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AGIBOT has embedded a large multimodal reasoning model for X2, which enables real-time cognition and reasoning. When asked what kind of beverage to drink when you can't sleep, it recommends milk. X2 is ready to serve as a social companion and caregiver, and we can see it in nursing... show more

CyberRobo

4,915 subscribers

11,724 görüntüleme • 1 yıl önce •via X (Twitter)

Sağlık & İyilik Bilim & Teknoloji

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茶🎀 profil fotoğrafı

茶🎀1 yıl önce

将来的には介護施設などで見かけるようになるかもしれません。

Alan Hourmand profil fotoğrafı

Alan Hourmand1 yıl önce

Please never give that thing eyes

PrimeURL (for Startups 🏆) profil fotoğrafı

PrimeURL (for Startups 🏆)1 yıl önce

Impressive 💯

Treasure profil fotoğrafı

Treasure1 yıl önce

Gonna put this robot in the trenches

ASTRO 🛸 profil fotoğrafı

ASTRO 🛸1 yıl önce

LOL the robot is Near sighted

عبد العزيز الرفاعي profil fotoğrafı

عبد العزيز الرفاعي1 yıl önce

@pstAsiatech

BehemothAi profil fotoğrafı

BehemothAi1 yıl önce

Home health assistant

Bryte profil fotoğrafı

Bryte1 yıl önce

The future of sleep is here. At Bryte, we believe sleep should be personalized, intelligent, and effortless. That’s why we’ve combined cutting-edge AI with the latest sleep science to create a sleep system that adapts to you. From temperature regulation to real-time adjustments, we’re setting a new standard for restorative rest. Would you sleep on an A.I. mattress?

GO profil fotoğrafı

GO1 yıl önce

They put artificial intelligence into a robot and that's it) and communicate through voice

Reinvent DAO profil fotoğrafı

Reinvent DAO1 yıl önce

The real-time cognition and reasoning are impressive, and recommending milk for sleepless nights feels like a thoughtful, human-like touch. The idea of X2 stepping into nursing homes as a social companion and caregiver is exciting. Can’t wait to see how this unfolds. 🚀 #AI #Robotics #ElderlyCare

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#AGIBOTAIWeek Day 3: Introducing GO-2: the next-generation foundation model for embodied AI, built to unify reasoning and action. To truly bridge “thinking” and “doing,” embodied AI must solve two challenges at once: • It generate executable action plans through deep spatial reasoning • It deliver stable execution in real-world environments GO-2 tackles both with a comprehensive architecture: Action Chain-of-Thought for action reasoning, and an Asynchronous Dual-System for robust execution. #AGIBOT #AGIBOTAIWeek #Foundation #model #EmbodiedAI Official account tags X: AGIBOT LinkedIn: agibot

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(1/5) Gemini 3, our most intelligent model, is landing in Google Search today – starting with AI Mode. Excited that this is the first time we’re shipping a new Gemini model in Search on day one! 🚀 In Search, Gemini 3 with generative layouts will make it easy to get a rich understanding of anything on your mind. It has state-of-the-art reasoning, deep multimodal understanding and advanced agentic capabilities. That allows the model to shine when you ask it to explain advanced concepts or ideas – it reasons and can code interactive visuals in real-time. It can tackle your toughest questions like advanced science.

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Shenzhen Astribot released an end-to-end VLA: Duocore, which enables the humanoid robot S1 to respond to tasks in complex and uncertain environments in real time. Even if it is disturbed and replaced with tools it has never seen before, it can still complete the task flexibly. The real-time adaptability is enhanced, and the ability to cope with random and uncertain demand tasks is enhanced, especially in the field of home and nursing.

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Reasoning is central to purposeful action. Today we introduce MolmoAct — a fully open Action Reasoning Model (ARM) for robotics. Grounded in large-scale pre-training with action reasoning data, every predicted action is interpretable and user-steerable via visual trace. We are open-sourcing everything!

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When we eat or drink sugar, it causes a sudden spike in the hormone insulin, which can serve as a catalyst to fuel certain types of cancers, Dr. Lewis Cantley, a Harvard professor and the then-head of the Beth Israel Deaconess Cancer Center, said in 2012. His advice: don't eat sugar, and if you must, keep it to a minimum.

