passage of time.
The saying 'bored people are boring people' isn't supposed to be taken literally. It is as logically fallible as any other quip in English, I think the difference with this one is that it is used in a more directly negative and judgmental way (and often perceived as such by the recipient).
My example demonstrated the orthogonal nature of your argument and that it doesn't hold true in all circumstances, and according to your criteria of only needing one example to disprove an assertion, then yours has been dispelled as well.
I'll add that I also dislike the adage 'only boring people get bored'. However I think there is some truth to it, perhaps a more accurate phrasing would be 'people who are always bored are boring people '
I know which person I'd rather converse with, wealth doesn't really matter.
For example if you were asked to draw and color a basketball, how would you approach the task without 'seeing' something in your mind?
A story I've heard first hand is that after the program, department staff can discuss diplomacy in the target language, but struggled to order a coffee!
If LLMs were trained using data from these services then it's possible that this will be challenged in court. Should the court rule in favour of the content services, then the LLMs may need to be re-trained (or likely negotiate compensation).
The comparison isn't US$1000 exchanged to Somali Shillings and looking at purchasing power. A Somali quartet is not earning anywhere near $1000 after conversion, and the price of many other products and services would be much cheaper compared to the US as well.
Nor is the comparison $1000 US dollars in 2024 and looking at what that same nominal amount would purchase in distant history.The quartet would be earning much less in nominal amounts, but the nominal amounts of everything are cheaper as well.
Here are some hard figures. Using the year 1800 as the comparison.
USA economy $1000 in 2024 = $40 in 1800. A 2388% increase attributed to inflation.
String quartet gig in 2024 = $1000 For 1800 it's hard to find earnings for anything outside of labor and manufacturing however the wage for a teacher was around $1 per day.
If we make a big assumption that teachers and musicians pay were equivalent, then it would appear that the purchasing power of a string quartet has 10x the purchasing power today after accounting for inflation $40 / 4 persons / $1 = 10).
10x is quite consistent across all occupations that I can find equivalents for (skewed heavily toward labouring and manufacturing, very few services are reported in 1800).
So in that sense the string quartet isn't an outlier, for the most part we are all enjoying around 10x the purchasing power since 1800.
One day's earnings now is equivalent to 10 days in 1800. This is great, but not anywhere near 1 day = 1 year.
Estimating inflation back to 1100 would be very difficult .. as would determining day wages, the economic system was very different.
Sources: Inflation - https://www.officialdata.org/us/inflation/1800?
Labor wages in 1800 - https://babel.hathitrust.org/cgi/pt?id=wu.89071501472&seq=17...
Current wages - bis.gov
Adjust for inflation and it would look much more reasonable. There are also four people earning wages in a quartet.
The player can interact freely with the NPC rather than through predetermined conversation decision trees, potentially driving a lot of unique emergent gameplay.
Downsides are that it is a lot quicker just to skip through conversations with the decision tree format and having to think about and type in questions could get tiresome. Another downside is players jailbreaking the LLM...
My takeaway from the author's example is that Google has set up a system that is incentivising actions leading to worse outcomes for both users (frustrating search experience) and advertisers (whose ad spend is not being well spent).
Google has no incentive to improve the situation - because google has an effective monopoly.
However, once the site owner decided to use Adsense then in order to use this service the site needed to change according to Google's requirements.
The point being made is that in order to serve ads the site owner had to add a lot of useless information irrelevant to what was driving traffic to the site in the first place.
Why did the first attempt get rejected, yet the final attempt after making the website objectively worse gets accepted?
The useless information that needed to be added to the site contributes to the decline in quality many people are noticing when using google search nowadays. This article provides a very interesting explanation for this decline.
When OKRs are tied to revenue, no executive is going to sign off on a change that reduces it