Latest Interviews

Arm, PsiQuantum, Intel, NextSilicon, Lightspeed: Moore’s Law vs AI’s Appetite The Compute Collision

Jean-Anne Philippe, Will Abbey, Elad, Pete Chabot

Intel's Jean-Luc Philippe, ARM's Will Abbey, and experts from Next Silicon and PsiQuantum convened to analyze the shift from traditional transistor scaling toward software-hardware co-design and heterogeneous computing architectures. The discussion highlighted critical advancements in quantum error correction and RISC-V integration while emphasizing that future AI infrastructure requires billions in capital to support hybrid edge-cloud systems and post-quantum cryptography. Industry leaders concluded that the end of Moore's Law necessitates fundamental architectural innovation over brute-force scaling, with a consensus that value is forged through massive, power-intensive supercomputing deployments rather than isolated component optimization.

WEKA, Intel, Graphite, InstaDeep & AWS: Scaling Without Crashing. AI Framework for Enterprise Growth

Eduardo, Mary, Damien, Val, Karim, Murray, Fula Ousmane

The event details the industry shift from experimental AI in 2023 to the scaling of autonomous agents in 2024-2025, driven by urgent economic pressures that are forcing a 75% reduction in cached input pricing. Industry leaders outline a strategic framework prioritizing top-level governance and data transparency to mitigate security risks while navigating a market where compute cost competitiveness will determine the survival of AGI-era businesses. Specific sector applications, ranging from diagnostic health agents to AI-driven code review systems, illustrate how organizations must integrate these tools as central transformation enablers rather than isolated initiatives.

A Fireside Chat with Nicolas Dessaigne (YC-Combinator) & Jean de la Rochebrochard (Kima Ventures)

Nicolas Dessaigne, Jean de la Rochebrochard, Nicolas Tassin

Kima Ventures' Jean de la Rochebrard and Y Combinator partner Nicolas Tassin discussed their investment strategies, emphasizing that AI has shifted from a distinct category to a de facto standard comparable to cloud computing. The investors outlined distinct regional dynamics, noting that US founders leverage superior risk tolerance and speed while European entrepreneurs must overcome cultural humility to access the capital pools required for billion-dollar growth. They concluded that future market leaders will likely emerge in vertical applications within "boring" industries rather than horizontal platforms, provided founders prioritize authentic execution over hype and build defensible data moats.

Lambda, Hugging Face, SemiAnalysis: The Neural Network Is the Computer

The discussion outlines a fundamental shift from traditional programming to "neural software," where generative models act as dynamic interfaces that execute user intent through natural language rather than static code. Key developments in video, audio, and multimodal integration are enabling consistent, real-time content creation while replacing fixed graphical user interfaces with adaptive, semantic environments. This evolution promises to eliminate conventional coding barriers by 2030, though it simultaneously introduces complex challenges regarding state retention and the societal implications of AI-driven interactions.

OVH Cloud, ClickHouse, Neon, Aiven, Airbyte & Commit: Open Software Infrastructure 2.0

Abel, German, Oskari, Heike, Michel, Alexei, Francois Beaufort

Executives from Aiven, Neon, Airbyte, ClickHouse, and OVHcloud converged to discuss how open-source data platforms are securing $10 billion in combined valuations while addressing enterprise needs for data sovereignty and interoperability. The panel detailed how the AI boom is driving a shift from human-led development to agentic provisioning, creating demand for storage-centric architectures that support short-lived, unstructured data workloads. Looking ahead, industry leaders predict a five-year trajectory where hundreds of millions of citizen developers leverage commoditized AI to compress development cycles, necessitating hybrid infrastructure strategies that balance local model execution with scalable cloud data management.

Alix, SAP, Daytona, Feedly, Prosus & Handelsblatt: The Future Agentic AI & Autonomous Workflows

Alix, Edwin Kodabachan, Paul Van der Boor, Alexander Maisor, Emmanuel Casimates, Ivan Bourazin

Experts at a recent industry gathering defined Agentic AI as a shift from simple request-response models to autonomous systems capable of multi-step planning, emphasizing that security and governance remain critical barriers requiring strict human oversight. SAP and other leaders proposed frameworks like "agentic quality controls" and locally hosted environments to manage agent identities and comply with regulations, while anticipating a workforce evolution where humans supervise "digital teammates" rather than performing manual tasks. Despite concerns over the hype cycle, participants agreed that organizations with mature data and processes will soon leverage these tools to exponentially increase productivity, provided they implement robust guardrails to direct this technological capability toward tangible business value.

Fractile AI, Rogo, Scribble VC, San Francisco Compute: The AI Trillion-Dollar Opportunity

Eric Manisse, Elizabeth Weill, Walter Goodwin, John Willett

San Francisco Compute CEO Eric Manisse, Scribble Ventures' Elizabeth Weill, and founders Walter Goodwin and John Willett convened to analyze strategies for scaling AI infrastructure, hardware, and enterprise solutions amidst rapid technological evolution. The panel detailed critical operational frameworks, including balancing hardware development timelines with software agility, mitigating hallucination risks in financial applications, and proactively shaping export control regulations rather than merely complying with them. Experts concluded that long-term success in this sector relies on specialized human expertise for deep tech, the creation of durable data moats, and a shift toward treating global compute as a utility to drive the next industrial revolution.

Data Overload into Actionable Gold: AI’s Rescue Mission for Enterprises Tackling Unstructured Data

Nassime Reyholt, Victoria, Samuel Cohen, Harry Folliter, Robert, Alonzo Garcia

Representatives from Doctolib, Databricks, Alorica, Fergen, and Blackbox AI convened to discuss the critical transition from structured legacy systems to leveraging unstructured data for enterprise decision-making. The panel emphasized that successful AI deployment requires strict governance, real-time evaluation frameworks, and the use of synthetic data to ensure agents can reliably execute tasks without the 80% pilot failure rate common in the industry. By prioritizing data intelligence over model architecture, these leaders outlined a roadmap for moving from experimental playground agents to autonomous systems that self-correct in live production environments.