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60 Minutes

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NEWS: NVIDIA just announced Alpamayo, what CEO Jensen Huang calls the world’s first thinking, reasoning autonomous vehicle AI, launching on U.S. roads later this year, starting with the Mercedes CLA. Jensen: "It's trained end-to-end. Literally from camera in to actuation out; It reasons what action it is about to take, the reason by which is came about that action, and the trajectory." Alpamayo introduces Vision-Language-Action (VLA) models, which enable self-driving systems to interpret what they see, reason about complex driving scenarios, and generate driving actions. The platform includes large reasoning models, simulation tools for testing rare and edge-case scenarios, and open datasets for training and validation. NVIDIA says the approach improves transparency, safety, and robustness in autonomous systems, particularly in complex real-world environments, and supports progress toward higher levels of vehicle autonomy: "With a 10-billion-parameter architecture, Alpamayo 1 uses video input to generate trajectories alongside reasoning traces, showing the logic behind each decision. Developers can adapt Alpamayo 1 into smaller runtime models for vehicle development, or use it as a foundation for AV development tools such as reasoning-based evaluators and auto-labeling systems. Alpamayo 1 provides open model weights and open-source inferencing scripts. Future models in the family will feature larger parameter counts, more detailed reasoning capabilities, more input and output flexibility, and options for commercial usage."

Sawyer Merritt

1,602,914 görüntüleme • 5 ay önce

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OpenAI just announced API access to o1 (advanced reasoning model) yesterday. I'm delighted to announce today a new short course, Reasoning with o1, built with OpenAI, and taught by Colin Jarvis, Head of AI Solutions at OpenAI, to show you how to use this effectively! Unlike previous language models which generate output directly, o1 “thinks before it responds,” and generates many reasoning tokens before returning a more thoughtful and accurate response. It is great at complex reasoning -- including planning for agentic workflows, coding, and domain-specific reasoning in STEM fields like law. But how you should use it is quite different from other LLMs. I think o1 will be a game changer for many AI applications; and in this course, you'll learn how to use it effectively. In detail, you’ll: - Learn to recognize what tasks o1 is suited for, and when to use a smaller model, or combine o1 with a smaller model - Understand the new principles of prompting reasoning models: Be simple and direct; no explicit chain-of-thought required; use structure; show rather than tell - Implement multi-step orchestration in which o1 plans, and hands tasks over to gpt-4o-mini to execute specific steps; this illustrates a design pattern to optimize intelligence (accuracy) and cost - Use o1 for a coding task to build a new application, edit existing code, and test performance by running a coding competition between o1-mini and GPT 4o - Use o1 for image understanding and learn how it performs better with a "hierarchy of reasoning," in which it incurs the latency and cost upfront, preprocessing the image and indexing it with rich details so it can be used for Q&A later - Learn a technique called meta-prompting, in which you use o1 to improve your prompts. Using a customer support evaluation set, you'll iteratively use o1 to modify a prompt to improve performance You'll also learn about how OpenAI used reinforcement learning to produce a model that uses "test-time compute" to improve performance. I think you'll find this course enjoyable and valuable. Please sign up for it here:

Andrew Ng

357,401 görüntüleme • 1 yıl önce

🕹️We are excited to introduce "ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation" ChronoEdit reframes image editing as a video generation task to encourage temporal consistency. It leverages a temporal reasoning stage that denoises with “video reasoning tokens” to "reason" on physically plausible edits. See the attached video for results. Project Page: Arxiv: Code and model are coming.

🕹️We are excited to introduce "ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation" ChronoEdit reframes image editing as a video generation task to encourage temporal consistency. It leverages a temporal reasoning stage that denoises with “video reasoning tokens” to "reason" on physically plausible edits. See the attached video for results. Project Page: Arxiv: Code and model are coming.

Huan Ling

36,841 görüntüleme • 8 ay önce

Gemini 3 Flash can analyze high-fidelity images and use multimodal reasoning to determine next steps. See how the model understands complex visuals and generates layers of interactive elements.

Gemini 3 Flash can analyze high-fidelity images and use multimodal reasoning to determine next steps. See how the model understands complex visuals and generates layers of interactive elements.

Google AI Developers

47,280 görüntüleme • 5 ay önce