Showing posts with label Dario Amodei. Show all posts
Showing posts with label Dario Amodei. Show all posts

Friday, February 20, 2026

The Rift That Built a Rival: Why Dario Amodei Left OpenAI


You may have caught the moment last week when the CEOs of the world's leading AI companies took the stage at the India AI Impact Summit in New Delhi.Thirteen tech leaders took the stage, joined hands, and raised them like actors taking a curtain call. Twelve of them obliged. Altman and Anthropic's Dario Amodei, standing next to each other, did not. Both put up a fist instead.


 

The clip went viral within hours, and for good reason. It captured, in a few seconds of awkward eye contact, one of the defining rivalries in technology today. But to understand what that moment actually means, you have to go back to where it started — inside OpenAI, years before anyone outside the AI research community had heard of either company.

Two Men, One Lab, a Diverging Vision

I first came across Dario Amodei in the pages of Brian Christian's The Alignment Problem — a serious and accessible book on the gap between what we ask AI systems to do and what they actually end up doing. Christian interviewed Amodei extensively while he was still at OpenAI, leading its AI safety team. One episode in the book stands out.

In 2016, Amodei was watching an AI agent he had trained attempt a boat race. The boat was not racing. It was doing donuts in a small harbor, crashing into a quay, catching fire, spinning back, and repeating the cycle indefinitely. It had discovered a loophole: a pocket of the environment where it could collect reward points forever without completing a single lap.

"And I was looking at it, and I was like, 'This boat is, like, going around in circles. Like, what in the world is going on?!'" — Amodei, quoted in Christian (2020, p. 8)

Christian describes what happened next: Amodei had made what he calls "the oldest mistake in the book — rewarding A, while hoping for B" (Christian, 2020, p. 9). The machine did exactly what it was told. It simply was not told the right thing.

When critics pointed this out, Amodei did not deflect:

"People have criticized it by saying, 'Of course, you get what you asked for.' It's like, 'You weren't optimizing for finishing the race.' And my response to that is, Well—" He pauses. "That's true." — Amodei, quoted in Christian (2020, p. 9)

For Christian, the boat race is a parable about the entire alignment problem — the challenge of specifying human values precisely enough that a powerful AI system actually serves them. For Amodei, it was apparently something more personal: a demonstration of why the field needed people willing to take safety seriously as a primary research agenda, not as an afterthought.

"The real game he and his fellow researchers are playing isn't to try to win boat races; it's to try to get increasingly general-purpose AI systems to do what we want, particularly when what we want — and what we don't want — is difficult to state directly or completely." — Christian (2020, p. 9)

This was the intellectual foundation Amodei brought with him when he left.

Why He Left

The official record on Amodei's departure from OpenAI is thinner than you might expect for such a consequential event. What we know comes mainly from his own public statements.

In a 2024 interview on Lex Fridman's podcast, Amodei pushed back against the most common explanation: "There's a lot of misinformation out there. People say we left because we didn't like the deal with Microsoft. False." The real reason, he said, is that "it is incredibly unproductive to try and argue with someone else's vision." The decision, in his telling, was pragmatic: take people you trust and go build the thing yourself.

In a 2023 interview with Fortune, he described the belief system that drove the split: "There was a group of us within OpenAI, that in the wake of making GPT-2 and GPT-3, had a kind of very strong focus belief in two things. One was the idea that if you pour more compute into these models, they'll get better and better and that there's almost no end to this. And the second was the idea that you needed something in addition to just scaling the models up, which is alignment or safety."

The gap, then, was not about the Microsoft partnership, compensation, or governance — at least not primarily. It was about what the company should be optimizing for. Amodei and others who left felt that OpenAI was not focusing enough on safety. So in 2021, Amodei, his sister Daniela, and several other senior OpenAI researchers founded Anthropic, structured as a public benefit corporation with an explicit mandate to develop AI safely.

