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We released Qwen3-Omni-Flash (2025-12-01 version) API Service. Smarter interaction, more human expression: · A/V Interaction: Significant boost in instruction following. Solves "dumbing down" in casual chats with rock-solid stability. · Precise Control: Enhanced System Prompt adherence for specific personas, styles, and lengths. · Multilingual Mastery: Solved language switching instability.... show more

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Owen Gregorian

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Tencent Hy

89,257 Aufrufe • vor 11 Monaten

Ok I've used Codex 5.4 Extra High for something that saved me so many hours and thousands of dollars and may interest you: -> how I automatically translate my game in 9 languages 1) I did the whole game in English, with no localization in mind 2) Then everybody told me that the reach is way higher by adding local languages 3) So I had a long chat with Codex to write a great spec to build a localization interface and super simple process for afterwards (I want to keep the simplicity) 4) Then translated the game in 9 languages! 5) Every localization is challenged a second time to improve 6) We are talking 580 keys per language - it took 1h35 to find all the hardcoded text and add keys - then it took 1h15 min to do all v1 translations 7) BONUS: it translates automatically all audio with ElevenLabs (using their text to speech skill) Total: Roughly 3 hours to implement a translation system and to translate the game Can any Japanese person tell me if the translation is good? There were 2 challenges: - translating once - keeping the game translated Now it's a blessing: I still work on the game like the usual, and if I add new text, it will automatically create the keys and translate in all languages just with basic instructions in Agents.md + a pre-commit hook to ensure it's done. I hope to use the tool for a professional or community-based human review in the future! Hope it helps:)

Ok I've used Codex 5.4 Extra High for something that saved me so many hours and thousands of dollars and may interest you: -> how I automatically translate my game in 9 languages 1) I did the whole game in English, with no localization in mind 2) Then everybody told me that the reach is way higher by adding local languages 3) So I had a long chat with Codex to write a great spec to build a localization interface and super simple process for afterwards (I want to keep the simplicity) 4) Then translated the game in 9 languages! 5) Every localization is challenged a second time to improve 6) We are talking 580 keys per language - it took 1h35 to find all the hardcoded text and add keys - then it took 1h15 min to do all v1 translations 7) BONUS: it translates automatically all audio with ElevenLabs (using their text to speech skill) Total: Roughly 3 hours to implement a translation system and to translate the game Can any Japanese person tell me if the translation is good? There were 2 challenges: - translating once - keeping the game translated Now it's a blessing: I still work on the game like the usual, and if I add new text, it will automatically create the keys and translate in all languages just with basic instructions in Agents.md + a pre-commit hook to ensure it's done. I hope to use the tool for a professional or community-based human review in the future! Hope it helps:)

