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amazon, google and microsoft Updates

The artificial intelligence landscape continues to evolve rapidly, influencing everything from global financial markets to military strategy and cybersecurity. Major tech companies are pouring vast resources into building the foundational infrastructure for this new era. Amazon, Google, Microsoft, and Meta, for instance, collectively plan to spend over $350 billion on capital expenditures in 2025, primarily to expand data centers that will power AI applications. Experts anticipate that the demand for this infrastructure will remain high, with space likely staying limited until at least 2027, indicating sustained growth beyond current hype. In the financial sector, AI is transforming operations, automating tasks, and analyzing vast datasets for trading, credit checks, and fraud detection. However, the "black box" nature of many AI models, where decisions are hard to interpret, poses a significant challenge. US regulators, including the Federal Reserve and SEC, are pushing financial firms to ensure explainability and transparency in AI decisions to maintain fairness and compliance. This lack of clarity is a key reason why some investment professionals hesitate to fully adopt AI. Despite these hurdles, Goldman Sachs CEO David Solomon believes that while AI might reduce some white-collar jobs, the economy is flexible, and people will adapt by finding new roles and creating new businesses, much like with past technological shifts. Goldman Sachs reports that 37% of its clients already use AI for production, a figure expected to reach 74% within three years. The development of AI models relies heavily on massive datasets. The Common Crawl Foundation, a nonprofit, has spent over a decade archiving billions of webpages, providing petabytes of internet data free to researchers and AI companies. Prominent AI developers like OpenAI and Anthropic utilize this data to train their models and have also contributed donations to the foundation. Common Crawl asserts that using copyrighted material for this purpose constitutes fair use, viewing the internet as a public good, and its scraper can even bypass some news paywalls, leading to millions of articles from publishers like The New York Times being archived. Securing this AI-driven world is also a growing priority. Palo Alto Networks is updating its security products to prepare businesses for an "AI-first" environment, introducing new features for autonomous AI, the agentic workforce, and quantum readiness. Their offerings include a unified Strata Network Security Platform, AI-powered Strata Cloud Manager, Prisma Browser for enterprise security, Prisma AIRS 2.0 for AI applications, and Cortex AgentiX to secure AI agents in security operations. Beyond commercial applications, AI is also making inroads into military strategy. The US military faces the critical question of AI trust, with the argument that warfighters, rather than engineers or lawyers, should ultimately decide if AI systems are reliable in combat situations. This calls for a reevaluation of current equipment acquisition processes to prioritize operator trust. Innovation in AI deployment is also advancing. Perplexity AI, for example, launched an open-source system on November 4, 2025, enabling large AI models with trillions of parameters to run efficiently on AWS infrastructure without relying solely on NVIDIA's specialized networking hardware. This system, featuring a library called 'TransferEngine,' utilizes AWS Elastic Fabric Adapter for fast data transfers, performing comparably to NVIDIA's NVLink and NCCL on a 64-GPU cluster, offering cloud users more flexibility and potentially lowering costs. Finally, educational initiatives are emerging to prepare the next generation for these changes. Kennesaw State University recently hosted its first Fintech Hackathon, attracting over 200 students from various Georgia institutions to learn about topics like cryptocurrency and artificial intelligence, aiming to educate them on new financial technologies.

Key Takeaways

Amazon, Google, Microsoft, and Meta plan over $350 billion in capital expenditures in 2025, primarily for AI infrastructure like data centers, with demand expected to keep space limited until at least 2027.
AI is transforming finance, but regulators like the Federal Reserve and SEC demand explainability for AI decisions to address the "black box" problem and ensure fairness.
Goldman Sachs CEO David Solomon believes humans will adapt to AI, with 37% of Goldman clients already using AI for production, projected to reach 74% in three years.
The Common Crawl Foundation provides petabytes of free internet data, used by major AI developers like OpenAI and Anthropic to train their models, despite archiving copyrighted material.
Palo Alto Networks is enhancing its security products, including Strata Network Security Platform and Prisma AIRS 2.0, to protect businesses in an "AI-first" world, securing AI applications, agents, and data.
US military operators, not engineers, should determine the trustworthiness of AI systems for combat, emphasizing reliance in critical situations.
Perplexity AI launched an open-source system on November 4, 2025, allowing large AI models to run on AWS infrastructure without NVIDIA-specific hardware, potentially lowering costs and increasing flexibility.
Kennesaw State University hosted its first Fintech Hackathon, educating over 200 students on topics like cryptocurrency and artificial intelligence.
Human judgment remains crucial in AI-driven trading, especially during unexpected market changes, despite AI's role in automation and data analysis.
Tools like SHAP and LIME are being developed to help explain complex AI models and address the "black box" issue in finance.

