Sesame Summit 2026 – application open

What’s next for voice & vision tech?

Our CEO Ben Costantini just got back from a quick trip to Germany where he was on-site at Siemens Mobility in Munich supporting Sebastian Greiss, Founder of StationX with the launch of their first internal event series aiming to unite and inspire their engineering teams to think bigger.

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Sebastian Greiss (StationX)

Voice Assistants: where do we stand between dysfunctional voice interfaces and truly AI powered assistants?

Keynote Speaker: Holger G. Weiss, CEO, Founder & Managing Director, German Autolabs (Germany)

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Holger G. Weiss (German Autolabs) & Sebastian Greiss (StationX)

Takeaways:

The underlying technology behind voice assistants has been around for at least the last 50 years but has only recently started accelerating via tools like Alexa and Siri.

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Holger G. Weiss (German Autolabs)

Specifically, the biggest barriers include:

  • Accuracy – many users have a low tolerance for inaccuracy when using these tools
  • End-user expectations – most users expect their voice assistance to work like a human being leading user’s to continue expecting more than what their voice assistants can currently offer
  • Language barriers – besides just having trouble matching the correct words, most of the friction comes from not understanding users’ accents when trying to pronounce words either in their own language or (worse) in another language
#LanguageBarriers

“While there’s no official killer use cases for voice assistants, we see that shopping (B2C) & customer support + music (B2B) as well as in-car voice assistants are getting there” – Holger G. Weiss

German Autolabs is developing voice assistance tools to augment the daily workflows of professional drivers, couriers and delivery teams, including:

  • Safety to multitask – their assistant can tell drivers what to do next and plan their driving without risking a loss of focus leading to 76% improvements in new driver performance in just 2 weeks and 90% quality compliance with customer expectations
  • Time-saving and efficient companies like DHL, Volkswagen and HERE have are now able to operate more safely by reducing distraction rate, facilitating logistics leading to boosted overall efficiency

“The creativity of the German Autolabs team has helped developed an innovative way of making last mile logistics more efficient. In a time-sensitive business where every minute counts, we really believe this will aid our drivers in ensuring that each and every parcel makes it on time.”   – R. Wenham DHL

In the near future, voice assistants will be more and more proactive, knowing more precisely what to do in response to varied vocal commands. Voice assistance could even be more of an extension to existing AR and VR deployment from companies like Siemens.

Using Autonomous Machine Vision at Siemens Mobility

Speakers: Axel Reimold, Siemens Mobility (Germany) & Uri Josefson, Sales Director, Inspekto (Israel) – moderated by Sebastian Greiss, Founder, StationX (Germany)

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Axel Reimold (Siemens Mobility) & Sebastian Greiss (StationX)

The goal of machine vision is to offer imaging-based inspection and analysis for applications such as automatic inspection, process control, and robot guidance usually used in industries but also becomes more common in society like Facial Recognition when using your phone.

Challenges

“The human eye is very flexible and precise and current tech doesn’t have that capability. Machine vision is hard to scale up and and it is difficult to automate, however there is still a need to an automate this process to make it more cost-effective.” – Axel Reimold

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Uri Josefson (Inspekto) & Sebastian Greiss (StationX)

Inspekto is on a mission to make Machine Vision (more) Autonomous and they have a system that helps Siemens tackle this problem. Their vision is to make the inspection of systems very easy – no need for technical skills – and to provide various inspections using the same system.

The ability to solve the process of high mix with low volume and to be able to deploy the system in 20mins. Generally, Inspekto can be applied in different use cases but it’s necessary to check especially since it only takes 30mins to deploy it and test it in real-time.

Conclusion

It’s clear that voice technology is at the edge. After decades of limited user experience and use cases, voice assistants are entering our daily lives. Thanks to this pragmatic review of the status quo with respect to technology, user behaviour and industries, we learned that we’re closer than we thought to experiencing ‘real’ assistants, helping people in their daily lives and work.


[Disclaimer: This event series was attended by Ben Costantini as part of a partnership with Siemens StationX. Opinions and information presented here may or may not represent those of Siemens StationX.]

