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Despite Nvidia's crisis, AI will march on

The exit of AI's biggest evangelist from the stage will change some things, but AI transformation and adoption across industries will continue apace.

On Thursday, the Nvidia board of directors announced that Nvidia co-founder Jensen Huang had resigned as president, CEO, and a board member, effective immediately. Huang's exit comes just days after he confirmed his extramarital affair with a woman whom US intelligence has accused of being a Chinese spy, and the report broke of another affair with a direct report, Nvidia's VP of healthcare, Kimberly Powell. 

The interim CEO will be Colette Kress, Nvidia's current EVP and CFO, who will continue to serve in these roles until a successor is named. The company's structure is also changing, with Harvey C. Jones, former Synopsys CEO, appointed as its first-ever board chair. The board disclosed that it is already initiating a search for a permanent CEO. 

People are already placing bets on Polymarket regarding who the next CEO may be, with Ian Buck, Nvidia VP and high-performance computing chief, leading the betting odds, followed by Kress and Rene Haas, CEO of Arm Holdings, with analysts making similar predictions. President Trump took to Truth Social to propose former Apple CEO Tim Cook as the next pick. While it is hard to say with confidence who will succeed Huang, since there was no plan in place to prepare the company for this moment, what we do know is that they will be pivotal in defining the entire AI industry, as Huang himself did. 

During his tenure, Huang became one of the most influential figures of the current AI boom. Under his leadership, Nvidia invested heavily in its own customers, including cloud providers, suppliers and major AI labs, and some of that money returned in the form of chip purchases. Analysts have flagged these arrangements as potentially circular, while others argue they are a strategic way to lock customers into Nvidia’s ecosystem. If a new CEO scales back these investments, it could raise financing costs for companies that relied on Nvidia’s backing and reduce some of Nvidia’s own revenue. 

Huang also became a prominent voice in Washington, and his close relationship with President Trump coincided with several policy outcomes favorable to Nvidia. According to CNBC, Huang and other Nvidia executives directed at least $26 million toward Trump-backed projects, and the company spent a record $2.15 million on federal lobbying in the third quarter. Huang lobbied against the GAIN AI Act, which would have restricted chip exports, and against state-level AI regulation in favor of a single federal framework. In December 2025, Trump approved sales of Nvidia’s H200 chips to China, though Beijing has blocked them.

The uncertainty of what is to come in the next era of Nvidia is already being seen on the stock market. As of November 12, Nvidia shares "tumbled more than 12% in early trading, putting the company on course to lose about $500 billion in market value," Reuters explained. Nvidia reached an all-time high $5.8 trillion market cap on October 6. Recent losses have pushed the value of the company down to $4 trillion. 

Huang helped define how the AI industry builds and funds itself, with Nvidia acting as both supplier and financier to many of the leading players in the ecosystem. If a new CEO steps back from that model, the effects could ripple outward. That said, AI is now embedded in nearly every industry, and demand for the technology isn’t going away, even if the stock market and investors sour on the AI trade and its effects spread across the industry. The train has already left the station when it comes to enterprises and organizations of all sizes investing in AI to streamline work, enhance productivity, and transform their relationship with software. While Nvidia's path forward may change how AI companies get financed, it won't change the fact that the years ahead are going to be all about a lot more professionals and organizations putting AI to work in more and more practical ways. 

TOGETHER WITH FINGERPRINT

Not every AI agent should get through. Here’s how to decide which ones

Some AI agents now sign in, browse, and buy on behalf of real customers, and some, like Meta’s Muse, never say who they are. If you block every agent, you break real user journeys. If you let every agent through, you open the door to abuse.

Join Fingerprint’s live build on Nov 17 at 9AM PT. Keshia Rose will code a server-side policy layer from the ground up, then test it against a live Muse session, a bot script, and a real human visitor.

What you’ll walk away with:

• How to tell humans, AI agents, and automation tools apart on the server side

• How to set trust levels for signed, verified, unknown, and spoofed agents

• How to write policies that allow, limit, or block traffic

Reserve your seat for the live build

GOVERNANCE

OpenAI sees a new enterprise frontier in cyber

As AI creates a cybersecurity minefield, OpenAI wants to give defenders a greater advantage.

