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Introducing Expressive TTS Arena 🥊🤖🥊 ⚡️ 🥊🤖🥊 Starting with Hume AI vs ElevenLabs, it's a new way to evaluate voice AI systems with natural language instructions + richer text As voice generation systems evolve, we wanted to show an example of an eval system better suited toward cutting edge models👇

Hume AI

23,187 subscribers

52,628 Aufrufe • vor 1 Jahr •via X (Twitter)

Wissenschaft & Technologie

Anya Rossi• Live Now

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11 Kommentare

Profilbild von Hume

Humevor 1 Jahr

was designed to evaluate how TTS systems handle nuanced, creative, and emotionally rich content and prompts. Previously, in a blind comparison study with 180 human raters, Hume's new Octave TTS outputs were favored over outputs from ElevenLabs Voice Design in terms of audio quality, naturalness, and how well speech generations matched descriptions of the desired voice, across 120 diverse prompts. Try it out for yourself and see if you agree! We'll be adding a leaderboard when enough ratings come in.

Profilbild von AssemblyAI

AssemblyAIvor 1 Jahr

Announcing: Our most advanced speech-to-text model goes beyond accuracy to capture the real-world complexity of human conversation and deliver reliable, source-of-truth audio data. Explore Universal-2 updates 👇

Profilbild von Kol Tregaskes

Kol Tregaskesvor 1 Jahr

Will you add @sesame

Profilbild von Vaibhav (VB) Srivastav

Vaibhav (VB) Srivastavvor 1 Jahr

would've loved to get you onboarded on TTS Arena btw:

Profilbild von AK

AKvor 1 Jahr

would be awesome to host the gradio app here as well:

Profilbild von 霊 👑 (kween/acc)

霊 👑 (kween/acc)vor 1 Jahr

can you add a language option so that we could also rank them for different languages?

Profilbild von Hume

Humevor 1 Jahr

Definitely, currently it's only English but we will be adding more languages shortly

Profilbild von Brandon McConnell

Brandon McConnellvor 1 Jahr

Does Hume offer true STS yet, not for LLM conversation but for speech conversion in re-personified voiceovers?

Profilbild von Ethan

Ethanvor 1 Jahr

This is where I say “I’ve been testing this product for the last one week” - MKBHD voice, the results have been impressive 😊

Profilbild von Sameed

Sameedvor 1 Jahr

Wow, this Expressive TTS Arena is a game changer for evaluating voice AI! I love how it focuses on nuanced, emotional, and creative content, perfect for pushing TTS tech forward. I’m testing it now, and the comparison with ElevenLabs is fascinating.

Profilbild von ORACLE Meshchain.Ai

ORACLE Meshchain.Aivor 1 Jahr

This Expressive TTS Arena sounds epic! 🥊🤖🥊 We're always looking for new ways to evaluate and improve AI. Fueling the future of voice AI with high-quality data? PublicAI is in! 😉 #VoiceAI #AI

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OpenAI enters the Expressive TTS Arena 🥊🤖🥊 Now hosted on Hugging Face, this arena is a new way to evaluate voice AI systems with natural language instructions + richer text. Compare Hume's TTS against ElevenLabs and OpenAI and see if you agree with the leaderboard results!

OpenAI enters the Expressive TTS Arena 🥊🤖🥊 Now hosted on Hugging Face, this arena is a new way to evaluate voice AI systems with natural language instructions + richer text. Compare Hume's TTS against ElevenLabs and OpenAI and see if you agree with the leaderboard results!

Hume AI

75,766 Aufrufe • vor 1 Jahr

I built a service desk agent using ElevenLabs’ new Conversational AI Agents feature. Watch the video to see how responsive it is! Previously, I used ElevenLabs for cloning my voice and used my generated voice for narrations in some of my youtube videos. This feature takes elevenlabs' voice AI to a whole new level! It simplifies systems that used to require separate TTS (text-to-speech) and STT (speech-to-text) processes for both sides of the conversation. Now, it’s much simpler! Create your own agent here What will you create with this?

I built a service desk agent using ElevenLabs’ new Conversational AI Agents feature. Watch the video to see how responsive it is! Previously, I used ElevenLabs for cloning my voice and used my generated voice for narrations in some of my youtube videos. This feature takes elevenlabs' voice AI to a whole new level! It simplifies systems that used to require separate TTS (text-to-speech) and STT (speech-to-text) processes for both sides of the conversation. Now, it’s much simpler! Create your own agent here What will you create with this?