AI Transforms Trading Human Judgment Remains Key

AI is changing how people trade by automating tasks and analyzing data. However, human judgment is still very important, especially during unexpected market changes. The Finance Magnates London Summit FMLS:25 will discuss how far AI can go in trading and its ethical challenges. Companies like Tiger Brokers and market simulators like ABIDES already use AI tools. Brokers face issues like making AI systems transparent for regulators and clients, dealing with ethical risks, and updating old systems.

Finance Needs Clear AI Decisions to Build Trust

AI is used in many parts of finance, like checking credit and spotting fraud. However, it is often hard to understand how AI makes its decisions, which creates a "black box" problem. US regulators, including the Federal Reserve and SEC, require financial firms to explain AI decisions to ensure fairness and compliance. This lack of clear explanations is a big reason why some investment professionals hesitate to use AI. Tools like SHAP and LIME are being developed to help explain these complex AI models.

AI Infrastructure Growth Will Last Beyond Hype

Despite some hype, the demand for AI infrastructure, especially data centers, is expected to continue growing for a long time. Companies are investing trillions of dollars globally into these facilities. Major tech giants like Amazon, Google, Microsoft, and Meta plan to spend over $350 billion on capital expenditures in 2025. Experts believe that current data center construction is not an overbuild, and space will remain limited until at least 2027. This infrastructure will likely form the foundation of a new economy.

Kennesaw State Hosts First Fintech Hackathon

Kennesaw State University held its very first Fintech Hackathon in late October. More than 200 students from various Georgia universities and high schools attended the event. Participants learned about important topics like cryptocurrency and artificial intelligence. The hackathon aimed to educate students on new financial technologies.

Warfighters Must Decide AI Trust in Military

The article argues that US military operators, not engineers or lawyers, should decide if AI systems are trustworthy. The current process for getting new equipment is slow and does not always focus on what matters in combat. For AI in warfare, trust means an operator can rely on the system when it counts. The author suggests the Secretary of Defense should make the Chief Digital and Artificial Intelligence Officer the main person to decide on AI trust. Congress should also add an operator trust assessment to the National Defense Authorization Act.

Common Crawl Feeds Internet Data to AI Firms

The Common Crawl Foundation, a nonprofit, has been collecting billions of webpages to build a massive internet archive for over a decade. This huge database, measured in petabytes, is given to researchers and AI companies for free. Major AI developers like OpenAI and Anthropic use this data to train their models and have also donated to Common Crawl. The foundation believes using copyrighted material is fair use, stating the internet is a public good. Its scraper can even bypass some news paywalls, leading to millions of articles from publishers like The New York Times being archived, despite requests to stop.

Global Shares Trade Lower After AI Boost

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Goldman Sachs CEO Says Humans Will Adapt to AI

David Solomon, the CEO of Goldman Sachs, believes that AI will not cause a job apocalypse. He states that the economy is flexible and people will adapt by finding new jobs and creating new businesses, just as they have with past technologies. Goldman Sachs reports that 37% of its clients already use AI for production, and this number is expected to reach 74% in three years. Solomon acknowledges that AI might reduce some white-collar jobs but expects new opportunities to appear in other areas of the economy.

Palo Alto Networks Boosts AI Security

Palo Alto Networks is preparing businesses for an AI-first world by updating its security products. At its Ignite event, the company introduced new features for autonomous AI, the agentic workforce, and quantum readiness. CEO Nikesh Arora highlighted a unified platform approach with the Strata Network Security Platform and AI-powered Strata Cloud Manager to simplify security. The new Prisma Browser offers strong security for enterprise browser use, while Prisma AIRS 2.0 provides comprehensive protection for AI applications, agents, models, and data. Additionally, Cortex AgentiX helps secure and monitor AI agents in security operations.

Perplexity Releases Open Source AI System for AWS

On November 4, 2025, Perplexity AI launched an open-source system that lets huge AI models, with trillions of parameters, run on AWS infrastructure. This new system provides a flexible option that does not rely on NVIDIA's special networking hardware. The key part is a library called 'TransferEngine,' which uses AWS Elastic Fabric Adapter for fast data transfers and works with different hardware. Tests show that Perplexity's system performs as well as NVIDIA's NVLink and NCCL on a 64-GPU cluster. This innovation gives cloud users more choices and could lower the costs of running large AI models, challenging NVIDIA's strong position.