There’s a feedback loop with inflammation and fat. We’ve been telling people for decades to break the cycle by losing weight, but we also have studies that say you can only sustain about 7.5% weight loss per year. Anything more tends to rebound.
Then GLP-1 comes along and we stop fat negativity/positivity overnight.
Not trying to argue about this particular case but how does a camera footage even work in a modern court system? I mean it can be generated nowadays, so how do they even make sure that it is real?
The chain of evidence has always been attackable and necessary for evidence to be admissible in court. It was actually designed to allow reasonable doubt for tampering and other such things.
Photoshop has been around a lot longer than AI. And people have attempted to doctor all kinds of evidence in court since courts began
Do police in the US has any unified system for dispatchers to track the history of incidents/resolutions? Just wondering if they could start making notes there for future calls, I guess it would be useful in general but not sure if they have/allowed to have something like that.
Do you rent from AWS or some other provider? I wonder if there are issues with on-demand rent for those high-end GPU instances, is capacity always there or sometimes it is unavailable?
I guess those estimations based on projection for data Center build out, which include 30GW+ in 2027 alone, more then 3 previous years combined. Surely every human on earth will start token-maxing tomorrow and bring all of their money to their AI labs overlords to justify that explosion in spending, right?
> where are all those great things that were created with them?
You will have to wait great amount of time for great things just as you did before.
LLMs are not AGI, if so they are not foundational technology, if so we can't really built upon them - we can just use their wrappers as productivity tool, if so we will be bottleneck by what we were bottlenecked before: corporate bureaucracy, slow physical world innovation pipeline, supply chains, just a small number of actual problem solvers/risk takers around, etc.
There will be of course a lot of attach LLM wrapper and improve productivity here / there underwhelming weak fart products, ex: Meta Muse.
I think "March of 9s" helps to describe this situation. Some devs seems to be happy with just one 9 as it suffice for their use-case while for others one 9 means that they would loose client's data 10% of the time or some other catastrophic consequence.
> But just go ahead and give the latest models (Opus 5.5 / Astra 6 as of today) another try.
I find my self going opposite direction recently. I start using frontier models less and less and smaller models more and more. I recently tried Opus Opus 5 with ultra-code level of effort and I wasted like 2 days on trying to migrate some project to new libs because it spits out a huge wall of text as replies/plans and waste huge amount of time on things I didn't ask it to check and see no point in checking. At the end I just took a smaller model and used it in more controlled fashion playing the role of orchestrator/planner. Smaller models are good enough and also much faster. My collisions from that, frontier models and high reasoning effort levels are for pure vibe-coding when you don't really control or understand what is happening. My application area is not pure SWE though, I didn't churn a lot of code before and I don't now, so I have enough time on understanding/polishing my projects if needed.
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