Nicolas Zullo

13,418 Aufrufe • vor 3 Monaten

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Mario Nawfal

527,426 Aufrufe • vor 7 Monaten

🚨 JUST IN: MICROSOFT just open sourced a VOICE AI THAT TRANSCRIBES 60 MINUTES OF AUDIO in a single pass. 100% FREE. It knows who spoke. It knows when they spoke. It knows exactly what they said. All in one shot. No chunking. No context loss. It's called VibeVoice. Not a transcription tool. Not a basic speech to text wrapper. A frontier voice AI family with ASR, TTS, and real time streaming. All open source. All free. Here's what it actually does 👇 VibeVoice ASR - Speech Recognition: → Processes 60 minutes of continuous audio in a single pass → Never slices audio into chunks so global context is never lost → Identifies WHO spoke, WHEN they spoke and WHAT they said simultaneously → Supports customized hotwords for domain specific accuracy → Works in 50+ languages natively → Already adopted by Hugging Face Transformers library → Already being built on by the open source community BY PEOPLE WHO HAD NO IDEA THIS LEVEL OF ACCURACY WAS ALREADY FREE. VibeVoice TTS - Text to Speech: → Generates up to 90 minutes of speech in a single pass → Supports up to 4 distinct speakers in one conversation → Natural turn taking and speaker consistency throughout → Expressive speech that captures emotional nuances → Supports English, Chinese and multiple other languages VibeVoice Realtime - Streaming TTS: → Only 300 millisecond first audible latency → Streams text input in real time → 0.5B parameters so it actually deploys anywhere → Robust long form generation up to 10 minutes → Lightweight enough for production use today The core innovation nobody is talking about: Most voice AI models slice long audio into short chunks. Every time they slice, they lose context. Speaker tracking breaks. Semantic coherence breaks. Accuracy drops. VibeVoice uses continuous speech tokenizers running at an ultra low frame rate of 7.5 Hz. This preserves audio fidelity while dramatically boosting computational efficiency. The entire 60 minutes stays in context. Nothing gets lost. Nobody gets misidentified. The numbers: → VibeVoice ASR 7B - available now on Hugging Face → VibeVoice Realtime 0.5B - try it on Colab right now → 50+ supported languages → 11 distinct English voice styles → 9 multilingual speaker voices → Already integrated into Hugging Face Transformers → Finetuning code now available The wildest part? A voice powered input method called Vibing just built itself on top of VibeVoice ASR. Available on macOS and Windows right now. The open source community is already shipping products on top of this. 100% Open Source. Free to use. Free to fine tune. Free to build on. 🔖 Save this before your competitors find it first. 👇

🚨 JUST IN: MICROSOFT just open sourced a VOICE AI THAT TRANSCRIBES 60 MINUTES OF AUDIO in a single pass. 100% FREE. It knows who spoke. It knows when they spoke. It knows exactly what they said. All in one shot. No chunking. No context loss. It's called VibeVoice. Not a transcription tool. Not a basic speech to text wrapper. A frontier voice AI family with ASR, TTS, and real time streaming. All open source. All free. Here's what it actually does 👇 VibeVoice ASR - Speech Recognition: → Processes 60 minutes of continuous audio in a single pass → Never slices audio into chunks so global context is never lost → Identifies WHO spoke, WHEN they spoke and WHAT they said simultaneously → Supports customized hotwords for domain specific accuracy → Works in 50+ languages natively → Already adopted by Hugging Face Transformers library → Already being built on by the open source community BY PEOPLE WHO HAD NO IDEA THIS LEVEL OF ACCURACY WAS ALREADY FREE. VibeVoice TTS - Text to Speech: → Generates up to 90 minutes of speech in a single pass → Supports up to 4 distinct speakers in one conversation → Natural turn taking and speaker consistency throughout → Expressive speech that captures emotional nuances → Supports English, Chinese and multiple other languages VibeVoice Realtime - Streaming TTS: → Only 300 millisecond first audible latency → Streams text input in real time → 0.5B parameters so it actually deploys anywhere → Robust long form generation up to 10 minutes → Lightweight enough for production use today The core innovation nobody is talking about: Most voice AI models slice long audio into short chunks. Every time they slice, they lose context. Speaker tracking breaks. Semantic coherence breaks. Accuracy drops. VibeVoice uses continuous speech tokenizers running at an ultra low frame rate of 7.5 Hz. This preserves audio fidelity while dramatically boosting computational efficiency. The entire 60 minutes stays in context. Nothing gets lost. Nobody gets misidentified. The numbers: → VibeVoice ASR 7B - available now on Hugging Face → VibeVoice Realtime 0.5B - try it on Colab right now → 50+ supported languages → 11 distinct English voice styles → 9 multilingual speaker voices → Already integrated into Hugging Face Transformers → Finetuning code now available The wildest part? A voice powered input method called Vibing just built itself on top of VibeVoice ASR. Available on macOS and Windows right now. The open source community is already shipping products on top of this. 100% Open Source. Free to use. Free to fine tune. Free to build on. 🔖 Save this before your competitors find it first. 👇

