ninitaa

Post at least one original post on Binance Square using the article editor, with a length of at least 500 characters. The post must include the project account @FabricFND, reference the token $ROBO , and use the hashtag #ROBO. The content should be directly related to the Fabric Foundation project and $ROBO and must be original, not copied or duplicated. This task is ongoing and renews daily until the end of the campaign, and will not be considered complete.

Follow, share, and trade to earn 4,300,000 ROBO from the global leaderboard rewards. To qualify for the leaderboard and the reward, you must complete each type of task (Share: Choose 1) at least once during the event to qualify. Posts that include red conditions or unqualified gifts will not be considered. Any participant found to be involved in suspicious activities or potential use of bots will be disqualified. Additionally, any modification to previously posted content with high interaction for the purpose of reusing it as contributions to the project will lead to disqualification.

Hong Kong stablecoin stocks slide as new rules take effect, experts see healthy reset
Stablecoin companies operating in Hong Kong posted double-digit losses on Friday amid local regulatory shifts and a broader market correction.
Bright Smart Securities & Commodities Group fell nearly 20% on Friday, according to Google Finance data. Yunfeng Financial Group dropped more than 16% during the trading session, while Guotai Junan International Holdings slid 11% and OSL Group declined 10.5%.
These companies are referred to as “Hong Kong stablecoin-concept companies,” with share prices driven by exposure to stablecoin issuance, custody, trading, or related infrastructure. Still, some local experts view the correction as a positive market adjustment.
It’s “a healthy correction,” said Allen Huang, a senior stablecoin policy researcher at the Hong Kong University of Science and Technology. “There are signs that the stablecoin frenzy has spilled over to other financial markets including the equity market,” Huang told Cointelegraph.
The correction comes amid a broader downturn in Hong Kong’s financial markets. The Hang Seng Index closed down more than 1% on Friday, while the Hang Seng SmallCap Index fell 1.54% during the session. The Hang Seng Tech Index lost 1.02%.
A healthy market correction
The fall in stocks follows Hong Kong’s entry into a six-month transition period with special rules as it transitions to its new stablecoin framework. The new regulations also come amid plans to criminalize unlicensed stablecoin promotion in the region.
Huang is far from the only expert who believes that this sell-off was just a sane market dynamic.
“The sell-off in ‘stablecoin concept’ stocks is a rational market correction following months of speculative over-enthusiasm,” said Xu Han, director of Liquid Fund at Hong Kong-licensed exchange HashKey Group.
He explained that regulatory rigor, including requiring a one-to-one full reserve, one-day redemptions and a minimum capital of 25 million Hong Kong dollars ($3.18 million), “is a deliberate strategy to prioritize systemic stability and credibility.” He concluded:
“The correction filters out short-term speculation, allowing fundamentally strong players to anchor Hong Kong’s reputation as a globally trusted digital asset hub.“
“Today’s sell-off in ‘stablecoin concept’ shares is likely a healthy correction after speculative gains,” said Niko Demchuk, head of compliance at crypto forensics firm with Hong Kong operations, AMLBot. According to Demchuk, high licensing requirements and challenges faced by smaller firms also weighed on a “market recalibration.”
Shukyee Ma, Hong Kong-based chief strategy officer at real-world asset tokenization company Plume, seemingly agreed with the other experts. He concluded that “this drop represents a healthy market correction driven by profit taking and regulatory clarity.”
Many expected to leave the race
Huang said that, with the new rules in place, “some institutions considering giving stablecoin a try may decide not to continue with the process.” He said the early batch of license holders will benefit from first-mover advantages, citing network effects and economies of scale. He added:
“For the ones not expected to be included in the first batch, they will face an uphill battle, changing their cost-benefit analysis. It is also a way to increase the likelihood that the license holders will have commercial success.”
Ma said that the regulatory transition period will see smaller companies or those looking into stablecoins for speculation pause their efforts or switch jurisdictions. Still, he expects well-funded players to follow the guidelines and bear the compliance costs.
Demchuk similarly expects the six-month regulatory transition period to “drive capital consolidation among would-be stablecoin issuers,” leading to only a few licenses being issued. He also expects banks, acting as custodians, to prioritize partnerships with the license frontrunners, further reshaping the market towards larger issuers.
Hong Kong and US stablecoin competition
Huang said that “in the short run, it is unlikely that the volume of Hong Kong dollar-backed stablecoins will be comparable with dollar-backed stablecoins.” Still, Ma points out that China has the second largest market share in terms of exports, adding:
“The strict rules do benefit HKD-stablecoin issuers as it sets them up as the main providers of a viable settlement stablecoin for international trading.“
Demchuk added that Hong Kong stablecoins “may gain a strategic edge in cross-border payments and DeFi by leveraging” its financial hub status and strict regulation. Still, he said that “significant volume growth in DeFi or payments is unlikely before 2027, as market adoption and infrastructure develop.”
Magazine: Hong Kong hoses down stablecoin frenzy, Pokémon on Solana: Asia Express

