Munawar Abadullah

DeepTech is no longer tomorrow’s story—it’s happening now. From AI supernovas to quantum breakthroughs, we’re at an inflection point. The global deep tech market is projected to soar from US $41 billion in 2024 to US $714 billion by 2031, growing at a staggering 48% CAGR. Generative/agentic AI, commercial quantum, post-quantum cryptography, robotics, biotech, climate-tech, space-tech and advanced materials are leading the charge. Founders of tomorrow must combine technical depth in AI/ML, robotics systems, biotech engineering, quantum foundations, climate resilience with hustle—and a knack for translating invention into impact. Experimentation in DeepTech takes time. As an Investor or a founder, be patient, lean into grants and non-dilutive funding, and refine your story for long-horizon stakeholders. Generative AI already pulled in US $49.2 billion in H1 2025, surpassing the full 2024 total. AI startups commanded 53% of global VC funding in H1, and 64% in the U.S. Deep tech funds are delivering a yield of ~17% net IRR, compared to ~10% for traditional tech—despite higher upfront costs. LPs are shifting to deeptech because breakthroughs in biotech, robotics, climate infrastructure drive real-world transformation, yield long-dated but potentially industry-reshaping exits, and also tap into urgent macro needs like climate action, security, resource scarcity. Governments are stepping up too, for example, Spain’s CDTI earmarked €1.94 billion in 2025 for deep-tech, including biotech, AI, and space, plus €300 million for deep-tech transfer funding. Europe is rising with its share of globally leading deep-tech firms jumping from ~14% to nearly 19%. Accelerators such as StartupBay offer domain-specific programmes. With such programs corporates can co-incubate or pilot; universities can unleash spinouts; governments can deploy grants, co-investments, and drive innovation missions. Together, we shorten path-to-market. Some other macro drivers fuelling this moment are geopolitics & national security where chips, AI dominance, sovereign defence tech are strategic stakes and climate urgency where AI-powered climate tech is pivoting to solve data-center energy use (expected to hit 4% of global electricity by 2030), with startups innovating in renewable power, modular electronics, hydrogen, battery tech. If you’re starting to build a deeptech venture, or funding it, enabling it, or catalyzing it, please drop a comment and talk to StartupBay accelerator. Let’s talk on how do you see your role in fueling DeepTech’s next wave? #DeepTech #FutureTech #Founders #InvestInDeepTech #ScienceToStartup #ClimateTech #QuantumRevolution #StartupBay #StartupSG #EUStartups #StartupIndia Data Sources : StartUs Insights, ITPro, Axios, CDTI, ECEPR, Financial Times, Business Insider

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Ever seen an R&D funding checklist up close? Most only glimpse the surface. Real progress happens in the details—like when a founder’s pitch deck gets dissected over coffee, or a single line on a funding form sparks a 30-minute debate. Today’s win: one overlooked requirement flagged, one startup’s path cleared. This is what hands-on advisory actually looks like. The difference is always in the room.

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#GeneralPurposeTechnologies (#GPT), such as #AI, must cause enterprises to rethink and redesign their workflows, organizational structures, and business models. Most enterprise information technologies, e.g., business intelligence, refine and optimize existing processes rather than forcing their complete redesign. If CEOs don't distinguish between a true General-Purpose Technology and standard information technology, they may view committees and #CentersofExcellence as the right bodies to introduce AI to their corporations. URL: https://wp.me/p4vHBq-14p #AICEOSqueeze #AIEmployeeSqueeze #AIStakeholderSqueeze, #AIStrategy, #EnterpriseAI, #GenerativeAI, #GenAI, #GPT

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Whether you're building a factory, an IP portfolio, a platform, an app, or any kind of asset, there's one foundational layer that drives long-term economic value: 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲. Infrastructure is what makes everything else possible. It’s the base that enables you to build, buy, or scale. It becomes your moat—because it takes time, thought, and effort to design and create. It’s built to last, and it’s where value begins. In software, infrastructure makes integration, security, speed, and adoption easier. But this idea goes far beyond tech or tangible assets. It applies to business too—𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: a solid, long-term strategy built with intention. So, what does it take to build great infrastructure? An 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 𝗺𝗶𝗻𝗱𝘀𝗲𝘁—someone who sees what matters in the long run and can turn that vision into protocols. Because protocols are the blueprint of infrastructure. I believe every product or company we build should start with its own protocol. It’s hard work. But it’s also what creates enduring value—and enduring companies.

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The “#TragedyOfTheCommons,” is the damage that actions by individuals can inflict on the environment at large, but what about the effects of the Internet as interconnections proliferate and increase in strength, creating valuable commons in virtual space. http://ow.ly/oZus30pocMN

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My review of Pablos Holman's seriously probing (yet occasionally witty) book, Deep Future, about the core technologies that can transform key industries, in CTech by Calcalist. A must-read for any DeepTech investor or entrepreneur.

