GOVERNANCE

Can OpenAI and Anthropic slow the AI race?

Amid a growing cacophony of pleas urging frontier labs to slow the development of their most powerful AI models, the world's two most advanced labs, OpenAI and Anthropic, are finally stepping forward to propose a slowdown. 

On Saturday, Anthropic CEO Dario Amodei published an essay titled "We Must Pace the Frontier," arguing that things like recursive self-improvement, recent rogue agent incidents such as the OpenAI-Hugging Face breach, and our general lack of understanding of these systems pose substantial risks. 

In the essay, Amodei pitched a three-part framework to slow the pace of model development in an attempt to let safeguards catch up, aiming to create an environment in which labs "race to the top" on safety, rather than race to the bottom on capabilities and, therefore, risk. The framework includes: 

1. Embedded evaluators, in which frontier AI companies commit to giving internal access to teams of embedded third-party evaluators to "verify adherence to safety practices," report incidents, and assess alignment

2. A democratic coalition established by frontier AI labs "within democratic countries" that coordinates safety standards and limits the rate of "unchecked AI progress" 

3. Global coordination between the US and other democratic governments to "attempt to coordinate with authoritarian governments" to try and verify compliance

Amodei noted that Anthropic has unilaterally committed to this framework, calling on other governments and labs to do so as well. However, he made it clear that these steps are not an outright pause, and "progress will still seem fast," but the buffer should allow safety standards to meet development. 

"To be clear, pacing does not mean halting model training or technical progress, but ensuring companies take adequate time to align and safeguard their models, and for third party evaluators to confirm this," Amodei wrote. 

Though this move makes sense in the current environment, it contradicts previous blog posts from Anthropic, in which the company said a unilateral pause by one lab wouldn't actually achieve much. "It would change who the front-runner is, but it would not create the wider deliberative process that is currently missing."

Still, Anthropic isn't the only company eyeing a slowdown. In a company all-hands meeting last week, OpenAI CEO Sam Altman told employees that it would potentially pace the development of its frontier AI, according to a Bloomberg report published Friday. Altman said that the slowdown could be in partnership with other major labs. 

This also shouldn't come as a surprise from OpenAI: The company had already slowed certain parts of model development in August, pausing some internal safety runs to bolster its safety and security measures. Additionally, some of OpenAI's own brass have urged for a slowdown. 

Paul Christiano, who joined the OpenAI Foundation last week as a board member and who serves as an advisor for the Center for AI Standards and Innovation, wrote in an essay about joining OpenAI that no major lab in the industry is on track to reduce AI's risk to an "acceptable level," and that "if OpenAI rises to the occasion we could significantly reduce risk." 

And Jakub Pachocki, chief scientist at OpenAI, wrote in an essay last week that the current era of AI "calls for extreme caution," noting that he expects and hopes "voluntary slowdowns to become commonplace until shared safety bars are established."

Though Anthropic and OpenAI are largely considered the industry's leaders, it's unclear whether other labs will follow suit. Though former Google DeepMind chief Demis Hassabis previously pitched a way to coordinate an international slowdown of AI development through a global framework, Google DeepMind did not respond to requests for comment from The Deep View. Neither Meta nor SpaceXAI responded either.

The inherent nature of the tech industry, and of the capital markets that fuel it, has always been to move fast and outpace competition. The grandiose vision of what AI can do and the intense market pressure to grow and stand out ahead of IPOs worth a trillion dollars each have only intensified those forces. But the current risks of AI mean the AI industry could be holding a ticking time bomb. Altman and Amodei have both repeatedly stated that they value altruistic ideals above financial incentives. At this point, with the risks of AI outweighing the potential rewards, creating AI that's actually safe could be the new moat. "If they build something that is a danger to society, then they are going to face consequences," Shashi Bellamkonda, distinguished analyst at Info-Tech Research Group, told The Deep View. The question remains how effective this will be in slowing the industry at large, with the jury still out on whether other US labs will slow down, as well as how the Chinese labs will respond. 

TOGETHER WITH GENERAL ASSEMBLY

The easiest way to make AI training stick? Build it around the job.

Throwing webinars or AI learning stipends at a busy workforce yields a predictable cycle: a lot of wasted time, zero change in execution.

For growing companies, generic training leaves employees stranded in the gap between basic chat prompts and job-specific workflows. In fact, General Assembly's recent study of SMB talent leaders confirms that 35% point to role-specific AI training as delivering the strongest results (outranking tool training and experimentation).

Real transformation happens when you stop explaining what AI does, and start showing people exactly how it rewrites their specific workday.

General Assembly bridges this gap with role-based training that turns abstract AI concepts into immediate daily habits.

See what role-specific AI training looks like in practice.

MARKETS

Why AI’s funding frenzy could actually make sense

As investors pour money into startups throughout the AI stack, valuations are skyrocketing. Despite rumblings of an AI bubble, investors claim to have a method to their madness around AI. 

In the past week alone, nearly a dozen AI startups have raised hundreds of millions each at billion-dollar-plus valuations, from model providers and applications to chip development to industry-specific firms like healthcare, legal and defense. 

