Nvidia, AMD AI Chips, Scale AI Funding, Zuckerberg Fears

The artificial intelligence landscape is rapidly evolving, marked by significant investments and growing trade in AI-related goods. Major tech companies are poised to reveal the impact of their AI spending in upcoming third-quarter earnings reports, with analysts like Dan Ives pointing to an ongoing 'AI super cycle' driving market growth. This optimism is reflected in global trade, where the World Trade Organization has raised its 2025 forecast, largely due to increased purchases of semiconductors, servers, and telecommunications equipment. Companies like Nike are integrating AI to enhance customer experiences, personalize recommendations, and even design products, as seen with their NikeAI Beta app and AI-created shoe designs for the Paris Olympics. Meanwhile, the security of AI systems is a growing concern. Agentic AI, capable of autonomous decision-making, introduces new risks, necessitating intent-based permissions rather than traditional action-based ones to manage access effectively. The proliferation of AI across multiple cloud applications further complicates data governance and identity management. The market for agentic AI is currently seeing supply outpace demand, a situation Gartner expects to lead to consolidation. To navigate this, new tools like SemiAnalysis's InferenceMax benchmark are emerging to test the efficiency and cost of AI software stacks, supporting hardware from Nvidia and AMD. Beyond business applications, AI's influence extends to creative fields, with producer Timbaland debuting an AI artist, Tata Taktumi. However, AI also presents challenges, including sophisticated scams where AI is used to impersonate businesses and defraud customers, as experienced by jeweler Deanna Newman. In the public sector, New York State is training its employees on AI fundamentals to prepare the workforce for its increasing role. Amidst these developments, some tech leaders, including Mark Zuckerberg, are reportedly preparing for potential doomsday scenarios, reportedly linked to concerns about Artificial General Intelligence.

Key Takeaways

• Upcoming third-quarter earnings reports will be a key indicator of the success and scale of AI investments by major tech companies.
• Global trade is experiencing a surge, with the World Trade Organization increasing its 2025 forecast due to strong demand for AI-related goods like semiconductors and servers.
• Nike is leveraging AI for customer experience enhancements, personalized recommendations via NikeAI Beta, and AI-generated product designs.
• Securing autonomous AI agents requires a shift to intent-based permissions, which consider the 'why' behind an AI's actions, rather than just traditional action-based controls.
• The widespread use of AI across multiple cloud applications creates complex data governance and identity management challenges.
• Gartner reports that the supply of agentic AI currently exceeds demand, anticipating a period of market consolidation.
• New benchmarks like SemiAnalysis's InferenceMax are being developed to evaluate the efficiency and total cost of ownership for AI software stacks, supporting hardware from Nvidia and AMD.
• AI is being used in creative industries, exemplified by music producer Timbaland's debut of an AI artist, Tata Taktumi.
• AI-powered scams are emerging, with businesses being impersonated to defraud customers, highlighting a growing security risk.
• Concerns about the potential risks of Artificial General Intelligence (AGI) are reportedly leading some tech leaders, including Mark Zuckerberg, to prepare for doomsday scenarios.

Agentic AI brings new risks and rewards for businesses

Agentic AI, a new form of artificial intelligence, presents both opportunities and challenges for businesses. These AI agents can make decisions and learn like humans but also inherit security risks from both human and machine identities. Managing their scale, oversight, and access to resources is complex. AI agents lack human security awareness, making them vulnerable to exploitation. Organizations must develop strong identity security strategies to manage these new AI identities effectively.

Intent-based permissions needed for AI agent security

Traditional action-based permissions are insufficient for securing AI agents, which operate autonomously. These systems need intent-based permissions that understand the 'why' behind an AI agent's actions, not just the 'what.' This approach uses context like task type and data sensitivity to make smarter access decisions, similar to a car's advanced safety features. By mapping permissions to goals, intent-based IAM reduces risks and supports productivity without compromising security. This shift requires a phased approach, starting with tighter action-based controls and moving towards unified identity frameworks.

Three ways to secure AI across multiple cloud apps

The rise of AI across various cloud and SaaS platforms creates new data governance and security risks due to increased interconnectivity. This multi-cloud sprawl makes consistent governance difficult, as different platforms have varying policies and access controls. The explosion of AI agents and connectors also multiplies the identity and access management burden. To address these challenges, organizations need strong data governance, a scalable identity and access strategy for AI identities, and unified visibility across all cloud environments. Focusing on core data and bringing AI workloads closer to it can help reduce complexity and risk.

Q3 earnings to validate AI spending, says analyst

Upcoming third-quarter earnings reports from major tech companies will be a critical 'validation moment' for their significant investments in artificial intelligence. Analyst Dan Ives believes Wall Street will get a clearer picture of these AI expenditures as results are released. Ives also suggests that investors are currently underestimating the impact of an 'AI super cycle' that is driving market growth. This period is expected to show how AI advancements and adoption are fueling market momentum.

