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News & insights

Expert analysis, bringing the latest R&D talent insights and market perspectives.

Artificial Intelligence, Frontier AI, Hiring

October 15, 2026

Better researchers than OpenAI. Worse retention than anyone. A $40 billion bet either way.

Thinking Machines Lab is reportedly in talks to raise $5 to $6 billion at a $40 billion valuation, with Nvidia supplying roughly half. Zeki's data explains why investors are prepared to write that cheque — and where the risks sit.

Deep-Tech, Hiring, quantum

October 5, 2026

The Hardest Hire in Deep Tech is the One that Proves You are Building a Company, Not a Lab

Planqc is a Munich-based quantum computing company, founded in 2022 as the first spin-out from the Max Planck Institute of Quantum Optics. The lab-to-product transition is the central risk in quantum hardware investing. It is also, until now, almost impossible to measure from the outside. Milestones are self-reported. Scientific papers say nothing about engineering execution. Founder credentials tell you what a team can prove in a laboratory, not whether they have started building the workforce to deliver to a customer. Hiring data tells you that. We have been tracking it across the neutral-atom quantum sector for several years. What we see in one company is a clear, quantified illustration of the risk Atomico named — and a template for how investors can read it in any deep-tech hardware company before a milestone is hit or missed.

Artificial Intelligence

September 30, 2026

Google Built the Research that Made AGI Plausible. Now the People Who Did the Work Have Left to Finish It.

Google DeepMind's decision to restrict research publications triggered an exodus. The people leaving are not going to other big labs. They are betting on AGI — and where they go, and who they hire next, tells investors everything about which approach they think will win. That elsewhere is London. In 2026, three separate AGI-focused labs have emerged from DeepMind's alumni network in quick succession. Ineffable Intelligence, founded by AlphaGo architect David Silver; Recursive Superintelligence, co-founded by former DeepMind researcher Tim Rocktäschel and former Salesforce chief scientist Richard Socher; and Emulate, founded in August by Jack Parker-Holder, Matthew McGill and Philip Ball — the team behind DeepMind's Genie world-model programme.

Deep-Tech, Energy

September 17, 2026

In a Narrow Talent Pool, Location is Strategy

Antora Energy, founded in 2017, builds and deploys thermal batteries for industrial customers. In August 2026 it closed a $550 million Series C — an oversubscribed round co-led by G2 Venture Partners and Eclipse — shortly after commissioning a 5 GWh project at POET's bioprocessing facility in South Dakota, one of the largest battery storage installations in the world. The company has 30 open roles and is building a second US manufacturing facility. The question Zeki's data answers is not whether Antora is a credible company — the funding and the deployment record settle that. The question is whether the talent behind its growth is as strong as the momentum suggests, and whether the risks accumulating quietly in the workforce are visible before they matter.
Headshot of Jacob Coxon

Artificial Intelligence, Deep-Tech

September 11, 2026

Who Is Jacob Coxon? Expertise, Proximity and the AI Safety Debate

Former Jacob Coxon has become a prominent voice in the AI safety debate after publicly criticizing both Anthropic and OpenAI and warning about the trajectory of advanced AI development. As the discussion around his comments grows, it is worth considering the experience supporting his observations as carefully as the observations themselves.

Deep-Tech, GTM, Hiring, Scale-Up

September 3, 2026

The Strongest Engineering Team in Earth Observation. The Weakest Sales Team.

Muon Space has built a more credentialed technical workforce than any of its earth observation peers — on less capital per head. The gap that matters now is not the engineering bench. It is the commercial team that does not yet exist at the scale the next phase requires. Earth observation has a structural talent problem. The specialist skills it requires — payload engineering, remote sensing science, RF and IR instrumentation, mission architecture — are concentrated in a small number of agencies and primes. Northrop Grumman, BAE Systems, NASA, ESA, Lockheed Martin, Airbus and Thales together hold roughly four in five of the relevant people globally. A new entrant wanting to hire from this pool competes directly with some of the best-resourced employers in aerospace.
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