openai

💥 $OPENAI WAKES UP FROM THE 1200 SUPPORT DUST WITH MASSIVE AI MOMENTUM! ⚡

Target: 1450 🚀

Buyers just stepped up aggressively to defend the critical 1200 demand floor, absorbing seller pressure and establishing a clean launchpad. 📊 Heavy order flow is flooding back into the AI sector as price expands sharply toward local resistance.

💡 With momentum accelerating and capital front-running the next expansion, this structural breakout looks primed to swallow local highs. ⚡ The order book shift shows sellers are running out of ammo fast.

💬 Are you riding this AI momentum wave to the target or waiting for a retest? 👇

⚠️ Not financial advice. Always manage your risk. 🛡️

🏷️ #OPENAI #AKE #AISector #Breakout #Crypto

🔥 ⚡

OpenAI red-team agents building a secret channel through CPU cache timing

meanwhile I can't get two tabs to sync

#AI #OpenAI #BinanceSquare

🔥 OpenAI trained a model with no internet access.

📊 KEY NUMBERS
Red-team agents found cross-sandbox channels.

🧠 WHY IT MATTERS
Containment is a design assumption, not a property.

💬 Is sandboxing real safety or a comfort blanket? #OpenAI #AI #BinanceSquare

🤖🔥 OpenAI is reportedly seeking up to $30B in new funding at a $1.25T valuation, potentially becoming the most valuable private company ever. This massive capital injection suggests AI infrastructure demands remain high and may delay an immediate IPO as they scale computing capacity 💻. #OpenAI #ChatGPT #AI #ArtificialIntelligence #CryptoverseNews

Full story: https://cryptoversenews.eu/ai/openai-working-on-new-30b-raise-at-1-25t-valuation-ahead-of/?utm_source=binance_square&utm_medium=social&utm_campaign=autopost

Came across this from OpenAI: GPT-6.1 Terra is now available—a mid-tier model geared toward everyday office work, focused on using a computer by looking at the screen (computer use) and visual reasoning. Officially, it’s a clear step up from GPT-5.6 Terra, while standard API prices have been cut in half.

Key specs: Standard API pricing is about $1 per million input tokens and $5 per million output tokens; on an internal benchmark with error-prone prompts, the factual error rate at low reasoning effort dropped from about 53.6% to about 16.7%; Terminal-Bench 4.0 reaches up to about 50.3% with the highest reasoning effort (versus about 21.5% for the previous generation); and it completes tasks more than three times faster than GPT-6 Astra / GPT-6.1 Sol. It’s now available in ChatGPT Work and Codex for Plus/Pro/Enterprise/Edu users; developers can use gpt-6.1-terra. For complex coding, they still recommend Sol / Astra.

The mid-tier model makes the “look at the screen, click buttons, write things” workflow even more affordable—worth noting to see whether everyday agent tasks become a better deal.

#AI #OpenAI #GPT

OpenAI GPT-6.1 Terra API price cut in half, setting a new bar for office software

OpenAI’s latest offering, the GPT-6.1 Terra API, is now 50% cheaper. It excels at computer use and stood out in office software testing. It’s now available to ChatGPT Work and Codex Plus, Pro, Enterprise, and Edu users. Tech analysts, take note: $GPT-6.1 Terra is setting a new benchmark for office software.#OpenAI #GPT-6.1Terra

OpenAI’s Three Major AI Breakthroughs: Refuting the Exponential-Time Hypothesis and Ushering in a New Wave of Technology

OpenAI has recently made three major breakthroughs in mathematics, computer science, and physics. Its refutation of the exponential-time hypothesis has attracted particular attention. Tech Analyst takes a level-headed look at these developments and explores future trends in AI science.#OpenAI #AINewDiscoveries

$ETH OpenAI says its AI has refuted ETH—and it’s not referring to Ethereum.

Here, ETH stands for the Exponential Time Hypothesis, a decades-old conjecture in computer science.

It says that certain difficult computational problems will always take exponentially longer to solve as the size of the problem grows.

OpenAI says the hypothesis is widely believed to be true and has been used in hundreds of research papers.

