More push back against AI. There is a realization that AI has severe limits in what it can do and that the field has a lot of hype. The idea that AI is going to replace large sections of the STEM workforce is simply not true. AI could replace bureaucratic or repetitive jobs but not jobs that require actual thinking. I think it could be a tool to aid in thinking and creative process but the big hope that it will "do" science, endangering, create new products on its own is not going to happen and in fact it could hinder or reduce the quality of science and engineering in some cases. A lot of LANL managers or ex managers have been saying the most naive things about AI and just unaware of where the field is actually heading.
https://medium.com/quantum-information-review/ai-has-a-critical-flaw-and-its-unfixable-06d6a5c294d4
AI Has a Critical Flaw — And it’s Unfixable.
"AI isn't intelligent in the way we think it is. It's a probability machine. It doesn't think. It predicts. It doesn't reason. It associates patterns. It doesn't create. It remixes. Large Language Models (LLMs) don't understand meaning -- they predict the next word in a sentence based on training data."
"The widespread excitement around generative AI, particularly large language models (LLMs) like ChatGPT, Gemini, Grok, and DeepSeek, is built on a fundamental misunderstanding. While these systems impress users with articulate responses and seemingly reasoned arguments, the truth is that what appears to be 'reasoning' is nothing more than a sophisticated form of mimicry.
These models aren't searching for truth through facts and logical arguments--they're predicting text based on patterns in the vast datasets they're 'trained' on. That's not intelligence--and it isn't reasoning. And if their 'training' data is itself biased, then we've got real problems.
I'm sure it will surprise eager AI users to learn that the architecture at the core of LLMs is fuzzy--and incompatible with structured logic or causality. The thinking isn't real, it's simulated, and is not even sequential. What people mistake for understanding is actually statistical association."
Comments
There are also more and more signals that AI in general is a bubble.
https://www.reuters.com/markets/europe/is-todays-ai-boom-bigger-than-dotcom-bubble-2025-07-22/
ORLANDO, Florida, July 22 (Reuters) - Wall Street's concentration in the red-hot tech sector is, by some measures, greater than it has ever been, eclipsing levels hit during the 1990s dotcom bubble. But does this mean history is bound to repeat itself?
The growing concentration in U.S. equities instantly brings to mind the internet and communications frenzy of the late 1990s. The tech-heavy Nasdaq peaked in March 2000 before cratering 65% over the following 12 months. And it didn't revisit its previous high for 14 years.
https://www.mymoneyblog.com/25-years-1929-stock-market-crash-myth.html
Beyond that, a market crash can create many bargains for an astute investor, focused on value or distressed assets. Those who are astute may also not overpay during periods of exuberance, and will retain cash or other liquidity as Warren Buffet is doing now as a portion of their assets.
I can recall in the late 1990's also, the gains kept going for many years during which time there were many claims a crash was imminent, a similar situation to now. The 14 year reference relates I think to someone who bought in at the peak and there was a huge run up prior to that.
There is some discussion on reddit on AI
I’m in an Ivy League AI research program, and our lab—like many others—is 70–80% international students and postdocs. These people are publishing state-of-the-art work, often on prestigious fellowships. But with tightening visa policies, general anti-immigrant sentiment, and increasing uncertainty, many are talking about leaving (or not coming at all, Fall apps are down by a lot, admissions office hasnt disclosed data but the inboxes are vacant)
At the same time, the U.S. is pouring billions into AI, robotics, chips, and biotech. Which is great! But who’s going to staff those projects if the international talent pipeline dries up?" The American Worker!"-I hear you say. But it takes years to train a top-tier researcher, and the U.S. education system—especially public STEM—hasn’t been receiving enough support(funding cuts and all that)
I'm struggling to see the long-term strategy here. Is there one? Or is this just policy contradiction from different arms of the government?
In a post-labor economy, where automation and artificial intelligence have rendered most human labor obsolete, elite overproduction would manifest as a crisis of purpose and status among a highly educated and credentialed populace. With traditional avenues to elite status through professional careers diminished, a surplus of individuals with the intellectual capacity and ambition for leadership roles would find themselves without meaningful positions to fill. This surplus of aspiring elites, often unburdened by the necessity of labor but still driven by the desire for social standing and influence, would likely lead to intense competition for the few remaining positions of power and prestige in areas like governance, cultural production, and strategic oversight of automated systems. The resulting friction and frustration among these "elite-wannabes" could fuel social and political instability, as they challenge the established order and vie for relevance in a world where their advanced skills have been largely decoupled from economic necessity.
the Crusades can be convincingly linked to a medieval form of "elite overproduction." By the 11th century, the system of primogeniture, coupled with population growth, had created a large class of landless, aristocratic younger sons with military training but no inheritance or clear path to power. This surplus of ambitious knights fueled endemic internal violence and social instability across Europe. Pope Urban II's call for the First Crusade masterfully redirected these aggressive energies outward, offering this restless warrior class a unique opportunity to fulfill their spiritual duties while simultaneously carving out new lands, fortunes, and titles in the East. In essence, the Crusades acted as a crucial social safety valve, exporting a generation of frustrated elite aspirants and their violent conflicts far from the European heartland.
The rise of Nazism was profoundly fueled by a severe crisis of "elite overproduction" in Weimar Germany. A massive surplus of demobilized military officers, unemployed university graduates, and a downwardly-mobile middle class felt their ambitions for status and power were blocked by economic collapse and a political system they despised. The Nazi Party masterfully harnessed their immense frustration by creating a parallel power structure within its own ranks and promising to violently overthrow the existing order. Upon taking power, the Nazis did exactly that: they purged the state bureaucracy, military, and academia, creating a vacuum of elite positions that were then filled by these loyal, "surplus" aspirants. Unlike the Crusades which exported their surplus elites, the Nazis weaponized them to engineer a hostile takeover of the state from within, making it a chillingly effective resolution to an internal power struggle.