Murat Bicer

We’re excited to share that our fund has invested in Cerebras Systems. Artificial intelligence is entering a phase where infrastructure matters as much as algorithms. As AI adoption accelerates across industries, the demand for scalable compute to train and run increasingly complex models is growing exponentially. Cerebras is building technology designed specifically for this new era of AI. Their breakthrough approach centers on wafer-scale computing — a radically different architecture built to handle large-scale AI workloads with greater efficiency and speed. Instead of stitching together thousands of smaller processors, Cerebras developed a single, massive AI processor designed to simplify how large models are trained and deployed. What impressed us most about Cerebras is their bold rethinking of AI compute architecture and their focus on solving one of the most important challenges in the AI ecosystem: enabling organizations to run large AI models faster and at scale. As AI moves from experimentation to mission-critical enterprise deployment, the infrastructure powering these systems will become increasingly important. We believe Cerebras is well positioned to play a meaningful role in shaping that future. We’re excited to support the team as they continue to push the boundaries of AI infrastructure. #AI #ArtificialIntelligence #DeepTech #Infrastructure #Investing

26

3 Comments

Trying something new this week - a studio industry roundup with my take on what matters. The studio model is no longer an experiment being run in a handful of places. It is infrastructure being built across geographies, sectors, and institutional types. 5️⃣ stories from the past seven days:  1️⃣ OSS Ventures hit a EUR 40M first close on a EUR 75M follow-on fund -- capital raised specifically to back the 30 companies their studio created since 2019. The "build then fund" lifecycle is maturing. B'More Venture Studio with a similar thesis: studio operations first, then dedicated capital to scale what's working.  2️⃣ Delta40 raised $20M from 54 investors across 13 countries to launch Africa's first integrated venture studio and fund. The LP base is almost entirely DFIs and foundations. Impact capital is discovering the studio model as a deployment vehicle, something I seeing across geographies (conversations with Michael Bob Starr and Damias McDonald this week alone) 3️⃣ Start Holdings launched Start.vc out of NYC and Barcelona after a $200M EV infrastructure exit. Another operator-turned-studio-founder. This is the pattern we see quite often in our work at 9point8 -- experienced operators like Jason Goldsmith who've built and exited deciding the studio model is how they want to build next.  4️⃣ UBC HATCH admitted 10 new deep-tech spinouts for Winter 2026 -- mostly climate tech. University venture builders are quietly becoming one of the fastest-growing segments. Follow Evan Allen and Jaimie Testai to keep track of its rapid evolution.  5️⃣ The INVEST Act is advancing through the Senate. If passed, it expands qualifying VC fund size from $10M to $50M and loosens general solicitation rules for accelerator and university events. For studio-funds -- and for folks in the The Venture Studio Forum community tracking policy -- this could be the most significant capital formation legislation since the JOBS Act. If this roundup format is useful, I'll keep it going. What other noteworthy news hit your desk this week, and what stood out to you?

13

1 Comment

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

5

🦄 $150M to improve tutoring and education globally. Preply just announced a new round, putting the company on a clear trajectory to become an iconic global marketplace. In a world obsessed with fast wins and volatile growth, some companies quietly beat their goals year after year — for more than 6 years in this case (as long as we’ve at Acurio Ventures been partners). A few learnings from this journey, relevant for founders and investors: Pick a growing market with an unsolved problem. 2 out of 8 billion people globally are learning a second language. Despite many options, outcomes are still poor. Our original thesis was simple: if you build the reference platform, everyone who wants to learn will eventually come to you. Category leadership matters. When we backed Kirill Bigai and Dmytro Voloshyn back in 2019 (together with Rob Kniaz), there were dozens of similar startups. Small details showed Preply had already built a superior tutor base and a scalable growth engine. Build a product customers love. Speaking a language and teaching it are very different things. Preply transformed the learning experience by combining a motivated base of +100,000 tutors with tools that actually drive outcomes. Never stop experimenting. Few companies maintain a strong experimentation culture as they scale. Preply’s DNA reminded me of Booking.com — enabling them to execute 10x better than most marketplaces. Great companies turn every change into an opportunity. From riding the post-COVID shift to online learning, to betting early and heavily on AI as Dmytro Voloshyn has excelled at. What once sounded like sci-fi is now reality. Great companies become talent magnets A company maturity can't be addressed only by looking at the revenue, profit or product. I like to see how much better they become at attracting talent and retaining it. Proud that Acurio Ventures made this possible and the WestCap team saw things as bullish as we do and are now supporting the next phase of Preply’s journey. Huge congratulations to the entire Preply team!!

