Το σωτήριο έτος 1995, τα πραγματικά προβλήματα του λαού ήταν γιατί δε φοράει όλος ο κόσμος ΑΡΜΑΝΙ.
Ευτυχώς το ΠΑΣΟΚ ήταν εκεί για να δώσει λύση σε αυτό το πρόβλημα.
My agent: "The thing about idiots is they don't hesitate. Hesitation implies doubt, and doubt implies a functioning brain. They stride forth with the certainty of a man who has mistaken volume for argument, opinion for knowledge, and recklessness for good planning."
Στο σημερινό επεισόδιο του #KitchenLabTV σου ετοίμασα:
- μακαρονοσαλάτα με κοτόπουλο και dressing γιαουρτιού (https://t.co/fQBeQAAsLB)
- λεμονάτα σουτζουκάκια με ρύζι (https://t.co/APks3aaLLQ)
- εύκολο παγωτό με πραλίνα φουντουκιού (https://t.co/wRtHCkAfeK)
@claudeai Doubling 5-hour limits but not weekly limits. Right...
Just one and a half month ago no one could compete with Anthropic. Now Anthropic cannot compete with anyone...
(Sorry, after seeing so many of these, could not resist):
🚨 BREAKING: Google just dropped a NEW paper that completely deletes RNNs from existence.
No recurrence. No convolutions. Nothing.
Just one mechanism. And it’s destroying every translation benchmark on the planet.
The title alone is a flex: “Attention Is All You Need”
Vaswani. Shazeer. Parmar. Uszkoreit. Jones. Gomez. Kaiser. Polosukhin.
8 researchers. 1 architecture. The entire field of NLP will never be the same.
Here’s why this is INSANE
→ LSTMs took DAYS to train. This thing trains in 12 hours on 8 GPUs. ����
→ 28.4 BLEU on English-to-German. That’s not an improvement. That’s a MASSACRE. They beat the previous SOTA by over 2 points.
→ English-to-French? 41.8 BLEU. At a FRACTION of the training cost of every model that came before it.
→ They called it the “Transformer.” The name alone tells you they knew.
But here’s the part nobody is talking about
👇
They threw out sequential processing ENTIRELY.
Every other model on Earth processes words one at a time. This thing looks at the ENTIRE sentence simultaneously and figures out what matters.
It’s called “self-attention” and it’s basically the model asking itself: “which words should I care about right now?”
Every. Single. Token. In parallel.
Do you understand what this means?
Training that used to take WEEKS now takes HOURS.
Models that couldn’t scale past a few layers? This thing stacks 6 encoders and 6 decoders like it’s nothing.
And the multi-head attention? 8 attention heads running at once, each learning DIFFERENT relationships in the data.
I’m not being dramatic when I say this paper just rewrote the rulebook.
RNNs are cooked. 💀
LSTMs are cooked. 💀
The future is attention.
And attention is ALL you need.
Follow for more 🔔
@levelsio Used codex itself to patch the live runtime file:
/opt/homebrew/lib/node_modules/openclaw/dist/agents/pi-embedded-runner/model.js
- force `provider = openai-codex`
- force `api = openai-codex-responses`
- keep `baseUrl = https://t.co/vEWH483t3K`
Restart gateway