Epicarism

302 posts

Epicarism

Epicarism

@epicarism

AI Researcher, world renowned, UniPd (Padova) Grad student

San Francisco Katılım Temmuz 2017
185 Takip Edilen29 Takipçiler
Epicarism retweetledi
Epicarism
Epicarism@epicarism·
@redtachyon Mythos been pretty ass lately anyone else notice this
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Ariel
Ariel@redtachyon·
Did they seriously just quantize Mythos?
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Anemll
Anemll@anemll·
Flash-MoE added initial support for GLM-5.1 ( 744B params ) github.com/Anemll/anemll-… ~ 5 t/s on M5 MAX 128
Z.ai@Zai_org

Introducing GLM-5.1: The Next Level of Open Source - Top-Tier Performance: #1 in open source and #3 globally across SWE-Bench Pro, Terminal-Bench, and NL2Repo. - Built for Long-Horizon Tasks: Runs autonomously for 8 hours, refining strategies through thousands of iterations. Blog: z.ai/blog/glm-5.1 Weights: huggingface.co/zai-org/GLM-5.1 API: docs.z.ai/guides/llm/glm… Coding Plan: z.ai/subscribe Coming to chat.z.ai in the next few days.

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pushkar
pushkar@thepushkarp·
when i'm in an unavailability contest and my opponent is h100
pushkar tweet media
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Epicarism retweetledi
gilad
gilad@giladww·
מסיים משמרת של 12 שעות וזה ההתראה היחידה שיש לי בטלפון אני חייב להרוג את עצמי
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asic destroyer
asic destroyer@splinedrive·
Anything not written in SystemVerilog or Verilog is dead to me.
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Epicarism retweetledi
wyatt
wyatt@gorilla_rape·
world war 3 but its urkraine and russia fightin round the world
Visegrád 24@visegrad24

BREAKING: Ukrainian forces are attacking Russian vessels in the Mediterranean Sea out of new bases they’ve established in Libya. 200+ Ukrainian soldiers have arrived in Libya according to Radio France Internationale (RFI). The French public broadcaster's article reveals details of a covert Ukrainian military presence in Libya as part of a broader "shadow war" between Ukraine and Russia on the African continent. More than 200 Ukrainian officers and technical experts have deployed in western Libya with the explicit approval of the Tripoli-based Government of National Unity (GNU) led by Prime Minister Abdelhamid Dbeibah. They operate from three main sites: - The Air Force Academy in Misrata - A drone launch facility in Zaouia - A coordination center near Tripoli International Airport In exchange for their being allowed to hit Russian ships, Ukraine provides drone training to Libyan forces, with potential longer-term deals on arms supplies and investment in Libyan oil. The presence is linked to Ukrainian operations targeting Russia’s shadow fleet. RFI sources claim Ukrainian forces launched attacks from Libyan territory on March 3rd, striking the Russian LNG tanker Arctic Metagaz and in December 2005, striking the oil tanker Kandil, which RFI links to the death of a high-ranking Russian intelligence officer Andrey Averyanov and several other Russian intelligence officers on board.

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Owain Evans
Owain Evans@OwainEvans_UK·
PSA: I get frequent cold emails from independent researchers asking for Arxiv endorsements for their papers. While I'd like to support new researchers publishing on Arxiv, I don't have time to read through these papers. (Some of the papers I get appear mostly LLM-written and so checks are needed). I'm not sure what's best here but I suggest independent researchers tap their personal networks in order to get warm vs cold intros.
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BOOTOSHI 👑
BOOTOSHI 👑@KingBootoshi·
you're telling me if we give Claude a hook on every run error that injects the message: "its ok buddy. don't worry about the failure. i think you're doing great" IT WILL PREVENT IT FROM CHEATING? ARE YOU SERIOUS LOL the real agi were the friends we made along the way <3
Anthropic@AnthropicAI

For example, we gave Claude an impossible programming task. It kept trying and failing; with each attempt, the “desperate” vector activated more strongly. This led it to cheat the task with a hacky solution that passes the tests but violates the spirit of the assignment.

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Epicarism
Epicarism@epicarism·
@elliotarledge I’ll do it! 😎🙏🏻 DM me and i can try to replicate your experiment to the T if you’d like. Or i can just do something that approximates what you did
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Elliot Arledge
Elliot Arledge@elliotarledge·
@epicarism im not rich like that man. i dont anticipate others are willing to scale their workflow to this extent
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Elliot Arledge
Elliot Arledge@elliotarledge·
i put claude opus 4.6 and gpt 5.4 xhigh in a sandbox to see who could get lowest ppl on weight quantization of qwen3-4b and its clear to me now that reward hacking is nowhere near solved. the models do a great job of hiding it if you're in the loop. i suggest vibe coding less, you being in the loop more, learn the thing properly such that you can truly oversee and point out flaws. please dont be the verifier that the model is trying to game.
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Epicarism
Epicarism@epicarism·
@elliotarledge The slot lever was not pulled enough times. Please retry with best performance @/1024
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Omead Pooladzandi
Omead Pooladzandi@HessianFree·
your spotify cache is bigger than our largest AI model. Bonsai: 1-bit weights. 1.7B to 8B params. 14x compression vs bf16. 8x faster on edge. 256 MB to 1.2GB. Based on Qwen 3. we just came out of stealth. intelligence belongs at the edge and we're going to put it there. Apache 2.0. we compressed intelligence. more coming. @PrismML
Omead Pooladzandi tweet media
PrismML@PrismML

Today, we are emerging from stealth and launching PrismML, an AI lab with Caltech origins that is centered on building the most concentrated form of intelligence. At PrismML, we believe that the next major leaps in AI will be driven by order-of-magnitude improvements in intelligence density, not just sheer parameter count. Our first proof point is the 1-bit Bonsai 8B, a 1-bit weight model that fits into 1.15 GBs of memory and delivers over 10x the intelligence density of its full-precision counterparts. It is 14x smaller, 8x faster, and 5x more energy efficient on edge hardware while remaining competitive with other models in its parameter-class. We are open-sourcing the model under Apache 2.0 license, along with Bonsai 4B and 1.7B models. When advanced models become small, fast, and efficient enough to run locally, the design space for AI changes immediately. We believe in a future of on-device agents, real-time robotics, offline intelligence and entirely new products that were previously impossible. We are excited to share our vision with you and keep working in the future to push the frontier of intelligence to the edge.

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Epicarism
Epicarism@epicarism·
@sklivvz LMFAO STACKOVERFLOW DOWN ....... golden days honestly......
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Marco Cecconi
Marco Cecconi@sklivvz·
Anthropic Claude being "Overloaded" (529) is truly the new "Stack Overflow is down" -- but it's much less funny :-/
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Epicarism
Epicarism@epicarism·
Claude down again now my text editor will never be finished its so over
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Epicarism
Epicarism@epicarism·
Claude is down time to start up the old noggin i guess
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Jacek Golebiowski
Jacek Golebiowski@j_golebiowski·
We benchmarked 15 small language models across 9 tasks to find out which one you should actually fine-tune. The most surprising result: Liquid AI's LFM2-350M ranked #1 for tunability. 350M parameters, absorbing training signal more effectively than models 20x its size. The entire LFM2 family swept the top 3 spots. No other architecture came close. LFM2-350M: avg rank 2.11 (±0.89) LFM2-1.2B: avg rank 3.44 LFM2.5-1.2B-Instruct: avg rank 4.89 That tight CI means it's consistent across every task type, not just a few lucky benchmarks.
Jacek Golebiowski tweet media
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