Tech stocks tied to artificial intelligence took a significant hit last week as investors grew cautious ahead of the midterms. The Philadelphia Semiconductor Index plunged 3.37% to 10,328.33, while chip makers AMD, Nvidia, and Marvell saw their shares decline. Google's stock price dropped 12% over the past week. The selloff followed a major decline on October 30 triggered by Intel's disappointing guidance, and TSMC's ADR fell 1.85% to $398.63, losing the $400 mark.
Despite the tech weakness, broader market signals offered some reassurance. J.P. Morgan raised its year-end S&P 500 target to 8,000, pointing to roughly 5% upside. Over half of S&P 500 stocks hit 20-day highs, and an AI-stripped S&P 500 rose 8% in October to a record high while AI-related shares fell more than 13%. Capital appears to be rotating from rich AI names into non-AI companies.
On the regulatory and policy front, India's Ministry of Electronics and Information Technology released the DEPA for AI Training Handbook in Bengaluru. The framework helps institutions share data for AI training without surrendering privacy or ownership. It uses binding contracts, secure computing systems, and cryptographic safeguards. A key feature is that AI models access data without institutions transferring their datasets — the model travels to the data, not the other way around.
Major investment activity in AI continued to accelerate. Apollo Global Management lent a record $114 billion to companies in the AI sector, including Anthropic and chipmaker Nvidia. The move reflects growing private equity interest in AI technology, driven by rapid growth and potential applications in healthcare, finance, and transportation.
Several companies also rolled out new AI-powered tools and platforms. AvaTrade launched a multi-asset trading platform using more than 20 years of historical trader behavior data. Tradeview Markets introduced its EDGE AI execution engine, which took over two years and millions of dollars to develop. NVIDIA Recovery, an automated system for AI training workload restoration, monitored nearly 200 jobs per day over three months with mean detection and recovery latencies of 69 and 94 seconds respectively.
Legal and partnership developments rounded out the week. A shareholder lawsuit was filed against Alphabet in Delaware, alleging directors breached fiduciary duties by allowing unlawful AI training practices. Burnham Park Capital Markets partnered with Sentinel AI to bring real-time retail investor sentiment data to its research services, covering over 250 public companies worth more than $350 billion in combined market cap.
Key Takeaways
- The Philadelphia Semiconductor Index fell 3.37% to 10,328.33 amid investor caution over AI spending ahead of the midterms.
- Intel's disappointing guidance on October 30 triggered a major selloff, with AMD, Nvidia, and Marvell shares declining and Google dropping 12% over the past week.
- J.P. Morgan raised its year-end S&P 500 target to 8,000, while an AI-stripped S&P 500 rose 8% in October to a record high.
- India's MeitY launched the DEPA for AI Training Handbook, enabling secure data sharing for AI training without losing privacy or data ownership.
- Apollo Global Management lent a record $114 billion to AI companies including Anthropic and Nvidia.
- AvaTrade launched a new AI-powered multi-asset trading platform built on over 20 years of historical trader behavior data.
- Tradeview introduced its EDGE AI execution engine, which took over two years and millions of dollars to develop and test.
- NVIDIA Recovery automated system monitored nearly 200 jobs daily with mean detection and recovery latencies of 69 and 94 seconds.
- A shareholder lawsuit filed against Alphabet in Delaware alleges directors allowed unlawful AI training practices and failed to disclose key information.
- Burnham Park Capital Markets partnered with Sentinel AI to track retail investor sentiment across 250+ companies worth over $350 billion in combined market cap.
Semiconductor Index Plunges as Investors Fear AI Spending Ahead of Midterms
On November 2, investors grew cautious about the AI boom and pulled money out of tech stocks. The Philadelphia Semiconductor Index fell 3.37% to 10,328.33. TSMC's ADR dropped 1.85% to $398.63, losing the $400 mark. The Dow Jones rose 0.41% while the Nasdaq fell 1.07% and the S&P 500 dropped 0.51%. This selloff followed a major decline on October 30 triggered by Intel's disappointing guidance.
Tech Stock Crash Raises Fears for ISAs and Pensions
Tech stocks tied to artificial intelligence fell sharply last week, raising concerns for investors. Chip makers like AMD, Nvidia and Marvell saw their shares decline. Google's share price dropped 12% over the past week. The S&P 500 fund Vanguard S&P 500 Accumulation ETF fell just 3% despite the tech weakness. Experts say diversification helps protect investors from heavy losses in any single stock.
J.P. Morgan Raises S&P 500 Target to 8,000 as AI Stocks Sell Off
U.S. stocks closed October lower as the AI trade retreated, but market breadth improved. J.P. Morgan raised its year-end S&P 500 target to 8,000, suggesting about 5% upside. Over 50% of S&P 500 stocks hit 20-day highs, the highest level since Q2 2025. An AI-stripped S&P 500 rose 8% in October to a record high while AI-related shares fell more than 13%. Capital is rotating from rich AI names into non-AI companies.
MeitY Launches DEPA Handbook for Secure AI Data Sharing
India's Ministry of Electronics and Information Technology released the DEPA for AI Training Handbook in Bengaluru. The framework helps institutions share data for AI training without losing privacy or ownership. It uses three tools: binding contracts, secure computing systems and cryptographic safeguards. Prof Ajay Kumar Sood said the model travels to the data instead of data traveling to the model. The handbook was developed with support from the iSPIRT Foundation.
