橙子Joyce
924 Posts
橙子Joyce
价值投资者:以十年为单位投资美股及BTC.ETH.BNB.SOL.推特X:@Joyce88ai
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@橙子Joyce 🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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An Apple research team ran a reinforcement learning experiment with 9 models and 11 languages to find out: if the training data is only in one language, can the model’s problem-solving abilities be applied to questions in other languages?
The answer is yes, and the effect is quite noticeable. Training with only one language still makes the model stronger across many other languages as well.
For example, on a French test, training directly in French improved the average score by 25.6 percentage points. If you don’t train in French at all and only use Spanish questions for practice, you can still improve the score on the French test by 24.6 percentage points—just a 1-point difference.
What the model learns isn’t only problem-solving for a single language; it also learns some problem-solving methods that can be transferred and continued to be used in other languages. So in the future, if you want to strengthen the model’s Chinese reasoning, you may not need to remake all reinforcement learning data into Chinese.
For example, on a French test, training directly in French improved the average score by 25.6 percentage points. If you don’t train in French at all and only use Spanish questions for practice, you can still improve the score on the French test by 24.6 percentage points—just a 1-point difference.
What the model learns isn’t only problem-solving for a single language; it also learns some problem-solving methods that can be transferred and continued to be used in other languages. So in the future, if you want to strengthen the model’s Chinese reasoning, you may not need to remake all reinforcement learning data into Chinese.
@橙子Joyce 🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings!
Goldman Sachs strategist Ben Schneidau said that companies are increasing their investments in artificial intelligence (AI) at an unprecedented pace, yet for most firms, this technology has not yet translated into tangible improvements in earnings.
In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings. Another 11% said they had observed measurable productivity gains in specific areas such as software programming and customer support.
However, the companies that have implemented these efficiency improvements have not significantly outperformed overall market levels in terms of profit growth. Data shows that their median year-over-year profit growth was 17%, while companies that have not quantified the contribution of AI efficiencies were at 14%. Goldman Sachs noted that this gap is not statistically significant.
In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings. Another 11% said they had observed measurable productivity gains in specific areas such as software programming and customer support.
However, the companies that have implemented these efficiency improvements have not significantly outperformed overall market levels in terms of profit growth. Data shows that their median year-over-year profit growth was 17%, while companies that have not quantified the contribution of AI efficiencies were at 14%. Goldman Sachs noted that this gap is not statistically significant.
@橙子Joyce 🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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An Apple research team ran a reinforcement learning experiment with 9 models and 11 languages to find out: if the training data is only in one language, can the model’s problem-solving abilities be applied to questions in other languages?
The answer is yes, and the effect is quite noticeable. Training with only one language still makes the model stronger across many other languages as well.
For example, on a French test, training directly in French improved the average score by 25.6 percentage points. If you don’t train in French at all and only use Spanish questions for practice, you can still improve the score on the French test by 24.6 percentage points—just a 1-point difference.
What the model learns isn’t only problem-solving for a single language; it also learns some problem-solving methods that can be transferred and continued to be used in other languages. So in the future, if you want to strengthen the model’s Chinese reasoning, you may not need to remake all reinforcement learning data into Chinese.
For example, on a French test, training directly in French improved the average score by 25.6 percentage points. If you don’t train in French at all and only use Spanish questions for practice, you can still improve the score on the French test by 24.6 percentage points—just a 1-point difference.
What the model learns isn’t only problem-solving for a single language; it also learns some problem-solving methods that can be transferred and continued to be used in other languages. So in the future, if you want to strengthen the model’s Chinese reasoning, you may not need to remake all reinforcement learning data into Chinese.
@橙子Joyce 🧧🧧🧧🧧🧧🧧💰💵
橙子Joyce
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In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings!
Goldman Sachs strategist Ben Schneidau said that companies are increasing their investments in artificial intelligence (AI) at an unprecedented pace, yet for most firms, this technology has not yet translated into tangible improvements in earnings.
In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings. Another 11% said they had observed measurable productivity gains in specific areas such as software programming and customer support.
However, the companies that have implemented these efficiency improvements have not significantly outperformed overall market levels in terms of profit growth. Data shows that their median year-over-year profit growth was 17%, while companies that have not quantified the contribution of AI efficiencies were at 14%. Goldman Sachs noted that this gap is not statistically significant.
In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings. Another 11% said they had observed measurable productivity gains in specific areas such as software programming and customer support.