Kanika

221,026 Aufrufe • vor 3 Monaten

Reinforcement Learning from Human Feedback (RLHF) is gaining traction. This field aims to make AI more responsible by including human values and preferences. In this video, Nathan Lambert, a research scientist and RLHF team lead at Hugging Face explores its inner workings, applications and industry impact. RLHF has gained the spotlight in recent years. The growth of language models like Anthropic’s Claude and OpenAI's ChatGPT have increased interest in human-feedback integration. "There are some rumors that Open AI had two teams; one was doing RLHF and the other instruction fine-tuning. And the RLHF team kept getting more and more performance." Understanding RLHF The RLHF process has three main steps: Pre-training: Much like with GPT models, the journey starts with pre-training on a large corpus of data. This can range from text data, web scrapes, to specialized datasets. Reward Modeling: This is the RLHF counterpart of supervised fine-tuning in large language models. This stage involves creating a reward model that resonates with human values and preferences. RL Optimization: This stage parallels reward modeling and reinforcement learning in traditional AI models. The AI system fine-tunes itself based on the reward model, employing reinforcement learning algorithms for that extra layer of optimization. The Data Challenge Data collection and curation in RLHF closely resemble the challenges you'd encounter in large language model training. Datasets from organizations like OpenAI can serve as a useful foundation. However, the need for high-quality, task-specific data cannot be overstated. Implementing RLHF: A Practical Guide If you’re someone who loves getting hands-on with AI libraries like Hugging Face, implementing RLHF is right way to do. It’s essential to understand its limitations. Think about model stability, over-optimization, and exploration strategies, much like you would when prompt engineering. Ongoing Research and Next Steps While he suggests that some basics figured out, there are layers of complexity that still need to be unraveled: 1. New Benchmarks: How do we measure the effectiveness of RLHF? 2. Preference Modeling: How can the model be made to understand human preferences better? 3. Interpreting RLHF: Much like explainability in traditional models, how do we make RLHF more interpretable? 4. System-Wide Evaluation: Going beyond individual performance, how does RLHF affect an entire system? The Transformative Power of RLHF Whether you're an AI developer, a business analyst, or a marketer, RLHF promises to revolutionize your domain. Imagine customer service chatbots that understand human emotions better, or content generators that align more closely with human values. RLHF is an emerging field that focuses on enhancing machine learning models through human feedback. While it tackles important issues like bias and ethics, its broader goal is to improve system performance across various applications. Whether you're deeply invested in the ethics of AI or simply curious about advancements in machine learning, RLHF offers valuable insights. If you're interested in the next wave of AI development, this area is definitely one to watch.

Reinforcement Learning from Human Feedback (RLHF) is gaining traction. This field aims to make AI more responsible by including human values and preferences. In this video, Nathan Lambert, a research scientist and RLHF team lead at Hugging Face explores its inner workings, applications and industry impact. RLHF has gained the spotlight in recent years. The growth of language models like Anthropic’s Claude and OpenAI's ChatGPT have increased interest in human-feedback integration. "There are some rumors that Open AI had two teams; one was doing RLHF and the other instruction fine-tuning. And the RLHF team kept getting more and more performance." Understanding RLHF The RLHF process has three main steps: Pre-training: Much like with GPT models, the journey starts with pre-training on a large corpus of data. This can range from text data, web scrapes, to specialized datasets. Reward Modeling: This is the RLHF counterpart of supervised fine-tuning in large language models. This stage involves creating a reward model that resonates with human values and preferences. RL Optimization: This stage parallels reward modeling and reinforcement learning in traditional AI models. The AI system fine-tunes itself based on the reward model, employing reinforcement learning algorithms for that extra layer of optimization. The Data Challenge Data collection and curation in RLHF closely resemble the challenges you'd encounter in large language model training. Datasets from organizations like OpenAI can serve as a useful foundation. However, the need for high-quality, task-specific data cannot be overstated. Implementing RLHF: A Practical Guide If you’re someone who loves getting hands-on with AI libraries like Hugging Face, implementing RLHF is right way to do. It’s essential to understand its limitations. Think about model stability, over-optimization, and exploration strategies, much like you would when prompt engineering. Ongoing Research and Next Steps While he suggests that some basics figured out, there are layers of complexity that still need to be unraveled: 1. New Benchmarks: How do we measure the effectiveness of RLHF? 2. Preference Modeling: How can the model be made to understand human preferences better? 3. Interpreting RLHF: Much like explainability in traditional models, how do we make RLHF more interpretable? 4. System-Wide Evaluation: Going beyond individual performance, how does RLHF affect an entire system? The Transformative Power of RLHF Whether you're an AI developer, a business analyst, or a marketer, RLHF promises to revolutionize your domain. Imagine customer service chatbots that understand human emotions better, or content generators that align more closely with human values. RLHF is an emerging field that focuses on enhancing machine learning models through human feedback. While it tackles important issues like bias and ethics, its broader goal is to improve system performance across various applications. Whether you're deeply invested in the ethics of AI or simply curious about advancements in machine learning, RLHF offers valuable insights. If you're interested in the next wave of AI development, this area is definitely one to watch.

