I don't live in the US but my country has also had a lot of immigration, invasions (true ones with armies, not mean ways to describe immigration), internal migrations from poorer parts of the country, you name it... Basically almost everyone is an immigrant in one way or another.
Well, our version of the far right has a lot of support from first or second generation immigrants.
One part of it is to pull the ladder up after ourselves and avoid others coming in and competing with us for the same jobs. Another part is that immigrants are on average poorer and angrier about the state of things, and for the populist far right, anger is fuel.
But also, Populists are becoming increasingly good at blurring the lines and making certain people feel included in the "in group" at election time, even if they are going to kick them in the head as soon as the ballots close. Case in point, AfD in Germany being led by a gay woman with an immigrant partner, "Brothers of Italy" being led by a single mom.... Usha Vance is not an isolated edge case, she seems to be part of a playbook, whether she knows it or not.
Trump is good (only?) at "fixing" problems that he himself created by.... stopping the thing that he did to create the problem. That's the TACO way. Enough backlash and he'll let go and claim he "brought peace to LA".
The problem is that "clamping down on immigration" is actually too popular (or not unpopular enough). The backlash Trump needs is about getting him to look bad, not shooting on the police and compacting the fuckers who already think they are on the right side. Peaceful resistance might actually be more powerful and effective in showing exactly who the bad guy is.
On the other hand I don't live in the US and I am aware how easy it is for me to say this from a safe distance....
I can't tell if it's "the true cause" of the massive tech layoffs because I know jackshit of US tax, but it does make more sense than every company realising at the same time that they over-hired or becoming instant believers of AI-driven productivity.
The only part that doesn't make sense to me is why hide this from employees. Countless all-hamds with uncomfortable CTOs spitting badly rehearsed bs about why 20% of their team was suddenly let go or why project Y, top of last year's strategic priorities, was unceremoniously cancelled. Instead of "R&D is no longer deductible so it costs us much more now".
I would not necessarily be happier about being laid off but this would at least be an explanation I feel I'd truly be able to accept
Machine learning has existed for many years, now. The issue is with these funding-hungry new companies taking their LLMs, repackaging them as "AI" and attributing every ML win ever to "AI".
ML programs designed and trained specifically to identify tumors in medical imaging have become good diagnostic tools. But if you read in news that "AI helps cure cancer", it makes it sound like it was a lone researcher who spent a few minutes engineering the right prompt for Copilot.
Yes a specifically-designed and finely tuned ML program can now beat the best human chess player, but calling it "AI" and bundling it together with the latest Gemini or Claude iteration's "reasoning capabilities" is intentionally misleading. That's why articles like this one are needed. ML is a useful tool but far from the "super-human general intelligence" that is meant to replace half of human workers by the power of wishful prompting
Public opinion is already swayed. Luigi Mangione has become a symbol to a lot of people and as such the super-rich want to punish him.
I bet they are more scared of the symbol than they are of the thought that Mangione is innocent and the real shooter might still be free and plotting another hit.
The "real shooter" would only be one person, but a symbol has the power to create 10 or 100 more or to spark a violent rebellion and that they can't let happen.
Innocent or not, it's unfortunately Luigi Mangione they need punished in the most horrific and exemplar way possible.
I've never used SHEIN so I can't tell if they are using these practices or how bad they are, but from the article I see they allegedly use fake urgency messaging, which I know has been sanctioned before in the EU (the company I used to work with had to rush removing it from our eCommerce site).
A company can tell you that the item you're looking at happens to be the last one in stock, if it's true. But if they lie about it, so you rush into a decision to buy it before it's gone, then it's a deceptive practice.
Same here. I also found myself trying to express things in my language using English constructs or colloquialism that don't have a direct translation. And my English isn't even that great, but I have to use it daily for work.
Depends what you mean by "valid". If you mean "profitable", sure: Fraud has always been a profitable business model.
But if you mean "valid" in terms of what Microsoft got out of their $455M investment, not so much, as they wanted a great new AI model, not the output that the "human-powered" model produced pretending to be an AI.
