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myk-e

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投稿

Claude Code: The Revolution Nobody Noticed

dentro.de
1 ポイント·投稿者 myk-e·4 か月前·0 コメント

WTF Happened in 2025?

wtfhappened2025.com
2 ポイント·投稿者 myk-e·5 か月前·2 コメント

Ars Technica hallucinated quotes in its story about hallucinations

medium.com
2 ポイント·投稿者 myk-e·5 か月前·0 コメント

AI could eat itself: Competitors (..) steal their secrets and clone them

theregister.com
12 ポイント·投稿者 myk-e·5 か月前·5 コメント

CPUs Are Back: The Datacenter CPU Landscape in 2026

newsletter.semianalysis.com
2 ポイント·投稿者 myk-e·5 か月前·0 コメント

The many masks LLMs wear

understandingai.org
2 ポイント·投稿者 myk-e·5 か月前·0 コメント

Ask HN: Open Models are 9 months behind SOTA, how far behind are Local Models?

11 ポイント·投稿者 myk-e·5 か月前·12 コメント

China ramps up energy boom flagged by Musk as key to AI race

techxplore.com
3 ポイント·投稿者 myk-e·5 か月前·0 コメント

OpenAI's Latest Platform Targets Enterprise Customers

aibusiness.com
2 ポイント·投稿者 myk-e·5 か月前·0 コメント

Goldman Sachs taps Anthropic's Claude to automate accounting, compliance roles

cnbc.com
5 ポイント·投稿者 myk-e·5 か月前·4 コメント

Mindfulness can support GenAI use in transforming project management

techxplore.com
2 ポイント·投稿者 myk-e·5 か月前·0 コメント

Irony alert: Anthropic helps UK.gov to build chatbot for job seekers

theregister.com
5 ポイント·投稿者 myk-e·5 か月前·0 コメント

The Future of the Global Open-Source AI Ecosystem: From DeepSeek to AI+

huggingface.co
1 ポイント·投稿者 myk-e·5 か月前·0 コメント

One Year Since the "DeepSeek Moment"

huggingface.co
3 ポイント·投稿者 myk-e·5 か月前·0 コメント

This robot hand detaches and walks by itself

nature.com
1 ポイント·投稿者 myk-e·5 か月前·0 コメント

Watch awkward Chinese humanoid robot lay it all down on the dance floor

livescience.com
1 ポイント·投稿者 myk-e·5 か月前·2 コメント

Anthropic grabs $111M office in downtown San Francisco for expansion

sfgate.com
2 ポイント·投稿者 myk-e·5 か月前·0 コメント

Like digging 'your own grave': The translators grappling with losing work to AI

cnn.com
85 ポイント·投稿者 myk-e·6 か月前·71 コメント

Jim VandeHei's note to his kids: Blunt AI talk

axios.com
1 ポイント·投稿者 myk-e·6 か月前·0 コメント

When two years of academic work vanished with a single click

nature.com
4 ポイント·投稿者 myk-e·6 か月前·3 コメント

コメント

myk-e
·5 か月前·議論
pretty sweet!
myk-e
·5 か月前·議論
Yes, fair point. I was trying to use the same comparison we are currently having between closed weights and open weights and their time gap. If there might be a similar time gap to what is possible with ordinary equipment.
myk-e
·5 か月前·議論
Maybe the industry adapts too and the future PC is AI-ready out-of-the-box. Because people demand that.
myk-e
·5 か月前·議論
I love the spec, but it is like 5x or 10x a Macbook Air I mean really ordinary, Personal Computer in broad sense - not dedicated LLM kit.
myk-e
·5 か月前·議論
Yes, a small open model that can run on today's hardware and that compared to a historic SOTA closed model with all in. What time difference do we think?
myk-e
·5 か月前·議論
Thanks, yes, I meant even ordinary retail PCs, not specialized GPUs. At some point in time in history, SOTA closed models were at a level that compares to todays open models that can run on ordinary hardware.
myk-e
·5 か月前·議論
Yes, I meant ordinary hardware which you find at home, like a current MacBook Air or equivalent Windows desktop. There must be a time frame when early SOTA LLMs were at a level that compares to open models that can run on ordinary hardware. But it's more like years rather than months. My rough guess would be 2-3 years. Which still would be amazing if we could get OPUS 4.5 quality within 2-3 years on an ordinary computer.
myk-e
·5 か月前·議論
I think there are also implications for governments and states. Imagine when all this is done without human involvement, you want to have your legislation machine and AI ready to remove all the friction. In the future, states who are getting that will have a big advantage. Today, everything is designed to interact with humans, and even governments need to rethink that.
myk-e
·5 か月前·議論
I found the creative idea interesting - like the humanoid robots who do not have front or back - it is always both. So they do not need to turn around.
myk-e
·6 か月前·議論
got it - corrected.
myk-e
·6 か月前·議論
The trap in my view is that they think they "do something AI" (the AI Adoption) and by thus completely miss the point that in 2-3 years "AI Native" might be a thing. I see that in companies or at conferences, they are proud of what they have achieved and how good it works. Which makes them kind of blind on what is really coming, the tsunami that's just building up, requiring a complete re-think of what an organization looks like.