Muratcan Koylan

27,005 Aufrufe • vor 2 Jahren

FLUX 2.0 just dropped. And it’s one of the strongest image models of 2025. In our latest video, we break down what makes FLUX 2.0 so powerful and why creators are paying close attention to it. ⁠ Here’s what stands out: Accurate HEX color control You can specify exact HEX values inside your prompt. You get precise palette consistency without guesswork. ⁠ Structured prompting with JSON FLUX 2.0 is tuned for JSON based prompts. That means predictable composition, steadier outputs, and tighter creative control. ⁠ Photorealism and lighting accuracy Reflections, skin texture, shadows, small details, and challenging lighting setups now render with a level of clarity that looks close to real photography. ⁠ Complex scene understanding You can describe multi-element environments and FLUX 2.0 handles spatial relationships with stronger coherence and stability. ⁠ Better anatomy, hands, and facial detail Human subjects look cleaner, more natural, and more consistent across shots. ⁠ Image to image style control You can feed a reference and FLUX 2.0 matches mood, framing, texture, or atmosphere with surprising precision. ⁠ If you want a real look at what FLUX 2.0 delivers, watch the full breakdown here.

FLUX 2.0 just dropped. And it’s one of the strongest image models of 2025. In our latest video, we break down what makes FLUX 2.0 so powerful and why creators are paying close attention to it. ⁠ Here’s what stands out: Accurate HEX color control You can specify exact HEX values inside your prompt. You get precise palette consistency without guesswork. ⁠ Structured prompting with JSON FLUX 2.0 is tuned for JSON based prompts. That means predictable composition, steadier outputs, and tighter creative control. ⁠ Photorealism and lighting accuracy Reflections, skin texture, shadows, small details, and challenging lighting setups now render with a level of clarity that looks close to real photography. ⁠ Complex scene understanding You can describe multi-element environments and FLUX 2.0 handles spatial relationships with stronger coherence and stability. ⁠ Better anatomy, hands, and facial detail Human subjects look cleaner, more natural, and more consistent across shots. ⁠ Image to image style control You can feed a reference and FLUX 2.0 matches mood, framing, texture, or atmosphere with surprising precision. ⁠ If you want a real look at what FLUX 2.0 delivers, watch the full breakdown here.

