It’s one thing to say something like: AI will enable lights out manufacturing and replace virtually all employees in that sector.

To which those employees respond: What will happen to us?

And they are told: things will be great, you won’t need to work in the factories any longer, and we will have no shortage of goods.

Do you see the missing link there? They might ask: “What happens to those goods? What happens to me? Do I get given the goods? Are the goods sold and then I am paid a stipend? I’m hungry. Will I still need to buy things? Okay, if so, but I have no money because I was fired.”

So even when it chokes or stumbles on a command, the kind of frustration the user expresses when correcting it feels natural and part of the game even.

To simply write this off as “they deserve it” would be a mistake, and is unproductive.

He began the conversation by saying: “so as far as I know there’s two kinds of ai, open ai and closed ai…”

This speaks to your point, the people are confused.

My dog often gets misidentified as a restricted breed. This used to make apartment hunting difficult because, occasionally, the property manager would visually ID the dog breed as banned, I’d have to go to the vet and get paperwork, potentially gene testing, arguing she wasn't, it was a whole thing.

But, recently, the apartment I moved into had an online portal where I had to upload a photo and it would identify the breed to determine if it was approved.

I correctly assumed the portal was using an LLM for this purpose. I wrote a script which submitted different photos of my dog to the major LLM providers until it found a photo which all the LLMs would identify as the correct breed.

I simply submitted that photo and, as expected, passed with flying colors.

Sometimes these strategies are used to provide LLMs with a greater understanding of your codebase to improve code generation results.

Additionally, techniques which allow humans to visualize the shape of code are being explored as engineers become less familiar with the specific implementation.

AI labs, I await your offers ;)

- Henry Kissinger

I often found that I learned more about the candidate by the way they phrased their Google searches and how they selected and explored sites for information than from the actual solution they produced.

I admit I was struck when I first heard someone use that shorthand in conversation at a party. It was the moment I knew that for better or worse LLMs use had permeated deep into regular life.

I watched someone ask Claude to replace all occurrences of a string instead of using a deterministic operation like “Find and Replace” available in the very same VSCode window they prompted Claude from.

The US bugged the “toilet partitions” of the Russian embassy in D.C. during its construction[0] and the FBI built a tunnel under it for espionage purposes in the 80s[1].

[0] https://www.cia.gov/readingroom/document/CIA-RDP90-00965R000...

[1] https://web.archive.org/web/20100514112651/http://articles.o...

On the one side you have some diplomats who really are quite capable career foreign policy wonks, appointed in a manner which appears to be meritocratic.

On the other side you have folks appointed, like you mention, as a kind of patronage.

Traditionally, it has been that the softer counterparties (Friendly countries, European allies, small island nations, etc) are staffed with patrons while the more difficult or geopolitically sensitive relationships are manned by professionals, but this is certainly not always true, and one can find many counterexamples.

The second paragraph is discussing drinking habits for all US adults.