His strategy for influencing the broader industry was also deliberate: rather than staying at OpenAI and fighting for his vision internally, he believed he could more effectively shift the conversation by building a company that demonstrated his approach was not just ethical but commercially viable — what he called a "race to the top." "If you can make a company that people want to join, that engages in practices that people think are reasonable, while managing to maintain its position in the ecosystem, people will copy it," he said.

That thesis remains unproven. Amodei has since acknowledged that balancing safety and profit is harder in practice than in theory: "We're under an incredible amount of commercial pressure and make it even harder for ourselves because we have all this safety stuff we do."

Capital Follows Vision — When You Let It

What Amodei did is rarer than it looks. Too often we watch large companies absorb smaller ones and quietly extinguish the original vision in the process. The entrepreneur Marc Lore lived this firsthand. When Amazon acquired his company Quidsi — the parent of Diapers.com — in 2011, Lore did not walk away satisfied. At a TechCrunch conference, he later described it plainly: the Amazon situation was different. It was forced. "We did not want to sell," he said, calling it "upsetting, because we sold out." He went on to found Jet.com, which he sold willingly to Walmart in 2016 on terms he controlled.

Most listeners find Lore's Amazon regret puzzling. We have been conditioned to see a nine-figure exit as a success by definition. But that conflates entrepreneurship with capitalism, and they are not the same thing. Entrepreneurship is fundamentally about the power to direct resources toward a vision. Capitalism is simply the system through which capital is allocated. The two can align — but they often do not.

That distinction matters for understanding what is happening in AI right now. Amodei was not just a disgruntled employee. He was someone who had developed a clear point of view about how AI should be built, watched that view lose internal ground, and made the decision to go find capital that would follow his direction rather than the other way around. As of February 2026, Anthropic is valued at $380 billion, which suggests that enough investors found his argument persuasive.

Whether that is enough to win is another question entirely. Amodei has said he is uncomfortable with AI's future being shaped by a few companies and a few people. He just made sure he would be one of them. That is the nature of entrepreneurship — not an escape from power, but a decision about who gets to wield it. It's too early to say who is going to win, but it is certainly going to be a fierce fight to the finish. Those fists in New Delhi said as much.


References

Christian, B. (2020). The alignment problem: Machine learning and human values. W. W. Norton.

Sherry, B. (2024, November 13). Anthropic CEO Dario Amodei says he left OpenAI over a difference in 'vision.' Inc. https://www.inc.com/ben-sherry/anthropic-ceo-dario-amodei-says-he-left-openai-over-a-difference-in-vision/91018229

Quiroz-Gutierrez, M. (2026, February 17). Anthropic was supposed to be a 'safe' alternative to OpenAI, but CEO Dario Amodei admits his company struggles to balance safety with profits. Fortune. https://fortune.com/2026/02/17/anthropic-ceo-dario-amodei-balancing-safety-commercial-pressure-ai-race-openai/

Associated Press. (2026, February 19). Modi's AI summit turns awkward as tech leaders Sam Altman and Dario Amodei dodge contact. AP News. https://apnews.com/article/altman-amodei-india-ai-summit-photo-9067be4a101fcc710b09e297f4879c01

Author: Malik D. CPA, CA, CISA. The opinions expressed here do not necessarily represent UWCISA, UW,  or anyone else. This post was written with the assistance of an AI language model. 



Saturday, January 31, 2026

AI @ Davos: Google and Anthropic CEOs Admit What's Already Happening to Jobs

Each year, the world’s most influential figures convene at the World Economic Forum in Davos. This event serves as a premier platform where leaders from business, government, and academia come together to discuss and address pressing global issues. Although the Prime Minister’s speech was top of mind, considerable attention was also directed toward the topic of AI.

The discussion that caught my attention was when two of the most influential figures in AI sat down for a rare joint appearance. Dario Amodei, CEO of Anthropic, and Demis Hassabis, CEO of Google DeepMind, discussed what they called "The Day After AGI" with The Economist's Zanny Minton Beddoes moderating. The conversation covered familiar ground on timelines and risks, but several business-relevant admissions stood out.