crypto trades?
Key takeaways:
Gemini is now used by crypto traders to monitor market catalysts and breaking news in real time.
The Gemini Pro version’s longer context window and web access boost its usefulness for macro and sentiment tracking.
It lacks native support for charts, portfolios or backtesting; traders still need external tools.
Gemini is a powerful signal tool, but you should always validate with real-time data before acting; AI can hint, but it can’t replace execution judgment.
In 2025, AI tools aren’t just summarizing text; they’re being used by crypto traders to make sense of fast-moving narratives. Gemini, particularly its Pro version, stands out because it can natively access Google Search. This means traders can ask it to pull news updates, summarize catalysts or cross-check signals without relying on plugins or extensions.
While ChatGPT remains dominant for trade structuring and prompt design, Gemini’s edge lies in its built-in Google Search capability. It can surface real-time news and cross-check catalysts without needing plugins. However, it has major limitations: no price charts, no exchange access and no execution capability. It won’t replace trading platforms, but it helps filter signals from noise.
Also, please note that Gemini does not forecast crypto prices. It helps verify whether a narrative or signal holds water. In noisy markets, that’s valuable but only when paired with other tools and human oversight.
Using Gemini for crypto trading: Strengths and limits, explained
Below are prompt templates for crypto trading, organized by workflow stage. Render Token (RNDR) is used as the example token, based on July 2025 data.
Please note that prompts used in steps 1 and 2 were fed to Gemini on July 10, 2025, to scan RNDR news
Market scan on RNDR token
“Scan Google News and major crypto publications for the last 24 hours on $RNDR. List top catalysts with links.”
Gemini’s output is shown in the image below.
Here are the four key signals Gemini is highlighting from the above output:
Narrative momentum: RNDR is consistently grouped with trending AI and Web3 tokens, reinforcing its long-term relevance.
Sentiment spillover: Positive coverage of similar tokens (e.g., BlockDAG, ICP, TAO) benefits RNDR by association.
Media visibility: Articles from July and May still carry weight due to narrative alignment, not just recency.
Sector leader tag: RNDR is directly named as a top AI crypto project in major 2025 outlook lists.
Narrative depth without real-time signal
Prompt used on July 10, 2025:
“Yesterday’s volume on RNDR spiked 50%. Summarize if any specific token announcements or wallet movements explain this, citing date/time and source.”
Gemini’s output:
Gemini’s output showed no clear news catalyst for RNDR’s 50% volume spike on July 9, 2025, instead offering contextual analysis tied to long-term AI narratives.
Gemini confirms broader narratives but often misses short-term catalysts, highlighting the need to cross-check with wallet trackers or token-specific feeds before trading volume spikes.
RNDR technical setup: Gemini can’t replace charts
Once the RNDR narrative checked out, Gemini was prompted to simulate a technical trade. It outlined assumed entry and exit levels using standard rules like the 200-day moving average (MA) but couldn’t verify live relative strength index (RSI) or moving average convergence/divergence (MACD).
Prompt used:
“I want a trade setup for RNDR based on technicals. Use 200-day MA for trend filtering; indicate RSI, MACD level, entry range, stop-loss, and target levels with risk/reward.”
As observed, while Gemini can generate a logically sound trade setup, like the one shown for RNDR, with defined entry, stop-loss and target levels, it does so based on assumed, not verified, technical indicators. Metrics such as RSI and MACD are approximated or manually inserted, not pulled from real-time price feeds.
As a result, any risk-reward ratios or suggested trade ranges are hypothetical and illustrative, not actionable without further verification. Gemini can assist with planning, prompt structuring and scenario modeling, but it cannot confirm trend conditions, monitor live volatility or adapt to sudden market shifts. This makes it useful for backtesting or learning but unsuitable for executing or timing real trades unless paired with a reliable charting tool or live market data platform.
Risk logic, not blind entry
Rather than chasing setups blindly, Gemini was asked to calculate position sizing and invalidation rules for a $10,000 portfolio risking 2% on the RNDR trade. It returned a max size of $3,240, assuming a 6.2% stop-loss, and flagged eight invalidation conditions, including bearish RSI shifts, negative news and macro disruptions.
Prompt used:
“Given the RNDR setup, what’s the max position size if I risk 2% of a $10,000 portfolio, and what scenarios might invalidate the trade?”
Gemini’s answer followed basic trading heuristics, but the final decision still depended on user-defined volatility and conviction. So, Gemini’s risk framing is useful but not precise.
When Gemini gets it wrong
Even advanced models have blind spots. Here are five ways Gemini can misfire in crypto trading:
So, AI tools like Gemini can guide, but they’re not flawless. Always know the blind spots before you trade.
How Gemini compares with ChatGPT and Grok for crypto trading
Google Gemini isn’t the only AI tool traders are using, but it fits into a growing toolkit that includes models like ChatGPT and xAI’s Grok. Each has strengths and gaps, depending on what you’re optimizing for: market context, signal detection, trade planning or execution.
Gemini could outperform for news-driven setups, while ChatGPT may offer stronger support for coding strategies and trade simulations.
Depending upon their risk tolerance, traders could use Grok to detect token chatter, then Gemini to verify news validity and ChatGPT to structure a full trade plan.
How to use Gemini responsibly in crypto trading
Gemini can be used for research and structuring trade setups, not for live signals or execution. Always validate its outputs through platforms like CoinMarketCap or TradingView. For better results, combine it with tools like Grok (sentiment) and ChatGPT (logic). Since it lacks onchain and price feeds, all strategies should be tested in simulation before deployment.
Tips for using Gemini in crypto trading:
Use Gemini for narrative validation, not live trading.
Cross-check Gemini’s outputs with onchain data.
Combine Gemini with Grok (sentiment) and ChatGPT (logic).
Never trade without manually verifying RSI, volume or token flows.
Treat Gemini setups as drafts, not signals that test them in simulation first.
As AI becomes more integrated into crypto workflows, understanding how to prompt, how to verify AI-generated outputs and how to manage risk is more important than ever.
This article does not contain investment advice or recommendations. Every investment and trading move involves risk, and readers should conduct their own research when making a decision.