Wall Street sees AI as key stock market driver

Wall Street is increasingly optimistic about artificial intelligence as a catalyst for stock performance. While some debate whether an AI-driven bubble is forming, experts like Goldman Sachs suggest the market is not there yet. Dan Ives of Wedbush Securities highlights that the upcoming earnings season will be crucial for Big Tech to justify their substantial AI investments. This focus on AI's impact on company value and market trends indicates a growing bullish sentiment among investors.

AI buying fuels unexpected global trade growth

The World Trade Organization (WTO) has significantly increased its forecast for global goods trade growth in 2025, driven by a surge in AI-related purchases. This includes strong demand for semiconductors, servers, and telecommunications equipment. The WTO also noted front-loaded imports in the U.S. due to tariff concerns and robust trade among developing nations. Despite headwinds, trade has shown resilience, with AI goods accounting for a substantial portion of global trade growth.

AI scammers steal business name to defraud customers

A jeweler named Deanna Newman has reported that AI scammers copied her business name, 'C'est la vie Jewellery,' to defraud customers. The fake company, operating from China, used the name to sell low-quality items, leading to complaints directed at Newman's legitimate business. Newman has faced customer anger and confusion, damaging her brand's reputation. She is working to separate her business from the scam and hopes social media platforms will remove the fraudulent page. This incident highlights the growing scale of AI-enabled fraud.

New York trains state employees on AI basics

New York State has launched a pilot program to train 1,000 state employees on artificial intelligence fundamentals. This hands-on initiative, a collaboration between the Office of Information Technology Services (ITS) and InnovateUS, aims to introduce staff to practical AI applications in their daily work. The program includes foundational knowledge, ethical considerations, and practical experience using AI tools. This pilot is part of Governor Kathy Hochul's broader strategy to advance AI adoption across the state, preparing the workforce for the technology's growing role.

Nike uses AI to boost customer experience and product design

Nike is integrating artificial intelligence across its business to enhance customer experience, advertising, and product design as part of its turnaround strategy. The company has launched NikeAI Beta for its iOS app users, offering personalized recommendations and conversational search. In South Korea, Nike is using AI-powered ads on Naver's platform to act as virtual brand ambassadors. Additionally, Nike showcased AI-created shoe designs for athletes during the 2024 Paris Olympics through its A.I.R. initiative. These AI applications aim to improve customer engagement and drive sales.

Tech billionaires prepare for doomsday amid AI fears

Several tech billionaires, including Mark Zuckerberg, are reportedly preparing for potential doomsday scenarios by investing in underground shelters and remote properties. This trend is fueled by concerns from AI leaders about the potential risks of Artificial General Intelligence (AGI). The uncertainty surrounding AGI's future impact on humanity and society appears to be a driving factor behind these secretive preparations. The actions of these tech leaders raise questions about their anticipation of future global events.

Timbaland debuts AI artist Tata Taktumi

Music producer Timbaland is testing his theory that AI has 'pure soul' with the debut of his AI-generated artist, Tata Taktumi. The single 'Glitch x Pulse' features AI-generated vocals and music, with Timbaland's signature ad-libs and beats. The lyrics are human-written, but the overall production and artist persona are AI-driven. This project, created in partnership with the AI music platform Suno, aims to pioneer a new genre of music called 'A-pop' or artificial pop. The music video also features the dance crew Jabbawockeez.

Agentic AI supply outpaces demand, Gartner reports

According to Gartner, the current supply of agentic AI models and products significantly exceeds market demand, leading to an expected period of consolidation and market correction. This situation is a normal part of the product lifecycle, not an economic crisis. Companies with strong resources are likely to acquire promising technologies and talent, while undifferentiated AI firms may struggle. This consolidation will eventually lead to more robust agentic products that meet customer needs, driven by domain-specific models and evolving consumer habits.

New benchmark tests AI software stacks and costs

SemiAnalysis has launched InferenceMax, an open-source benchmark suite that evaluates the efficiency and total cost of ownership (TCO) of AI software stacks. Unlike traditional benchmarks that focus on hardware, InferenceMax measures performance in real-world inference scenarios nightly. It assesses factors like throughput and interactivity to determine the most cost-effective GPU configurations, measured in dollars per million tokens. The benchmark supports various Nvidia and AMD hardware and aims to provide vendor-neutral insights into AI performance and TCO.

Sources

• The Business Rewards and Identity Risks of Agentic AI - SPONSOR CONTENT FROM CYBERARK
• Securing agentic AI with intent-based permissions
• Three ways to secure AI across cloud apps
• Q3 earnings will be 'validation moment' for AI spend: Dan Ives
• Wall Street increasingly bullish on AI catalysts for stocks
• WTO says AI-related buying binge and a spike in US imports spur unexpected rise in goods trade
• 'AI scammers stole my business name to scam customers'
• New York Launches Hands-On AI Pilot for State Employees
• Ecommerce Trends: How Nike is using AI
• Tech billionaires like Zuckerberg are reportedly prepping for doomsday; are we next?
• Timbaland Puts His AI Music Has ‘Pure Soul’ Theory to the Test With Tata Taktumi Debut
• Agentic AI supply far exceeds demand, says Gartner
• InferenceMax AI benchmark tests software stacks, efficiency, and TCO — vendor-neutral suite runs nightly and tracks performance changes over time