市场资讯及洞察

The “Magnificent Seven” technology companies are expected to invest a combined $385 billion into AI by the end of 2025.

‍Microsoft is positioning itself as the platform leader. Nvidia dominates the underlying AI infra. Google leads in research. Meta is building open-source tech. Amazon – AI agents. Apple — on-device integration. And Tesla pioneering autonomous vehicles and robots.

With such enormous sums pouring into AI, is this a winner-take-all game?

Or will each of the Mag Seven be able to thrive in the AI future?

Microsoft: The AI Everywhere Strategy

Microsoft has made one of the biggest bets on AI out of the Mag Seven — adopting the philosophy that AI should be everywhere.

Through its deep partnership with OpenAI, of which it is a 49% shareholder, the company has integrated GPT-5 across its entire ecosystem.

‍Key initiatives:

• GPT-5 integration across consumer, enterprise, and developer tools through Microsoft 365 Copilot, GitHub Copilot, and Azure AI Foundry
• Azure AI Foundry for unified AI development platform with model router technology
• Copilot ecosystem spanning productivity, coding, and enterprise applications with real-time model selection
• $100 billion projected AI infrastructure spending for 2025

Microsoft’s centrepiece is Copilot, which can now detect whether a prompt requires advanced reasoning and route to GPT-5's deeper reasoning model.

This (theoretically) means high-quality AI outputs become invisible infrastructure rather than a skill users need to learn.

However, this all-in bet on OpenAI does come with some risks. It is putting all its eggs in OpenAI's basket, tying its future success to a single partnership.

Elon Musk warned that "OpenAI is going to eat Microsoft alive"[/caption]

Google: The Research Strategy

Google’s approach is to fund research to build the most intelligent models possible. This research-first strategy creates a pipeline from scientific discovery to commercial products — what it hopes will give it an edge in the AI race.

‍Key initiatives:

• Over 4 million developers building with Gemini 2.5 Pro and Flash
• Ironwood TPU offering 3,600 times better performance compared to Google’s first TPU
• AI search overviews reaching 2 billion monthly users across Google Search
• DeepMind breakthroughs: AlphaEvolve for algorithm discovery, Aeneas for ancient text interpretation, AlphaQubit for quantum error detection, and AI co-scientist systems

Google’s AI research branch, DeepMind, brings together two of the world's leading AI research labs — Google Brain and DeepMind — the former having invented the Transformer architecture that underpins almost all modern large language models.

The bet is that breakthrough research in areas like quantum computing, protein folding, and mathematical reasoning will translate into a competitive advantage for Google.

Today, we're introducing AlphaEarth Foundations from @GoogleDeepMind , an AI model that functions like a virtual satellite which helps scientists make informed decisions on critical issues like food security, deforestation, and water resources. AlphaEarth Foundations provides a… pic.twitter.com/L1rk2Z5DKk

— Google AI (@GoogleAI) July 30, 2025

Meta: The Open Source Strategy

Meta has made a somewhat contrarian bet in its approach to AI: giving away their tech for free. The company's Llama 4 models, including recently released Scout and Maverick, are the first natively multi-modal open-weight models available.

‍Key initiatives:

• Llama 4 Scout and Maverick - first open-weight natively multi-modal models
• AI Studio that enables the creation of hundreds of thousands of AI characters
• $65-72 billion projected AI infrastructure spending for 2025

This open-source strategy directly challenges the closed-source big players like GPT and Claude. By making AI models freely available, Meta is essentially commoditizing what competitors are trying to monetize. Meta's bet is that if AI models become commoditized, the real value will be in the infrastructure that sits on top. Meta's social platforms and massive user base give it a natural advantage if this eventuates.

Meta's recent quarter was also "the best example to date of AI having a tangible impact on revenue and earnings growth at scale," according to tech analyst Gene Munster.

However, it hasn’t been all smooth sailing for Meta. Their most anticipated release, Llama Behemoth, has all but been scrapped due to performance issues. And Meta is now rumored to be developing a closed-source Behemoth alternative, despite their open-source mantra.

Amazon: The AI Agent Strategy

Amazon’s strategy is to build the infrastructure for AI that can take actions — booking meetings, processing orders, managing workflows, and integrating with enterprise systems.