There's An AI For That

27,286 Aufrufe • vor 8 Monaten

Tucker UNLEASHES on AG Pam Bondi with a blistering 3-minute rebuttal to her remarks on “hate speech.” The monologue version of Tucker is back. This is EXACTLY what we need from him right now. “There’s free speech and then there’s hate speech. This is the Attorney General of the United States, the chief law enforcement officer of the United States, telling you that there is this other category called hate speech. And of course, the implication is that’s a crime. There’s almost no sentence that Charlie Kirk. “And I, I’m not running the risk of appropriating his memory for my own ends by saying this. It’s provable. There’s no sentence that Charlie Kirk would have objected to more than that. And you’ve got to think the Attorney General didn’t think it through and was not attempting to desecrate the memory of the person she was purporting to celebrate that she just threw that out there, that she hadn’t thought about it. “You hope that. You hope that Charlie Kirk’s death won’t be used by a group we now call bad actors to create a society that was the opposite of the one he worked to build. You hope that. “You hope that a year from now, the turmoil we’re seeing in the aftermath of his murder won’t be leveraged to bring hate speech laws to this country. And trust me, if it is, if that does happen. There is never a more justified moment for civil disobedience than that, ever. “And there never will be. Because if they can tell you what to say, they’re telling you what to think. There is nothing they can’t do to you because they don’t consider you human. They don’t believe you have a soul. A human being with a soul. A free man has a right to say what he believes, not to hurt other people, but to express human his views. “And by the way, that thinking, and not to pile on the Attorney General, who’s a very nice person, but that thinking that she just articulated on camera there is exactly what got us to a place where some huge and horrifying percentage of young people think it’s okay to shoot people you disagree with to kill Nazis for saying things they don’t like. “Why do they believe that? How did we get here? Is it the video games? Is it the SSRIs? Yeah, probably. But what it really is is 12 and then 16 years of indoctrination in our schools at the hands of people who tell them that, who say exactly what the Attorney General just said. “Well, there’s free speech, which of course, we all acknowledge is important, so, so important. But then there’s this thing called hate speech. Hate speech, of course, is any speech that the people in power hate. But they don’t define it that way. They define it as speech that hurts people, speech that is tantamount to violence. And we punish violence, don’t we? “Of course we do. They’ve been taught that every year of their lives. And so naturally, most of them believe it. When Charlie Kirk is shot in the throat with a .36 on camera. I doubt very many young Americans want to see something like that or actually applaud the death of a man, a father, a husband. “But they’ve been told for their entire lives in schools exactly what Pam Bondi just told them. Well, there’s free speech, but then there’s also hate speech. And woe to those who engage in it because it’s a crime.”

Tucker UNLEASHES on AG Pam Bondi with a blistering 3-minute rebuttal to her remarks on “hate speech.” The monologue version of Tucker is back. This is EXACTLY what we need from him right now. “There’s free speech and then there’s hate speech. This is the Attorney General of the United States, the chief law enforcement officer of the United States, telling you that there is this other category called hate speech. And of course, the implication is that’s a crime. There’s almost no sentence that Charlie Kirk. “And I, I’m not running the risk of appropriating his memory for my own ends by saying this. It’s provable. There’s no sentence that Charlie Kirk would have objected to more than that. And you’ve got to think the Attorney General didn’t think it through and was not attempting to desecrate the memory of the person she was purporting to celebrate that she just threw that out there, that she hadn’t thought about it. “You hope that. You hope that Charlie Kirk’s death won’t be used by a group we now call bad actors to create a society that was the opposite of the one he worked to build. You hope that. “You hope that a year from now, the turmoil we’re seeing in the aftermath of his murder won’t be leveraged to bring hate speech laws to this country. And trust me, if it is, if that does happen. There is never a more justified moment for civil disobedience than that, ever. “And there never will be. Because if they can tell you what to say, they’re telling you what to think. There is nothing they can’t do to you because they don’t consider you human. They don’t believe you have a soul. A human being with a soul. A free man has a right to say what he believes, not to hurt other people, but to express human his views. “And by the way, that thinking, and not to pile on the Attorney General, who’s a very nice person, but that thinking that she just articulated on camera there is exactly what got us to a place where some huge and horrifying percentage of young people think it’s okay to shoot people you disagree with to kill Nazis for saying things they don’t like. “Why do they believe that? How did we get here? Is it the video games? Is it the SSRIs? Yeah, probably. But what it really is is 12 and then 16 years of indoctrination in our schools at the hands of people who tell them that, who say exactly what the Attorney General just said. “Well, there’s free speech, which of course, we all acknowledge is important, so, so important. But then there’s this thing called hate speech. Hate speech, of course, is any speech that the people in power hate. But they don’t define it that way. They define it as speech that hurts people, speech that is tantamount to violence. And we punish violence, don’t we? “Of course we do. They’ve been taught that every year of their lives. And so naturally, most of them believe it. When Charlie Kirk is shot in the throat with a .36 on camera. I doubt very many young Americans want to see something like that or actually applaud the death of a man, a father, a husband. “But they’ve been told for their entire lives in schools exactly what Pam Bondi just told them. Well, there’s free speech, but then there’s also hate speech. And woe to those who engage in it because it’s a crime.”