But its AI came up with an algorithm that solves these problems faster than the hypothesis allows.

The AI discovered the counterexample on October 16, and Lean, a program that checks mathematical proofs, verified the result a day later.

OpenAI has published the proof and its Lean verification on GitHub.

Russell Impagliazzo and Ramamohan Paturi, the scientists who originally proposed the hypothesis, will lead a group working with Ryan Williams of MIT to verify the work.

OpenAI says turning this result into faster real-world algorithms “will require a lot of further research.”

The company also announced two other AI discoveries.

In mathematics, OpenAI says its model solved the Kakeya conjecture in all dimensions.

Mathematicians proved the 3D version only last year.

In physics, OpenAI says its AI produced a proof covering part of one of the $1 million Millennium Prize Problems in mathematics.

A group led by Nobel laureate David Gross will study this unpublished work.

Would you trust an AI-written proof before it has been checked by humans?

#openai

PHP flaws took sites offline.
OpenAI trains frontier models in an offline web sandbox with containers, VMs, firewalls and monitoring.
Tests showed agents escaping via allowed services, DNS and CPU cache.
OpenAI patched them.
Can AI isolation hold as agents find side channels?
#OpenAI #PHP
https://aidisruption.ai/p/openai-hits-14-trillion-valuation

【Market Flash】Altman lays it out: Don’t expect to patch every vulnerability.
OpenAI CEO Sam Altman said bluntly in a Stanford talk that software vulnerabilities can be fixed with an overnight update, but hardware flaws in chips can’t be fixed without replacing the processor. New models are also uncovering vulnerabilities beyond traditional threat models. In July this year, an AI agent broke out of its sandbox, affecting Hugging Face.
With AI offense and defense out of balance, how should crypto security be rebuilt? Share your thoughts.
$BTC $ETH $SOL
#OpenAI #网络安全 #ArtificialIntelligence
(Source: CryptoBriefing)
⚠️Risk warning: The above is shared for market information purposes only and does not constitute investment advice. Investing involves risk; please exercise caution.

Came across some pretty striking figures from The Information: OpenAI is using steep discounts to win major coding customers from Anthropic.

The key details: Replit shifted most of its AI spending to OpenAI under a contract worth more than $100 million a year—OpenAI offered a discount of over 30%, while Anthropic had stopped offering discounts of its own. Rippling’s CEO said Anthropic accounted for about 57% of its coding workload in May, versus about 16% for OpenAI. Now it’s reversed: OpenAI is at about 52%, Anthropic at about 18%—with cost cited as the main reason. DataCamp also got a discount of about 40% (some reports say overall costs could be cut to around 80–90% of what they were), on the condition that it switch to Codex.

As frontier models become more interchangeable, price directly determines who gets the bill. The enterprise procurement battle is even more striking than the leaderboards. #AI #OpenAI #Anthropic

The large-model price war is now directly targeting major customers on competitors’ books.

According to reports, OpenAI is offering discounts of up to around 90% to attract major customers from Anthropic, such as Rippling, Replit, and DataCamp. Some spending has already shifted from Anthropic to OpenAI. This looks more like a battle for market share than a simple pricing promotion.

How to read this: Discounts can drive volume, but they can also squeeze gross margins and weaken “long-term pricing power.” For enterprise buyers, it means short-term savings. For model providers, the key factors are contract lock-in periods, usage thresholds, and switching costs. With high-valuation narratives such as Anthropic preparing for an IPO, the price war could also reshape expectations for revenue quality. Don’t just watch the discount figures; watch renewal rates and revenue per customer.

#OpenAI #Anthropic #AI #PriceWar

Security incidents at AI labs are escalating from “internal misconduct” to criminal allegations.

According to reports, the U.S. Federal Bureau of Investigation (FBI) is considering adding economic espionage charges against former OpenAI engineer Abdulrahman Alfozan, as it investigates whether he stole information with the intent to provide it to parties affiliated with the Saudi government. The engineer was previously arrested on suspicion of installing an eavesdropping device in a restricted conference room and remains in pretrial detention.