Rather than building the best AI model, Amazon has focused its efforts on becoming the platform where all AI models live.

‍Key initiatives:

• Amazon Bedrock offering 100+ foundation models from leading AI companies,  including OpenAI models.
• $100 million additional investment in AWS Generative AI Innovation Center for agentic AI development
• Amazon Bedrock AgentCore enabling deployment and scaling of AI agents with enterprise-grade security
• $118 billion projected AI infrastructure spending for 2025

The goal is to become the “orchestrator” that lets companies mix and match the best models for different tasks.

Amazon’s AgentCore will provide the underlying memory management, identity controls, and tool integration needed for these companies to deploy AI agents safely at scale.

This approach offers flexibility, but does carry some risks. Amazon is essentially positioning itself as the middleman for AI. If AI models become commoditized or if companies prefer direct relationships with AI providers, Amazon's systems could become redundant.

Nvidia: The Infra Strategy

Nvidia is the one selling the shovels for the AI gold rush. While others in the Mag Seven battle to build the best AI models and applications, Nvidia provides the fundamental computing infrastructure that makes all their efforts possible.

This hardware-first strategy means Nvidia wins regardless of which company ultimately dominates. As AI advances and models get larger, demand for Nvidia's chips only increases.

‍Key initiatives:

• Blackwell architecture achieving $11 billion in Q2 2025 revenue, the fastest product ramp in company history
• New chip roadmap: Blackwell Ultra (H2 2025), Vera Rubin (H2 2026), Rubin Ultra (H2 2027)
• Data center revenue reaching $35.6 billion in Q2, representing 91% of total company sales
• Manufacturing scale-up with 350 plants producing 1.5 million components for Blackwell chips

With an announced product roadmap of Blackwell Ultra (2025), Vera Rubin (2026), and Rubin Ultra (2027), Nvidia has created a system where the AI industry must continuously upgrade to Nvidia’s newest tech to stay competitive.

This also means that Nvidia, unlike the others in the Mag Seven, has almost no direct AI spending — it is the one selling, not buying.

However, Nvidia is not indestructible. The company recently halted its H20 chip production after the Chinese government effectively blocked the chip, which was intended as a workaround to U.S. export controls.

Apple: The On-Device Strategy

Apple's AI strategy is focused on privacy, integration, and user experience. Apple Intelligence, the AI system built into iOS, uses on-device processing and Private Cloud Compute to help ensure user data is protected when using AI.

‍Key initiatives:

• Apple Intelligence with multi-model on-device processing and Private Cloud Compute
• Enhanced Siri with natural language understanding and ChatGPT integration for complex queries
• Direct developer access to on-device foundation models, enabling offline AI capabilities
• $10-11 billion projected AI infrastructure spending for 2025

The drawback of this on-device approach is that it requires powerful hardware from the user's end.  Apple Intelligence can only run on devices with a minimum of 8GB RAM, creating a powerful upgrade cycle for Apple but excluding many existing users.

Tesla: The Robo Strategy

Tesla's AI strategy focuses on two moonshot applications: Full Self-Driving vehicles and humanoid robots.

This is the 'AI in the physical world' play. While others in the Mag Seven are focused on the digital side of AI, Tesla is building machines that use AI for physical operations.

‍Key initiatives:

• Plans for 5,000-10,000 Optimus robots in 2025, scaling to 50,000 in 2026
• Robotaxi service targeting availability to half the U.S. population by EOY 2025
• AI6 chip development with Samsung for unified training across vehicles, robots, and data centers
• $5 billion projected AI infrastructure spending for 2025

This play is exponentially harder to develop than digital AI, and the markets have reflected low confidence that Tesla can pull it off.

TSLA has been the worst-performing Mag Seven stock of 2025, down 18.37% in H1 2025.

However, if Tesla’s strategy is successful, it could be far more valuable than other AI plays. Robots and autonomous vehicles could perform actual labour worth trillions of dollars annually.

The $385 billion Question

The Mag Seven are starting to see real revenue come in from their AI investments. But they're pouring that money (and more) back into AI, betting that the boom is just getting started.

