Good morning. It's Friday, July 3, and we're covering how AI agents are moving into investing, why AI's economic impact is proving difficult to track, and OpenAI's proposal to share AI wealth with the public.

Plus: yesterday's poll results on AI layoffs, and a Friday Fact on memory transfer.

OpenAI is exploring an unusual proposal to give the US government a 5% equity stake, reflecting growing efforts to align the AI industry with public interests. CEO Sam Altman reportedly argues the model could help distribute AI-generated wealth more broadly if other leading AI companies adopt similar plans. The discussions remain conceptual, could require congressional approval, and may involve a public investment fund.

Microsoft is investing $2.5 billion and assigning 6,000 employees to a new AI implementation unit, highlighting that enterprise adoption has become the industry's next competitive battleground. The new Microsoft Frontier Co. will embed engineers, consultants, and sales specialists directly with customers to accelerate AI deployments. The move follows similar initiatives from Amazon, Anthropic, and OpenAI, as companies increasingly offer hands-on implementation services alongside AI models.

Amazon is designing its own AI chips for key consumer devices, signaling that control over hardware is becoming central to its AI strategy. Hardware chief Panos Panay says the company already builds end-to-end silicon for products including Echo Show and Fire TV, allowing AI features to run directly on devices instead of in the cloud. Amazon unveiled its AZ3 chips last year and says a new generation of AI-powered wearable devices is already in development, with launches expected in the near future.

The Information reports Anthropic is in early-stage talks with Samsung to manufacture a custom AI chip using Samsung's 2nm process and advanced packaging, having already hired Clive Chan (an early member of OpenAI's custom-chip team) and held discussions with multiple chip-design firms, though it has yet to enter detailed design or testing. The move signals a partial shift for the last major "hardware-agnostic" frontier lab: Anthropic told The Information that AWS Trainium, Google TPUs, and Nvidia GPUs will remain central.

In 2018, a team of neuroscientists gave an animal a memory it never actually lived through — the full story is at the bottom of this newsletter.

GPT-5.6's staggered rollout could concentrate AI access among a few companies, raising concerns about competition and government influence.

Robinhood CEO Vlad Tenev said on July 2, 2026, that AI agents will soon be capable of performing the same trading tasks as human traders, extending sophisticated automated strategies beyond institutional firms to everyday investors. Robinhood introduced agentic AI tools in May that allow AI agents to trade stocks and make purchases on users’ behalf, part of a broader industry push led by companies including OpenAI and Anthropic.

Tenev said much of institutional trading is already automated and AI-powered, but these capabilities have historically been inaccessible to retail investors. The comments come as Robinhood expands into U.K. crypto trading and Europe, with the company serving nearly 28 million customers across 38 countries despite recent workforce cuts aimed at improving efficiency. → Read the full article here.

An analysis by The New York Times highlights how artificial intelligence is spreading through the economy faster than economists and policymakers can reliably measure its effects. Current data paint conflicting pictures, with some studies linking AI to job losses—particularly among recent graduates—while others suggest the technology is boosting hiring, productivity, or helping ease inflationary pressures.

Researchers also disagree on fundamental questions, including how widely businesses have adopted AI and which workers are most at risk of disruption. The rapid adoption of generative AI in less than four years has outpaced traditional economic measurement, raising concerns that policymakers may struggle to respond before its full effects become clear. → Read the full article here. (Paywall)

The Economist argues that the U.S. should establish clear, predictable regulations for frontier AI rather than relying on ad hoc restrictions that limit access to advanced models. The publication points to the Trump administration's temporary export controls on Anthropic's Fable model and subsequent policy reversal as evidence of an opaque regulatory approach that creates uncertainty for AI companies.

It argues that permanently restricting powerful AI models is both impractical—given rapid advances by Chinese developers—and counterproductive, since broad access helps economies adapt gradually to new capabilities. Instead, the editorial advocates for formal evaluations, phased releases to trusted institutions, and oversight by independent technical bodies working alongside governments. → Read the full article here. (Paywall)

Electricity Demand Outpaces GDP: AI data centers and electrification will drive power demand above GDP growth, boosting demand for key industrial metals.

Singapore Seizes $42M Mansion: Authorities allege the luxury home was bought with proceeds from NVIDIA chip smuggling in a wider export probe.

Neo Takes on Microsoft Office: Bhavin Turakhia is investing $30M of his own money to build an AI-first workplace platform for businesses.

Anthropic Denies Government Stake Talks: A source says Anthropic has not discussed giving the U.S. government an ownership stake.

Here's how you voted: The top answer was that AI couldn't do the job yet, followed closely by failed cost savings.

In 2018, a team led by David Glanzman at UCLA trained sea snails (Aplysia californica) by giving their tails a series of mild electric shocks, producing a heightened, long-lasting defensive withdrawal reflex.

The researchers then extracted RNA from the nervous systems of the trained snails and injected it into snails that had never been shocked. The untrained recipients immediately displayed the same sensitized reflex as the snails that had actually gone through the training. Snails injected with RNA from untrained donors showed no such change.

For over a century, memory has been understood as something stored in the strength of connections between neurons. This experiment, published in the journal eNeuro, suggests RNA itself can carry a memory-like instruction, likely through an epigenetic change called DNA methylation. It doesn't overturn the standard theory of memory, but it complicates the assumption that memories live only in synapses.

Thanks for reading. See you next time!

— Matthew Berman, Nick Wentz & the Forward Future Team