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How to build the Spanish Deep Tech Ecosystem, Challenges – Selected

The following is my distillation of the Spanish Deeptech ecosystem as obtains through countless hours of conference and event participation, data culled from The Collider‘s Technology Transfer and Business: Challenges and Opportunities report, and interviews done to key stakeholders and players from the Deeptech ecosystem in Spain including:

Many challenges arise from key players

1. Entrepreneurs & Researchers

  • Fear of missing their economic stability
  • Lacking knowledge on how to start their companies
  • Failure of projects due to a non specific market problem solution (focus on their research topics instead of looking at the market needs and trends)
  • Looking to license the technology instead of developing it into a business
  • Lack of emotional support and fear of emotional loneliness during the entire business creation process
  • Willingness to find alternatives to develop their projects and research out of academia

2. Tech Universities & R&D Centers

  • Need of more human capital
  • Need of more funding resources
  • Necessity to track spinoffs situation and evolution
  • Aquire more education on the business side
  • Need to have a closer relation with organisations
  • Need to understand technology applications in the market and business needs
  • Lack of exponential innovations (moonshots) vs incremental innovations
  • Lack of ecosystem unification (who is who?)

3. Organizations

  • Looking for incremental innovations, not exponential
  • Focus on short-medium term results
  • Lack of an agile collaboration structure (companies – startups)
  • Involvement in later stages, when risk is lower
  • Focus on the operational side, lack of time to understand market evolution and innovations developments
  • Looking to understand technology applicability in business
  • Looking for new business models to stay competitive in the market

4. Investors

  • Need for a bigger funding approach to initial phases and industrialisation stages (be more risk averse)
  • Looking for a higher number of qualitative and quantitive dealflow in scientific and new technology innovations
  • Need to adapt indicators for each stage: quantitative vs. qualitative

5. Public Institutions

  • Capital access to motivate researchers to start a business
  • Capital access for Deeptech innovations (TRL3-7 – 3 being “Experimental proof of concept” and 7 “Prototype demonstrated in a relevant environment.” )
  • Provide constant support to universities and R&D Centres
  • Attract talent to the city / region / country
  • Work on fiscal incentives to attract investments
  • Provide more visibility to Deeptech innovations
  • Educate about science and new technologies
  • Create quality job employment
  • Build a Deeptech entrepreneurship culture since School
  • Boost and expose more science into the market
  • Knit the Deeptech innovation culture

Therefore, in order to build a strong Deeptech ecosystem, Spain must provide more visibility and exposure, more resources, funding capital and, especially, more education on scientific and high technologies to its citizens and key players.

Building relationships between key players is vital and necessary. If the Spanish economy wants to become a strong economy, investing in the Deeptech ecosystem is key for its long-term survival.

Stay tuned as I expect to have my part followup, (Part 2), with further data and conclusions within the next weeks.

In the meanwhile, three events you should take a look at:

International Conference on Agricultural, Biotechnology, Biological and Biosystems Engineering – 21-22 October 2020 – ICABBBE 2020 aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Agricultural, Biotechnology, Biological and Biosystems Engineering.

Kaspersky Security Summit – 6-8 October 2020 – The Kaspersky Security Analyst Summit (SAS) is a yearly event that gathers high-caliber anti-malware researchers, global law enforcement agencies and CERTs and senior executives from financial services, technology, healthcare, academia, and government agencies.

BIO-Europe 2020 Digital – 26-29 October 2020 – BIO-Europe is the largest partnering conference in Europe dedicated to the global biotechnology industry. This year reaches its 26th edition and will be held in digital format.

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Fundraising 5 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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