Honestly some of the posts defending "it could be true!!" when nearly any rational reading of it would deem it "fake beyond a reasonable doubt" are just tiresome at this point.
Like you say, it's easy to have a rational discussion that these adverts are dumb and annoying, and purporting this fan fiction as truth just weakens the case.
Why would ICE leave the number as low as "70%" if they could be higher? Every illegal alien is a criminal as far as the law is concerned. Every illegal alien arrested is "charged with a crime". Otherwise ICE is openly stating to its supporters that they arrest illegal aliens and then release them, something their supporters are vocally against, and the administration believes and claims to be a serious problem.
A direct reading of ICE's claims (that seem to be contrary to information obtained through FOIA?) is that 70% of the people they arrest are criminals, which by their own definitions, would imply 30% of the people they arrest are not illegally here, but that's reading between the lines and it's hard to lend any credence to anything said by an administration that treats public statements as a fun gaslighting game.
But essentially, if ICE COULD claim everyone they arrest is an illegal alien (and literally a criminal they are legally allowed to arrest and deport), why wouldn't they?
I think this is a misinterpretation of the document. The claim is:
> 70% of ICE arrests are of criminal illegal aliens charged with or convicted of crimes in the U.S.
I believe the claim here is that 70% of the people ICE arrests have been charged with or convicted of crimes other than being present in the USA illegally. I don't think this is at all meant to imply that 30% of arrests are of people who are present in the USA legally. I think it's just sloppy writing.
I'm glad I asked the question, and I thank you for responding, but come on, don't you think it's not just a stretch but just flat out false to go from Homeland Security's quote of "Despite FALSE claims by sanctuary politicians and the media, 70% of ICE arrests are of illegal aliens who have been charged or convicted of a crime in the U.S." to "ICE cannot legally arrest people who are citizens for no reason, and yet they have done exactly that 30% of the time by their own admission." Like it's hard for me to even imply good faith if that's the stretch you made.
As the other commenter wrote, ICE is saying that 70% of arrests have a criminal conviction, implying something other than just being in the country illegally. First, many illegal aliens (e.g. those who overstay their visas) have not committed any criminal offense - overstaying a visa is a civil charge.
Yes, I do admit there is wiggle room for ICE to make it sound like all the people they are arresting are rapists and murderers (crossing the border illegally is itself a criminal offense), and as you point out, the Cato institute and many others have pointed out that high percentages of those deported don't have other criminal convictions. And given how much wide reporting there's been about how the administration is dissatisfied with the pace of deportations, it's clear there is pressure and incentive for ICE to deport as many people as possible.
So you can make all those valid arguments. Falsely stating (i.e. "making up" or "lying") that 30% of ICE arrests are citizens with no convictions doesn't help your point.
Technically not a word, but the US government uses "lawfully present individuals" in its policy docs. In addition to US citizens, this covers lawful permanent residents, people with valid non-immigrant visas/visa waivers, some country-specific exceptions (e.g. Canadian citizens visiting for short-term business and pleasure), and various humanitarian categories (refugees, people seeking asylum who have filed the proper paperwork, etc).
In short, an unfortunately very wide field of people for ICE to chew through without touching any citizens (even if one takes the most uncharitable interpretation, i.e. only 70% of arrests have been of unlawfully present individuals)
Just a minor correction, but I think it's important because some comments here seem to be giving bad information, but on OpenAI's model site it says that the knowledge cutoff for gpt-5 is Sept 30, 2024, https://platform.openai.com/docs/models/compare, which is later than the June 01, 2024 date of GPT-4.1.
Now I don't know if this means that OpenAI was able to add that 3 months of data to earlier models by tuning or if it was a "from scratch" pre-training run, but it has to be a substantial difference in the models.
IBM did a lot of pretty fragmented and often PR-adjacent work. And getting into some industry-specific (e.g. healthcare) things that didn't really work out. But my understanding is that it's better standardized and embedded in products these days.
Not to be rude, but that didn't answer my question.
Taking a look at IBM's Watson page, https://www.ibm.com/watson, it appears to me that they basically started over with "watsonx" in 2023 (after ChatGPT was released) and what's there now is basically just a hat tip to their previous branding.
I think that's essentially accurate even if some work from IBM Research in particular did carry over. As I recall my timelines, yes, IBM rebooted and reorganized Watson to a significant degree while continuing to use a derivation of the original branding (and took advantage of Red Hat platforms/products).
So you experienced a bug, which happens on software. I've traveled a lot and have never had an issue with my ChatGPT subscription. I'm not doubting you, but I don't think your anecdote adds much to the conversation of OpenAI vs Google.
This is pretty laughably false. Sure, the CEO has a lot of power and I've certainly seen companies relocate so they are basically within walking distance from the CEO's house.
But "execs" covers a lot of people, and nobody gives a shit where the CIO or VP of engineering lives. If anything, these folks are more career driven and are expected to up and move at the drop of a hat if business conditions warrant.
Look what happened in Austin, TX, which has much less housing regulation tamping down construction than CA (despite a good deal of local NIMBYism).
Prices spiked during the pandemic, and in response a shit ton of housing was built, much of it multifamily residential. Rents went down significantly and home prices are down 20% since the peak.
> The introduction of ads was seen as crazy, yet nobody stopped using Google.
Where is this revisionist history coming from? The introduction of ads to Google was not seen as "crazy", in fact it was basically seen as inevitable. And when Google did introduce ads, they were generally praised because ads were highlighted and clearly separated in a different color (yellow) at the top and right rail. Of course, that slowly eroded until ads were nearly indistinguishable from organic results and took up the entire first page, but when they launched I don't remember anyone being surprised that Google added ads.
> So, if you have a LOT of chances to try things that are highly improbable but high upside, your odds are quite good.
But that perfectly highlights why the "startup gamble" is a great bet for VCs but a horrible bet for most employees. Let's say N is, generously, 50 (i.e. 1 in 50 startups are a resounding success, which seems probably a bit over-optimistic but reasonable). VCs can easily spread investment around to 100 startups, but employees get a few swings at bat at most when it comes to where they work.
For most things in life, you often just don't have that many chances. E.g. most people don't date a hundred people before finding their spouse.
> If, through grade inflation, the only thing that matters to an employer is what school you went to and that you completed it (the sheepskin effect), then isn't the correct optimization to reduce wasting time on levers that won't make any practical difference in the end?
The reason I don't think this is rational at all is the amount of work needed to "look good for employers" isn't really that far off from the amount of work needed to understand and learn the info well in the first place.
I used to do a lot of college hiring for software devs. We did on-campus recruiting at a bunch of top universities, so sure, the school you went to is inherently one factor in our hiring process. But we also definitely cared about the grades you got, especially in core CS courses. Most importantly, my on-campus interviews were focused on things that someone should have learned in their data structures and/or algorithms course (but used examples that were as "real world" as possible). If you didn't actually understand the material, we weren't going to hire you.
Like you say, it's easy to have a rational discussion that these adverts are dumb and annoying, and purporting this fan fiction as truth just weakens the case.
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