The platform players like Microsoft and Amazon are betting on becoming essential infrastructure. Nvidia’s play is to sell the underlying hardware to everyone. Google and Meta compete on capability and access. While Apple and Tesla target specific use cases.

The $385 billion question is which of the Magnificent Seven has bet the right way? Or will a new player rise and usurp the long-standing tech giants altogether?

‍You can access all Magnificent Seven stocks and thousands of other Share CFDs on GO Markets.

提到 Adobe，你可能第一反应就是 PS 修图，什么“P 个证件照”、“把前任抠掉”、“给自己多修两根头发”。但别小看这家公司，它早已不只是修图工具，而是一个彻头彻尾的“内容生意收租户”。本文带你轻松了解 Adobe 的商业模式、护城河，以及它和竞争对手们的市场动态。一、Adobe 卖的是什么？三朵云撑起的江山根据 Adobe 官网及 2024 财报披露，目前其业务主要分成三大板块：

1. Creative Cloud：包含 Photoshop、Illustrator、Premiere Pro、After Effects、Lightroom，以及新推出的生成式 AI 工具 Firefly 和 Express。很多 APP 界面、广告海报、短视频包装的制作工具都来自这里。
2. Document Cloud：以 PDF 和电子签名为核心。PDF 已成为全球文档标准之一。Adobe 也在 Acrobat 中引入了 AI 助手，还推出 Acrobat Studio，帮助用户更高效处理合同、报告等文档。
3. Experience Cloud：这是企业级营销与数据平台，包含实时客户数据平台、自动化用户旅程工具，并在 2024 年推出了 GenStudio，结合 AI 生成营销内容。

二、钱从哪来？订阅才是大头根据 Adobe 2024 财年年报（来源：Adobe Investor Relations）：

• 订阅模式为主要收入2024 财年，Adobe 总营收 215 亿美元，其中 95% 来自订阅（约 205 亿美元）。传统的一次性授权软件收入已降至不足 4 亿美元。
• 创作与文档工具收入Creative Cloud 收入 127 亿美元，Document Cloud 收入 32 亿美元，两者合计 159 亿美元。Adobe 将其归入 Digital Media 板块。
• 企业客户贡献Digital Experience 板块实现收入 54 亿美元，主要来自大型企业签署的营销与数据服务合同。
• 收入确定性截至 2024 财年末，Adobe 的 年化经常性收入（ARR）达到 173 亿美元，未来待确认合同收入（RPO）约 200 亿美元。这显示其订阅模式具备较强稳定性。

一句话总结：Adobe 的核心盈利模式是“工具即服务”，持续收取订阅费用。三、AI 的角色：Adobe 的“新店小二”Adobe 在生成式 AI 上的布局强调合规与版权安全：

• Firefly：训练素材主要来自 Adobe Stock 和公共领域资源，降低版权风险。生成内容带有“内容凭证”标识，便于追溯。
• 收费模式：Adobe 引入“生成点数”机制，用户使用 Firefly 生成图片或视频会消耗额度，不同订阅计划包含的点数不同。
• 业务规模：在 2025 财年 Q1 财报电话会（来源：Adobe IR Conference Call），管理层表示 AI 产品已带来约 1.25 亿美元收入，公司预计全年会进一步增长。

四、护城河：行业标准的力量

• Photoshop、Illustrator、Premiere 等长期在专业创意和影视制作中占据主导地位。
• PDF 格式已成为国际通用文档标准，Acrobat 和 Sign 构建了从生成、流转到签署的一体化链条。
• 丰富的教程、插件、模板、认证培训构成完整生态。
• 在 AI 时代，“内容凭证”等安全与合规机制成为 Adobe 的新壁垒。

五、竞争者：Figma 与 Canva

• Figma：Adobe 曾计划以 200 亿美元收购，但因监管原因未能完成。Figma 已独立上市，并将在 2025 年 9 月 3 日公布财报（来源：Figma 公告）。市场将关注其盈利能力和用户增长情况。
• Canva：2024 年收购了 Affinity 三件套，进一步进入专业设计市场。其优势在于简洁易用，受到中小企业和个人创作者的青睐。