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Fundraising 4 hours ago

London-based AI laboratory Ineffable Intelligence has emerged from stealth with a $1.1 billion seed round at a $5.1 billion post-money valuation, the company confirmed on 27 April 2026. The financing is the largest seed round ever raised by a European company and one of the largest first-money-in rounds in the global history of artificial intelligence. The round was co-led by Sequoia Capital and Lightspeed Venture Partners. Participating investors included Nvidia, DST Global, Index Ventures, Google, and the UK Sovereign AI Fund, the British government’s recently established vehicle for backing strategic AI capacity on home soil. A bet on a different path to general intelligence Ineffable Intelligence was founded in 2025 by David Silver, the former Vice President of Reinforcement Learning at Google DeepMind and the principal architect of AlphaGo, AlphaZero and AlphaStar. He is joined by three further DeepMind alumni: Wojciech Czarnecki, Lasse Espeholt and Junhyuk Oh. All four have spent the past decade at the frontier of reinforcement learning research, the discipline behind some of the most consequential demonstrations of machine learning over the past ten years. The company describes its objective as building a “superlearner” — an AI system capable of acquiring knowledge directly from its own experience rather than from human-generated text or imagery. “Our mission is to make first contact with superintelligence,” Silver said in a statement accompanying the launch. “We are creating a superlearner that discovers all knowledge from its own experience, from elementary motor skills through to profound intellectual breakthroughs.” The framing is a deliberate departure from the dominant industry trajectory. Most leading AI laboratories, including OpenAI, Anthropic and Google DeepMind itself, have built large language models trained primarily on the corpus of the internet, then refined that training with human feedback. Ineffable’s wager is that the marginal returns on scaling text-based pretraining are diminishing and that the next leap in capability will come from agents that learn endlessly from the consequences of their own actions, in much the same way AlphaZero learnt the game of Go without studying any human matches. Why $1.1 billion at seed The size of the round is unusual even by the inflated standards of the 2026 AI capital cycle. Two factors appear to explain it. First, frontier reinforcement learning at the scale Ineffable describes is computationally extraordinarily expensive: the company will need to operate vast simulation environments and train very large models against them, an undertaking that consumes capital at a rate closer to physical R&D than to traditional software. Second, the round signals a strategic move by Europe’s investor and policy ecosystems to retain the most ambitious AI researchers on the continent. The presence of the UK Sovereign AI Fund alongside Sequoia, Lightspeed and Nvidia is the clearest expression of that intent. The British government has publicly framed the investment as a bet on breakthrough AI that “can discover new knowledge”, positioning the country as a willing co-investor in domestic frontier laboratories. For Ineffable, the implication is access not only to capital but to compute, regulatory engagement and the still-resilient academic talent base around UCL, Oxford, Cambridge and Imperial. Founder pledge of historic scale Alongside the funding announcement, Silver disclosed that he is committing 100 per cent of any personal proceeds from his Ineffable equity to charity via the Founders Pledge network — described by the organisation as the largest pledge in its history. At the round’s $5.1 billion valuation, that commitment could ultimately exceed several billion dollars if the company succeeds. It is a meaningful gesture in a sector where the reputational stakes around concentrated AI wealth are escalating, and one likely to be referenced in subsequent founder-led commitments. Implications for the European AI landscape Ineffable’s emergence reshapes the European AI map in three concrete ways. It establishes London as the home of the continent’s largest-ever seed-stage company, complicating Paris’s recent narrative of frontier-AI primacy after Mistral’s earlier rounds. It validates a thesis — that reinforcement learning, not transformer scaling, is the next frontier — that has lately been losing capital share to language-model incumbents. And it confirms that the UK government is now willing to act as a balance-sheet co-investor in domestic AI laboratories, a posture much closer to the French model than to the predominantly grant-based regimes elsewhere in Europe. The execution risk is non-trivial. Reinforcement learning at frontier scale has historically required years of careful environment design before producing competitive systems, and Ineffable’s “first contact” framing sets a high bar against which it will be judged. But for now, with a billion dollars on the balance sheet, four of the discipline’s most accomplished researchers in the founding team and a sovereign co-investor at its back, Ineffable Intelligence is the most heavily resourced new entrant in the European AI cycle. Sesamers covers European fundraising rounds across deeptech, fintech and AI. Source: tech.eu.

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