Thinking Machines Lab, the AI startup founded last year by former OpenAI CTO Mira Murati, on Monday announced something called interaction models, which, at its essence, sounds like AI that can interrupt you.

Right now, every AI model you’ve ever used works the same way. You talk, it listens. It responds, you listen. Thinking Machines is trying to change that by building a model that processes your input and generates a response at the same time, so it’s more like a phone call than a text chain.

The technical term for this is “full duplex,” and the company claims its model, TML-Interaction-Small, responds in 0.40 seconds, which is roughly the speed of natural human conversation and significantly faster than comparable models from OpenAI and Google.

Still, this is a research preview, not a product. The company isn’t releasing it to the public yet. A “limited research preview” is coming in the next few months, it says, with a wider release set for later this year.

So what to make of it? We’re not sure. The benchmarks are impressive and the underlying idea — that interactivity should be native to a model, not bolted on — is definitely interesting. Whether the real-world experience lives up to the technical claims is something we won’t know until people can actually use it.

Just two months after listing its first venture fund on the stock market, Robinhood is preparing to launch a second. The company has filed a confidential registration for RVII, a standard regulatory step that allows it to work through the approval process before making details public.

Unlike its first fund, which currently holds stakes in 10 late-stage companies — Airwallex, Boom, Databricks, ElevenLabs, Mercor, OpenAI, Oura, Ramp, Revolut, and Stripe — RVII will cast a wider net, investing in growth-stage and early-stage startups. It’s a meaningful distinction, given that early-stage startups are younger and carry more risk but also offer the potential for greater returns.

The fundraising target for RVII has not yet been set, the company said in a blog post. For its inaugural fund, Robinhood sought to raise $1 billion but ultimately fell several hundred million short of that goal.

Despite the shortfall, the first fund has performed strongly. RVI — the ticker for Robinhood’s first fund, which trades on the NYSE (New York Stock Exchange) — debuting on the NYSE at $21 a share in early March and has since more than doubled, closing on Monday at $43.69. Market enthusiasm for the AI prospects of the fund’s underlying startups has likely fueled the stock’s rise.

The premise behind both funds addresses a longstanding gap in who gets to invest in startups. Under federal rules, only “accredited” investors — those with a net worth exceeding $1 million or annual income above $200,000 — can put money into private companies. That has historically locked ordinary investors out of the earliest and most lucrative stages of a company’s growth. RVI and now RVII, are designed to change that, letting anyone invest in a portfolio of private startups through a regular brokerage account.

“You can think of [Robinhood Ventures] as a publicly traded venture capital firm with daily liquidity. No accreditation requirements and no carry,” Robinhood CEO Vlad Tenev said in an interview at The Wall Street Journal’s Future of Everything conference last week. Daily liquidity means shares can be bought or sold any day the market is open, unlike traditional VC funds, where capital is locked up for years. No carry means Robinhood doesn’t take a percentage of investment profits, as conventional venture firms typically do.

Over the past few years, the most valuable AI startups have gone from early bets to companies worth tens or hundreds of billions of dollars, and almost all of that appreciation has happened in the private markets, out of reach for most investors.

Tenev’s longer-term vision goes further still. “The aspiration is, if you’re a company raising a seed round and a Series A round — so, just first capital — retail should be a big chunk of that round, much like it now is in the public markets,” Tenev said at the conference. “And we should let those people in at the ground floor, so that they can actually benefit from this potential appreciation that’s increasingly happening in the private markets.”

If that vision takes hold, it could fundamentally change how startups raise their earliest capital, with retail investors eventually sitting alongside venture firms, including in the earliest rounds, where the biggest returns are often made, a whole lot of money is lost, as well.

General Motors has laid off more than 10% of its IT department, or about 600 salaried employees — in a deliberate skills swap: clearing out workers whose expertise no longer fits and making room for some with AI-focused backgrounds.

GM confirmed to TechCrunch that it had conducted layoffs; they were first reported by Bloomberg News.

In an emailed statement, the automaker framed the layoffs as means to prepare it for the future, without providing specifics. “GM is transforming its Information Technology organization to better position the company for the future,” the company said.

These layoffs are not all permanent headcount reductions. A person familiar with the layoffs told TechCrunch that the company is still hiring people for roles in its IT department, but for different skills. The most sought-after capabilities are AI-native development, data engineering and analytics, cloud-based engineering, and agent and model development, prompt engineering, and new AI workflows. In practical terms, GM is looking for people who know how to build with AI from the ground up — designing the systems, training the models, and engineering the pipelines — not just use AI as a productivity tool.

GM has laid off white-collar employees in several departments over the past 18 months, as it focuses its resources on high-priority initiatives, including AI. In August 2024, for example, the company cut about 1,000 software workers.

The software workforce has undergone significant change since Sterling Anderson — co-founder of the autonomous trucking startup Aurora and a veteran of the autonomous vehicle industry — was hired in May 2025 as chief product officer. Last November, three top executives left the company’s software team as Anderson pushed to consolidate GM’s disparate technology businesses into one organization: Baris Cetinok, senior vice president of software and services product management, Dave Richardson, senior vice president of software and services engineering, and Barak Turovsky, a former VP at Cisco who spent just nine months as GM’s chief AI officer.

GM has since moved to fill the gap with new AI-focused hires. It hired Behrad Toghi, who previously worked at Apple, in October as AI lead. The company also brought on Rashed Haq as its vice president of autonomous vehicles. Haq spent five years at Cruise — the self-driving vehicle company acquired and later shuttered by GM — as its head of AI and robotics.

For the industry, GM’s restructuring is a signal of what enterprise AI adoption actually looks like in practice — not just adding AI tools on top of existing teams, but deliberately rebuilding the workforce from the ground up. The specific capabilities it’s hiring for — agent development, model engineering, AI-native workflows — point directly at where large-enterprise demand is heading.