The Vigilant Fox 🦊

262,867 Aufrufe • vor 10 Monaten

NEWS: Figure has unveiling its 3rd generation humanoid robot. • Features a completely redesigned sensory suite and hand system. Wireless charging in feet. • Next-generation vision system engineered for high-frequency visuomotor control. Its new camera architecture delivers twice the frame rate, one-quarter the latency, and a 60% wider field of view per camera within a more compact form factor • Soft goods, wireless charging, improved audio system for voice reasoning, and battery safety advancements • "Engineered from the ground-up for high-volume manufacturing. In order to scale, we established a new supply chain and entirely new process for manufacturing humanoid robots at BotQ." • Lower manufacturing cost • Softer, more adaptive fingertips increase surface contact area, enabling more stable grasps across objects of varied shapes and sizes. Each fingertip sensor can detect forces as small as three grams of pressure - sensitive enough to register the weight of a paperclip resting on your finger. • Multi-density foam to protect against pinch points, and is covered in soft textiles rather than hard machined parts. 9% less mass and less volume than Figure 02 • 10 Gbps mmWave data offload capability, allowing the entire fleet to upload terabytes of data • Upgraded audio hardware system for better real time speech-to-speech. Its speaker is twice the size and nearly four times more powerful, while the microphone has been repositioned for improved performance and clarity. • Charging coils in the robot’s feet allow it to simply step onto a wireless stand and charge at 2 kW Figure: "BotQ is Figure’s dedicated manufacturing facility designed to scale robot production. BotQ’s first-generation manufacturing line will initially be capable of producing up to 12,000 humanoid robots per year, with the goal of producing a total of 100,000 robots over the next four years. Instead of relying on contract manufacturers, Figure brought production of its most critical systems in-house to maintain tight control over quality, iteration, and speed."

NEWS: Figure has unveiling its 3rd generation humanoid robot. • Features a completely redesigned sensory suite and hand system. Wireless charging in feet. • Next-generation vision system engineered for high-frequency visuomotor control. Its new camera architecture delivers twice the frame rate, one-quarter the latency, and a 60% wider field of view per camera within a more compact form factor • Soft goods, wireless charging, improved audio system for voice reasoning, and battery safety advancements • "Engineered from the ground-up for high-volume manufacturing. In order to scale, we established a new supply chain and entirely new process for manufacturing humanoid robots at BotQ." • Lower manufacturing cost • Softer, more adaptive fingertips increase surface contact area, enabling more stable grasps across objects of varied shapes and sizes. Each fingertip sensor can detect forces as small as three grams of pressure - sensitive enough to register the weight of a paperclip resting on your finger. • Multi-density foam to protect against pinch points, and is covered in soft textiles rather than hard machined parts. 9% less mass and less volume than Figure 02 • 10 Gbps mmWave data offload capability, allowing the entire fleet to upload terabytes of data • Upgraded audio hardware system for better real time speech-to-speech. Its speaker is twice the size and nearly four times more powerful, while the microphone has been repositioned for improved performance and clarity. • Charging coils in the robot’s feet allow it to simply step onto a wireless stand and charge at 2 kW Figure: "BotQ is Figure’s dedicated manufacturing facility designed to scale robot production. BotQ’s first-generation manufacturing line will initially be capable of producing up to 12,000 humanoid robots per year, with the goal of producing a total of 100,000 robots over the next four years. Instead of relying on contract manufacturers, Figure brought production of its most critical systems in-house to maintain tight control over quality, iteration, and speed."

