Nvidia CEO Jensen Huang to join Trump-Xi state dinner in Washington

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Reviewed by
Suketu GScanX News Team
Key Highlights
  • Nvidia CEO Jensen Huang expected to attend Trump-Xi state dinner on Sept. 24
  • White House prioritizing deals benefiting US amid tech competition
  • Limited H200 chip shipments approved for China in August
  • Nvidia shares closed up 0.57% at $212.17 on Tuesday
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Nvidia Corp (NASDAQ: NVDA) CEO Jensen Huang is reportedly expected to attend a state dinner hosted by US President Donald Trump for Chinese President Xi Jinping in Washington on Sept. 24.

The invitation aligns with the White House’s stated goal of prioritizing deals that benefit the US, as Trump invited several prominent business leaders to the event.

Diplomatic Context

Huang’s attendance underscores the central role of AI and semiconductors in US-China relations. Nvidia supplies chips critical to developing and running AI systems, positioning the company at the heart of the technology competition between Washington and Beijing.

Huang has maintained close ties with Trump. In May, he traveled to China with the president during his first state visit since 2017. He also attended a dinner hosted by Xi for Trump in China.

Trade Dynamics

Reports in August indicated that limited shipments of Nvidia’s H200 AI chips had been approved for mainland China. This development occurs against a backdrop of ongoing regulatory scrutiny and export controls affecting semiconductor trade between the two nations.

Market Reaction

Nvidia shares closed at $212.17 on Tuesday, up 0.57%. The stock rose another 0.10% to $212.39 in after-hours trading.

According to Benzinga Edge Rankings, Nvidia ranks in the 98th percentile for Growth. The company shows positive medium- and long-term price trends but a downward short-term trend.

Disclaimer: This article is AI-generated using data from ViewTrade. ScanX is not liable for any inaccuracies.

How might the approval of limited H200 chip shipments influence Nvidia's revenue projections for the Chinese market in the coming quarters?

Could Jensen Huang's diplomatic presence signal a potential easing of broader US export controls on advanced semiconductors to China?

What impact will this high-profile political engagement have on Nvidia's competitive positioning against domestic Chinese AI chip manufacturers?

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Nvidia, Palantir Tighten AI Model Use Over Data Security Fears

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Reviewed by
Ritika DScanX News Team
Key Highlights
  • Nvidia, Palantir, and Booz Allen Hamilton are tightening use of Anthropic and OpenAI models over data security fears
  • Nvidia shares fell about 3% Monday amid a broader selloff in AI-linked stocks
  • Ohalo CEO David Friedberg said his company is moving off Claude for sensitive data to local models
  • Nvidia and Palantir unveiled a system using Nemotron models to analyze Nvidia's supply chain data internally
  • Polymarket puts odds of Anthropic IPO this year at 86% despite enterprise data retention concerns
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Nvidia Corp. (NASDAQ: NVDA), Palantir Technologies Inc. (NASDAQ: PLTR), and Booz Allen Hamilton Holding Corp. (NYSE: BAH) are restricting their use of advanced AI models from Anthropic and OpenAI due to concerns about exposing sensitive corporate information.

The companies are demanding stronger guarantees or dropping specific models to prevent providers from retaining or learning from proprietary customer data, according to a report by The Information on Monday.

Nvidia shares fell about 3% on Monday amid a broader selloff in AI-linked stocks.

Alternative Models for Sensitive Data

Ohalo CEO David Friedberg described similar concerns during a podcast appearance on Friday. He stated that Ohalo is "moving off Claude for a lot of our sensitive data" and shifting work toward locally run models.

Friedberg cited anecdotal cases where novel scientific ideas discussed with one model appeared to resurface when querying another version from a different account. His concern extends beyond leaking confidential documents to potentially giving AI providers valuable internal know-how.

Nvidia and Palantir Build an Alternative

Nvidia is applying a similar approach to its supply chain operations. Last week, Nvidia and Palantir unveiled a system using Palantir software and Nvidia’s open Nemotron models to analyze Nvidia’s own supply-chain data.

Nvidia is the first customer for this technology. The company says clients can customize models using proprietary operational data while retaining control over the data, models, and infrastructure location.

This approach allows Nvidia to capture how its planners make decisions without handing supply-chain knowledge to an outside model provider.

Anthropic Responds to Customer Pressure

Anthropic introduced 30-day data retention with Fable 5 in June to detect misuse across multiple sessions and accounts. The company states this information is not used to train its models.

Anthropic later acknowledged that many enterprises, particularly in regulated industries, found the retention requirement difficult to accept. Its proposed solution, Enterprise Frontier Safeguards, will keep activity data used for misuse monitoring in customer-controlled cloud infrastructure. It begins rolling out in phases later this fall.

Despite these data concerns, expectations for Anthropic’s IPO remain high. Polymarket puts the odds of a listing this year at 86%.

Nvidia is also reportedly considering a roughly $10 billion anchor investment in an offering that could value Anthropic near $2 trillion.

The debate echoes Palantir CEO Alex Karp’s recent warning that companies risk handing AI providers their proprietary "alpha" along with their data.

Disclaimer: This article is AI-generated using data from ViewTrade. ScanX is not liable for any inaccuracies.

How might the shift toward locally run or proprietary AI models impact the revenue growth projections for cloud-based AI providers like Anthropic and OpenAI?

Will Nvidia's development of the Nemotron-based supply chain system establish a new industry standard for enterprise AI infrastructure, prompting competitors to adopt similar closed-loop architectures?

What regulatory measures might emerge to define 'proprietary alpha' and protect corporate intellectual property from being inadvertently used in the training of public AI models?

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