However, the companies that have implemented these efficiency improvements have not significantly outperformed overall market levels in terms of profit growth. Data shows that their median year-over-year profit growth was 17%, while companies that have not quantified the contribution of AI efficiencies were at 14%. Goldman Sachs noted that this gap is not statistically significant.
@橙子Joyce 🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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--
An Apple research team ran a reinforcement learning experiment with 9 models and 11 languages to find out: if the training data is only in one language, can the model’s problem-solving abilities be applied to questions in other languages?
The answer is yes, and the effect is quite noticeable. Training with only one language still makes the model stronger across many other languages as well.
For example, on a French test, training directly in French improved the average score by 25.6 percentage points. If you don’t train in French at all and only use Spanish questions for practice, you can still improve the score on the French test by 24.6 percentage points—just a 1-point difference.
What the model learns isn’t only problem-solving for a single language; it also learns some problem-solving methods that can be transferred and continued to be used in other languages. So in the future, if you want to strengthen the model’s Chinese reasoning, you may not need to remake all reinforcement learning data into Chinese.
For example, on a French test, training directly in French improved the average score by 25.6 percentage points. If you don’t train in French at all and only use Spanish questions for practice, you can still improve the score on the French test by 24.6 percentage points—just a 1-point difference.
What the model learns isn’t only problem-solving for a single language; it also learns some problem-solving methods that can be transferred and continued to be used in other languages. So in the future, if you want to strengthen the model’s Chinese reasoning, you may not need to remake all reinforcement learning data into Chinese.
@橙子Joyce 🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings!
Goldman Sachs strategist Ben Schneidau said that companies are increasing their investments in artificial intelligence (AI) at an unprecedented pace, yet for most firms, this technology has not yet translated into tangible improvements in earnings.
In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings. Another 11% said they had observed measurable productivity gains in specific areas such as software programming and customer support.
However, the companies that have implemented these efficiency improvements have not significantly outperformed overall market levels in terms of profit growth. Data shows that their median year-over-year profit growth was 17%, while companies that have not quantified the contribution of AI efficiencies were at 14%. Goldman Sachs noted that this gap is not statistically significant.
In a report published by Goldman Sachs on August 14, it said that during this year’s second-quarter earnings season, only 2% of the constituents of the $S&P 500 Index (.SPX.US)$ had quantified the specific impact of AI on earnings. Another 11% said they had observed measurable productivity gains in specific areas such as software programming and customer support.
However, the companies that have implemented these efficiency improvements have not significantly outperformed overall market levels in terms of profit growth. Data shows that their median year-over-year profit growth was 17%, while companies that have not quantified the contribution of AI efficiencies were at 14%. Goldman Sachs noted that this gap is not statistically significant.
帮帮Bonnie
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疲时知休 郁时知通 燥时知止
Rest when weary, release when weighed down, pause when agitated.
#牛来 #Financial Convenience Store
Rest when weary, release when weighed down, pause when agitated.
#牛来 #Financial Convenience Store
阿婧1688
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Spirits have their own spirit, and the mortal world has its own gentle joy.
Warm hearth smoke, soft tenderness—year after year, peace and safety. Follow the link below to claim 🧧🎁. It’s a pleasure to meet you!
Warm hearth smoke, soft tenderness—year after year, peace and safety. Follow the link below to claim 🧧🎁. It’s a pleasure to meet you!
燕寶Melissa
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Bearish🚨 Strategy: To Resume Buying Bitcoin Within the Year!
Long-term Bitcoin believers, here comes another strong signal.
According to FOX Business, Strategy CEO Phong Le said:
📌 The company plans to resume purchasing more BTC later this year.
Data shows: 🔥 Since the beginning of this year, Strategy has cumulatively bought about 175,000 BTC
📉 In the same period, it sold about 7,000 BTC
That means:
Bought amount ≈ 25 times the sold amount!
Selling BTC recently is not a change in strategy, but for:
✅ Paying preferred stock dividends
✅ Stock repurchases
✅ Increasing U.S. dollar reserves
Strategy’s core logic has not changed:
Using corporate capital allocation, with Bitcoin as a long-term value reserve asset.
From MicroStrategy to Strategy, this company is exploring a brand-new model of corporate asset management:
🏦 Traditional companies hold cash
➡️ In the future, companies may allocate digital assets
As institutions continue to raise their Bitcoin allocation, market attention is no longer just price volatility, but:
Bitcoin is gradually moving from being an investment asset to becoming part of corporate financial strategy.
📊 What to watch next:
1️⃣ Whether institutional funds continue to flow into BTC
2️⃣ Whether corporate Bitcoin reserve models will spread
3️⃣ How the trend of “financializing” BTC evolves
#BTC走势分析
$BTC
$ETH
$BNB
Long-term Bitcoin believers, here comes another strong signal.