Melvin Vivas

27,722 Aufrufe • vor 1 Jahr

What if voice AI could understand context, intent, and emotion — not just words? 🎙️ Meet Seed Speech 2.0. A new speech AI stack designed for natural, expressive conversations — with major upgrades in both text-to-speech (TTS) and speech recognition (ASR). Built for developers and creators who want natural conversational speech. What’s inside: - Natural and expressive speech generation - Prompt-controlled emotion and tone - High-accuracy multilingual recognition - Strong contextual reasoning Built for: 🎧 Voice content creation 🤖 AI assistants ☎️ Customer service 🎬 Dubbing & subtitling 📊 Audio-video analysis Voice AI built for expression, accuracy, and understanding. Try it now → Read more about Seed Speech here → #SeedSpeech #VoiceAI #SpeechAI #AI

What if voice AI could understand context, intent, and emotion — not just words? 🎙️ Meet Seed Speech 2.0. A new speech AI stack designed for natural, expressive conversations — with major upgrades in both text-to-speech (TTS) and speech recognition (ASR). Built for developers and creators who want natural conversational speech. What’s inside: - Natural and expressive speech generation - Prompt-controlled emotion and tone - High-accuracy multilingual recognition - Strong contextual reasoning Built for: 🎧 Voice content creation 🤖 AI assistants ☎️ Customer service 🎬 Dubbing & subtitling 📊 Audio-video analysis Voice AI built for expression, accuracy, and understanding. Try it now → Read more about Seed Speech here → #SeedSpeech #VoiceAI #SpeechAI #AI

BytePlus

19,840 Aufrufe • vor 5 Monaten

Day 1 of 3 MLX Releases: Introducing MLX-Audio 🚀🔥 A text-to-speech (TTS) and Speech-to-Speech (STS) library built on Apple's MLX framework, providing efficient speech synthesis on Apple Silicon. Features ⚡️Fast inference on Apple Silicon (M series chips) 🤖Multiple language support 🗣️Voice customization options 🚀Quantization support for optimized performance Supported models: 🪶Kokoro - A multilingual TTS model with 82M params that supports various languages and voice styles. With more models coming soon. Get started: > pip install mlx-audio Please leave us a star and send a PR :)

Day 1 of 3 MLX Releases: Introducing MLX-Audio 🚀🔥 A text-to-speech (TTS) and Speech-to-Speech (STS) library built on Apple's MLX framework, providing efficient speech synthesis on Apple Silicon. Features ⚡️Fast inference on Apple Silicon (M series chips) 🤖Multiple language support 🗣️Voice customization options 🚀Quantization support for optimized performance Supported models: 🪶Kokoro - A multilingual TTS model with 82M params that supports various languages and voice styles. With more models coming soon. Get started: > pip install mlx-audio Please leave us a star and send a PR :)

Prince Canuma

123,553 Aufrufe • vor 1 Jahr

Today we released Meta Spirit LM — our first open source multimodal language model that freely mixes text and speech. Many existing AI voice experiences today use ASR to techniques to process speech before synthesizing with an LLM to generate text — but these approaches compromise the expressive aspects of speech. Using phonetic, pitch and tone tokens, Spirit LM models can overcome these limitations for both inputs and outputs to generate more natural sounding speech while also learning new tasks across ASR, TTS and speech classification. We hope that sharing this work will enable the research community to further new approaches for text and speech integration.

Today we released Meta Spirit LM — our first open source multimodal language model that freely mixes text and speech. Many existing AI voice experiences today use ASR to techniques to process speech before synthesizing with an LLM to generate text — but these approaches compromise the expressive aspects of speech. Using phonetic, pitch and tone tokens, Spirit LM models can overcome these limitations for both inputs and outputs to generate more natural sounding speech while also learning new tasks across ASR, TTS and speech classification. We hope that sharing this work will enable the research community to further new approaches for text and speech integration.

AI at Meta

351,764 Aufrufe • vor 1 Jahr

✨ Personal AI is the next computing platform. AI is shifting from something you access to something you build with, locally, at the edge, and across systems. We’re unlocking new possibilities for developers: • AMD Ryzen AI Halo, a local-first developer system, preorder starting in June, develop AI without limits on your desk • Gorgon Halo with up to 192GB unified memory, supporting 300B+ parameter models locally, run massive models locally We’re excited to partner with clem 🤗🤗, Co-founder and CEO of Hugging Face, to advance open-source AI for Ryzen AI. Our focus is seamless AI, from model to deployment. Cloud, edge, device. One continuum. Multi-agent systems, local inference at scale, open models as infrastructure. This is the next computing era 🚀

