OpenAI's Jalapeño Chip Is Here

Plus: $2.3B Raised to Train AI Agents via Video Games

June 26, 2026

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The Last Time Stocks Were This Expensive Was December 1999.

"Right now, it's good. But it was in '72, '86, 2000, and 2007." - Jamie Dimon, May 2026.

The Shiller CAPE ratio just hit 42.3. The only time in 140 years it's been higher? December 1999.

Stocks can stay expensive for a long time...

It’s one metric to consider, but when your portfolio is built around the most expensive equities in modern history, what else you diversify with could really matter.

Blue-chip contemporary and post war art has shown near-zero correlation with the S&P since 1995.* Prices are largely driven by private collectors competing for a fixed supply of artwork by artists like Banksy, Basquiat, and Picasso.

Masterworks lets you invest in shares of that market.

  • $1.3B deployed across 500+ artworks

  • 29 exits to date

  • Net annualized returns like 16.5%, 17.6%, and 17.8%, not including those unsold

*According to Masterworks data. Investing involves risk. Past performance is not indicative of future returns. See important Reg A disclosures at masterworks.com/cd.

AI News + AI Tools | Daily Newsletter (Reading Time: ~1 minute)

Welcome to ListedAI — your go-to source for staying ahead in the fast-moving world of artificial intelligence. ⚡

Today's news cycle is defined by a single theme: the rising cost of running AI at scale — and who's building infrastructure to solve it. OpenAI unveiled its first custom inference chip to cut costs in half, ex-Apple and NVIDIA engineers raised $80M to slash agent token costs by 10x, and a $2.3B startup is betting that Fortnite players are the fastest path to training real-world robots. Meanwhile, Salesforce and Patronus are hardening the enterprise AI layer from opposite ends.

Today's Top Stories

OpenAI & Broadcom Launch "Jalapeño" — A Custom AI Inference Chip

OpenAI unveiled Jalapeño, its first purpose-built AI accelerator, co-developed with Broadcom and manufactured by TSMC. The chip is an ASIC optimized for LLM inference — not training — and went from initial design to tape-out in just nine months, with OpenAI using its own AI models to assist in the design process. Broadcom CEO Hock Tan says early testing shows Jalapeño cuts inference costs roughly in half versus current GPU alternatives, with deployment planned before year-end. A detailed performance report and a multi-generation roadmap are coming later in 2026. Source →

General Intuition Raises $320M at $2.3B Valuation to Train AI Agents via Video Games

General Intuition closed a $320M round led by Khosla Ventures — with participation from General Catalyst, Jeff Bezos, Eric Schmidt, and researchers from Google DeepMind and MIT — bringing total funding to $454M. The startup's core thesis: video game environments are the ideal training ground for AI agents that must eventually navigate physical space. It also launched Nerve, a jobs marketplace where gamers earn income through data labeling and robot teleoperation using their existing gaming setups. Source →

Salesforce Launches Help Agent — Prebuilt AI Customer Service with Pay-Per-Resolution

Salesforce announced Help Agent, a prepackaged AI service agent built on its Agentforce platform that connects to company knowledge bases, communication channels, and action workflows in minutes — including web, text, and voice. The biggest change is a new pay-per-resolution pricing model: companies only pay when t htmlhe agent autonomously resolves a customer issue end-to-end. Help Agent and a redesigned Customer Service Portal go generally available in July 2026. Source →

Sail Research Raises $80M to Make AI Agent Inference 10x Cheaper

Sail Research, founded by ex-Apple and ex-NVIDIA engineers, closed $80M in combined seed and Series A funding at a $450M valuation. The San Francisco startup claims it can serve AI agent tokens at up to 10x lower cost than current infrastructure providers — directly targeting the economics problem blocking most companies from running ambitious agentic workloads at scale. Sequoia led the seed; Kleiner Perkins led the Series A, with angels from Anthropic, OpenAI, SpaceX, and Thinking Machines joining in. Source →

Patronus AI Lands $50M Series B to Stress-Test AI Agents in Simulated Worlds

Patronus AI — founded by former Meta AI researchers Anand Kannappan and Rebecca Qian — raised a $50M Series B led by Greenfield Partners, with Lightspeed, Datadog, and Samsung participating. The company builds simulated digital environments where enterprises can stress-test AI agents before deploying them in production — a critical need as agents take on higher-stakes roles. Revenue grew 15x over the past year; total funding is now $70M. Source →

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