The best proof isn’t what we say about RAISE. It’s what the people in the room say.  Founders, executives and partners from @Lovable, @Replit, and @IREN_Ltd share why RAISE has become the AI conference outside the US. If you’re planning where your brand shows up in 2027, start here:

NVIDIA-validated performance for production AI at scale. IREN is an NVIDIA Exemplar Cloud provider on NVIDIA GB300 NVL72 connected with NVIDIA Quantum-X800 InfiniBand networking for training workloads. This validates performance against NVIDIA reference architecture, meeting the threshold across all benchmarking recipes. For AI builders choosing where to run their most demanding workloads, IREN AI Cloud delivers verified performance, end-to-end control of the stack, and the scale to meet what AI demands next. Read more about IREN's NVIDIA Exemplar Cloud achievement:

An AI that writes code is useful. One that answers a funeral home’s overnight calls, negotiates with suppliers or helps businesses handle the grunt work nobody wants to touch is useful to a much larger market. That’s the shift behind Forbes’ inaugural Agentic 20 list. AI agents—systems that can take action on our behalf, not just spit out answers—are moving beyond software triage and calendar management into the messier work of the real economy. The list highlights 20 companies and projects making a dent in the agentic AI world. Read more: Illustration: Hansje van Halem for Forbes

In 2025, @Molly_J_Presley, Senior Vice President Global Marketing at Hammerspace, came to RAISE as an attendee. In 2026, Hammerspace had a booth by the front door. @Hammerspace_Inc builds the data layer that AI systems depend on, and RAISE brings the full AI ecosystem into one room: the builders, the infrastructure leaders and the buyers deciding what gets deployed. RAISE 2027 is now open for booking at the Palais des Congrès de Paris. The 2026 edition reached capacity five months early, and returning sponsors are already rebooking. Early confirmation secures priority access to the best locations.

Cyber will be one of the most defining domains for AI in the coming years, and a huge area of focus for most enterprises. AI is going to now create a whole new level of work for security dealing with the increase of vibe coded issues, agentic attacks, and even accidental agent swarms hunting for data. OpenAI + Hugging Face is just a preview of what’s to come. Security teams have often been the most strapped for resources teams in the enterprise, and now it’s only going to get more intense. AI agents of course become the solution to this problem as well, and we’ll see a range of new agentic products for protecting code, enterprise systems, mission critical infrastructure, and enterprise data. Huge opportunity here right now. And it’s going to be a booming market for cyber professionals that can effectively deploy agents for security purposes in the enterprise. Great time to be in security.

Today, we're open-sourcing the Personal Agent Consent & Trust Protocol (PACT), co-developed by @Instinct. We're also joining the Personal Agent Protocol working group by @Muse. Built on A2A and OAuth, PACT enables businesses to verify who a personal agent is acting for and what the customer has authorized it to do. Excited to shape the industry standard for how personal agents will interact with businesses.

AI is moving at the speed of software. Data centers are moving at the speed of real estate. That is why AI is so supply constrained. Demand for compute has grown exponentially. Almost nobody expected it to rise the way it has. But every part of the supply chain that delivers compute is a multi-year physical bet. Start with chips. A leading-edge fab costs $40 to $50 billion and takes about 5 years to build. Only a few companies in the world know how to build one, and even they can't build a dozen at once. So by the time a new fab opens, demand has already outgrown it. Then we need data centers. Even with a good builder, going from raw land and permits to a 50-megawatt data center takes about 18 months. And each part of the supply chain has its own supply chain. The building itself goes up fairly quickly. Turning it into a high-powered hotel for compute takes electricians, cooling, chillers, generators and electrical transmission switches, and many of those have long lead-times right now. Under all of it sits a grid built on technology from the 1940s and '50s. Builders are even buying up old paper mills and factories in the Rust Belt, because those sites already have the power and the permits. 5 years from now, the industry will still be racing to build enough compute to meet demand.

