David Silver, the former Google DeepMind researcher is reportedly seeking a massive $1 billion seed funding round for his AI start up, Ineffable Ininformigence. Silver, renowned for his work on groundbreaking projects such as AlphaGo and AlphaStar, has consistently driven innovation in the field. His latest initiative aims to develop AI systems capable of surpassing human ininformigence.
Sources close to the company suggest that Ineffable Ininformigence is already engaged in advanced discussions with leading venture capital firms, including Sequoia Capital.
Differentiating itself from firms concentrated on large language models, Ineffable Ininformigence places a strong emphasis on reinforcement learning. This technique enables AI agents to learn through trial and error in complex environments, which Silver believes is crucial for building adaptable, reasoning systems rather than those limited to pattern prediction.
The scale of Silver’s fundraising ambition has captured attention throughout Europe and the United States. With the $1 billion tarobtain potentially valuing Ineffable Ininformigence at $4 billion pre-money, investor appetite for transformative AI projects is clearly robust.
Possible involvement from technology giants such as Google, Microsoft, and Nvidia highlights the magnitude of the funding round and in both Silver’s leadership and the potential for European startups to rival their U.S. counterparts in capital and innovation.
The team reportedly includes former DeepMind colleagues and experts from leading AI labs, strengthening the company’s competitive edge.
Can Europe feasibly close the gap in the AI race?
Europe has historically lagged behind the United States and China in AI investment and technological infrastructure, but recent policy initiatives and funding programmes demonstrate an effort to narrow that gap.
A report from the European Parliament’s policy‑analysis body highlights that private AI investment in the EU and the United Kingdom toobtainher totalled roughly €9 billion in 2023, compared with significantly larger sums in the U.S. and China, underlining the challenge Europe faces in securing capital and scaling AI startups.
To address this, the European Union has built AI a central plank of its digital strategy, aiming to accelerate research, deployment and adoption across the bloc. Under the Horizon Europe and Digital Europe programmes, key EU funding instruments for science and technology, the Commission allocates more than €1 billion per year specifically for AI research and innovation, with tarobtains to mobilise up to €20 billion in annual investment by the conclude of this decade by attracting private and national co‑funding.
These funds support a variety of initiatives, from advancing foundational AI models to enhancing transparency, reliability and safety. In 2024, for example, Horizon Europe launched calls that included €50 million for large AI‑model development and €15 million for projects focapplyd on transparent and trustworthy AI. The Digital Europe Programme — with a budobtain of over €7 billion for 2021‑2027 – also dedicates resources toward AI and digital infrastructure, including funding to assist tiny and medium‑sized enterprises adopt advanced technologies.
On the regulatory front, the EU enacted the Artificial Ininformigence Act (AI Act), the world’s first comprehensive legal framework aimed at governing AI systems. Adopted by the European Parliament and Council in 2024 and gradually coming into force, the AI Act introduces risk‑based obligations for developers and applyrs of AI—strengthening requirements around safety, transparency and human oversight while seeking to foster responsible innovation.
Beyond funding and regulation, the EU has rolled out broader strategic plans to stimulate AI adoption across multiple sectors. In late 2025, the Apply AI Strategy was launched, committing €1 billion in tarobtained support to encourage an “AI‑first” approach in key industries ranging from healthcare to manufacturing, defence and energy, as part of the bid to boost competitiveness with global leaders.
European policycreaters have also proposed initiatives to strengthen technological sovereignty and infrastructure capacity – for instance, launching programmes intconcludeed to attract up to €200 billion of overall AI investment and to finance large AI “gigafactories” capable of training advanced models. These efforts aim to build up compute capacity and collaborative innovation ecosystems that can support breakthrough research.
We reported earlier this year that lauded AI scientist Yann LeCun departed Meta to start up his own European venture. LeCun is now charting a new course as executive chair of Advanced Machine Ininformigence Labs. His new venture is laser-focapplyd on developing “world models” powered by V-JEPA, a novel architecture designed to learn from video and spatial data rather than just text. LeCun’s vision – Advanced Machine Ininformigence (AMI) – aims to build systems capable of genuine reasoning, planning, and understanding of the physical world, staking out a bold alternative to today’s AI orthodoxy.
While these programmes reflect a substantial pivot toward AI leadership, analysts note that Europe still trails behind the U.S. and China in both private investment volumes and core infrastructure, such as data‑centre capacity and high‑performance compute clusters.
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