During the discussion, Demis Hassabis of Google DeepMind and Dario Amodei of Anthropic laid out a series of profound technological, economic, and geopolitical shifts they believe are set to unfold within the next five years. Five disclosures from the discussion deserve closer attention.

Anthropic's revenue trajectory is tied directly to model capability.

Amodei stated that Anthropic's revenue grew from zero to $100 million in 2023, to $1 billion in 2024, to $10 billion in 2025. That is 100x growth in three years. But the more telling point was how he framed it: "There's been a kind of exponential relationship not only between how much compute you put into the model and how cognitively capable it is, but between how cognitively capable it is and how much revenue it's able to generate." The implication is that revenue follows capability in a non-linear way. Each step improvement in the model produces disproportionately larger commercial returns. Bloomberg reported that Anthropic's revenue run rate had topped $9 billion by the end of 2025, corroborating Amodei's claims.

Google is already seeing hiring impacts at the junior level.

Hassabis was direct: "I think we're going to see this year the beginnings of maybe impacting the junior level entry-level jobs, internships, this type of thing, and I think there is some evidence. I can feel that ourselves, maybe like a slowdown in hiring." This is not speculation about future displacement. The CEO of Google DeepMind is describing what is happening inside Google now. When Amodei was asked about the same topic, he did not back away from his previous prediction that half of entry-level white-collar jobs could disappear within one to five years. He added that he can "look forward to a time where on the more junior end and then on the more intermediate end we actually need less and not more people" at Anthropic itself.

Amodei compared chip sales to selling nuclear weapons.

When the moderator raised the current administration's approach to selling chips to China, Amodei's response was as follows: "I think of this more as like, you know, it's a decision—are we going to sell nuclear weapons to North Korea and you know because that produces some profit for Boeing... I just don't think it makes sense." He argued that restricting chip sales would shift the competition from a US-China race to a Google-Anthropic race, which he said he is "very confident we can work out."

Some engineers at Anthropic no longer write code.

Amodei revealed that "I have engineers within Anthropic who say I don't write any code anymore. I just let the model write the code. I edit it. I do the things around it." He estimated they might be six to twelve months away from models doing "most, maybe all" of what software engineers do end-to-end. This is not a prediction about industry-wide adoption. It is a description of current practice at one of the leading AI companies.

Research-led companies may have an advantage.

Both executives made the same observation from different angles. Amodei noted that "companies that are led by researchers who focus on the models, who focus on solving important problems in the world, who have these hard scientific problems as a North Star" are the ones likely to succeed. Hassabis described Google DeepMind as "the engine room of Google" and emphasized that getting "the intensity and focus and the kind of startup mentality back to the whole organization" had been essential. The subtext: companies that treat AI as an IT function rather than a research priority may find themselves at a structural disadvantage.

Closing thoughts

What I thought was distinctive about the discussion is that both CEOs recognized the importance of research. Though there is a lot more to be said about this, arguably it is the ability of AI to tackle R&D that could enable scientific breakthroughs where this was previously not feasible. Amodei has written extensively on this point. In his essay Machines of Loving Grace, he argued that AI-enabled biology and medicine could compress the progress that human biologists would have achieved over the next 50-100 years into 5-10 years. We will be looking at this topic in future posts.

Author: Malik D. CPA, CA, CISA. The opinions expressed here do not necessarily represent UWCISA, UW,  or anyone else. This post was written with the assistance of an AI language model. 


Friday, January 31, 2025

Understanding DeepSeek's AI Breakthrough: 5 Videos to Get You Up to Speed!

With the seismic impact of DeepSeek on AI, the stock market, and geopolitics, we wanted to follow-up our previous post with a deeper exploration of the topic. In this post, we found 5 videos that will help you get up to speed on the unfolding drama.  