MeitY Unveils New Handbook for Safe AI Data Sharing
MeitY Secretary S Krishnan launched the DEPA for AI Training Handbook at a roundtable in Bengaluru on October 31. The framework helps organizations share data for AI training while keeping control of their information. It combines data agreements, secure computing systems and privacy protections. A key feature is that AI models can access data without institutions transferring their datasets. The roundtable included representatives from government, industry, academia and research groups.
Tickeron AI Trading Agents Show Strong Results Across Tech and Finance Sectors
Tickeron published AI Trading Agent results from November 3, 2025 through November 2, 2026. The Financials, Technology and Health Care Services agent earned $62,692.82 across 450 trades with a 73.56% profitable trade rate. The Semi agent earned $113,815.95 across 107 trades with a 73.83% profitable trade rate. Tickeron also expanded its computing infrastructure and Financial Learning Models. CEO Sergey Savastiouk said the Ask AI initiative aims to give investors instant answers powered by AI.
Marc Cuniberti Says the Artificial Intelligence Stock Trade May Be Facing Trouble
Marc Cuniberti wrote an opinion piece suggesting the artificial intelligence trade may be in trouble. He noted that the views expressed are his own and not investment advice. Cuniberti holds a B.A. in Economics with honors from 1979 and a California Insurance License OL34249. The article warns readers about market risks without recommending specific securities.
AvaTrade Launches New AI-Powered Trading Platform After FXCM Deal
AvaTrade launched a new in-house multi-asset trading platform with AI-driven fundamental and technical analysis. CEO Daire Ferguson said the platform was built using more than 20 years of historical trader behavior data. The platform generates trading signals and market insights for retail clients. The launch came weeks after AvaTrade agreed to acquire most of FXCM's business and brand rights. Ferguson said the goal is to expand global reach and build a stronger trading group.
Apollo Lends Record $114 Billion to AI Companies Including Anthropic and Nvidia
Apollo Global Management lent a record $114 billion to companies in the artificial intelligence sector. The funding went to Anthropic, a leading AI research company, and chipmaker Nvidia. This move reflects growing private equity interest in AI technology. The investment wave is driven by rapid AI growth and potential uses in healthcare, finance, and transportation. Apollo has been actively seeking AI opportunities and working with other investors on startup funding.
Burnham Park Capital Markets and Sentinel AI Form Strategic Partnership
Burnham Park Capital Markets partnered with Sentinel AI to bring real-time retail investor sentiment data to its research services. Sentinel AI monitors social media and online news for stock-related conversations and sentiment shifts. The platform currently tracks retail sentiment for over 250 public companies worth more than $350 billion in combined market cap. Burnham Park CEO Sagar Sheth said the partnership keeps the firm at the forefront of cutting-edge research. Sentinel AI CEO Krishan Arora said retail investors are now a permanent and influential force in public markets.
Tradeview CEO Explains EDGE AI Trading Engine
Tradeview Markets CEO Timothy Furey discussed EDGE, the company's new AI-powered execution engine, at iFX EXPO Asia 2026 in Hong Kong. EDGE uses smart order routing to find the best prices across about 20 liquidity providers and AI to reduce slippage. Furey said the engine took over two years to build and millions of dollars to develop and test. He also argued that trading conditions matter more than deposit bonuses for attracting long-term clients.
Alphabet Directors Face Shareholder Lawsuit Over AI Training
A shareholder lawsuit has been filed against Alphabet Inc. in the Delaware Court of Chancery. The suit claims that Alphabet's directors breached their fiduciary duties by allowing or failing to stop unlawful AI training practices. It also alleges the directors failed to disclose important information about these practices, which may have inflated the company's stock price. The lawsuit seeks to hold the directors liable for damages and prevent further unlawful AI training.
NVIDIA Recovery Automates AI Training Workload Restoration
NVIDIA Recovery is a new automated system designed to keep distributed AI training running smoothly. It manages recovery across cluster workloads by attributing failures, deciding where jobs should restart, and coordinating infrastructure remediation. In a three-month period, it monitored nearly 200 jobs per day and recorded about 8,550 anomaly detections with mean detection and recovery latencies of 69 and 94 seconds. The system reduces dependence on manual recovery by individual engineers.
Sources
- AI Rally Cools, Investors Wary Ahead of Midterms: Philadelphia Semiconductor Index Plunges 3.37%, TSMC ADR Falls Below $400
- Tech stocks are crashing. Will AI kill my ISA and pension?
- Breadth Rebounds Against the Tide as AI Stocks Sell Off; J.P. Morgan Calls for 8,000 by Year-End
- MeitY unveils DEPA framework handbook to unlock secure data sharing for AI training
- MeitY Launches New Handbook To Ensure Safe Data Sharing For AI Training
- AI Trading Technology Targets Fintech and Digital Infrastructure Stock Opportunities (NVDA, AVGO, PLTR, ANET, HOOD, SOFI)
- Marc Cuniberti: The artificial intelligence trade may be in trouble
- AvaTrade Launches In-House Trading Platform With AI Analysis
- Apollo lends record $114bn as it piles into AI financing boom
- Burnham Park Capital Markets and Sentinel AI Announce Strategic Partnership
- Tradeview Markets CEO on EDGE and AI Trade Execution
- Alphabet Directors Face Shareholder Suit Over AI Training Policies
- Keep Distributed Training Running with Automated Workload Recovery
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