It’s different because those were singular technological advances, each in their own niche. They spread out change between time, geography, and industries.
The fear is this will replace engineers, scientists, accountants, lawyers, service workers, etc, etc all within a small time window.
Investment types have shown repeatedly that their primary concern is money, not workers. There is no reason to believe that those currently in power are open to sharing their wealth or influence.
> clocks are less sensitive to environmental perturbations and can function without extreme cooling. This “opens a possible route to compact and robust optical clocks”
> drifting over the course of a day by only the equivalent of around one second in three million years
If these can be made reasonably cheap, even with a much higher drift rate, I, for one, would welcome the replacement of quartz-based clocks and their tendency to drift wildly in datacenters.
I love Ted Chiang’s fiction, but his Julius Caesar and Genghis Khan scenario totally misses the point that the writer has consciousness, not the characters. No normal person thinks a fictional character in a book has consciousness. Likewise it’s not the character presented to the user that may or may not have consciousness but the LLM itself.
I wonder how this affects that combining General Relativity with Quantum Mechanics leads to mathematical infinities “that render calculations meaningless.”
It appears that they are testing using Max. For 4.7 Anthropic recognizes the high token usage of max and recommends the new xhigh mode for most cases. So I think the real question is whether 4.7 xhigh is “better” than 4.6 max.
> max: Max effort can deliver performance gains in some use cases, but may show diminishing returns from increased token usage. This setting can also sometimes be prone to overthinking. We recommend testing max effort for intelligence-demanding tasks.
> xhigh (new): Extra high effort is the best setting for most coding and agentic use cases
Somewhere I read that vigilanteism arises when there is a perceived last of justice. This guy gets rich while people everywhere are losing jobs. Seems about right.
Is there a point where you step back and let it blow up so that management HAS to take the issues seriously? In other words, if you care, you might get enough minor fixes through to keep the product limping along instead of letting it become a big enough bonfire that management has to address it?
I suppose that’s the point where you look for a job elsewhere. But maybe if you stuck around you would get the satisfaction of finally fixing the broken stuff (if you were still employed after the disaster that is). Wishful thinking?
So, instead of making LLMs smarter let’s make everything abstract again? Because everyone wants to learn another tool? Or is this supposed to be something I tell Claude, “Hey make some code to make some code!” I’m struggling to see the benefit of this vs. just telling Claude to save its plan for re-use.
Because it’s cold? Here in Minnesota it’s 17F / -7C. Factoring in the wind chill it feels like 7F / -14C.
There are other reasons too of course (geography, lack of urban density, distrust of news, apathy, etc etc) but I think the weather is a definite factor right now.
> many of their systems were running out of date EOL software, to the point of being a security liability
This is more likely a management problem rather than a staffing problem. Lower level management knows about these kind of things but often they are not incentivized to make them a priority due to a culture focused on growth and “winning”.
Copilot is the absolute worst. Yesterday I had tried to have it create a printable calendar for January 2026 but no matter how I instructed it, it kept showing that the first was on a Wednesday, not Thursday. I even fed it back its own incorrect PDF in a new conversation, which clearly showed the 1st on a Wednesday and asked it to tell me what day the calendar showed the first on. It said the calendar showed the 1st as a Thursday. It started to make me disbelieve my own eyes.
Edit: I gave up on Copilot ant fed the same instructions to ChatGPT, which had no issue.
The point here is that some models seem to know your intention while some just seem stuck on their training data.
It’s missing almost all technical details, which seems fishy to me. But I’m sure this defense company is honest and has a system that works great and so that’s why no technical details are needed. /s
My take is that orbits below 500 km are “cleaned out” and during solar minimum there is less drag going on there. So, it’s a good spot to home your satellites for a while because there isn’t as much junk to maneuver around.
The fear is this will replace engineers, scientists, accountants, lawyers, service workers, etc, etc all within a small time window.
Investment types have shown repeatedly that their primary concern is money, not workers. There is no reason to believe that those currently in power are open to sharing their wealth or influence.