I'm Japanese, and the 80286 at 10MHz was huge for Japan's PC-98 scene. The V30 handled backward compatibility while the 286 ran much faster than what we had before. This project brought back memories—the 286 was the chip of my era, and it's great to see people still exploring its capabilities decades later.
Since generative AI exploded, it's all anyone talks about. But traditional ML still covers a vast space in real-world production systems. I don't need this tool right now, but glad to see work in this area.
Thanks for helping me understand. I wasn't aware of Python's type annotation support. I did some quick research and learned that type annotations don't cause compile errors even when there are type errors. Is that why type checkers like Pyrefly exist?
That makes me think—why do I enjoy conversations with friends then? What's really the difference between a friend and a stranger? Friends annoy me too, maybe even more often than strangers do.
I agree that expanding communication with strangers is important. But starting with "Do you mind if I sit here? Or did you want to be alone with your thoughts?" and then continuing a conversation for 10+ minutes is a real struggle for me. Sometimes I even wonder—how exactly does this kind of individual conversation actually help me? Maybe this is just me.
Is there a compile-to-Python language with built-in type safety, similar to how TypeScript transpiles to JavaScript? I'm aware of Mojo and mypyc, but those compile to native code/binaries, not Python source.
In Japan, Omron developed early ATMs that looked similar to American and European machines. Though those early forms have changed significantly over time, Omron remains a top maker today (their ATM division later became a joint venture with Hitachi, so the Omron name is no longer used).
Unlike IBM, Omron specializes in ATM hardware, not bank internal systems. That difference in focus could have mattered.
That's a solid approach, and for high-level logic, it's definitely the way to go.
I find that a lot of my development time is actually spent on lower-level tasks—like writing custom string operations—since we don't have the rich standard libraries of a host environment.
This is exactly where an emulator really shines for me. It enables a "device-less" workflow where I can work through those low-level details on a sofa at a cafe without needing to bring the physical hardware along just to verify the behavior.
For a hobbyist embedded developer like me, the adoption of RISC-V in the ESP series is big news. In day-to-day development, instruction sets are often abstracted away by the compiler, but I appreciate open specifications and architectures. This makes me particularly interested in how an emulator like Emuko could facilitate evaluating code without the slow process of repeatedly burning it to ROM. I'm keen to see reports of its application in actual ESP32 development.
I am not a literature lover. I found a modern language interpretation of the poem. Many interpretation are possible. But I feel this is relevant.
I translated it to English.
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おほけなき床の錦や散り紅葉 "Ohokenaki toko no nishiki ya chiri momiji" is interpreted as a haiku-like expression of introspection and refined aesthetic sensibility — one in which the speaker, surrounded by undeserved honor (ohokenaki) and luxurious living (toko no nishiki = sumptuous furnishings), gazes upon the fleeting falling autumn leaves and reflects on their own vanity and attachment to life.
Key points of interpretation:
おほけなき Ohokenaki (身の程知らず /畏れ多い): Refers to a luxurious situation or standing that exceeds one's true worth or station — something almost presumptuous to possess.
床の錦 Toko no nishiki: Literally, a beautifully brocaded floor covering; a symbol of opulence. By extension, it evokes the sight of vivid autumn leaves carpeting the ground — the splendor of autumn (nishiki-aki) likened to a gorgeous spread of fabric.
散り紅葉 Chiri momiji : Falling, scattering autumn leaves — a classic symbol of impermanence and the Buddhist sense of transience (mujo).
Overall picture: The speaker finds themselves in lavish surroundings that feel undeserved (ohokenaki), while the scattering leaves (mujo) adorn that world with a beauty that is at once gorgeous and hollow — a quiet contrast between humility and the ephemeral.
Even amid a life of splendor, the sight of leaves falling reveals a universal truth — that all things must eventually end. The poem captures a mood that is gently melancholic yet elevated: savoring that beauty from a place of quiet, dignified acceptance.