On Thursday at the AI lab's "Cyber at the Frontier" keynote, OpenAI debuted two new cyber defense tools, aiming to expand access to frontier AI-powered cyber capabilities to a broader pool of defenders with turnkey, easy-to-implement solutions. The offerings add to the company's growing cybersecurity footprint, following the release of GPT-6 Cyber last week. 

"The thing that needs to change is, as we're seeing this change in the physics of cybersecurity, this democratization of cybersecurity expertise, is that we need to build software in a fundamentally more secure way," OpenAI president Greg Brockman said in the keynote. 

In a briefing with the press, Johannes Landgraf, head of cyber at OpenAI, said the "defender's window," previously described by Brockman as the ability to find and fix weaknesses ahead of attackers, is "under pressure" as more "broadly diffused models" become more widely available.  

"Attackers are able to move faster. I think we see that right now almost on a daily basis," said Landgraf. "Defenders also have to move faster at that." 

OpenAI unveiled two answers to this:

• Daybreak Red Team, a suite of security agents that can discover whether flaws in code can be exploited. One agent coordinates assessments, others investigate source code and application context, and finally reviewer agents check the results. This gives cyber teams the ability to prioritize which flaws to address first. Landgraf said that Red Team "paves the path for us to dramatically expand the access to our frontier cyber models over time." 

• Daybreak Defense Factory, meanwhile, helps defenders "close the loop" on the exploits that Red Team digs up, said Landgraf. This release builds on Codex Security, which helps firms find and remediate code vulnerabilities, with agents that scan code as it changes, review pull requests and investigate alerts from tools. Upon finding a vulnerability, the agent reports what it found to the engineer responsible for the code, as well as proposes a patch in Codex. 

The goal of these products is not to replace a conventional red team, Clint Gibler, who leads cybersecurity research at OpenAI, told the press. Rather, it's to help bridge the growing gap between what cyber defenders can protect and the sheer amount of code being generated by AI. 

"There's always been a dearth of security expertise in the world," said Gibler. "There are many people building things, and now there's more people than ever, especially people without an engineering background. Our ability to secure the world needs to scale." 

Additionally, because cyber defenders and expertise are stretched thin amid this changing landscape, it was a focus for OpenAI to make these products "turnkey and easy to use," Fouad Matin, cyber preparedness and safety lead at the lab, said in the briefing. 

"As we look to more organizations who might not have the red team staff on hand, they might not have the same level of technical resources that some organizations do," said Matin. 

Though OpenAI didn't offer any information on pricing for these products, Red Team is launching in early access with select customers and a waitlist open today, and Defense Factory is available through the Daybreak plugin in Codex.

It's commendable that OpenAI is actively creating tools to better arm a larger swathe of defenders as AI creates an increasingly complex cybersecurity landscape. However, security could represent more than just a way for OpenAI to help clean up the mess that, effectively, it helped create with its powerful frontier AI. Rather, it could represent a new revenue stream. These products, in addition to the release of GPT-6 Cyber, signal that OpenAI may be eyeing cyber as another path into the enterprise as it battles with rivals like Anthropic for high-value customers. And as these organizations scramble to secure themselves against AI-enabled attackers, many of which might not have strong cyber expertise, as Matin noted, the market is ripe for the taking. 

TOGETHER WITH ZENDESK

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Explore how Zendesk’s Outcome AI Platform is transforming service.

HARDWARE

Google's eyewear play hinges on Gemini

After years of anticipation, Google's AI glasses are finally here, and the question everyone is asking is how they measure up.

On Thursday, pre-orders opened for the new Intelligent Eyewear collections, a collaboration brought to life by Google, Samsung, Gentle Monster, and Warby Parker. The glasses let users capture video and photos with the 12-megapixel ultra-wide camera, listen to audio with the open-ear speakers, and notably, utilize Gemini assistance with a simple tap of the frame. 