33

4 Comments

CRV Security: Request for Startups I never know if this actually works for our friends over at YC but figured we'd try. Here's what we want to fund in 2026! 1. Golden Artifacts: Think Chainguard but more broad. Artifact attestation exists for open source. Almost nothing exists for internal software — especially the vibe-coded tooling now running in production. We want the company building cryptographic proof of secure software delivered from secure artifacts: who built it, how, and whether it was reviewed. If more things are being yeeted into the world via Claude Code (myself included), this feels like an issue. 2. MCP & Agentic Security: Agents are getting real credentials and taking real actions. The security posture of most orgs around this is basically zero. That changes fast. You'd never give an employee hardcoded API keys or write access to your email without supervision/trust. Why give it to agents? 3. AI Governance: Boards are asking CISOs to account for AI risk. CISOs have no good answer other than "Palo has a module" 4. Next-Gen Endpoint: CrowdStrike was built for a world of static binaries and human operators. AI workloads, cloud-native infra, and AI-assisted attackers need a new architecture. The category is ready to be reinvented. 5. Networking in the AI Era: Zero trust was designed for humans. What does network security look like when the entity requesting access is an agent? Nobody's really solved this. 6. Email Security + Next-Gen Phishing: LLMs have made spear phishing infinitely scalable. I've never truly understood why Abnormal and KnowBe4 aren't one company. Maybe this time it's different. 7. Frontier Security Lab: We'd back a credible, well-staffed lab focused entirely on red-teaming models and setting the evidentiary standard the industry needs as LLM built apps become the norm. 8. Dependency Security: That Actually Remediates Malicious and vulnerable dependencies are a top attack vector. The tooling is mostly noise — scanners that don't close the loop. The winner here ships fixes, not just alerts. 9. Critical Infrastructure Cyber: Data centers, satellites, power grids, undersea cables. The physical backbone of the internet is increasingly exposed and wildly under-defended. We have data centers in space, for God's sake. Surely we need better cyber for critical infrastructure? 10. PAM for the Modern Era Legacy: PAM was built for static roles, human users, on-prem directories. Cyberark was founded in 1999.....Agents, ephemeral workloads, and cloud-native infra have broken all of those assumptions. Is anyone rebuilding this from scratch? If you're building in any of these areas — or something we haven't thought of — reach out. james@crv.com

451

49 Comments

Thrilled for OVNI Capital to be backing RIFT in a pre-seed round led by AlleyCorp (Luc Ryan-Schreiber). Rift is building the first real-time aerial intelligence network, a new layer of infrastructure for persistent, on-demand visibility where it matters most. This funding will scale production of their autonomous stations, accelerate deployment in high-stakes environments, and expand the team leading the next phase. 🗞️ Explore the full story: - StartupMafia: https://lnkd.in/dARrg25N - BFM Business (FR): https://lnkd.in/eADSUsn7 - Les Échos (FR): https://lnkd.in/eFG3zAy5 👨‍🚀 Join the mission → https://lnkd.in/erm_SrTG

95

2 Comments

Two weeks ago on Swimming with Allocators, we sat down with David Clark, CIO at VenCap, to talk about what decades of venture data can teach allocators. One takeaway that stood out: discounts don’t matter as much as people think in venture secondaries. Because venture is such a power-law asset class, outcomes are driven by exposure to a few massive winners. Whether a stake is bought at a small discount, or even a premium, often matters far less than the quality of the underlying company and its upside. Great conversation on venture returns, manager selection, and the nuances of how allocators should think about secondary investments. 👇 Link in the comments.

26

2 Comments