六、近期关注点

• Document Cloud 增速：2024 财年增长 18%，高于 Creative Cloud 的增速。
• AI 收入贡献：能否在 2025 财年内实现翻倍增长，将是投资者和分析师关注的重点。
• Experience Cloud 的渗透率：GenStudio 等产品能否成为企业营销日常工具。
• 定价调整效果：Adobe 在北美推出 Creative Cloud Pro，并提升 AI 配额，价格上调后的市场接受度仍待观察。

一句话总结Adobe 的商业模式就像“房东”，靠订阅模式获得稳定现金流；AI 则是它刚上岗的“新店小二”，未来贡献尚待验证；而 Figma 与 Canva 则是市场上不同定位的竞争者，后续发展仍需关注官方财报与市场反馈。免责声明：GO Markets 分析师或外部发言人提供的信息基于其独立分析或个人经验。所表达的观点或交易风格仅代表其个人；并不代表 GO Markets 的观点或立场。联系方式：墨尔本 03 8658 0603悉尼 02 9188 0418中国地区(中文） 400 120 8537中国地区(英文） +248 4 671 903

Traders love to talk about “trading the gap,” but they often skip over the first, and most critical step — defining what a gap is and why it is happening. The reality is that there are multiple types of gaps, and each can offer different opportunities and risks.The key is knowing the type of gap you are dealing with and how to respond.

What Is a Gap?

In price action terms, a gap on a chart occurs when the price jumps from one trading period to the next without any trades in between. It is most commonly seen between the close of one session and the open of the next session across multiple asset classes. Even with assets that trade 24 hours a day, gaps are often seen at the start of the next trading week.

Why Do Gaps Form?

The market is a continuous auction of buyers and sellers, but between sessions or over weekends, new information can drop that affects the market.Economic data releases, corporate earnings announcements, geopolitical developments, and unexpected supply/demand changes can all occur outside of market hours.When the market reopens, the price adjusts instantly to reflect this. If the next available trades are far from the previous close, you get a gap.In continuous markets like forex, gaps most often appear on Monday opens after weekend news, but may show up on intraday charts after unexpected events that cause major liquidity changes.

The Main Types of Gaps

Common Gaps

• Usually small.
• Occur within an established range or trend
• Most likely to fill quickly
• No strong underlying cause
• Successful trades reliant on being there at the time of occurrence

Breakaway Gaps

• Appear at the start of a new trend
• Break out from a long consolidation or key support/resistance
• Driven by strong conviction created by a big event
• Less likely to fill quickly
• Represent a genuine shift in market positioning.

Runaway (Continuation) Gaps

• Tend to occur mid-trend
• Signal momentum in the previous direction is intact
• Often act as future support or resistance levels
• May not fill until the trend is complete

Exhaustion Gaps

• Form near the end of a strong move
• Often result from a final push of buying/selling pressure.
• Price will often reverse after exhaustion gaps as the last participants are trapped

The key is to identify when and which of these four types of gaps is in play and decide whether to fade (trade against) the gap or go with it.

Why Price Often Fills Gaps

The idea of “gap filling” is generally dependent on market mechanics when a gap forms:Traders caught on the wrong side may want to exit near the pre-gap price. Large unfilled orders from before the gap can be sitting in the relevant price range. And if the gap was driven by an emotional overreaction rather than strong fundamentals, the price often reverts to normal.But although gap filling may be a common occurrence, it is not guaranteed. As with any trading approach, risk management is critical, and having a clear set of unambiguous criteria for both entry and exit is a must.Ideally, your risk management should consider the following:

• Knowing the context. Understand whether the gap is technical (range breakout) or news-driven before acting. This impacts the type and longevity of any move.
• Avoid chasing. Gap approaches are always best actioned early to provide a higher probability outcome. Not entering at all and waiting for the next opportunity is better than entering late.
• Place stops strategically. For gap fill approaches, many traders will place stops go beyond the gap extreme, for go trades, stops go just inside the gap.
• Consider the volatility of the underlying asset. Position your trade size accordingly, appropriate to the technical picture and your tolerable level of risk.

