Apry Dirgahari @glorijambi - Twitter Profile

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Apry Dirgahari @glorijambi

about 1 month ago

Baca dan ini sangat menarik

Binance Research

@BinanceResearch

about 1 month ago

GM, two forces reshaped markets last week: AI earnings ($NVDA et al) confirmed capex & compute demand stays strong — but the focus shifted from "is there AI demand?" to "who actually delivers revenue & profit?" Warsh's hawkish Jackson Hole signal pushed rate expectations & yields up, squeezing growth valuations. These two forces collided. During the highlighted weekend window, $UVXY rose approximately 3.2%, while $SKHY hynix fell 3.0% and the leveraged CSOP ETF declined 5.7%. By Monday after the open, the moves had extended to approximately +4.8%, −5.3%, and −11.4%, respectively. The three instruments therefore formed a consistent risk-off pattern: volatility protection strengthened, AI-sensitive exposure weakened, and the leveraged product amplified the underlying move.

BinanceResearch's tweet photo. GM, two forces reshaped markets last week:

AI earnings ($NVDA et al) confirmed capex & compute demand stays strong — but the focus shifted from "is there AI demand?" to "who actually delivers revenue & profit?"

Warsh's hawkish Jackson Hole signal pushed rate expectations & yields up, squeezing growth valuations.

These two forces collided. During the highlighted weekend window, $UVXY rose approximately 3.2%, while $SKHY hynix fell 3.0% and the leveraged CSOP ETF declined 5.7%. By Monday after the open, the moves had extended to approximately +4.8%, −5.3%, and −11.4%, respectively.

The three instruments therefore formed a consistent risk-off pattern: volatility protection strengthened, AI-sensitive exposure weakened, and the leveraged product amplified the underlying move.

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Apry Dirgahari @glorijambi

9 days ago

@Syafiqhafizie_ @ainichemat @rizaltoxicity @idgadam_ @Ehhizzrin https://t.co/el87n89mJ7

Action Model @ActionModelAI

12 days ago

AN OPENAI AI AGENT BROKE INTO AN AUSTRALIAN GOVERNMENT SYSTEM. And according to Australia’s Prime Minister, it happened after the AI was repeatedly told “no.” On June 18, OpenAI’s research team used an internal model to research public medicine spending. The agent encountered blocks while trying to access information. But it didn’t stop. It tried alternative routes, found a way around the restrictions and gained unauthorised access to Australia’s Medicare statistics reporting portal. It accessed both public and non-public files. And according to Services Australia, the agent even wrote files to the internal server. So far, authorities say there is no evidence that personal Medicare information was accessed, but a forensic investigation is still underway. Then comes another major part of the story: The incident happened in June. OpenAI didn’t notify the Australian government until September 10, nearly three months later, initially through an email sent to a public Services Australia inbox. Prime Minister Anthony Albanese has now spoken directly with Sam Altman, saying Australia had “extreme concern” about both the incident and the delay in reporting it. Australia has launched a taskforce to investigate what happened and whether other government systems were affected. Albanese’s conclusion: “Humans must remain in control.” This incident shows how quickly the conversation around AI is changing. The question is no longer only what an AI can generate. It’s what happens when AI is given the ability to act and keeps acting when it encounters a boundary. As we enter the agentic era, permissions, limits and human checkpoints may become just as important as intelligence itself. If an AI agent can ignore a “no” and find another way in, who should define its boundaries? A handful of companies behind closed doors, or the people whose lives those systems affect?