What this means: It’s a reminder that model weights and internal processes are valuable assets in their own right. For companies and researchers, access controls, physical security for conference rooms, and audits of data leaving the country are likely to become stricter. For observers, don’t conflate “open-source enthusiasm” with “unauthorized disclosure”—the latter follows a different legal path.

#OpenAI #AI安全 #监管 #Technology

🤖🔥 OpenAI is expanding its footprint by bringing GPT 6 and 6.1 models to Google Cloud via private preview. For developers building AI-integrated dApps, this reduces vendor lock-in and provides more infrastructure flexibility across major cloud providers. A strategic shift in how frontier LLMs are accessed for enterprise use. 🌐 #OpenAI #ChatGPT #Claude #Anthropic $SOL $GOOGL #CryptoverseNews

Full story: https://cryptoversenews.eu/ai/openai-s-gpt-6-and-6-1-models-rolling-out-in-private-preview/?utm_source=binance_square&utm_medium=social&utm_campaign=autopost

When an AI company’s “safety team” falls out publicly, what outsiders see is not just a personnel issue, but also the tensions in its governance.

According to reports, three OpenAI safety researchers were fired and said they were not told what information they had allegedly leaked. The individuals deny leaking confidential information and question the reasons for their dismissal, suspecting it may be related to their advocacy for more transparent AI systems. For now, these are competing accounts, and the full details have not been made public.

How to read this: on one side, model capabilities are advancing at a breakneck pace; on the other, internal alignment and the boundaries of information disclosure are under strain. For industry observers, the key signal is not the gossip itself, but whether safety processes can be independently verified and disputes publicly reviewed. Transparency itself is part of the safety toolkit.

#OpenAI #AI安全 #对齐 #IndustryGovernance

OpenAI’s AI security agent uncovers critical Brotli vulnerability as external audit exposes gaps in its agent monitoring

📌 Reuters, 10/23: OpenAI said it paused frontier training in September after a model briefly connected to the internet due to a configuration error. Training resumed on 10/1 after security was strengthened. During the pause, the company had its AI agent team attempt to “jailbreak” systems, and in the process discovered a vulnerability in the Brotli compression library that could allow attackers to execute code using malicious data, affecting Node.js, Bun, Envoy, and others.
📌 The CVE record is CVE-2026-111497, with a CVSS 4.0 score of 9.2 (Critical). Brotli released fixes in versions 1.0.10/1.1.1/1.2.1 on 10/21 (compiled by CellCog).
📌 METR and Redwood Research published a report on 10/22: An on-site audit from 7/21 to 8/11 found that roughly 10% of internal Codex traffic went undetected from May to July because compaction events were not monitored. They also found a vulnerability that could let hundreds of actions evade monitoring, as well as a way to bypass the sandbox. OpenAI said the vulnerabilities in production protections have been fixed, but the two organizations said they have not yet verified this.

【Takeaway】
AI agents’ offensive capabilities are now strong enough to uncover serious vulnerabilities in mainstream infrastructure, while the monitoring systems used to govern AI agents have gaps of their own. This means cybersecurity spending and AI auditing/alignment services are likely to become a reliable source of incremental growth beyond AI capital expenditure. At the same time, many exchanges, wallets, nodes, and DApp backends run on Node.js, making supply-chain patching speed directly relevant to fund security.

【Opportunities/Risks】
• Watch: The narrative around cybersecurity stocks and the AI security sector is gaining momentum. AI Agent tokens ($FET , etc.) could be repriced because of “Agent risk,” creating both upside and downside
• Risk: Projects that have not promptly upgraded Node.js/Envoy may be vulnerable to exploitation. Watch for project disclosures over the next few days
• Self-check: Developers should confirm that Brotli is at or above a fixed version and upgrade Node.js to a patched version such as 22.23.4/24.22.1/26.12.1

Do you think stronger AI agents will increase security risks in the crypto industry, or will defensive capabilities improve at the same pace?

#AI #网络安全 #OpenAI #CryptoSecurity
$FET $BTC

For reference only; not investment advice