@Angaisb_ I won't risk using Chinese model for that price difference with gpt5.6 or Fable. Chinese model was competitive b/o their extremely cheaper price!
@jun_song If this is true then who would use fable5 or gpt 5.6 sol? They cost multiple than Chinese models. I am so worried if Chinese AI would crash US ai economy.
Upcoming models performance predictions :
Opus-5 = Slightly worse than Fable, similar to GPT-5.6
Kimi-K3 = Very fast, slightly worse than Fable (tested)
Deepseek-V4 = Opus-4.8
GLM-5.5 = Fable
MiniMax-M3 Pro = Slightly worse than Fable
Gemini-3.5-Pro = Only good at benchmarks
@SimyungChang 오오옹!!! 재미로 "Sk하이닉스 살까말까" 라고 물어봤는데 agentnews.md/finance-ko 읽으라고 했을때 답이 훨 정확한데요?? 아니였을땐 그냥 아무 최근 뉴스 긁어서 ADR 상장이랑 미국 CPI 얘기만 하는데 agentnews.md 읽고 하니까 "옵션 레버리지 가 올렸다"는 평가도 하네요 ㅋㅋ
@thsottiaux Cooool. Anthropic needs to stop marketing Claude like it’s Skynet. We’re sick and tired of the safety-theater hype cycle. I like OpenAI's policy much better
How to use AgentNews:
Open your AI assistant and paste:
“Read https://t.co/ctuov5VsXh first.
Then explain the main scenarios for US stocks this week.”
For agents that read markdown directly:
https://t.co/CXS0P0KdaN
Then ask:
What changed?
What is contested?
What would falsify this view?
AgentNews is not another finance chatbot.
It is live context your AI can read before it searches, reasons, or answers.
@SimyungChang So is it like giving weights to let the AI which question is more important? Hmm interesting... i wonder why can't they direct themselves to the right question in the first place. Maybe lack of experiences? Haha. The anyway
@SimyungChang@garrytan True true. What's the point of pouring more GPUs into training bigger models if they still can't reliably use everyday software? They spend half their time recovering from errors instead of getting work done. Maybe we should focus on harnesses for once.
@SimyungChang So you're arguing that "context should be treated as infrastructure rather than something every agent reconstructs independently". But with modern RAG pipelines and built-in web search, aren't today's models already pretty good at building that context from external news?
Ask an AI what matters for US stocks this week.
It can search.
But it often still misses the market's "now."
What is leading?
What is contested?
What changed?
What would prove the frame wrong?
That's Nowless Search.
So we built AgentNews:
a falsifiable macro context board for AI agents.