Iván de Prado

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Iván de Prado

Iván de Prado

@ivanprado

Head of AI at @magnific

Segovia, Spain Katılım Şubat 2008
1.3K Takip Edilen2K Takipçiler
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Iván de Prado
Iván de Prado@ivanprado·
🚀Excited to announce F Lite: a new open-source text-to-image model by @freepik and @FAL! The first at this scale that’s both open-source and trained exclusively on licensed, high-quality data.🧵
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Magnific
Magnific@magnific·
On the night of San Juan, we jump over the fire. We talk, we drink, we kiss, until it's just embers In this story, the creators went the other way. Back to the moment before everything turns gray. Even in the ashes, there's still warmth. And you will always remember how the fire started Candela is made by people, using Magnific. From the music, to the characters, to the story This is created by the team at Magnific Studios
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Magnific
Magnific@magnific·
Candela is coming with us to Cannes Lions Made by three creatives, entirely in Magnific One connected workflow: → Consistent characters across every scene → 2,591 generations inside Spaces → MCP agents keeping context under control Exclusive premiere on June 22
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Carlos Riquelme
Carlos Riquelme@rikelhood·
MAI-Thinking-1: el primer modelo fundacional de Microsoft SuperIntelligence (MSI). El equipo de MSI Madrid ha participado activamente en su diseño y entrenamiento! Y buscamos más AI engineers excepcionales para crear los próximos modelos de Microsoft desde España! DM para+info 🚀
Mustafa Suleyman@mustafasuleyman

Super excited to announce seven new world-class MAI models today. They represent what we consider a new era in AI designed to keep you in control and on the frontier. First is our text foundation model, MAI-Thinking-1, exceptionally strong on reasoning and SWE tasks. - It’s a 35B active parameter MoE with a 256K context window. Independent human raters on Surge prefer it for overall quality in blind side-by-sides versus Sonnet 4.6, and it’s achieved 97% on AIME 2025, the key measure of its general-purpose reasoning abilities. - It's at 53% on SWE Bench Pro, placing it right alongside Opus 4.6 on one of the toughest coding benchmarks. - And since we co-designed our models with our own silicon, MAI-Thinking-1 is optimized on our MAIA 200 chip. Benchmarking head-to-head against the GB200, we see 30% better performance per dollar as well as a 1.4x performance-per-watt gain when running our MAI models on the MAIA 200 end-to-end. Next is MAI-Image-2.5 and its Flash variant. Two super strong models now at #2 on the leaderboards, surpassing the score of Nano Banana 2 on image editing. Last for now is MAI-Code-1-Flash, our new inference efficient coding model, especially tuned for VS Code and GitHub Copilot CLI. - Code-1-Flash achieves 51% on SWE Bench Pro, despite having just 5B parameters, putting it closer to Haiku in size but cheaper in cost. All of this is the foundation for Microsoft Frontier Tuning. It lets you customize our models to create custom, company-specific agents that only you control. You can make our model, your model. Your data. Your agents. Your moat. Early adopters are already seeing a difference. When we tuned our models for McKinsey’s tasks, MAI delivered the highest win rate, outperforming GPT-5.5 on quality, while being 10x lower on cost. Also really excited to be collaborating with the amazing team at Mayo Clinic to jointly train a new frontier AI model for healthcare. Our announcements today mark another milestone on the road to humanist superintelligence. You can learn more and about our other new models in our latest blog: microsoft.ai/news/building-…

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elie
elie@eliebakouch·
microsoft MAI tech report is a gold mine, one of the most transparent for a model at this scale. this model uses zero synthetic data or distillation from previous models. this means reasoning, agentic behavior, tool use are all learned fully during post-training with no cold start. bold choice that makes it harder and requires more iterations to reach sota, but you get FULL control over your model series and it proves they are serious about being a frontier lab. the tech report is insanely detailed and precise about numbers. to give an example, they give the exact MFU across all the iterations of the model, with the exact changes etc. they also share the full scaling ladder recipe, to my knowledge this is the first time i've seen this in a tech report at this scale let's look at all of this in this likely very long thread 🧵
elie tweet media
Mustafa Suleyman@mustafasuleyman

