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.Fireworks AI is helping teams scale AI applications with a production platform for open-weight models, supporting world-class inference, fine-tuning, and enterprise AI workloads.

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15,485 görüntüleme • 8 gün önce •via X (Twitter)

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Announced at #MicrosoftBuild, a new partnership with Fireworks AI brings open weight models into Foundry. Developers can build next generation agent applications with more flexibility, strong performance, and enterprise grade governance to scale.
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Announced at #MicrosoftBuild, a new partnership with Fireworks AI brings open weight models into Foundry. Developers can build next generation agent applications with more flexibility, strong performance, and enterprise grade governance to scale.

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Accelerate AI innovation with ASI:Cloud, a high-performance cloud platform focusing on inference and AI workloads. Designed with performance, permissionless access, transparent pricing, and access to industry-leading LLMs, including ASI:One, the platform helps builders, developers, and enterprise teams move from idea to inference at scale. Ready to start your ASI infrastructure journey? Explore here:

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Stop stitching vendors together to run open models in production. Fireworks AI on Microsoft Foundry is GA. One endpoint. Enterprise SLAs. Zero setup. Build your next production workload with Fireworks AI on Foundry:
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Stop stitching vendors together to run open models in production. Fireworks AI on Microsoft Foundry is GA. One endpoint. Enterprise SLAs. Zero setup. Build your next production workload with Fireworks AI on Foundry:

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Fireworks AI is now live on EvoSkill v1.3.0! You can now use Fireworks AI directly with EvoSkill to run fast inference on open models as both the evolution harness backend and the LLM scorer. Alongside Claude API and OpenRouter, Fireworks AI is now a first-class provider in EvoSkill.

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2026: the year of explosive AI innovation. Fireworks AI Co-founder & CEO Lin Qiao speaks on how the massive expansion of customized inference and models is creating speed of light production to scale timelines.
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Masako Yamada, our Senior Director, Quantum Applications, presents on the quantum edge in enterprise AI: how to unlock real-world outcomes with hybrid QML fine-tuning and beyond.
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Most AI projects don't fail because models aren't good enough. They fail because inference economics don't scale. During #CXOSpice, Roman Chernin Nebius broke it down: ✅Closed models kill margins ✅Open models unlock control, if you can run them well ✅DataData only becomes a moat when inference is sustainable One team cut inference costs 26× in production. Only 30% of orgs use AI at scale, mostly in 1% of workloads. We're just getting started. Full conversation: #AI #Inference #TechInnovation Learn more about Nebius Token Factory:

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⚡️Today marks a big milestone for Nebius. We’re launching Nebius Token Factory, the evolution of Nebius AI Studio, built to make open-source AI production-grade. Token Factory transforms raw open models into governed, scalable systems with dedicated inference, sub-second latency, 99.9% uptime and zero-retention compliance. It’s where inference, post-training and governance converge, turning raw compute into reliable intelligence. Run AI inference at scale:
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⚡️Today marks a big milestone for Nebius. We’re launching Nebius Token Factory, the evolution of Nebius AI Studio, built to make open-source AI production-grade. Token Factory transforms raw open models into governed, scalable systems with dedicated inference, sub-second latency, 99.9% uptime and zero-retention compliance. It’s where inference, post-training and governance converge, turning raw compute into reliable intelligence. Run AI inference at scale:

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Our approach to AI infra is simple: build the most fungible and flexible fleet to meet the real world's needs across inference and training as Scott Guthrie shared with Alex Kantrowitz. And we are already doing it at scale today, as we power the biggest AI workloads like Copilot and ChatGPT, APIs that power 3P products & enterprise workloads and high scale training.
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Our approach to AI infra is simple: build the most fungible and flexible fleet to meet the real world's needs across inference and training as Scott Guthrie shared with Alex Kantrowitz. And we are already doing it at scale today, as we power the biggest AI workloads like Copilot and ChatGPT, APIs that power 3P products & enterprise workloads and high scale training.