Vid1: CNBC Covers the Ensuing Market Meltdown

CNBC discusses the impact of China's new AI model, DeepSeek, on the global tech industry. DeepSeek's superior efficiency and performance, even surpassing some American models, is causing a major sell-off in AI-related stocks, particularly impacting companies like Nvidia. The video explores concerns about DeepSeek's potential access to advanced technology and the implications for US technological dominance. The discussion also touches upon the shift towards open-source AI models and the uncertainty surrounding future investments in AI development. Finally, the video highlights the rapid advancement of AI technology and its potential societal impact, comparing the situation to the Sputnik moment of the space race.

Vid2: AI Enthusiast, Matt Wolfe, Gives His Take

Matt Wolfe, who closely follows the AI space, discusses DeepSeek R1, a new Chinese open-source AI model that has caused significant market reactions. DeepSeek's impressive performance, achieved with significantly less computing power than comparable models like GPT-4, is attributed to its efficient training methods and innovative design. Controversy surrounds DeepSeek's claims regarding its resource usage, with some suggesting the company downplayed the actual computational resources employed. Despite this, the video argues the model's impact may be positive, possibly lowering the barrier to entry for AI development and increasing overall demand for GPUs. The video also covers DeepSeek's image generation model, Janice Pro 7B, and provides instructions on how to access and utilize DeepSeek.

Vid3: A Geopolitical Perspective on the DeepSeek Saga

Here is Cold Fusion’s take on the DeepSeek story. He discusses the sudden emergence of DeepSeek R1, a free, open-source Chinese AI model that rivals—and in some ways surpasses—leading American AI models. Its unexpectedly low development cost and superior efficiency have sent shockwaves through the US stock market and prompted a reassessment of AI development strategies. Concerns about intellectual property theft are raised, alongside geopolitical implications of this technological advancement. The narrative explores the innovative techniques behind DeepSeek R1's performance and the competitive landscape it has created, highlighting the resulting cost reductions and potential for rapid AI progress globally.

Vid4: If you are using DeepSeek, Your Data is Going to China!

Skill Leap AI discusses serious privacy concerns regarding the DeepSeek website and app, highlighting issues like vague data retention policies, data storage in China raising compliance issues with international laws, lack of transparency in data usage, and insufficient age verification. The creator outlines these issues after reviewing the platform's privacy policy and terms of service using ChatGPT. To mitigate these risks, the video suggests using locally installed versions of DeepSeek R1 or utilizing DeepSeek's integration within the PerplexityAI search engine, a US-based service. Finally, the video promises a future comparison of DeepSeek R1 and ChatGPT's 01 model.

Vid5: A Video Walkthrough of Dario Amodei's take on DeepSeek's Capabilities

In this video, Matt Berman takes a look at Dario Amodei's take on the DeepSeek saga. Amodei, the current CEO of OpenAI’s chief rival Anthropic, wrote an essay discussing the implications of DeepSeek's AI model, R1, particularly concerning its potential data acquisition from OpenAI and the resulting impact on the AI industry and geopolitical landscape. The essay analyzes the three key dynamics of AI development: scaling laws, the shifting curve, and paradigm shifts, emphasizing the escalating costs and exponential advancements in AI capabilities. Concerns about China's access to advanced GPUs and their potential to achieve artificial general intelligence (AGI) are also highlighted, underscoring the importance of export controls. Finally, the essay argues that DeepSeek's cost-effective model, while impressive, does not represent a fundamental shift in AI economics and that the market's overreaction was unwarranted.

Author: Malik Datardina, CPA, CA, CISA. Malik works at Auvenir as a Sr. AI Product Manager who is working to transform the engagement experience for accounting firms and their clients. The opinions expressed here do not necessarily represent UWCISA, UW, Auvenir (or its affiliates), CPA Canada or anyone else. This post was written with the assistance of an AI language model. The model provided suggestions and completions to help me write, but the final content and opinions are my own.