While the fact that these eye-popping checks are becoming commonplace may seem like an indicator that the AI is overvalued, Jahanvi Sardana, partner at Index Ventures, told The Deep View that FOMO-fueled investing may be a viable path in the current market.  

The meteoric growth of frontier labs like Anthropic and OpenAI provided a lesson for investors who missed their chance to get in early, said Sardana. "If you missed out on Anthropic and OpenAI, you look at this pot of gold and then you retrofit everything else into that pot of gold, just hoping that you hit that home run," she said. 

• After that, the frontier was AI coding agents, she said. Tools like Cursor, Code Rabbit, Lovable, Cognition and more have raked in millions from investors seeking to capitalize on one of the most viable paths to AI ROI. However, Sardana said, now investors are trying to figure out what's next. 

• This is where FOMO can be thought of as a skill, rather than a detriment, she said. "It is FOMO investing, but it's also not. It actually makes you think on your feet, think really fast and react to the market." 

• Additionally, if you spread your eggs among multiple baskets, in a market like this, an investor is likely to see significant returns if even a small fraction of those eggs end up hatching. 

"There are multiple paths to heaven. FOMO investing can be one, founder-first investing can be another," said Sardana. "You kind of just have to decide what game you want to play and be true to it. I don't think there's a right or wrong way of doing this job." 

At Index Ventures, focusing on which companies are solving actual problems, rather than creating technology first and then finding a market fit later, is what Sardana sees as the path to success. "To me, the most important thing is weeding out the missionary founders from the mercenary founders. That comes down to: Why are you building a business? Who is your customer? Why do they care?"

It's undeniable that there is a lot of overvaluation happening in the AI industry. As Sardana said, of the hundreds of AI startups raising millions to billions of dollars, the ones that make it are likely going to be the ones that are clearly doing something worthwhile. The desire to solve a pressing problem is where the most powerful innovation lies. For instance, with recent increased focus on AI efficiency, startups have emerged throughout the stack that are helping solve foundational problems, from the energy to power AI to the architecture of the model. The result could have wide-reaching benefits, both for the industry and society more broadly. That's what VCs are betting on and that's why we're seeing so much investment pouring into this sector of the economy.

TOGETHER WITH DESCOPE

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• Validate tokens from your customers' IdPs, so their admins decide which agents reach your MCP server

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Support SSO-like experiences for your AI agents and MCP servers.

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CONSUMER

How Apple reimagined the iPhone for the AI era

Apple's first foldable iPhone makes the case that a bigger screen is better for nearly everything in the AI era. Its new Apple Watch features raise a harder question: how much of our conversations should AI remember?

In this special episode of The Deep View Conversations, we record from Apple's campus in California following its September 2026 event to unpack the iPhone Duo, the new Audio Intelligence features in Apple Watch, and what Apple's latest devices mean for AI.

We share our first hands-on impressions of the Duo, explain why foldables are becoming more useful for AI agents and multitasking, and examine the price and hardware compromises that come with Apple's new form factor. We also debate Live Rewind and Siri Recap, two new Apple Watch features coming in beta later this year. We disagree on which feature we would feel more comfortable using, opening up a broader discussion about privacy, trust, and staying present.

The conversation also covers:

+ How the iPhone Duo compares with foldables from Google and Samsung
+ Why Apple's software experience is the Duo's biggest advantage
+ Camera, battery, durability, and Touch ID tradeoffs
+ Whether foldables will eventually become the default iPhone
+ Siri AI, iOS 27, and Apple's approach to other smart features without AI washing
+ The social questions surrounding AI-generated conversation summaries
+ The iPhone 18 Pro's camera upgrades and Apple's computational photography
+ Apple silicon, the A20 Pro, and the possibilities of running AI models locally on a phone

If you're following the future of AI in phones and wearables, this conversation connects Apple's announcements to the ways people will actually use them, along with the questions that still need answers.

📺 Watch on YouTube
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LINKS

• Anthropic banned accounts developing Yemeni missile guidance software

• Meta AI suggests investigating identity of child in Utah mother’s video

• Ayar Labs raises $150 million more, bringing 2026 total to $650 million

• YC's Garry Tan says 'do nothing' on AI model distillation by China 

• Anthropic sects NASDAQ for upcoming public offering

• Sam Altman confirms OpenAI won’t go public this year

• Fugu Max and Fugu Ultra v2: next evolution of Sakana Fugu’s multi-agent orchestration system

• ChatGPT Sites: Over 5M sites created since launch; a series of updates to celebrate

• GPT Images 2.5: takes the top two spots on the Artificial Analysis Image Arena

• Projects in Cursor: a new way of working in which you work with a coordinator agent in a single, persistent thread

• Smartish: AI Systems & Automation Specialist

• Anthropic: Applied AI Architect, Startups

• Ivo: AI Researcher

• Obin AI: Agentic AI Engineer

GAMES

A QUICK POLL BEFORE YOU GO