Slate Money – Money Talks: Battle of the AI Bots (Sept 16, 2025)

Host: Elizabeth Spiers
Guest: Gary Rivlin (Pulitzer Prize-winning investigative journalist, author of AI: Microsoft, Google, and the Trillion Dollar Race to Cash in on Artificial Intelligence)

Episode Overview

This episode takes a deep dive into the world of artificial intelligence, focusing on the current competitive landscape—including big tech’s “trillion dollar race” to dominate AI, the unique challenges facing start-ups, and differing philosophies guiding leading investors and founders. Journalist Gary Rivlin joins Elizabeth Spiers to discuss his new book and share behind-the-scenes stories of AI development, the culture of Silicon Valley, and the broader societal implications of AI’s rapid rise.

Key Discussion Points & Insights

1. The Trillion-Dollar AI Race: Incumbents vs Startups

• AI as 'Big Stakes':
  • Gary Rivlin describes the “mad dash to cash in on AI” and escalating stakes: “They don’t even really use the word billion anymore. It’s now the trillion dollar race because that really is the stakes here.” (01:14)
• Barriers for startups:
  • Discusses how big tech’s data, money, and Aqua Hires (talent acquisitions) make it nearly impossible for new players to compete:
    “It’s really hard for a startup to get access to that kind of money...How are two people in a dorm room going to have access to the data that you need for training and stuff?” (02:21)
  • Points to massive offers to individual AI researchers, citing a $250 million contract: “That’s like the highest paid baseball players kind of contract.” (02:58)
• The role of compute power:
  • Elizabeth Spiers points out that, unlike classic “software is scalable” logic, AI is resource-intensive at scale due to compute and data requirements. (03:14)

2. Inside Inflection AI: Personality, Emotional Intelligence, and Philosophy

• Origins of the book and Inflection’s vision:
  • Rivlin was inspired by an email from Reid Hoffman (LinkedIn co-founder) about launching Inflection AI, focused on making computers “speak human.” (03:48)
  • Hoffman backed OpenAI, is on Microsoft’s board, but sought to build a product prioritizing EQ (emotional intelligence), not just IQ.
• Building an emotionally attuned chatbot ("Pi"):
  • The chatbot Pi aimed to be engaging, friendly, and empathetic—sometimes to a fault:
    “It had really loved emojis at first. They had like, okay, chill folk. PI it was called. PI is the name of their chatbot.” (05:01)
• Balancing friendliness and utility:
  • The engineering challenge: finding the sweet spot between being too sycophantic and too bland. (06:46)

3. Human-AI Attachment and Public Response

• People get attached to bots:
  • Some users developed deep, even “romantic” bonds with bots (07:15)
  • Quote: “I think the future is going to be very, very interesting. Very, very weird because 10 years from now there are going to be people who have very deep, I call it romantic relationships. I mean, it’s already starting to happen, but I think it’s going to be far more commonplace.” — Gary Rivlin (07:36)
• Product changes disrupt relationships:
  • OpenAI’s switch from GPT-4 to GPT-5 frustrated users who’d bonded with previous versions. (07:03)

4. Hype, Disappointment, and the Reality of AI Progress

• Hype cycles hurt AI’s perception:
  • Rivlin criticizes tech leaders for overselling incremental improvements:
    “Hype is really hurting the cause of those advancing AI. I use AI all the time…It’s a tool. A calculator is a tool, A camera is a tool. It’s amazing…But as a co-pilot.” (08:27)
  • Contrasts ChatGPT’s understated, viral launch in 2022 with today’s splashy announce-and-disappoint cycles. (09:36)

5. Why Did OpenAI Break Through?

• History and missed opportunities:
  • AI as a field since the 1950s; machine learning broke through in the 2010s
  • Google had ChatGPT-like capability as early as 2020 but hesitated to launch, wary of PR disasters (e.g., Microsoft’s failed 2016 Tay chatbot):
    “The specter of Tay just kind of hung over Microsoft, Google, every big company. So… it was inevitable it was going to be a startup… because they didn’t have as much to lose.” (11:29)
• AI was already everywhere, just invisible:
  • Search, Netflix recs, Google Translate—AI has run in the background for years, but ChatGPT put it “front and center” where consumers could interact directly. (12:34)

6. Techno-Optimism, Pessimism, and The ‘Bloomer’ Middle

• Comparing Hoffman and Andreessen:
  • Rivlin distinguishes Mark Andreessen's hardline “zoomers” (full speed ahead, no regulation) from “doomers” (AI apocalypse), and situates himself and Hoffman as “bloomers”—optimistic but urging caution and regulation. (17:05–18:28)
• Trust and safety lost primacy:
  • As the stakes and arms race intensified, trust and safety teams at Google and others were deprioritized:
    “The trust and safety teams, like, oh no, we’re in a war against OpenAI… So a lot of people were shifted from trust and safety.” (18:52)
• Ethos of “fix it afterwards” in Silicon Valley:
  • “There is an ethos in Silicon Valley where you ship your product and then if it has deleterious effects somewhere, you fix it after it happens. And that’s how a lot of the really destructive things happen.” — Elizabeth Spiers (20:28)

7. Beyond Hype: AI, Electricity, and Climate Impact

• Data centers and climate:
  • The arms race strains electrical grids and may soon drive up consumer rates and cause brownouts. Investment in green tech isn’t keeping pace. (21:53–22:59)
  • “It’s really putting a huge strain on the electric grid...within the next year or two, consumer rates are going to go way up and we’re going to start to have brownouts.” — Gary Rivlin (21:31)