Gap Trading Strategies

Gap Fill (Fade) Strategy

This tends to offer the optimum opportunities with common and exhaustion gaps.Traders should be patient and wait for early signs across multiple short timeframes that momentum is fading after the open bar(s).The approach here is to enter in the opposite direction of the price gap move. Profit targets are usually set at a price prior to (but not at) the pre-gap price Stops may be placed just above the initial gap price, and a trailing approach to locking in profit can be used to enable early exit if conditions change.Example: If EURUSD gaps up 40 pips on a quiet Monday with no news, and price struggles to push higher in the first hour, you might consider a short trade with a profit target at Friday’s close.

Gap and Go Strategy

This approach is suited to breakaway or continuation gaps. Traders should look for a move in the gap direction after the first bar with a high-volume confirmation that the pressure is continuing in that direction.Trade entry is in the direction of the gap, and many traders would accumulate further positions should the momentum increase on continuation of a price move. Initial stops are often placed just inside the gap, giving a little space to accommodate market noise and a potential retest. Aim to capture momentum, with a trailing stop approach to ride the trend aligned with any accumulation into the positionExample: Oil price gaps up on a Monday after Friday's COT (commitment of traders) data release, suggesting a change in institutional interest and breaks out from a 1-month range on high volume.Important: Both these strategies, although they can often be seen at the same initial gap on a chart, are different in terms of entry and exit approaches. They merit a separation in terms of trading plan and should not be combined as a single approach with a variation.

Final Thoughts

Gap trading is as much about identifying context and having clear criteria for what constitutes a gap. A real edge with gap trading comes from understanding why it has formed, what type it is, and early identification of what is happening.Whether you trade gaps manually or with an EA, it is good to remember that a gap is simply the space; any opportunity will come from reading what that space is telling you.

最近，特朗普一句话 “退休账户也可以买数字货币！”直接像给烧烤架泼了桶酒精，整个数字货币市场“呼”地燃了起来。比特币、以太坊接连冲高，连带着几家“买币当家业”的上市公司股价也跟着蹦起来。今天咱就用大白话聊聊这四家代表公司：1. MSTR（Strategy）——“比特币仓库”这家公司原名 MicroStrategy，本来是做企业数据分析软件的。但老板 Michael Saylor 心想：“美元放银行会贬值，不如换成比特币！”于是从 2020 年开始，MSTR疯狂买 BTC，不光用公司利润买，还发行债券、卖股票筹钱买。现在他们手里有 58 万多枚比特币，按市价算价值六百多亿美元！玩法很简单：融资 → 买币 → 币价涨 → 资产变多 → 股价也涨 → 再融资 → 再买币股民直接把它当成“比特币股票化”，想投 BTC 但不想自己存币，就买它的股票。当然，币价要是跌，账面就跟坐滑梯一样。2. SBET（SharpLink Gaming）——“以太坊版 MSTR”SBET 原来是个小型科技公司，2025 年突然转型：拉来 4 亿多美元，直接买了十几万枚以太坊（ETH）。买了币不闲着，还拿去质押，年化收益 7%-8%。随着 ETH 涨价，SBET 的股票一个月飙了 140%，还跑到纳斯达克敲钟庆祝自己是全球最大以太坊上市公司。一句话总结：SBET 就是把 MSTR 的套路搬到以太坊身上，还加了“利息”这个buff。3. BMNR（BitMine）——ETH 财库新对手BMNR 原来是挖比特币的矿企，后来觉得 ETH 更有潜力，于是转型走“以太坊财库”路线。操作流程：私募融资 2.5 亿美元买 ETH买到手后继续融资、继续买宣布股票回购计划，把股价托上去玩质押、DeFi，把 ETH 用到极致现在它和 SBET 形成了竞争关系。ETH 波动比 BTC 大，赚得多的时候更猛，但跌起来也更疼。4. TRON（波场）——借壳上市的 TRX 财库TRON 是孙宇晨创立的公链项目，这次他们也想玩上市公司财库模式。具体做法：找一家纳斯达克上市公司，通过反向并购变成“Tron Inc.”，然后宣布——我们是全球最大上市 TRX 持有公司，手里有 3.65 亿多枚 TRX，还会质押拿收益。这个故事性十足。四家公司小对比