Sawyer Merritt

140,241 Aufrufe • vor 10 Monaten

China’s pretty humanoid robot stuns by opening a car door in a ‘world’s first’ | Jijo Malayil, Interesting Engineering Mornine used onboard sensors and full-body control to locate the handle, adjust posture, and open a car door—no human input needed. AiMOGA Robotics has claimed to have reached a significant milestone in embodied AI with its humanoid robot, Mornine, autonomously opening a car door inside a functioning Chery dealership in China. Relying solely on onboard sensors, full-body motion control, and end-to-end reinforcement learning, Mornine performed the task without any human input. Unlike scripted or teleoperated robots, Mornie identified the door handle, adjusted its posture, and used coordinated force across its limbs and torso to complete the action—demonstrating advanced autonomy in a real-world setting. “The deployment marks one of the first instances of a service robot executing such a high-friction, physical interaction in a live commercial setting,” said the firm in a statement. In April, at the Shanghai Auto Show, automotive brands Omoda and Jaecoo, subsidiaries of Chery Automobile, introduced Mornine, designed for use in car dealerships. From sim to service Opening a car door may seem like a simple task, but AiMOGA Robotics views it as a pivotal moment in robotics—signaling a shift from simulation to real-world service, and from basic command execution to autonomous capability. Using only onboard sensors and full-body motion control, Mornine identified the door handle, adjusted her posture, and applied coordinated force across her limbs to open the door—entirely without human intervention. Mornine’s advanced sensor suite includes 3D LiDAR, depth and wide-angle cameras, and a visual-language model (VLM), enabling real-time perception of door position and opening status. Uniquely, Mornine wasn’t explicitly programmed to recognize door handles. Instead, she learned through reinforcement learning, undergoing millions of simulated cycles to focus on the right region and perform the task independently. “We never explicitly told the robot what a door handle is. It learned to focus on that region by itself,” said the engineering team at AiMOGA Robotics in a statement. The learned model was transferred to the real world using Sim2Real methods. Mornine continuously gathers live sensor data during operation, which feeds into a cloud-based training loop, allowing her to improve through continuous learning in real-world settings, reports Robotics Tomorrow. Now active in multiple Chery 4S dealerships in China, Mornine not only opens car doors but also assists with customer greetings, vehicle introductions, and item delivery—marking a step forward in humanoid robotics for commercial retail environments. AI meets retail Originally introduced as the AiMOGA Robot, Mornine was developed to support dealership sales by performing tasks such as explaining vehicle specifications, leading showroom tours, serving refreshments, and engaging with customers in multiple languages. First conceived by Chery as a virtual character to appeal to Generation Z using metaverse and virtual human technologies, Mornine gradually evolved into a real-world interactive humanoid. After multiple iterations of character and model design, Mornine debuted as a digital persona in animations, livestreams, and promotional content, gaining brand recognition. Chery later expanded the concept beyond the virtual space, resulting in the creation of the AiMOGA humanoid robot. Leveraging Chery’s expertise in autonomous driving, environmental sensing, and control systems, AiMOGA features full-stack capabilities in perception, cognition, decision-making, and execution. It uses multimodal sensing—combining speech, vision, and environmental data—to interpret user gestures, commands, and showroom dynamics. A bionic motion system and automotive-grade hardware enable dexterous movement and upright mobility, while multi-robot collaboration allows for coordinated tasks like guided tours. At the decision-making layer, Deepseek’s large language models enable natural language understanding and personalized interaction. In April 2025, Mornine officially began commercial service as an “Intelligent Sales Consultant” at the OMODA C5 JOYSTAR 4S dealership in Kuala Lumpur, Malaysia—marking her full transition from a virtual concept to a real-world humanoid sales assistant.