Super excited to announce seven new world-class MAI models today. They represent what we consider a new era in AI designed to keep you in control and on the frontier. First is our text foundation model, MAI-Thinking-1, exceptionally strong on reasoning and SWE tasks. - It’s a 35B active parameter MoE with a 256K context window. Independent human raters on Surge prefer it for overall quality in blind side-by-sides versus Sonnet 4.6, and it’s achieved 97% on AIME 2025, the key measure of its general-purpose reasoning abilities. - It's at 53% on SWE Bench Pro, placing it right alongside Opus 4.6 on one of the toughest coding benchmarks. - And since we co-designed our models with our own silicon, MAI-Thinking-1 is optimized on our MAIA 200 chip. Benchmarking head-to-head against the GB200, we see 30% better performance per dollar as well as a 1.4x performance-per-watt gain when running our MAI models on the MAIA 200 end-to-end. Next is MAI-Image-2.5 and its Flash variant. Two super strong models now at #2 on the leaderboards, surpassing the score of Nano Banana 2 on image editing. Last for now is MAI-Code-1-Flash, our new inference efficient coding model, especially tuned for VS Code and GitHub Copilot CLI. - Code-1-Flash achieves 51% on SWE Bench Pro, despite having just 5B parameters, putting it closer to Haiku in size but cheaper in cost. All of this is the foundation for Microsoft Frontier Tuning. It lets you customize our models to create custom, company-specific agents that only you control. You can make our model, your model. Your data. Your agents. Your moat. Early adopters are already seeing a difference. When we tuned our models for McKinsey’s tasks, MAI delivered the highest win rate, outperforming GPT-5.5 on quality, while being 10x lower on cost. Also really excited to be collaborating with the amazing team at Mayo Clinic to jointly train a new frontier AI model for healthcare. Our announcements today mark another milestone on the road to humanist superintelligence. You can learn more and about our other new models in our latest blog: microsoft.ai/news/building-…

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madarbro
madarbro@madarbro·
@javilopen getting glitch after video precision upscaling
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Upscale Conf
Upscale Conf@upscaleconf·
Where AI meets creativity. For the fourth time Upscale Conf returns to San Francisco, June 3–4 Two days to unpack what AI is changing about creative work Talks. Hands-on workshops. The space where the industry connects Grab your ticket ⬇️
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Magnific
Magnific@magnific·
Freepik is now Magnific One platform to rewrite the rules of creativity
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javi santana
javi santana@javisantana·
Es este de los mejores artículos técnicos que he leído en meses? No por lo avanzado, que también, pero por lo práctico, útil, cercano y por el pragmatismo que transmite especialmente estos meses que la mayoría de contenido es vacío. Si Mercadona estuviese en SF estaríamos dando palmas con las orejas gemba.es/p/como-constru…
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Magnific
Magnific@magnific·
Seedance 2.0 is NOW on Freepik, the world's biggest AI creative suite Business and Enterprise accounts can start generating today, individual users are next Verification is required for Business. Available in 150+ countries, except US and some exceptions Get access today 💥
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Magnific
Magnific@magnific·
Your next 3D photo shoot will be done with AI 3D Scenes generates full environments from any image → Place your objects in the scene → Move the camera like a real shoot → Consistent lightning and detail across every angle Available now on Freepik 👇
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Magnific
Magnific@magnific·
Magnific Precision, now available in Video Upscaler → Up to 4K with every texture preserved → Get a 12-frame preview before generating the full video → Full control over sharpness, grain, and strength → Boost FPS for smoother motion Now live on Freepik 👇
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Google Research
Google Research@GoogleResearch·
Introducing TurboQuant: Our new compression algorithm that reduces LLM key-value cache memory by at least 6x and delivers up to 8x speedup, all with zero accuracy loss, redefining AI efficiency. Read the blog to learn how it achieves these results: goo.gle/4bsq2qI
GIF
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Javi Lopez ⛩️
Javi Lopez ⛩️@javilopen·
We're in Forbes 🤯
Javi Lopez ⛩️ tweet media
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