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🔥 Launching the Fireworks AI Experimentation Platform (GA) and Build SDK (Beta)🔥 Top AI teams don't win by chance - they win by running 10X more experiments than competitors. Launching early, collecting feedback, tuning and selecting models, running offline evals, and validating impact with product metrics in a fast, continuous cycle is critical to build successful AI products. But, the need to manage complex infrastructure, wait for GPUs, reconcile differences between training and serving, and maintain reliability, slow AI teams down. Now, with the Firework’s experimentation platform, experimenting with open models just got a whole lot easier. With the help of our brand-new Python SDK (in beta), you can: → Stop waiting for GPUs, fine-tune and deploy 1000s of models on a single GPU deployment using Multi-LoRA → Programmatically run large-scale fine-tuning experiments → Scale evals with fully managed and autoscaling GPU deployments Check out our blog post to learn more and see a demo of running 125 experiments in 3 minutes on a single deployment:

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$SNOW doesn't need to know whether usage is coming from a human analyst or an AI agent but just needs more workloads running through the platform. Thats why Snowflake is trying to become the governed data layer where enterprise data, AI models, applications & workflows all come together.

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🎤 Overheard at #CES2026: AI compute is entering the yottascale era. William Myrhang shows how the AMD Helios AI Platform enables AI to scale by the rack and by the data center, not one server at a time. Designed for agentic and large-scale AI workloads, Helios makes yottascale compute practical, deployable, and sustainable. Zettaflops defined the early AI boom. Yottaflops will define what comes next. AMD is helping build the open foundation needed to support this unprecedented scale.

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OpenLedger is powering decentralized AI inference with DGrid AI, built on verifiable, onchain infrastructure. DGrid routes AI workloads across a distributed compute network, while OpenLedger anchors execution, attribution, and settlement fully onchain. Together, this enables AI systems that are auditable by design, transparent in cost and performance, and built for real Web3 applications.

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Fireworks AI is now available first-party in Microsoft Foundry, as part of a multi-year partnership, starting today in private preview. Enterprise AI has a speed problem. Most infrastructure can't keep up with how fast open models are moving. New architectures, fine-tuned weights, models that aren't on anyone's approved list yet. The usual answer was "manage your own serving infrastructure." That's a real cost. Fireworks runs the inference. Azure owns the governance. Your weights stay yours. Beyond custom weights, teams can also access the latest open models on day zero. No waiting for the marketplace to catch up. Serverless inference for prototyping, and a path to production that doesn't require re-architecting anything. Fireworks handles the serving layer. Azure handles the rest. Your boss handles the congratulations. Want in →
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Fireworks AI is now available first-party in Microsoft Foundry, as part of a multi-year partnership, starting today in private preview. Enterprise AI has a speed problem. Most infrastructure can't keep up with how fast open models are moving. New architectures, fine-tuned weights, models that aren't on anyone's approved list yet. The usual answer was "manage your own serving infrastructure." That's a real cost. Fireworks runs the inference. Azure owns the governance. Your weights stay yours. Beyond custom weights, teams can also access the latest open models on day zero. No waiting for the marketplace to catch up. Serverless inference for prototyping, and a path to production that doesn't require re-architecting anything. Fireworks handles the serving layer. Azure handles the rest. Your boss handles the congratulations. Want in →

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Top announcement from the Developer Keynote: Gemini Enterprise Agent Platform—a unified dev ecosystem for building production-ready AI agents and infrastructure. What's that mean? Access to 200+ models, including Gemini and Gemma 4 + open source models →

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ROCm 7 is here! ✅MI350 Series support ✅Enhanced usability and performance ✅Advanced AI features (distributed inference, large-scale training) ✅Easier enterprise AI deployment

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The future of compute is open. Vultr and AMD are delivering a collaborative, cloud-native ecosystem for next-gen enterprise applications. 📺 See why delivering AI at scale takes more than GPUs.
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The future of compute is open. Vultr and AMD are delivering a collaborative, cloud-native ecosystem for next-gen enterprise applications. 📺 See why delivering AI at scale takes more than GPUs.

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