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Six months ago we started planning the busiest stretch IgniteGTM has ever run. Six events between September and December, each one chosen to build on the last.

Here's how they connect.

It starts September 17 in South San Francisco with AI for Life Sciences. Biotech puts real weight on AI infrastructure. Genomic pipelines, drug discovery, and clinical data that can't leak and can't wait. The requirements here are specific: different workloads, different security constraints, different performance demands than general enterprise AI. Starting here sets up a question the rest of the fall answers: how infrastructure changes to fit the workload.

A week later, on September 24, we're in New York for the AI for Financial Services Summit. Financial services runs into its own version of the problem: latency that costs money, compliance that can't bend, and data that lives under heavy regulation. Same theme as Life Sciences, different constraints, two industries showing why one-size-fits-all infrastructure doesn't hold up.

Next is our first-ever NeoCloud Summit in San Francisco on October 8. Neoclouds are building GPU-dense, AI-native infrastructure as an alternative to the hyperscalers. Over the past two years that movement has grown in pieces: individual raises, new data centers, founders with a thesis. The Summit puts those founders and operators in one room to trade notes on where the industry goes next.

On October 13 the OCP Networking Party is on our home turf in San Jose, the middle and the heart of Silicon Valley, with Supermicro and AMD, sitting alongside OCP Global Summit and the nearly 11,000 people building the open hardware stack. Then we take it on the road: SuperCompute 26 in Chicago on November 17, the year's biggest HPC and AI gathering (SC24 drew more than 18,000), where the hardware teams, hyperscalers, researchers, and operators are all in one place. Both parties sit inside those rooms, so we tap the full crowd of each conference.

All of it feeds AI INFRA SUMMIT 6 on December 3 in San Francisco. What we learn from September to December, what life sciences needs, what financial services demands, what the neoclouds are betting on, and what the hardware ecosystem is shipping, goes into the AIS6 agenda. It's the flagship, on a bigger stage, pulling the full infrastructure stack into one room.

We close the year with Enterprise AI Day on December 16 at Santana Row in San Jose. This one measures whether the rest of it is working in production. Leaders running real AI at scale, with real budgets and real consequences. Life Sciences and Financial Services open the year's questions, AIS6 puts them on the main stage, and Enterprise AI Day checks the results inside the companies that have to make the economics work.

The sequence tracks how the industry is actually moving: specialized workloads (Life Sciences, Financial Services), the infrastructure layer built to serve them (NeoCloud), the broader ecosystem shipping it (OCP, SuperCompute), the full stack convening (AIS6), and the enterprises putting it into production (Enterprise AI Day). Every venue and speaker was picked to move that sequence forward.

We've been heads down building this for months. It's the most ambitious run we've attempted, and we're just getting started.

Whether you're building this infrastructure, buying it, or investing in it, there's a room for you.

See you out there.

Bay Area Startups Collectively Secured $16B+ in August MTD

It doesn't feel like summer - funding activity is not slowing down. There were eleven megadeals for $4.9B, 93% of the week's $5.3B total The week's megadeals included multiple AI infrastructure startups – Groq (neocloud), Etched (high speed inferencing) and Velaura AI (fka Auradine – pivoting from building high-efficiency Bitcoin mining hardware to ultra low power AI compute).

Early this year, Groq was the target of a reverse acquihire as NVIDIA hired their CEO and top talent and licensed Groq's technology, leaving the company to re-invent itself. Groq pivoted to being a neocloud provider using NVIDIA hardware, and has $1B to begin scaling from 54 to 200+ megawatts to support inferencing.

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Early Stage:

• Groq closed a $350M Series A, operates the inference cloud infrastructure that runs real-time AI.

• Velaura AI (fka Auradine) closed a $110M Series A, develops ultra-low-power compute technologies that enable the next generation of AI infrastructure.

• Thunder Compute closed a $13M Series A, a virtualized GPU cloud platform for building AI/ML.

• idler closed a $9M Seed, building the evals and environments that frontier labs use to measure and train their models.

• Synthefy inc closed a $6.5M Seed, building multi-modal generative AI models for time series data.

Growth Stage:

• Etched closed a $700M Series D, builds frontier inference clusters designed to make AI inference dramatically faster and cheaper.

• Higgsfield AI closed a $400M Series B, an AI-native multimedia content creation platform for creators, marketers, brands, agencies, and studios.

• Wispr Flow closed a $280M Series B, smart voice-to-text that helps you work 4x faster in any app.

• Muon Space closed a $250M Series C, designing, building, and operating high-performance satellite constellations for defense, civil, and commercial customers.

• Fuse Energy Technologies closed a $100M Series B, a nuclear fusion company dedicated to accelerating the world's transition to fusion energy.

AI applications are getting more demanding. Reasoning models need to generate longer outputs, agents are chaining together multiple calls, and interactive applications cannot afford to leave users waiting while inference catches up.

For builders, inference speed is starting to influence what products can actually be built and how people interact with them.

That was the focus at Cerebras Supernova.

What it is
Supernova is Cerebras’ flagship event, bringing together developers, founders, researchers, enterprise AI leaders, and infrastructure partners working on the next generation of AI applications and compute.

Why this, why now?
The event put fast inference into practical context. Cerebras showcased live production AI applications alongside technical talks, customer deployments, product updates, and a CEO keynote from Andrew Feldman.

The conversation matters because faster inference changes the experience at the application layer. Reasoning can happen closer to real time. Agents can complete more steps without creating long waits. Developers can start designing around responsiveness that previously was difficult to achieve at scale.

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Logan Lemery
Head of Content // Team Ignite

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