It was a truly ridiculous idea to put an i9 in any laptop. That generation of i9 is difficult to cool even with liquid cooler systems in big ATX cases.
As much as that’s true it’s clear a huge amount of people have accepted the current state and are working around it, successfully(in terms of ticking an executive’s checkbox) in a lot of cases. And it’s worth considering we’re seeing strong strides outside of model quality in the tooling and integration
While I think the author is entirely right about 'natural language programming' in the current day, if LLMs (or some other AI architecture) continue to improve, it is easy to believe touching code could become unnecessary for even large projects. Consider that this is what software co. executives do all the time: outline a high level goal (software product) to their engineering director, who largely handles the details. We just don't yet know if LLMs will ever manage a level of intelligence and independence in open-ended tasks like this. And, to expand on that, I don't know that intelligence is necessarily the bottleneck for this goal. They can clearly tackle even large engineering tasks, but often complaints are that they miss on important architectural context or choose a suboptimal solution. Maybe with better training, context handling, documentation, these things will cease to be problems.
I think you're misunderstanding the paradigm shift completely -- AI does not just generate code N(x) more quickly. It thinks N(x) faster, it researches N(x) faster, it tests N(x) faster. There are hundreds of tasks that you'll find engineers are offloading to AI every day. The major hurdle right now is actually pivoting LLMs from just generating code: integrating those tasks into workflows. This is why tool-use and agentic workflows have taken engineering by storm.
When someone says passwords are ‘stored’, the assumption will always be ‘stored on disk’. ‘stores in memory’ is not an accurate representation because memory is inherently volatile and they are loaded there temporarily. Plaintext on disk is egregious, plaintext in memory is considerably less so.
I think they're going for more of a 'monkeys will eventually produce shakespeare' thing here. Which you can apply the same argument to - monkeys do not know english, don't know what they're typing, and theoretically english could devolve to a state where every sentence could be qualified as shakespeare, right? Your argument just seems unnecessarily pedantic.
Not sure why all the other commentors are failing to mention you can spend considerably less money on an apple silicon machine to run decent local models.
Fun fact: AWS offers apple silicon EC2 instances you can spin up to test.
yeah it seems like sonnet 4.6 burns thru tokens crazy fast. I did one prompt, sonnet misunderstood it as 'generate an image of this' and used all of my free tokens.
Strangely, it is super fast on my 16 Plus, but with longer messages it can slow down a LOT, and not because of thermal throttling. I wish I could see some diagnostic data.
It just depends on the UI frameworks available to developers and their interest in building something good-looking. Different UI frameworks are available for different platforms, and there are only a few good ones that are cross-platform. Qt and GTK are pretty common for linux apps and typically don't look great.
Does anyone know if this is still the most comprehensive archive? I'd like to know if the owner found any of the missing 91-01 datasets or if they are available anywhere.
I think the problem is the distinction here between chips and boards. The entire GPU assembly can absolutely be worn down from continuous use, thermal pads, paste, VRMs, fans do degrade. The chip itself may be fine but it's very rare to find anyone willing to transplant a GPU from one board to another.
Windows is still a solid 'gets out of the way' operating system (with numerous tweaks, customizations, and stripping) when it works. If they focus on fixing UX issues and improving stability and performance, it may be enough to slow the rise of desktop Linux.
Better support for F#, or really any language other than C# is a longshot though. Those resources were likely 'reallocated' to AI R&D indefinitely.