Everyone is sick of generic AI, including us. Gamma was the first AI presentation platform to reach real scale. But now that AI tools are everywhere, everything looks the same. Earlier this summer, we came to an uncomfortable conclusion: without a step change in visual variety, Gamma’s output would look and feel too similar to all the other AI tools. The entire point of a presentation is to help someone "get" your idea, to see it as unique and do something with it. We started over. Today we're shipping Gamma 5, the biggest product overhaul in our company's history. We rebuilt Gamma to create presentations that actually look like you and your brand. Your teams can design anything they dream up, following your brand's aesthetic or something entirely new, with every frontier and image model under the hood. And the same goes for your docs, social assets, and graphics. We revamped our agent, design tools, editing, import, export, connectors, and more. Get your ideas out there.

Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.

In case you missed it, here's what shipped last week: - Build with new models: GPT-6.1 Sol and Claude Sonnet 5.5 - Ask agent to use Jev via AI integration - Updated UI in Settings - Enterprise: Set advanced Workplace settings with company-wide rules or controlled exceptions. More at our changelog:

Announcing Together Link! Run frontier open models in your favorite coding harness. Track your spending and let our Auto router pick the model for you: low-cost models for quick fixes, more capable models for harder tasks.

We're expanding our approach to content provenance to include text in response to EU regulatory requirements, while recognizing the significant limitations of current text watermarking technology. Our tools already help verify whether an image or audio file was created with our models. This work builds on those efforts to help people better understand when content may have been generated or edited with an OpenAI model. In the EU, we’ll start watermarking eligible text from ChatGPT and Codex over the coming weeks to comply with the EU AI Act. Customers using our API can turn on text watermarking for select models worldwide today.

Introducing Dreaming: Across sessions, Devin builds a memory graph of how you like to work At night Devin self-improves its memory to remove stale records and discover latent information We are creating an OSS standard called Agent Memory Repo:

"What would you do with an infinite army of software engineers?" That's how @ScottWu46, CEO of @Cognition, opened his keynote at RAISE Summit 2026. Not a thought experiment about the future. A question about right now. From November 2025 to April 2026, Cognition shipped 10x more software with only a 40% increase in headcount. Devon, their AI software engineer, went from writing 13% of their code in December 2025 to over 90% by April 2026, and most of its work now starts without a human prompting it at all. His answer to the obvious follow-up, "what happens to human engineers?", wasn't needing fewer of them. It was that every engineer becomes 10x more productive, while the backlog of things worth building is 10x bigger than anyone's ever been staffed for. The DMV that doesn't work. The medical portal nobody enjoys using. That's not a shortage of ambition. It's a shortage of engineers, and that constraint just started loosening. He closed the keynote the same way he opened it. By the end, the question isn't rhetorical anymore. What would you do with an infinite army of software engineers?

Projects finishing ahead of schedule. Engineers self-funding work that never made the business case before. A consistent 20% net productivity gain across the board. @marcoargenti, CIO of @GoldmanSachs, doesn't throw numbers around loosely. So when he shared those figures at RAISE Summit, in conversation with @TomMackenzieTV (@business), the room paid attention. The shift he described: engineers used to start from a napkin sketch. Now they vibe-code a rough version first. Not production-ready, but close enough to show a client exactly what they're getting. Then the real work begins, swapping paper walls for steel, hardening the architecture underneath. The productivity gains are real. But Argenti was equally clear about where the line stays human. Final decisions don't get outsourced. That's judgment, and he hasn't seen evidence yet that AI judgment beats human judgment when it counts. One of the world's most influential financial institutions is rethinking how work gets done. The results are already showing up in the numbers. Watch the full conversation:

A young snake sheds its skin every two to four weeks. @thisisgrantlee , Co-Founder & CEO of @GammaApp, used that image at RAISE Summit to describe what building in AI actually feels like right now. Not a single launch. Not a pivot. A constant cycle of invention to reinvention, shedding and rebuilding faster than most companies can keep up. His thesis: models are the steel of this generation. But steel was never the moat. It's general-purpose, it's commoditising, and open source is closing the gap fast. The edge belongs to whoever turns that raw material into something purpose-built. Gamma has lived that. $100M ARR. 70 million users. A team of 50 people. And yesterday, an acquisition of Accel-backed design startup Lica World, building out their own design research lab as the product expands beyond presentations into the full visual stack. On the human side, Grant was clear: the best salespeople don't win on efficiency. They win on relationships. The goal was never to replace that, it was to clear everything else out of the way. The snake keeps shedding. That's the point. Full conversation on our YouTube channel: