AI companies reach out for help: OpenAI records computer actions, while Google uses uploaded content to train AI.
Axios begins investigating what user data AI companies are actually collecting.
The findings show that chat logs aren’t enough anymore. Now they also want to know what you click on your computer, what photos you upload, and what content you’ve viewed—then use that data for memory, personalization, and advertising.
OpenAI has added Computer History. Once Mac users manually enable it, ChatGPT and Codex can record your clicks, inputs, and switches within specific apps and websites, gradually building a long-term work memory about you. The feature is turned off by default; it doesn’t record your screen or audio. OpenAI says temporary action logs won’t be used to train its models.
Google is even more aggressive. A new Search Services History will save images, documents, and audio/video that users upload through services like Lens, Search Live, and Translate—and it can also be used to train generative AI. For accounts that meet the criteria, it’s enabled by default; if you want to opt out, you have to do it yourself. Even some data that is later unlinked from an account may be retained for up to 4 years after entering the training process.
Advertising has kept up too. Meta will use users’ interactions with Meta AI to adjust the content and ads on Facebook and Instagram; OpenAI and Google are also exploring ad models for chatbots. The better AI understands you, the more detailed the “portrait” the ad system has in its hands.
What used to be a concern was that chat logs would be used for training. Now, even how you work on your computer—and what you throw into Google—has started to become data in the hands of AI companies.
No matter whether open-source AI wins or closed-source AI wins, cybersecurity will be the ultimate winner! Palo Alto and CrowdStrike seize the windfall of the AI inference era!
The Wall Street financial giant Wells Fargo Bank recently released a research report stating that cybersecurity supergiant $CrowdStrike (CRWD.US)$ and $Palo Alto Networks (PANW.US)$ are seeing momentum in growth of orders for cybersecurity software products driven by the rapid expansion of the AI inference market. After AI moves into the stage of large-scale, massive inference and AI intelligent agent-style workflows (Agentic AI), cybersecurity demand is not simply likely to accelerate growth by “updating and iterating alongside cutting-edge AI technologies.” Instead, it may see a structural incremental expansion far beyond traditional IT spending.
No matter whether open-source AI wins or closed-source AI wins, cybersecurity will be the ultimate winner! Palo Alto and CrowdStrike seize the windfall of the AI inference era!
The Wall Street financial giant Wells Fargo Bank recently released a research report stating that cybersecurity supergiant $CrowdStrike (CRWD.US)$ and $Palo Alto Networks (PANW.US)$ are seeing momentum in growth of orders for cybersecurity software products driven by the rapid expansion of the AI inference market. After AI moves into the stage of large-scale, massive inference and AI intelligent agent-style workflows (Agentic AI), cybersecurity demand is not simply likely to accelerate growth by “updating and iterating alongside cutting-edge AI technologies.” Instead, it may see a structural incremental expansion far beyond traditional IT spending.
AI companies reach out for help: OpenAI records computer actions, while Google uses uploaded content to train AI.
Axios begins investigating what user data AI companies are actually collecting.
The findings show that chat logs aren’t enough anymore. Now they also want to know what you click on your computer, what photos you upload, and what content you’ve viewed—then use that data for memory, personalization, and advertising.
OpenAI has added Computer History. Once Mac users manually enable it, ChatGPT and Codex can record your clicks, inputs, and switches within specific apps and websites, gradually building a long-term work memory about you. The feature is turned off by default; it doesn’t record your screen or audio. OpenAI says temporary action logs won’t be used to train its models.
Google is even more aggressive. A new Search Services History will save images, documents, and audio/video that users upload through services like Lens, Search Live, and Translate—and it can also be used to train generative AI. For accounts that meet the criteria, it’s enabled by default; if you want to opt out, you have to do it yourself. Even some data that is later unlinked from an account may be retained for up to 4 years after entering the training process.
Advertising has kept up too. Meta will use users’ interactions with Meta AI to adjust the content and ads on Facebook and Instagram; OpenAI and Google are also exploring ad models for chatbots. The better AI understands you, the more detailed the “portrait” the ad system has in its hands.
What used to be a concern was that chat logs would be used for training. Now, even how you work on your computer—and what you throw into Google—has started to become data in the hands of AI companies.
SanDisk sparks the market; the Air Force finally gets relief. 1. HBF prototype — H2 2026 The next-generation stacked NAND, designed specifically for AI scenarios, is called by SeekingAlpha as “the next game-changer,” directly targeting the HBM market. 2. BiCS9 QLC — ramping production step by step Capacity per chip increases by 60%, significantly lowering AI storage costs and accelerating the penetration of enterprise-grade QLC/TLC SSDs. 3. Enterprise SSD capacity roadmap 2025: 128TB → 2026: 256TB → 2027: 512TB → long-term: 1PB, doubling every year. 4. The 2028–2030 financial framework First release of a multi-year financial model: a commitment to 100% excess cash returned to shareholders, with a $6 billion share buyback still in progress. 5. Next earnings report — expected around late Oct to early Nov 2026 Focus points: progress on the HBF prototype + the BiCS9 production ramp. One sentence: The HBF prototype and BiCS9 ramp are the two biggest variables—if execution exceeds expectations, it could ignite the stock price again.
💥 Filter the circle: Stay away from circles full of negative-energy gamblers and people who only complain and lie flat. Move closer to steady, self-disciplined people who understand risk control. The circle will gradually change your mindset and your choices.
*The end of an era, the start of a legend* 👑🤍 This photo says more than a thousand words. Wearing Real Madrid’s number 7 white kit, Cristiano Ronaldo, after helping the team achieve a UEFA Champions League three-peat, raises a thumbs-up as he leaves the pitch. 450 goals, 4 Champions League trophies, nine years of domination. He doesn’t just play for Real Madrid—he *represents* Real Madrid himself. When he left in 2018, he left behind a legend that cannot be erased. Consistently steady performances, wholehearted dedication, and rock-solid composure under pressure 💎 Just as Ronaldo knows exactly when to make a major decision and begin a new chapter, timing is also crucial in trading. That’s why I’ve been paying attention to *Predict Token*—a platform that lets you predict real football match outcomes and market trends. Read the game, hold your conviction, and keep stacking wins 📈⚽ Thanks to everyone for your support—aiming to reach 20,000 followers! 🙏 Which moment of Ronaldo in Real Madrid colors is the most unforgettable for you? Share it in the comments 👇 answer:7 回答:7 #1688家族family #Binance #PredictAndWin
On August 18, MaxForAI disclosed that an AI project called J-Space Cognition Suite, which has gone viral on the X platform today, is facing criticism from the community. The claim is that the DeepSeek V4 test results promoted by the project cannot be reproduced. The project previously stated that with V4 Flash combined with J-Space, it could match GLM-5.3, and that V4 Pro could surpass Fable 5 on multiple Agent Benchmarks while improving speed by 2.53x and token efficiency by 2.21x.
GitHub user GoForceX used the 87-question subset from Terminal Bench 2.1 to perform high-concurrency re-tests and confirmed that the J-Space related modules were loaded. The results showed that after adding J-Space, the benchmark scores actually dropped slightly, while token usage and cost both increased—opposite to the performance, speed, and token-efficiency improvement directions claimed by the project.
The community subsequently requested that the project release the complete evaluation configuration, per-question results, run logs, original runtimes, and data such as token consumption. So far, the project has mainly published aggregated results and has not provided complete raw experimental records sufficient to verify the precise data mentioned above. Notably, in response to the criticisms, the project’s authors previously said that the relevant data were “indeed exaggerated,” adding that the real improvements are roughly in the range of 1.6x to 3x. As of now, the author has not issued an official response to the community’s concerns, and some related Issues have been deleted.
[Ended] 🎙️ DSC Poseidon|Binance Square AMA special event is coming in hot 🔥 Tune in to the 520 Long March event livestream ✨ In-depth analysis of the DSC Poseidon global ecosystem and a breakdown of the key highlights of the public chain ecosystem
In life, no matter what you do, you can devote your whole heart and work wholeheartedly. The more you do, the better your body becomes, the stronger your spirit feels, and the more joy you find—relishing it in the process, with no worry or toil.
What’s the real cost of that “liquidation free” leverage on TermMax Alpha? I keep seeing people treat the upfront premium like it’s the only price you pay. It’s not. According to their own docs, the actual stack looks like this: The premium itself (what they call Max Cost) Financing cost on the full notional interest paid daily to the Dual Investment vaults Take profit fee that starts at 1.9% of notional and decays as you get closer to expiry Normal slippage and any residual spread That financing piece is the one I think most people miss. It’s calculated on notional, not just the premium you put up, so every day you hold costs you even if the price is just sitting there. Compare that to regular perps. You’re dealing with funding every 8 hours that can spike or quietly bleed you, but you get continuous exposure and no hard expiry date. From what I’ve looked at, TermMax Alpha wins when I have a clear short-term directional view, the expected move more than covers the total cost, and I just want to sleep without watching liquidation prices. It loses when funding is relatively calm, the premium is rich relative to the move, or I want the flexibility to hold and adjust through multiple regimes. I treat that premium the same way I treat an options debit now. If the thesis doesn’t clear it with some room to spare, I just pass. Would you pay the premium for no liquidation, or stick with perps? @TermMax
🌙 Evenings are good for self-reflection, and for building strength 💪 Let go of the daytime noise, and hold fast to inner certainty. Take it slowly—time will not fail every bit of perseverance 🌟 Keep your heart full of light; the road ahead will have brilliant light of its own ✨
🧧🧧🧧🧧🧧🧧 If you’re good at forecasting the Federal Reserve and international situations! I recommend you come to the market prediction platform ☞ predict. You can use it directly by opening the Binance Wallet app!
In the past there was the “thin-biscuit” era, then the Four.mm platform; now there is predict. It’s wealth passwords and treasure-level gains—next up, the next trend, the next Binance life, it’s predict
🚨 The crypto market suddenly went quiet, but this kind of “quiet” may be more worth paying attention to.
$BTC is still ranging around $63K–$64K repeatedly.
There’s no clear breakout, trading volume is declining, and volatility is also staying low.
Meanwhile, the market isn’t short on variables:
🔹 BTC ETF flows recently showed renewed outflows 🔹 Institutional funds had previously returned noticeably 🔹 Fed policy expectations are still changing 🔹 Geopolitical developments are again adding uncertainty to oil prices and risk assets 🔹 ETH and most Altcoins have not yet formed a sustained independent trend
The current market state is quite obvious:
The bulls haven’t really launched, and the bears haven’t fully taken control.
Everyone is waiting.
And historically, the phases truly worth关注 are often not when the market is most lively, but when both trading volume and volatility start falling together—then a new direction for capital begins to form.
So next, instead of guessing BTC’s daily moves, it’s better to watch three signals:
👀 Whether ETF capital resumes sustained inflows 👀 Whether BTC can break free from the current range 👀 Whether ETH and Altcoins show real capital rotation
The quieter the market gets, the more you should focus on where the next wave of capital is heading.
The question now is: who will break this calm first?
Come to this feast—what kind of feelings will “predict” bring you? Guess it! See if you’ll be the next king. Will these stunning views, delicious food, and beautiful women belong to you? Try it! 🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧🧧
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