小结这四家公司把数字货币搬进上市公司的金库，通过股票让投资者间接参与市场。政策利好为他们打开了更多资金渠道，但币价涨跌波动大，投资者心态要稳，不要被短期涨幅冲昏头脑。联系方式：墨尔本 03 8658 0603悉尼 02 9188 0418中国地区(中文） 400 120 8537中国地区(英文） +248 4 671 903作者：Mill Li | GO Markets 墨尔本中文部

隔夜美股延续强势走势，纳斯达克与标普500高开低走但依旧收阳，道琼斯指数则持续上行。投资者的目光再度集中在美联储9月降息预期上——市场传出有官员支持一次性降息50个基点的观点，引发关注。科技板块方面，美国政府与英伟达、AMD达成的芯片收入分成协议成为热点话题，白宫还透露该机制或将扩展至其他企业。与此同时，数字货币领域全面走高，比特币突破历史高点，以太坊再度刷新纪录，新近上市的“Bullish”凭借美国本土背景备受追捧，首日暴涨逾83%，盘后再涨近10%，上演一场资本市场的“速度与激情”。今日市场焦点转向澳大利亚与美国经济数据。澳洲将公布最新失业率数据，预期小幅回落或缓解澳联储降息压力；美国方面，PPI数据将在今晚发布，或对美元与通胀预期产生短期影响。个股表现上，部分上半年新上市的明星股出现回调压力：CRWV财报不及预期，股价大跌20%跌破120美元支撑；CRCL宣布增发1000万股，股价下挫逾6%，未能站稳160美元关口。澳股今日则出现补涨行情，银行股反弹削弱昨日下跌带来的拖累；资源板块中，澳铀价格小幅反弹，但SLX股价回落至增发价。汇市方面，澳元兑美元继续走强，日元表现坚挺，带动美元兑日元与澳元兑日元均回落。美元兑人民币跌破7.18关口，澳元兑人民币稳定在4.70附近。尽管澳联储降息对澳元构成利空，但美元因降息预期升温而走弱，反而间接支撑了澳元与人民币的相对稳定。贵金属方面，金价明显反弹，油价则持续下行，市场风险情绪依旧偏乐观。联系方式：墨尔本 03 8658 0603悉尼 02 9188 0418中国地区(中文） 400 120 8537中国地区(英文） +248 4 671 903作者：Xavier Zhang | GO Markets 高级分析师

上周五，美股再度走高，市场情绪受到多重利好推动。美国最新行政令鼓励养老金入市，带动虚拟货币板块全面上涨，以太坊创下历史新高，比特币逼近12万美元关口。周末行情的火热，也为新一周市场定下了积极基调。本周金融市场看点颇多。澳大利亚方面，周二澳联储将公布利率决议，市场普遍预期降息25个基点，周四将发布最新失业率，预计较前值小幅回落至4.2%。美国方面，周二CPI数据即将公布，市场预测同比增速在2.8%左右，略高于前值2.7%，若符合预期，对市场冲击有限。目前，美联储在人员调整之际，市场普遍认为9月降息几乎已成定局，部分机构甚至预计降息幅度可能达到50个基点。周四将迎来PPI数据，周五则是被称为“恐怖数据”的零售销售月率，预计环比变动不大。此外，热门公司OKLO、CRWV、CRCL等将陆续发布财报，或将引发短期交易机会。外汇与大宗商品方面，美元指数本周或随数据公布小幅波动。CPI若略超预期可能短暂支撑美元，而零售销售若走弱则可能施压美元。黄金价格近期承压，短期或难守住3400美元/盎司关口；油价则继续下探，市场情绪保持谨慎。外汇市场早盘整体平稳，澳元兑日元保持在0.65上方，美元兑日元在148附近震荡，美元兑人民币徘徊于7.19，澳元兑人民币呈现一定升势。总体来看，本周市场焦点集中在澳美利率政策、通胀数据与大宗商品走势，投资者可关注降息预期与风险资产表现的互动变化。联系方式：墨尔本 03 8658 0603悉尼 02 9188 0418中国地区(中文） 400 120 8537中国地区(英文） +248 4 671 903作者：Xavier Zhang | GO Markets 高级分析师