Clarifai, Oracle, TensorWave, Cherry & Vaire: Sovereign AI in a Borderless Tech World

Nadia, Rodolfo, Don Barnetson, Peter Tomasik, Hakim Lumi, Matt Zehler

Panelists including Peter Tomasik, Hakim Lumi, and Don Barnetson established that physical infrastructure and talent are the primary prerequisites for Sovereign AI, warning that Europe faces a competitive deficit while the Middle East leverages energy wealth to emerge as a third global contender. The discourse highlighted significant risks regarding stranded hardware assets due to rapid obsolescence and emphasized that current enterprise adoption remains driven by pragmatic cost and performance rather than theoretical sovereignty. Strategic recommendations from the session urge diverse silicon sourcing, cohesive national policy frameworks, and a shift toward "security by design" to address the complex vulnerabilities inherent in large language model deployment.

Antoine Bordes (Helsing) & Gaël Varoquaux (INRIA): Where Public Research Meets Innovation

Antoine Bordes, Gaël Varoquaux, Rob, Isabelle Riel, Joëlle Barral

At the expanded RAISE conference, experts from institutions including INRIA, Google DeepMind, and Helsing discussed the critical friction between public research and private innovation in the European AI ecosystem. Panelists outlined a 2035 vision where generative AI transforms healthcare and defense through rapid commercialization, while warning that bureaucratic bottlenecks and a "one-way door" for talent are stifling Europe's competitive growth. The discussion emphasized a need to shift from funding isolated technologies to building scalable products that bridge the gap between foundational academic discovery and urgent market application.

Ori, PolyAI, Cresta, Writer & Fireworks AI: Is Enterprise Defensibility Possible in an AI's World?

Mike Butcher, May Habib, Russell Banzon, Nicola, Lynn, Amalia, Mahdi

Industry leaders convened to declare that traditional SaaS and seat-based pricing models are collapsing as enterprises pivot to agentic AI, where value is derived from direct outcomes and autonomous revenue generation rather than software access. The consensus emphasizes that architectural advantages are temporary, with true defensibility emerging only through proprietary data flywheels and comprehensive organizational adoption strategies that integrate AI into core workflows. Looking toward 2025, the panel predicts a surge in production-level deployments driven by a tenfold reduction in infrastructure costs, forcing companies to prioritize offensive scaling over defensive postures to survive rapid market disruption.

AI Visionaries Panel: Collaboration is All You Need! Open Source as AI's Great Accelerator

Olivier, Ankit, Matt, Mitchell, Jim, Jonathan

Leaders from Nvidia, Red Hat, Mozilla, and the Linux Foundation convened to analyze the symbiotic relationship between AI-driven investment strategies and the accelerating open-source ecosystem. The panel emphasized that while artificial intelligence boosts code velocity, the primary value in commercial open source now lies in community coordination and neutral standards that prevent market fragmentation. Key outcomes included the identification of a "reverse venture capital" approach for selecting durable projects and a consensus that human oversight remains critical for navigating the legal and architectural challenges of AGI development.

WEKA, Cohere, Nebius: Rewriting the Rules Agentic AI and the Race to Scale

Lauren Vaccarello, Cécile Robert-Michon, Dan Shtan, VYACHESLAV TYKHONOVSKYI, DAN GALPIN, Danila

At a panel on AI infrastructure and economics, Weka CMO Lauren Vaccarello, Cohere's Cécile Robert-Michon, and Nabeus CTO Dan Galpin discussed the necessity of rethinking legacy systems to support massive scale and agentic AI. The speakers emphasized that modern requirements prioritize intelligence per token over raw cost efficiency, citing Nabeus's software-first approach that achieves near-NVIDIA benchmark performance without virtualization and Cohere's converged storage solutions that deliver 20x faster checkpointing. They concluded that enterprises must abandon rigid long-term planning in favor of short-cycle agility to navigate the rapidly shifting demands of privacy, security, and compute resources in a commercial AI landscape.

RAISE Summit 2025: The AI Evolution Open Source, Fast Inference, and the Agentic Revolution

Tony Kim, Thomas Wolf, Rodrigo Liang, Arjun Kharpal

The AI sector is rapidly pivoting from foundational model development to agentic inference and production, driven by a strategic race for full-stack superiority where proprietary models currently retain a six-to-twelve-month performance lead. Enterprises are increasingly adopting open-source alternatives to ensure data privacy and cost efficiency, prompting a hardware shift focused on energy-efficient inference rather than raw training power. While consumer assistants and automated SaaS applications are expected to mature within two years, the industry faces critical bottlenecks regarding gigawatt-scale energy demands and the potential for data security breaches.

RAISE Panel 2025: The AGI Ascent Climbing Toward Superhuman Intelligence

Chase Lockmiller, Ilya, Peter, Sarah, Biang, Dario

A diverse panel of industry leaders and researchers analyzed the trajectory of artificial general intelligence, identifying energy scarcity and data quality as primary constraints while debating the future of centralized versus decentralized model architectures. Discussion highlighted a strategic shift toward massive test-time compute and human-AI collaboration, contrasting fears of cognitive atrophy with the potential for AI to automate outcome-based tasks while preserving process-driven human uniqueness. Experts concluded that regulatory frameworks must evolve alongside technological speed, with the consensus that AGI remains a moving target defined by the symbiotic relationship between human creativity and machine capabilities.