It’s the Trump administration trying to pick winners and losers. The chief ai person in the administration is David Sacks. He’s been completely biased and is always going on rants against Anthropic on his podcast (wild that he is participating while in the administration). It’s clear the administration is at odds with Anthropic and will do what they can to stop them from succeeding.
Unfortunately we cannot trust this guy. He’s deep in the Trump administration and has been doing everything in his power to try and pick other companies to win over Anthropic. Just before all this happened, he was going on a rant about how Anthropic was doing too much to disable their models for safety / regulatory capture reasons!
There are certain things you can leave running for a while. I think the distinction between vibe coding and hitl based coding routines will blur as workflows prove themselves and models become smarter and less expensive. Most of the best engineers I know have transitioned a lot more into vibe coding this year. The possibilities are much better nowadays.
To be honest I’m not doing too much. I’m just on one of the $200 plans, but always hit limits. I only use the best models and mostly use it for various software projects I always wanted to build, but didn’t have time for. I just closely monitor the usage caps and have something running on a Ralph loop most of the time, unless I get near the cap. The post here is more about how I’d start a self-funded software company, if I wasn’t already working full time.
This phase that all these companies went through doesn’t seem that bad. Before these places had a big problem where all their employees didn’t understand how to us ai for their work. Now they’ve overspent and tokenmaxxed and haven’t seen much from it. The next phase is to set the goalpost lower and set quotas based on who uses ai more effectively. Eventually the folks that use it well and are productive will bring in roi. Then you can fire all the folks that aren’t using it effectively and replace them with people that know how to use it. We’re already starting to see this.
I haven’t done any coding or anything that would use a lot of tokens and somehow I’ve already hit my session limit with my $20 plan. I’m just using it to ask basic questions most of the time and occasionally I have it write code but I haven’t done anything like that since the new model rolled out. It looks like some sort of issue where they’re incorrectly capping things for people?
You can get around context in large codebases by solving the memory problem. Also works better if you can break up larger projects into smaller sub components with adequate documentation.
Texas is a quasi fascist state at this point. I wouldn’t hold your breath about Greg Abbott coming to the rescue. This type of interaction with their constituents is common now.
You can still get old Mac minis for less than that, which have more memory and can run Debian. Probably best performance per dollar hardware available on the used market
You seem to fall into the same set of criticisms as everyone who’s bearish about ai. It’s somehow so powerful that we can’t handle the ramifications. Meanwhile, it’s a waste of money and doesn’t do anything. You have to pick a criticism and stick with it. Otherwise, it’s just angst-driven noise.
All these bills about age verification have nothing to do with protecting kids. This is just an easier pill for folks that aren’t privacy minded to follow. In the end, all your online activity and offline activity (flock cameras) will be tracked, because it gives our politicians and national security apparatus the type of power they crave.
This like many other attempts at this type of thing don’t understand the in distribution vs out of distribution aspect of ml models. Using something the model has the most training on will have the best outcomes. A new handcrafted programming language will perform significantly worse than a poorly thought out programming language that is widely used. Everything is going to revert to the mean as llms continue to progress.