HN user
I literally had a non technical family member ask me last week about “AI”.
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.
This is already underway.
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.
Interest has risen in tandem with the popularity of LLMs. I have worked on these sorts of things as part of internal tooling.
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.
I majored in both CS and Philosophy. I think the very first paper I submitted for my phi 101 course was on the topic of machine ethics.
AI labs, I await your offers ;)
The notion that Mussolini made the trains run on time is a myth, a bit of state propaganda.
“Before the Freedom of Information Act, I used to say at meetings, 'The illegal we do immediately; the unconstitutional takes a little longer.' But since the Freedom of Information Act, I'm afraid to say things like that.”
- Henry Kissinger
In a similar vein, in the pre-LLM era I gave a few interviews where the candidate was asked to screenshare while solving the problem. The candidates were allowed to use any resource they wanted from the broader internet.
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.
Friends and family who are largely non-technical have referred to ChatGPT as Chat for at least a year.
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.
This is interesting, but what is the advantage of running a proxy to achieve this over pre-commit hooks?
There may not be many, but these people do exist.
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.
It’s all part of the game it seems.
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...
I think it’s fair to say that diplomats appear to be appointed under a two-faced system.
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.
Your quoted paragraphs are not discussing the same trend, your first paragraph is referring to drinking habits in those 65 or older.
The second paragraph is discussing drinking habits for all US adults.
This is interesting, do all major airports have the ability to set up this cable system if needed? Or is this unique to PDX, or perhaps only those airports which are near where fighters train.
I looked it up since I was also curious. There’s this story making the rounds right now in FL: https://youtu.be/ia1qP1DmJdg
It seems as if these are developments which didn’t get completed.
This reads like a fluff piece for Goldman Sachs and the startup Cognition. It’s running in a bunch of outlets concurrently.
Goldman gets to appear as being on the cutting edge by incorporating AI. The startup behind the agent GS is using, Cognition (who is seeking a $2B valuation), gets to be seen as effective and bolster their name recognition.
Paul Graham’s “The Submarine” article seems relevant: https://www.paulgraham.com/submarine.html
The “AI Software Engineers” at my company, whose applications and workflows I often support as an SRE, by and large build things with LLMs rather than train or create them.
What they build ranges from product features to internal tools. They make heavy use of LLM vendor inference APIs, vector databases, etc. They end up writing a lot of glue code and software to manage the context of the LLM, query for data, integrate with other systems and so on. They also develop front-end interfaces for their applications.
Only recently have they started to, lightly, explore the idea of training LLMs with managed services like AWS SageMaker.
All this is to say that, the “AI Engineer/SWE” title will probably represent vastly different things depending on the technical sophistication of the organization.
If someone told me they were an AI Engineer at OpenAI I’d be more inclined to expect their role to be more fundamental, elsewhere, not so much.
Perhaps you’re thinking of Ocracoke, North Carolina[0]
[0]https://www.bbc.com/travel/article/20190623-the-us-island-th...
I have used Netlimiter on Windows in the past. It seems to have comparable functionality to Little Snitch
FWIW, eBay no longer works like this. When you put up a listing there’s now an option, enabled by default, to require payment at checkout.
This situation may still occur if you are taking offers on an item. In that case the buyer has to pay within 48 hours of the offer being accepted or the listing will become eligible for re-posting.
I was curious about the calculator comment, so I looked it up. The following terminal command supposedly does the trick:
open -na Calculator
This is basically the point of PSLF[0]. The cost to participants is not $0, but it can ultimately be very low if they only make income adjusted payments during their 10 years of service.
https://studentaid.gov/manage-loans/forgiveness-cancellation...
I think the idea is that if you were recording a podcast it wouldn’t be live (I know the parent used the word live but I think they meant “live” during recording or in conversation while the episode is being created), so you are free to make references to soon to be declared URLs.
You just have to make sure you have populated the content at the location you are referencing before you upload or publish your episode for your listeners.
I wonder to what extent formal verification methods are being employed in the development of these kinds of things.
I always took democratize access to X to mean “I would like to give many people the opportunity to give me lots of money by buying my product.”
According to this article walking burns about 30% less, but still closer than I would have expected!
https://health.clevelandclinic.org/qa-can-you-burn-the-same-...
If I had to guess: side load F-Droid onto the Fire Stick and install Termux from there.
Then you could SSH into a cloud computing environment and work off that.
I’m as excited about LLMs as the next guy, but I am sort of confused about stuff like this.
From the article: “One of Casetext's key products is CoCounsel, an AI legal assistant launched in 2023 and powered by GPT-4 that delivers document review, legal research memos, deposition preparation, and contract analysis in minutes, Thomson Reuters said in a statement.”
I get using an LLM to generate code snippets or text, where a human developer or author might be able to pick out the good parts and resolve any syntactical mistakes.
But for something like contract analysis or document summary, in a profession where cases have been won and lost on something as precise as comma placement, are LLMs really useful here? Their inherent inexactitude makes me wonder.
I have always had it as far as I know.
I have a vivid memory of asking my father if he could see atoms too when I was between 5 and 8.
I told him that when I stared at an object long enough, I saw little dots (snow). I must have just recently heard about atoms and mapped them to my experience.
Fortunately he understood what I was talking about and said told me it’s just my eyes or my mind presenting me with bad data. I’m sure it was a strange question for him, “can you see atoms too?”