The radar "reading" was done by first plotting analog radar signals to the antique rotary radar displays. Then there would be human operators with a light pen, marking each radar signature on each radar turn.
So the Univac would receive input coordinates for each target and track those in memory each turn.
CPU's microcode can be surprisingly simple: The CPU has bunch of internal signals, which activates certain parts of the CPU and the logic when to turn each signal on comes from reading bunch of input signals. The microcode can be just a memory where the input signals are the memory address and the output is the control signals.
It's just that at some point when it's all physically wired up in hardware as opposed to being stored in some form of memory I have difficulty thinking of it as code or a program. By the time you're rearranging wires to enter a "program" aren't you actually refactoring the CPU itself?
Anyway I feel like the answer to the chicken and egg problem originally posed is to point out that things used to be different. Tools such as text editors and compilers are merely modern syntactic sugar.
Not hard, but time consuming. In the past two weeks I've had Claude Code write me around 35k lines of code across 350 commits. It's a project which is giving positive impact to the company, but we would never have started it without CC as the effort would have been too big compared to the impact.
I'm an avid user of the Claude Code planning feature and I like how Claude Code asks for questions. I also often iterate the plan before finally giving it a go.
How do you solve this in Kelos?
I tried to check the code base, but it didn't really provide any glues. I guess I could instruct the agent to build a plan and to post the plan in the issue and then iterate that with written comments in the issue. Is that how you run it?
> I guess I could instruct the agent to build a plan and to post the plan in the issue and then iterate that with written comments in the issue. Is that how you run it?
Exactly.
I simply just create an issue if there's a simple bug and let Kelos handle it.
If there's a complex issue that I'd like to build a plan for before implementing it, I build the plan locally and let the agent create a github issue for it, then Kelos will handle it.
But there are companies which are only serving open weight models via APIs (ie. they are not doing any training), so they must be profitable? here's one list of providers from OpenRouter serving LLama 3.3 70B: https://openrouter.ai/meta-llama/llama-3.3-70b-instruct/prov...
Not sure about that. My Android warns me about my wife's airtags so often, that if I would actually be tracked by a malicious airtag, I would just assume it's one of my wife's tags. This could be prevented if I could mark a tag to be trusted on my Android phone, but no such feature exists.
I was just helping my dad with a brand new Lenovo laptop with Windows 11. It felt unbelievable slow and sluggish. Just opening file manager to create a new folder lagged so much it felt like this would have been a 15 years old computer.
While I personally use Ubuntu on my laptop for several years now, when I helped my relative with a brand new laptop (huawei) with Windows 11 I was suprised how fast it was despite being very cheap, I don't remember any version of Windows that had such a performance, at least visually.
Out of curiosity, what model does your father have?
To me it's generally pretty quick outside of File Explorer. The reskinned File Explorer is an absolute car crash - it's like they've taken everything that made 2005 KDE awkward and bolted it on top of Windows.
Hopefully you can write the teased next article about how Feedforward and Output layers work. The article was super helpful for me to get better understanding on how LLM GPTs work!
So the Univac would receive input coordinates for each target and track those in memory each turn.
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