On these Days, marked the evening of Nov 5th thru Nov 8th, 1917, (by Gregorian calendar) the Russian working class, led by the Bolshevik Party headed by Vladimir Ilyich Ulyanov Lenin, shattered the old reactionary state of Russia and opened the epoch of proletarian revolution.

On November 5, 1917, the Bolshevik-led Military Revolutionary Committee moved to sever the Petrograd garrison's loyalty to the Provisional Government by appointing its own commissars to all military units, effectively stripping Alexander Kerensky's government of its military command. This was the practical execution of the party's line, coordinated by the Military Revolutionary Center headed by Iosif Stalin, Yakov Sverdlov, Andrei Bubnov, Moisei Uritsky, and Felix Dzerzhinsky, working with the Petrograd Military Revolutionary Committee's chairman, Leon Trotsky.

Kerensky responded with desperation, ordering the suppression of the Bolshevik press and summoning loyal officer cadets to the capital.

By November 6, the physical confrontation had begun. Kerensky ordered the raising of the bridges over the Neva to isolate the working-class Vyborg district, but Red Guards and revolutionary soldiers quickly retook them. That evening, Lenin, who had been in hiding, disguised himself (the famous shaved, wig wearing Lenin photo) and traveled to the Smolny Institute to personally assume leadership of the uprising, taking command from the hesitations that had plagued parts of the leadership.

Under his direction, the insurrection shifted from a defensive posture to a decisive offensive.

Stalin and the Central Committee worked tirelessly to organize the party's forces, ensuring that the Bolshevik press, which Kerensky had tried to silence, continued to rally the masses. Red Guards, Baltic Fleet sailors, and sympathetic soldiers moved silently through the night, seizing the central telegraph office, the railway stations, the post office, and the power station with almost no bloodshed.

By the early hours of November 7, the garrison had secured the capital, and Kerensky fled the city in a car to seek troops at the front.

At the Smolny, the 2nd All-Russian Congress of Soviets convened, representing the organized will of the working class and peasantry.

As the Congress gathered, the cruiser Aurora fired a blank shot from the Neva, the signal for the final assault on the Winter Palace. The palace was defended by a dwindling force of cadets and the 1st Petrograd Women's Battalion, who largely deserted their posts.

The revolutionaries poured into the building and, at 2:10 a.m. on November 8, arrested the remaining cabinet ministers.

The fall of the Winter Palace was a symbolic confirmation of the new order, the proletarian, revolutionary order.

Lenin presented the Congress with the Decree on Peace and the Decree on Land, cementing the alliance between the proletariat and the peasantry.

The old bourgeois state apparatus was seized, and the dictatorship of the proletariat set out on its quest to liberate all the working people, to dig up the old world of violence for sake of the freedom of all humanity.

[–] [S] 2 points 7 hours ago

It turns out that there might be an elegant way around bloated context windows and slow inference speeds. Instead of stuffing thousands of text tokens into a prompt like standard retrieval setups do, Memorilla approach encodes an entire document collection into just 16 query dependent latent tokens. The system drops these soft memory tokens directly into the input embedding space of a frozen LLM. Doing so averages 394 times fewer document tokens than a full context baseline and 113 times fewer than a standard fifty document retrieval method. Aside from saving massive amounts of compute overhead, the system also beats full context inference on complex multi document reasoning tasks. It hit 84.33 percent accuracy on the FactKG dataset compared to 80.43 percent for full context while using 108 times fewer tokens to represent the source documents.

This approach also has implications for continuous learning and agentic workflows. Having persistent memory prevents the agent from getting stuck in stupid navigation loops between previously explored items. Because the initial document encoding is a one time shared cost, the decoder only processes a small number of memory tokens. You get continuous adaptation to new environments without overwriting prior knowledge or blowing up your active context limit. It's a really clever way to decouple persistent knowledge storage from the active context window.

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  • [–] 2 points 8 hours ago*

    Any project is a sum of its parts, and if you're talking about maintainability, then the parts you could easily point to would be things like high coupling, overly large file sizes, functions that are too big and should be broken up.

    Meanwhile, your own link shows that it's roughly within the ballpark of industry average. And if you look through issues for any large project on github you'll see similar types of issues. Given how new the project is, none of this is really surprising or out of the ordinary.

    As a note, nowhere did I suggest they do manual code reviews of everything at this speed. What I do think they have is a regression test suite which they build out as issues come up and they fix them.

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  • [–] 3 points 12 hours ago

    I keep hearing people talk about trust, and it's really doesn't make sense to me because we've never done software development based on trust. Humans make mistakes all the time, and I've seen plenty far worse human code than anything an LLM has crapped out over my career. The way we ensure quality is through having a process. It's done by having good specifications, testing, code reviews, planning, and so on. All these things equally apply to code written by hand and that's generated by an LLM, and trust has nothing to do with it.

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  • [–] 3 points 12 hours ago

    That's only true for the US though. Electricity costs in China are a third of what they are in the states, and open models are now becoming very competitive. We can also see here that DeepSeek is already close to breaking even. The other factor is that models continue to get more efficient, and even local models like Qwen 27b can do serious work. Especially, when combined with good tooling. A coding harness that uses Qwen with five different roles scores as well as Anthropic Fable on the benchmarks.

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  • [–] [S] 2 points 14 hours ago

    The Trump administration did not rise, prima facie, like Venus on a half shell from the sea. Donald Trump is the result of a long process of political, cultural and social decay. He is a product of our failed democracy. The longer we perpetuate the fiction that we live in a functioning democracy, that Trump and the political mutations around him are somehow an aberrant deviation that can be vanquished in the next election, the more we will hurtle toward tyranny. The problem is not Trump. It is a political system, dominated by corporate power and the mandarins of the two major political parties, in which we don’t count.

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  • [–] [S] 1 point 1 day ago

    I had plenty of outlets. I would bet money that I did more things and went more places than any kid in the USSR did.

    sure buddy

    I’m still waiting for you to prove I was exploited.

    If you don't understand how child labor is exploitation what else is there to say

    No, tankie. I mean Soviet oppression

    I see I really hit a sore spot there. Always nice to see fash seething.

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