More choice = better.
On the other hand, Germany and France are both getting uncomfortably close to having neo-Nazi governments, with AfD and RN respectively being both very pro-Russia, anti-EU and aligned with Trump policies (even though Le Pen can't say it too loudly because of her party's historical anti-Americanism).
I hope these efforts to create a EU infrastructure succeed, but on the other hand big investments on AI:
take time that I'm not sure we have
sound exactly like the technocratic solutions "far from the real problems of the people" that these parties love to exploit to gain votes and get to power
I agree. I was almost skipping it because of the title, but the article is nuanced and has some very good reflections on topics other that AI.
Every technical progress is a tradeoff. The article mentions cars to get to the grocery store and how there are advantages in walking that we give up when always using a car. Are cars in general a stupid and useless technology? No, but we need to be aware of where the tradeoffs are. And eventually most of these tradeoffs are economic in nature.
By industrializing the production of carpets we might have lost some of our collective ability to produce those hand-made masterpieces of old, but we get to buy ok-looking carpets for cheap.
By reducing and industrializing the production of text content, our mastery of language is declining, but we get to read a lot of not-very-good content for free. This pre-dates AI btw, as can be seen by standardized tests in schools everywhere.
The new thing about GenAI, though is that it upends the promise that technology was going to do the grueling, boring work for us and free up time for us to do the creative things that give us joy. I feel the roles have reversed: even when I have to write an email or a piece of coding, AI does the creative piece and I'm the glorified proofreader and corrector.
cover letters, meeting notes, some process documentation: the stuff that for some reason "needs" to be done, usually written by people who don't want to write it for people who don't want to read it. That's all perfect for GenAI.
the point I was trying to make is that the reason both pro and anti-AI sentiments are blind is because "AI" companies are purposely mixing up things that don't belong together, in order to attract investments.
If you wrote "cruise ships are generating a lot of pollution" and someone answered "but it Magellan or Columbus hadn't had ships, our knowledge of the World wouldn't have advanced", you'd think they are gaslighting you, right? You wouldn't say "this blind anti-ship sentiment is going to hurt geography"
Machine Learning Models have existed for a long time. They are at their core predictors: you give them data, you carefully tweak the model's parameters for a long time and you can finally train a model that can make predictions in a specific domain. That way you can have a model trained specifically to identify patterns that look like cancer on medical imaging or another one (like in your example) to predict a protein's structure.
LLMs are ML models too, but they are trained on language. They learn to identify patterns in human language and predict long pieces of text that are similar to those language patterns. They also accept input in natural language.
The hype consists in slapping a new "AI" marketing label onto all of Machine Learning, mixing LLMs and other types of models, and creating the delusion that predicting a protein's structure was done by people at Google casually throwing prompts at Gemini.
And as these LLMs are exceptionally power-hungry and super expensive (turns out that predicting human language based on a whole internet's worth of training requires incredibly complex models), that hype is to gather all the needed trillions of investment.
GenAI is not the whole of Machine Learning and saying "Copilot is not worth the cost of the energy that's needed to power it" doesn't mean creating obstacles to ML used for cancer research.
I don't live in the US but my country has also had a lot of immigration, invasions (true ones with armies, not mean ways to describe immigration), internal migrations from poorer parts of the country, you name it... Basically almost everyone is an immigrant in one way or another.
Well, our version of the far right has a lot of support from first or second generation immigrants.
One part of it is to pull the ladder up after ourselves and avoid others coming in and competing with us for the same jobs. Another part is that immigrants are on average poorer and angrier about the state of things, and for the populist far right, anger is fuel.
But also, Populists are becoming increasingly good at blurring the lines and making certain people feel included in the "in group" at election time, even if they are going to kick them in the head as soon as the ballots close. Case in point, AfD in Germany being led by a gay woman with an immigrant partner, "Brothers of Italy" being led by a single mom.... Usha Vance is not an isolated edge case, she seems to be part of a playbook, whether she knows it or not.