Daily AI Newsletter: 'It's going to be really bad': Fears over AI bubble bursting grow in Silicon Valley

Loading page…

In today’s email:

🔥 Suspect in Palisades Fire Allegedly Used ChatGPT to Generate Images of Burning Forests and Cities
🇨🇳 AI researcher leaves Anthropic over anti-China stance
🤑 The best ChatGPT that $100 can buy.
🧰 10 new AI-powered tools and resources. Make sure to check the online version for the full list of tools.

'It's going to be really bad': Fears over AI bubble bursting grow in Silicon Valley

Key Takeaway: A surge of intertwined megadeals, cross-investments, and “vendor financing” is fueling AI’s meteoric rise, stoking fears that valuations outrun real demand and could trigger a painful, economy-wide unwind.

More Insights:

Sam Altman admits “bubbly” pockets but says OpenAI’s growth is real—even as it remains unprofitable.
Big warnings (BoE, IMF, Jamie Dimon); AI names drove ~80% of U.S. market gains; Gartner pegs AI spend near $1.5T by end-2025.
OpenAI’s web: $100B with Nvidia, plans to buy billions from AMD, deep ties with Microsoft and Oracle; Nvidia also backs CoreWeave, an OpenAI supplier.
Critics call this “circular/vendor financing” (Nortel déjà vu); Nvidia’s Jensen Huang says no exclusivity or spending strings attached.
Signs of froth: splashy plans without secured capital, retail rush into chip stocks, massive 10-GW data-center builds—and environmental concerns—though some argue overbuild could still seed future innovation.

Why it matters: If AI demand is being propped up by circular money rather than durable economics, the eventual comedown could hit chips, cloud, and startups simultaneously—leaving stranded megaprojects and exposing how concentrated the funding power has become—so transparency, stress-testing, and true unit-economics discipline are critical right now.

Master AI in 16 hours and become irreplaceable before 2025 ends!

Join Outskill’s 2-Day AI Mastermind — a hands-on training to make you an AI-powered pro who can learn, earn, and build with AI. Usually $395, but as a part of their Halloween sale 🎃, you can get in for completely FREE!

In 16 hours & 5 sessions, you will learn:

✅ Build AI agents that save up to 20+ hours weekly
✅ Master 10+ AI tools
✅ Automate 80% of your workload, And Much more.

🎁 Unlock $5000+ in AI bonuses: prompt bibles, roadmap to monetize AI, and your personalised AI toolkit builder!

Join Now (Limited free seats)

Jony Ive & Sam Altman on Designing the Next Interface for AI

Key Takeaway: A candid conversation on how LoveFrom and OpenAI are reimagining the way humans relate to technology—prioritizing care, craft, and joy to build a new, humane interface era powered by AI.

More Insights:

Ideas start fragile: trust, vulnerability, and tenacious questioning help them become inevitable.
Craft = care: sweating imperceptible details signals respect for users—especially when no one is looking.
Focus amid momentum: AI’s rapid progress spawns many good ideas; the hard part is choosing and finishing.
Beginner’s advantage: this wave levels the field—curiosity, humility, and rejecting dogma matter more than pedigree.
Beyond legacy UI: the future may rethink “OS” and “apps,” drawing cues from human-to-human interaction, tools, and play.

Why it matters: If AI products are shaped with empathy, restraint, and delight—not just capability—they can reverse today’s tech-induced anxiety and become tools that make people calmer, happier, and more connected.

Thinking Machines Lab Co-Founder Departs for Meta

Key Takeaway: Andrew Tulloch, co-founder of Mira Murati’s Thinking Machines Lab and ex-OpenAI and Meta researcher, has rejoined Meta as part of its aggressive AI recruitment drive led by Mark Zuckerberg.

More Insights:

Tulloch co-founded Thinking Machines Lab with Murati earlier this year after stints at Meta and OpenAI.
Meta has recruited over 50 AI experts from top firms including OpenAI, Google DeepMind, Apple, and xAI.
Zuckerberg personally led recruitment efforts, offering massive compensation packages to top researchers.
Thinking Machines recently launched Tinker, an API for fine-tuning large language models, and raised $2 billion.
Meta formed a new Superintelligence Labs division, led by Alexandr Wang of Scale AI, to focus on next-gen AI models.

Why it matters: Meta’s high-profile AI hires highlight the escalating arms race for talent among top tech giants—signaling that the battle for artificial general intelligence is no longer about products alone, but the people who can build them.