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Aumentada Soluciones Informáticas: Noticias, web, hosting, seguridad, realidad aumentada/virtual y drones

Colombia
Joined November 2009
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.@jack nos presenta un modelo de voz llamado Dessa: teapawt.net/jack/status/2113697902…
We believe voice is the most natural way to interact with intelligence, so we created Dessa, the most authentic full-duplex speech model ever built. Talking with it feels like talking with a person…full of emotion, nuance, pauses, and a natural cadence. block.xyz/dessa
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1/4 Today, we’re releasing Mercury 3. Mercury 3 is by far our most powerful model and the most intelligent diffusion LLM ever released. It outperforms GPT-6 Luna and Haiku 5.5 on quality while running at 1000+ tok/sec.
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y cerramos con @MiniMax_AI y lanzamiento de MiniMax M3.1 Flash teapawt.net/minimax_ai/status/2112…
MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: platform.minimax.io M Plan: minimax.io/m-plan MiniMax Code for desktop: agent.minimax.io/download
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Vamos con las AI news de la última semana de Octubre: Empezamos con @OpenAI anunciando GPT-6.1 terra teapawt.net/openai/status/21147807…
GPT-6.1 Terra: delivering fast and capable computer use at a lower price. GPT-6.1 Terra understands what’s on screen, takes action across apps, writes naturally, and is a more capable model for your whole workday with the efficiency to take on more of it.
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.@mirendil presenta fern con 10m de tokens de contexto teapawt.net/mirendil/status/211475…
Introducing Fern, Mirendil’s first model: pretrained from scratch, with up to 10 million tokens of context. That’s ~0.5M lines of code or days of an agent’s work - all in context at once. Built for high-volume agentic work in AI R&D: auditing training data, debugging training runs from logs, and reading agent traces end to end. Fern’s next-token prediction keeps improving as context grows to 10M tokens. Fern 0.1 is Mirendil-Base after a short round of post-training. It’s the first and smallest of three models, with two larger ones now being pretrained. We’ll ship frequent updates and make the model available soon.
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