A key theme of the release is accommodating user choice, with the glasses working across Pixel, Samsung, and iOS phones with a nearly identical experience on each. Gentle Monster's six designs are a bit bolder for those willing to take more of a risk with their style, starting at $449. Warby Parker offers three styles, which it says were all inspired by its most beloved silhouettes and starts at a slightly more affordable price of $395. 

Regardless of designer or style, the glasses felt very light at only 41 grams — about 10 grams less than the lightest Ray-Ban Meta Gen 3. The glasses are also meant to offer users 9 hours of battery life, which is on par with Meta's most competitive offering. 

Pre-launch, I had the opportunity to wear them at three different events, totaling about three hours of use, and got to talk to the people who worked to bring these models to life. In my testing, I found two major standouts: Gemini and privacy. 

My most practical use case for my Meta Ray-Bans has typically been the audio experience, as the mics and speakers are excellent for hands-free calls or music and podcast streaming. I was pleased that the Intelligent Eyewear's audio was just as compelling, with the addition of more useful AI through Gemini, so much so that I can see myself using the AI features as much as I use the audio features. 

Gemini seamlessly connects to popular Google apps, such as Gmail or Maps. I trust it with access to my information, which gives it the context it needs to be truly helpful. While I could do the same with Meta AI, connecting it to all my apps is a more manual, tedious process. 

Additionally, I don't trust Meta with all my personal data given its history, which brings me to my next point: Google has been particularly careful with this release to address all privacy concerns users would have, taking a number of precautions to make users more comfortable, such as:

• The LED recording indicator light can't be tampered with

• Camera visuals aren't saved in your Gemini History or used for AI training or ad targeting 

• The data stored on the glasses is encrypted 

• The glasses redact faces before sending images to Gemini 

• Gemini is designed to focus on the user's voice, not picking up conversations around you in which the individuals wouldn't be consenting to being recorded 

Given the negative public perception of AI glasses as a result of Meta's devices, Google's strict stance is crucial for it to have any chance at success. It also may be enough to remedy some of the bad PR that smart glasses currently have, paving the way for more trust in the product category. 

“Our strategy here is that we’re coming in at a time where the history has not been written yet on this category, and we want to raise the bar on privacy," Juston Payne, senior director of product management for XR at Google, told me.

I’ve always felt the AI glasses category has struggled because, in my experience, its best use case has been audio. Yet, the real promise of AI glasses is giving an assistant context for what you’re seeing and doing, so it can help you from your point of view. After my brief time with these glasses, I think Gemini may be what finally cracks that code. I could see myself reaching for it instead of my phone in many situations. For instance, I could ask how far away my next meeting is and whether it would be faster to take the train, drive, or walk, saving time that I would have otherwise spent jumping between apps because I'm comfortable giving Gemini access to the context of my Google Calendar and Maps. While I wish the hardware design had taken a bigger leap to set it apart from competitors, Gemini makes enough of a difference to give these glasses a real competitive edge.

LINKS

• Apple HomeView earns praise for speed, sound, Siri, criticized for price

• MIT scientists develop faster AI training method for climate simulation

• Terradot, Microsoft build AI model to test crushed rock carbon removal

• OpenAI, Anthropic hit with lawsuit aiming to halt frontier AI development

• Kalshi in talks to raise funding at a $65 billion valuation

• SpaceX plan $74 billion investment in Texas, Arizona data centers

• Gemini 4 Hydrogen: The company's latest edition to its model line-up, built for speed and efficiency

• ChatGPT Finances: now works with desktop app

• Runway: Generate detailed 3D models from text or images with Tripo H3.1

• Bing: Blog post details how to turn the AI on/off

• Claude: now supports more of the MCP Apps extension

• Anthropic: Applied AI Demo Engineer

• Tenex: Applied AI, Engineer & Creator

• Cerebro: Artificial Intelligence Researcher

• Digital Waffle: AI Engineer

GAMES

A QUICK POLL BEFORE YOU GO