According to FOX Business, Strategy CEO Phong Le said:
📌 The company plans to resume purchasing more BTC later this year.
Data shows: 🔥 Since the beginning of this year, Strategy has cumulatively bought about 175,000 BTC
📉 In the same period, it sold about 7,000 BTC
That means:
Bought amount ≈ 25 times the sold amount!
Selling BTC recently is not a change in strategy, but for:
✅ Paying preferred stock dividends
✅ Stock repurchases
✅ Increasing U.S. dollar reserves
Strategy’s core logic has not changed:
Using corporate capital allocation, with Bitcoin as a long-term value reserve asset.
From MicroStrategy to Strategy, this company is exploring a brand-new model of corporate asset management:
🏦 Traditional companies hold cash
➡️ In the future, companies may allocate digital assets
As institutions continue to raise their Bitcoin allocation, market attention is no longer just price volatility, but:
Bitcoin is gradually moving from being an investment asset to becoming part of corporate financial strategy.
📊 What to watch next:
1️⃣ Whether institutional funds continue to flow into BTC
2️⃣ Whether corporate Bitcoin reserve models will spread
3️⃣ How the trend of “financializing” BTC evolves
#BTC走势分析
$BTC
$ETH
$BNB
CipherX 零号
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Bitmart’s official account officially fires back at the company’s boss.
$BTC
$ETH
$BNB
$BTC
$ETH
$BNB
Verified
According to CNBC, last week Nvidia reached a partial guarantee agreement worth a total of $500 billion with a private equity firm to support what it calls a new “asset class” for computing power. Legal experts say recent guidance from the U.S. Securities and Exchange Commission (SEC) is paving the way for data center debt financing, which could make such financing more flexible and improve capital efficiency, while reducing the equity proportion required by the exchanges.
NAIO洋洋
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It has to be said that CZ has maximized the level of support for GIGGLE—no less than once delivering funding and traffic. Both timing and external forces have already fallen into place; what remains depends entirely on whether the project itself can seize the opportunity and break through.#giggle
从0开始1688
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📌Oh my, is Ethereum about to climb up 15,000? 😱
On August 17, BitMine’s chairman Tom Lee cited technical analysis, expressing expectations for a potential technical breakout in Ethereum.
Ethereum’s current price is only 3.5% away from the top boundary of the Ichimoku cloud of the daily chart—this would be the first time it has closed above that key resistance since October 9, 2025.
At present, the price of Ethereum is around $1,906, with cloud resistance just within reach.
Tom Lee continued his earlier bullish view on Ethereum. He previously posted publicly in July that the ETH/BTC ratio would strengthen in the second half of 2026. His core logic centered on the combined momentum of ETH’s monetary narrative, stablecoin growth, and the tokenization of assets.
The top of the Ichimoku cloud is regarded by technical analysts as an important reference for trend reversals. If it breaks out effectively, it may open up further upside room.
On August 17, BitMine’s chairman Tom Lee cited technical analysis, expressing expectations for a potential technical breakout in Ethereum.
Ethereum’s current price is only 3.5% away from the top boundary of the Ichimoku cloud of the daily chart—this would be the first time it has closed above that key resistance since October 9, 2025.
At present, the price of Ethereum is around $1,906, with cloud resistance just within reach.
Tom Lee continued his earlier bullish view on Ethereum. He previously posted publicly in July that the ETH/BTC ratio would strengthen in the second half of 2026. His core logic centered on the combined momentum of ETH’s monetary narrative, stablecoin growth, and the tokenization of assets.
The top of the Ichimoku cloud is regarded by technical analysts as an important reference for trend reversals. If it breaks out effectively, it may open up further upside room.
艾伦Eren1688
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Bullish*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
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
@Elena mythology
Elena神话
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Lately, I’ve been increasingly thinking that if Web3 truly wants to expand its user base, it can’t just keep spinning in its own circle.
$niulai $niuIai Choosing to start with film IP is, in my view, a fairly direct attempt.
《Niu Lai》 itself belongs to traditional content, and when combined with the Meme community, it effectively adds a new distribution channel for film IP.
This direction is worth continuing to explore. #niulai #牛来
$niulai $niuIai Choosing to start with film IP is, in my view, a fairly direct attempt.
《Niu Lai》 itself belongs to traditional content, and when combined with the Meme community, it effectively adds a new distribution channel for film IP.
This direction is worth continuing to explore. #niulai #牛来
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