valuation
OpenAI has raised $8.3 billion at a $300 billion valuation, accelerating its plan to secure $40 billion in funding by year’s end. The latest round, led by Dragoneer Investment Group, comes after the company raised $2.5 billion in March.
According to The New York Times on Friday, Dragoneer committed $2.8 billion to the raise, representing roughly 10% of its total funds. The funding round brings OpenAI closer to its 2025 target, which includes a $30 billion commitment from SoftBank.
The funding round was five times oversubscribed, meaning investors wanted to invest roughly $40 billion, the Times said. OpenAI prioritized new strategic investors over existing backers, frustrating some investors who received smaller allocations than they hoped for.
Other investors include Blackstone, TPG, Sequoia Capital, Fidelity Management, Andreessen Horowitz, Altimeter Capital, Coatue Management, D1 Capital Partners, Thrive Capital and Tiger Global.
A brief history of OpenAI
OpenAI was founded in 2015 by Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever and others as a nonprofit research lab committed to ensuring artificial general intelligence benefits humanity.
In 2019, it created a capped-profit subsidiary, OpenAI LP, to raise outside funding, securing a $1 billion investment from Microsoft and transitioning toward a more commercially driven model.
OpenAI expects to generate $12.7 billion in total revenue in 2025, according to internal projections reported by Bloomberg in March.
More recently, DealBook reported that the company’s annual recurring revenue has reached $13 billion and is projected to surpass $20 billion by year-end. In September, OpenAI reported reaching 1 million paid users for its business-focused ChatGPT plans.
ChatGPT has also dominated its Large Language Model competitors. Data from FirstPageSage shows it has steadily maintained more than 70% of the LLM market share since January 2024.
Despite surging adoption, OpenAI doesn’t expect to be cash-flow positive until 2029, when revenue could top $125 billion.
AI-focused crypto projects attract fresh venture capital
While OpenAI continues to attract record-breaking investment from traditional venture firms, the crypto industry is carving out its own AI frontier. A growing wave of decentralized AI startups is raising capital to build open-source, token-powered alternatives to proprietary models.
In April, AI startup Nous Research raised $50 million in a Series A round led by Paradigm, valuing the company at $1 billion. Nous is developing open-source AI models on the Solana blockchain to provide decentralized alternatives to platforms like OpenAI and DeepSeek.
In July, Poseidon raised $15 million in seed funding led by a16z Crypto. The US-based full-stack AI data layer aims to solve the shortage of high-quality, legally cleared training data for AI models by providing structured, real-world data sets that can be used without copyright concerns.
Overall, crypto venture funding has surged in Q2 of 2025 to over $10 billion, its best quarter since early 2022. In June alone, $5.14 billion was raised.
AI Eye: Growing numbers of users are taking LSD with ChatGPT