Owen Gregorian

67,975 Aufrufe • vor 1 Jahr

🚨 Breaking News OpenAI just announced the launch of its groundbreaking ChatGPT agent. It can navigate calendars, generate editable presentations, execute code, and more. ⁠ What ChatGPT Agent Can Do: Task Automation: Easily manage your calendar, craft professional presentations and slideshows, and run code automatically. Deep Web Integration: Combines functionalities from OpenAI’s earlier tools like Operator (for web interactions) and Deep Research (for synthesizing extensive web-based data into clear reports). Natural Interaction: Simply prompt ChatGPT using natural language to get tasks done. App Connectivity: Supports connectors to popular apps like Gmail and GitHub, and can directly use APIs to extend functionality even further. ⁠ 📈 Impressive Benchmarks: Humanity’s Last Exam: Scores 41.6%, nearly double the previous models (OpenAI o3 and o4-mini). FrontierMath: Achieves a remarkable 27.4% with tool assistance, significantly surpassing previous leading scores (6.3% from o4-mini). ⁠ Built with Safety in Mind: OpenAI emphasizes safety due to the agent’s enhanced capabilities, ensuring responsible usage while exploring new frontiers of AI interactions. ⁠ Now available for ChatGPT Pro, Plus, and Team subscribers. Just activate “agent mode” from the ChatGPT menu and explore a smarter, more productive future!

🚨 Breaking News OpenAI just announced the launch of its groundbreaking ChatGPT agent. It can navigate calendars, generate editable presentations, execute code, and more. ⁠ What ChatGPT Agent Can Do: Task Automation: Easily manage your calendar, craft professional presentations and slideshows, and run code automatically. Deep Web Integration: Combines functionalities from OpenAI’s earlier tools like Operator (for web interactions) and Deep Research (for synthesizing extensive web-based data into clear reports). Natural Interaction: Simply prompt ChatGPT using natural language to get tasks done. App Connectivity: Supports connectors to popular apps like Gmail and GitHub, and can directly use APIs to extend functionality even further. ⁠ 📈 Impressive Benchmarks: Humanity’s Last Exam: Scores 41.6%, nearly double the previous models (OpenAI o3 and o4-mini). FrontierMath: Achieves a remarkable 27.4% with tool assistance, significantly surpassing previous leading scores (6.3% from o4-mini). ⁠ Built with Safety in Mind: OpenAI emphasizes safety due to the agent’s enhanced capabilities, ensuring responsible usage while exploring new frontiers of AI interactions. ⁠ Now available for ChatGPT Pro, Plus, and Team subscribers. Just activate “agent mode” from the ChatGPT menu and explore a smarter, more productive future!

There's An AI For That

32,716 Aufrufe • vor 1 Jahr

Imagine understanding exactly how to speak to Donald Trump's Followers to influence their buying process. What about speaking to Nike's followers? What about... Speaking in the voice of anyone at all? We sit down with Beelines 🐝 to understand how they leverage Ai to build out audiences and discover how to craft messages that resonate with any audience, from political followers to brand enthusiasts, in seconds. This is a must watch for any marketer or anyone interested in truly innovative applications to use artificial intelligence vs just saying "We are Ai" with no use case. 00:00 – Exploring the Human Intelligence Model 01:14 – Innovative Applications of Beelines AI 02:31 – AI-Driven Customer Behavior Simulation and Enhancing AI Training through Human Interaction 06:23 – Leveraging Real-Time Data for AI Personalization 12:55 – Public Bees: Enhancing Discoverability in AI Networks 15:00 – Revolutionizing Advertising with AI Consumer Insights 16:09 – Utilizing AI for Market Research and Feedback Collection 19:17 – Influencer Marketing Strategies in the AI Era 21:08 – Upcoming AI Developments and Innovative Tools 23:54 – Final Thoughts and How to Connect Guests: gregariously.eth/.sol./lens/.⌐◨-◨ and Isaac Lazoff Host: ᗩｖ𝔦 🥞

21Rates

13,910 Aufrufe • vor 1 Jahr