Try an image search with 紅葉 落葉. The result will be the typical image a Japanese person imagines when hearing 散り紅葉. Then try the same search with "crimson carpet." From the standpoint of literary and artistic sensibility, the difference is not small.
As a native Japanese speaker, I'm happy to see our literature introduced to other countries. But I also feel conflicted.
The original Japanese of the first poem is:
おほけなき床の錦や散り紅葉
The translation on the site:
> I am not worthy
> of this crimson carpet:
> autumn maple leaves.
This contains the translator's interpretation, and the sound and intonation are completely lost. I admire the translator's effort, but I want visitors to understand how much this differs from the original.
Genuine question: what kinds of workloads benefit most from this speed? In my coding use, I still hit limitations even with stronger models, so I'm interested in where a much faster model changes the outcome rather than just reducing latency.
I agree. I’m a gadget lover too. But we still have a real problem: for major household products like air conditioners and dishwashers, there usually isn’t a practical open-source hardware alternative yet. Iowa farmers are probably in a similar situation.
I live in Japan, and our repair framework feels weak.
A lot of it is based on industry association rules (業界団体ルール), not enforceable regulation. For example, major electronics companies sometimes disclose a parts retention period (部品保有期限), like keeping parts for X years, but that is mostly traditional large companies.
On repair policy/enforcement, the EU and US seem more advanced than Japan. That is why stories like this (farmers pushing back on dealer lock-in and repair access) are interesting to me.
I focused on B/op because it was the only apparent weakness I saw. My “reuse” note was about allocation behavior, not false sharing. We’re talking about different concerns.
Go maps reuse memory on overwrites, which is why orcaman achieves 0 B/op for pure updates. xsync's custom bucket structure allocates 24 B/op per write even when overwriting existing keys.
At 1M writes/second with 90% overwrites: xsync allocates ~27 MB/s, orcaman ~6 MB/s. The trade is 24 bytes/op for 2x speed under contention. Whether this matters depends on whether your bottleneck is CPU or memory allocation.
Benchmark code: standard Go testing framework, 8 workers, 100k keys.
I was developing games on MSX/MSX2 about 40 years ago. It was already a fight with hardware resources, but the Apple II was an even stricter environment. Impressive work. Below is a quick comparison for those unfamiliar with the specs:
Macintosh (1989): 16-40MHz 68000, 1-4MB RAM, hardware acceleration, QuickDraw, non-blocking sound
Apple II (1979): 1MHz 6502, 64KB RAM, no hardware multiply/divide, race against CRT beam (4550 cycles), blocking sound only
* 10-year age gap, 16-40x slower CPU, 16-64x less RAM
I have similar and deep privacy concerns. But I also know that cameras have helped find criminals and assist crime victims. I don't want to let fugitives go without punishment. In fact, I must admit that cameras are a realistic choice given the current technology.
Flock Safety must be under public evaluation. Tech companies tend to hide technical specs, calling them trade secrets. But most internet security standards are public. What should be private is the encryption key. The measure to protect development effort is patents, which are public in the registry.
I'm new to 3D scanning but very interested in trying it myself. I'm looking at OpenScan (€203+) for scanning small Japanese souvenir handicrafts. Does anyone know if this pricing is competitive, or are there better options in this price range?
Why not show both? Wikipedia could display archive links alongside original sources, clearly labeled so readers know which is which. This preserves access when originals disappear while keeping the primary source as the main reference.
Thanks for your reply.
In fact, I've grown tired of programming by myself — I do 95% of my coding with Claude Code. But the remaining 5% of bugs can't be solved by the AI agent, which forces me to step in myself. In those cases, I'm thrown into a codebase I've never touched before, and code readability becomes key. That's what drew me to this article and to Forth.
I would look into the Rosetta.
Inspired by this article, I tried to read some tutorials on Forth. My question is whether concatenative languages are AI-coding friendly. Apart from the training data availability, the question is also whether LLMs can correctly understand long flows of concatenated operations. Any ideas?