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Meta's potential investment in Scale AI might be a bet that high-quality training data and human feedback loops are the real bottleneck to AGI. Instead of building larger and larger models, Scale AI's expertise in creating precise datasets could help Meta in building smarter AI that learns faster. Link for more info - https://lnkd.in/g78E8Qm5 #Meta #ScaleAI #TechTrends

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I was glad to contribute to the National Security Institute (NSI)’s response to America’s AI Action Plan. The real test isn’t invention, it’s deployment. " Today, we face a different challenge. We’re no longer the upstart we’re the incumbent. Our legacy systems and built-out infrastructure make it harder to absorb new technologies quickly. In contrast, China though behind in foundational AI can scale deployment across society through a top-down model with fewer constraints." Read the full piece: https://lnkd.in/dyjQ6j6s #AI #NationalSecurity #NSI

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Wharton's This Week in Business podcast with Dan Loney interviewed me about the Blockchain and Digital Asset Project's recently-released Stabelcoin Toolkit, and why it's important to better understand stablecoin developments. https://lnkd.in/eeHc9aSH The Toolkit itself is available at: https://lnkd.in/ephxiBm7

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High-quality hardware debt has performed better than tech peers, particularly as concerns regarding AI disruption and rising debt to support capital expenditures have rattled credit confidence of their software and hyperscaler brethren. As direct beneficiaries of AI spending, we envision the relative stability of hardware issuers will remain a theme in 2026. Improving balance sheets, supported by rising free cash flow appear to be reflected in stable-to-improving ratings profiles.

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Keith Teare breaks AI into three categories — and the distinction matters more than most people realize. 1. Additive AI: supplements existing human tasks. Lawyers using Harvey, accountants using copilots. This is where most enterprise adoption lives today. 2. AI-first platforms: starts with AI, plugs into legacy tools. ChatGPT, Claude Code, Codex. The current state of the art. 3. AI-only: fully emergent systems where AI operates autonomously. Moltbook (the AI agent social network Meta just acquired) is an early example. Most of the public only experiences category 1 — and judges all of AI by it. But category 3 is where the transformation actually lives. The gap between "AI as a tool" and "AI as an agent" is the gap between a calculator and a colleague. 🎬 Full issue: https://lnkd.in/gttscQFp

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NYC-based Dazl has raised $10 million in seed funding for its AI creation platform. Dazl provides an AI creation platform for building high-fidelity, production-ready applications. The company is focused on enabling a powerful partnership between humans and AI to drive the development process. The new company will be led by Assaf Sagy, TikTok's former Global Head of Gaming, who joins as CEO and Co-Founder. The round was led by 40RTY Fund, with participation from Wix and Wix co-founder Nadav Abrahami. The company will use the funds to expand its operations and development efforts. Congratulations to CEO Assaf Sagy and the Dazl team. FinSMEs: https://lnkd.in/ds7DTqmt #AI #DeveloperTools #ApplicationDevelopment #LowCode #NoCode #Funding #SeedRound #NYCTech

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Exploring the Upsides and Downsides of Venture Capital | Lanturn: Discover the benefits and drawbacks of venture capital investment. Learn how it can fuel growth or pose challenges for startups. #VentureCapital #StartupGrowth https://buff.ly/4AHFvcA

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👀 Web3 x AI is accelerating, aligning economics with intelligence. In our latest blog along the AI x Web3 Market Map series, my colleague Abdul Al Ali explores this innovation in the Sui Foundation ecosystem. What we found: Sui is quite supportive of its AI founders and projects. This alignment of investors, infrastructure and interfaces across the Sui ecosytem sustains durable adoption. Their team and social accounts often post partnerships with Sui AI builders, including Atoma Network (inference layer on Sui) that enables decentralized and scalable inference on Sui’s network. Abdul is active alongside Alex N. in convening the Sui community together in Chicago, recently speaking on a panel along other AI innovators from #TalusNetwork and #Lofi. Explore more on Web3 x AI on Sui below:

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**Why WeTransfer Co-founder is Building Another File Transfer Service** Nalden, co-founder of WeTransfer, is venturing into a familiar landscape with a new file transfer service that prioritizes user convenience by eliminating the need for login. This move highlights the evolving expectations of users for seamless digital experiences. At ElevenX Capital, we believe that innovation often stems from entrepreneurs who identify gaps in their previous successes. What trends do you see shaping the future of file sharing? #investing #innovation #venturecapital #entrepreneurship

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Sustained ~252–291 GiB/s of HBM memory throughput on H100s under decode load — essentially hitting the hardware roofline. This matters because HBM throughput, not FLOPs, is the real bottleneck in LLM inference. By keeping memory nearly fully saturated, I’ve unlocked far higher efficiency and throughput than standard engines. The result: 0.9–1.36M tokens/sec with ~0.1 ms first-token latency  #AI #LLM #GPURouter #H100 #Inference #CostEfficiency #Innovation #DeepLearning #AIInfrastructure #HighPerformanceComputing NVIDIA AMD OpenAI Google Shilpa Kolhatkar Keith Strier a16z speedrun

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Found this interesting article "Do AI-enabled companies need fewer people?" by Laurie Voss within the Venture Capital topic on AI Colorado. AI-Native vs Traditional SaaS: AI-native startups operate with roughly 60% fewer people at $10M ARR (15-20 vs 50-70), generate 6x higher revenue per employee ($3.48M vs $580K), and raise 30% larger Series A rounds ($51.9M vs $39.9M). Layoffs Continue: Over 126,000 workers were cut at US tech companies in 2025, with the pace carrying into 2026. Tech job growth has flatlined since 2023 in what the author calls another K-shaped graph. Interesting times ahead.

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