8. The Limitations and Risks of LLMs (Large Language Models)

• AGI is far off—LLMs have clear limits:
  • Cites Gary Marcus and the “stochastic parrot” criticism:
    “They know a lot about everything...but they don’t understand a word. They don’t have common sense, they don’t have reason.” (24:03)
• Autonomous AI is cause for concern:
  • “Another big fear I have is autonomous AI. AI in charge? No, no, no. It’s a tool. A human has to be in charge.” (24:39)

9. Jobs, Automation, and Economic Consequences

• Displacement and slow adoption:
  • AI likely to slowly but steadily shrink many professional teams; may eliminate more jobs than it creates:
    “The marketing team of 20…is going to be a marketing team of 15 or 10 or 8. Because you could use AI as sort of your junior member of your team.” (25:42)
• AI as a tool for research and brainstorming:
  • Rivlin’s personal uses: research assistant, editor, idea generator, but not for actual writing.
    “If I made a living writing press releases, I’d be worried because that is formulaic.” (27:05)

10. AI’s Usefulness, Limits, and Forgiveness

• AI is not perfect, and neither are humans:
  • The public is less forgiving of AI errors because we don’t trust it’ll learn the way humans do. (29:29)
  • “I’ve hired interns in the past and they’ve made mistakes too. Sometimes I think we’re unforgiving about AI, about the mistakes it makes. Humans can say really stupid things too.” — Gary Rivlin (27:40)
• Best role = Supercharged assistant:
  • Summarization, checklists, brainstorming; ultimately, it’s always human-in-the-loop. (29:11–29:52)

11. Creativity, Human Agency, and the Myth of AI as Creator

• AI gives creative ‘superpowers,’ but concept must come from humans:
  • “You, the human, still have to have the plots, the characters, the twists and all that. And I think that’s the way to understand it. You could be faster…but it’s still as an artist, as a creator… you’re still the one in charge.” (31:59)
• Memorable user experiences:
  • Spiers describes using a generative model to produce abstract angel imagery, which inspired but did not replace her artist’s creativity. (33:08)
  • Rivlin’s story: Google Gemini animated his son’s drawing and eerily grasped the story’s theme.

12. What’s Next? Cautious Optimism, Pessimism, and Busts

• P(doom) and long-term outlook:
  • “So this idea of P Doom, it’s not zero…it’s very, very low. These things aren’t even close to doing, able to do the kind of things we’re scared of. They’re really limited.” — Gary Rivlin (36:10)
  • Predicts disappointment and a possible “AI bust,” analogous to the dot-com bubble. Progress and mainstream adoption will take 10–15 years. (36:10–38:31)
  • Key worry: placing AI in autonomous decision-making roles before it’s ready.

Notable Quotes & Memorable Moments

• “I call [Reid Hoffman] a billionaire you can almost root for.” — Gary Rivlin (05:46)
• “If people use ChatGPT… It’s a conversation. You go to ChatGPT and it’s like, what should I do in this situation? And here’s five things to consider. They just give you bullet points. But with Pi, it was kind of fun… it would compliment you on your stupid jokes.” — Gary Rivlin (06:18)
• “People get very attached to their bots and do insane things.” — Elizabeth Spiers (07:03)
• “Hype is really hurting the cause of those advancing AI… Don’t tell us it’s amazing because we’re going to be disappointed because it’s not artificial general intelligence. It’s a slight improvement for most of us on the previous version.” — Gary Rivlin (09:17)
• “Don’t be evil. I thought that is the lowest bar in the world.” — Gary Rivlin (20:04)
• “The real way I use it, or maybe the most valuable way, it’s a great editor. I’ll tell it, something’s not working here. I need a transition. Give me 10 different transitions… But it gives me a lot of good ideas and it’s good at spotting mistakes.” — Gary Rivlin (28:36)
• “My favorite construct for AI is alien intelligence. We’ve never had anything like this. Again, it knows so much about everything…but doesn’t understand a thing.” — Gary Rivlin (29:59)
• “It gives us superpowers…but it’s you. The human had this idea, use this tool, shared it with another human who didn’t copy it.” — Gary Rivlin (34:01)
• “It is here. It’s going to have a big impact on society… Let’s figure out what’s the best approach so it would be more of a positive thing and negative… But we could debate whether television, the car, you know, the Internet are good things. And I think that’s the kind of debate we will be having. But let’s do what we can now to ensure it’s more of a positive than a negative.” — Gary Rivlin (35:49)

Timestamps for Key Segments

• 01:14 — Why start-ups can’t compete with big tech in AI
• 03:48 — Origins of Inflection AI and the push for emotional intelligence
• 07:15 — Human attachment to AI bots and product transitions
• 08:27 — Hype cycles and public disappointment with new AI releases
• 10:47 — Why OpenAI overtook Google despite big tech’s early leads
• 17:05 — Comparing Andreessen’s and Hoffman’s tech philosophies
• 21:31 — AI’s impact on energy use and climate
• 24:03 — Stochastic parrots: the limits of current LLMs
• 25:42 — Job displacement and economic impact
• 27:05 — How writers and researchers use AI as a tool
• 29:59 — “Alien intelligence” as a metaphor for AI
• 33:08 — Creativity with AI as a jumping off point
• 36:10 — P(doom), the ‘AI bust’ and the long view on AI’s impact

Summary

This wide-ranging episode explores the fierce competition to lead in artificial intelligence, the real-world limits of current AI technology, human behaviors and irrational attachments to bots, and the intertwined risks and hopes for a future shaped by AI. Through candid and often humorous anecdotes, Gary Rivlin demystifies the nature of AI breakthroughs and underlines the continued indispensability of human creativity, judgment, and oversight—even as supercharged “AI co-pilots” become part of everyday work and life. While the trillion-dollar arms race continues among giants, the guest and host urge listeners to prioritize careful, collaborative, and ethical deployment—before the AI tide becomes truly unstoppable.