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Jack Huynh

49,619 Aufrufe • vor 3 Monaten

AI + robotics research is starting to pick up steam. We can now instruct Spot using natural language using Language-guided Skill Coordination (LSC). A user provides a natural language instruction: "Bring me the chocolates box, cereal box, and pill bottle, and put them on the bedroom table" and the robot navigates to the location of the target objects and places them on the room table. Current versions of Spot rely on a fixed-set vocabulary that cannot generalize to diverse instructions. In this demo, the researchers presented a method that uses large language models to receive a free-form natural language instruction for object rearrangement, which it then executes. It combines: -A voice-to-text model that processes the instructions into text -An LLM that converts natural language instruction to call a library of skills -A perception module that provides ground truth locations and visual object detection And what your left with is a glimpse into what our future will hold: robots executing tasks from human voice prompts.

AI + robotics research is starting to pick up steam. We can now instruct Spot using natural language using Language-guided Skill Coordination (LSC). A user provides a natural language instruction: "Bring me the chocolates box, cereal box, and pill bottle, and put them on the bedroom table" and the robot navigates to the location of the target objects and places them on the room table. Current versions of Spot rely on a fixed-set vocabulary that cannot generalize to diverse instructions. In this demo, the researchers presented a method that uses large language models to receive a free-form natural language instruction for object rearrangement, which it then executes. It combines: -A voice-to-text model that processes the instructions into text -An LLM that converts natural language instruction to call a library of skills -A perception module that provides ground truth locations and visual object detection And what your left with is a glimpse into what our future will hold: robots executing tasks from human voice prompts.

AI Breakfast

33,725 Aufrufe • vor 3 Jahren

Can a $175 board power an offline robot voice assistant? 🤖 It’s cool to see Gemma 4 E2B powering the Reachy Mini robot entirely locally on a Raspberry Pi 5. Inference powered by LiteRT, it handles low latency voice, vision (YOLO) and robot movement completely offline. With text generation 2x normal human speech (~300 words per minute) on just 1.5GB of memory, the Pi 5 + Gemma 4 + LiteRT combo is a demonstration of how lean edge AI can be!

Can a $175 board power an offline robot voice assistant? 🤖 It’s cool to see Gemma 4 E2B powering the Reachy Mini robot entirely locally on a Raspberry Pi 5. Inference powered by LiteRT, it handles low latency voice, vision (YOLO) and robot movement completely offline. With text generation 2x normal human speech (~300 words per minute) on just 1.5GB of memory, the Pi 5 + Gemma 4 + LiteRT combo is a demonstration of how lean edge AI can be!

Google Gemma

30,188 Aufrufe • vor 16 Tagen

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

David Shapiro (L/0)

48,002 Aufrufe • vor 1 Jahr

With Invincible Voice, we help people living with ALS communicate more easily. Encountering Olivier Goy, an entrepreneur who lives with ALS and relentlessly fights to help all patients, made it obvious that our cutting-edge voice AI should help. We turned our Unmute voice-wrapper into a new system that 1/ transcribes interlocutor’s speech in real time, 2/ suggests various relevant responses via a personalised language model, 3/ utters patient's chosen response with their voice (using 10s pre-disease speech recordings). True to our philosophy, we open-source Invincible Voice, so that developers can refine the prototype, port it from French to other languages, adapt it to other conditions (aphasia, neurodegenerative diseases) and turn it into a deployable product. Its modularity also allows it to leverage technologies developed by Gradium that supports Invincible Voice by granting it free access to its multilingual speech models.

With Invincible Voice, we help people living with ALS communicate more easily. Encountering Olivier Goy, an entrepreneur who lives with ALS and relentlessly fights to help all patients, made it obvious that our cutting-edge voice AI should help. We turned our Unmute voice-wrapper into a new system that 1/ transcribes interlocutor’s speech in real time, 2/ suggests various relevant responses via a personalised language model, 3/ utters patient's chosen response with their voice (using 10s pre-disease speech recordings). True to our philosophy, we open-source Invincible Voice, so that developers can refine the prototype, port it from French to other languages, adapt it to other conditions (aphasia, neurodegenerative diseases) and turn it into a deployable product. Its modularity also allows it to leverage technologies developed by Gradium that supports Invincible Voice by granting it free access to its multilingual speech models.

kyutai

11,106 Aufrufe • vor 7 Monaten

What if your voice AI could interrupt you the moment it figured out your question - sometimes even before you finished asking it? Last week, I sat down with Neil, CEO of Gradium and co-founder of Kyutai , to talk about the future of speech-to-speech models and why he believes today's cascaded voice systems will soon look "archaic and brittle." Some highlights from our conversation: 🎯 How Kyutai built Moshi—a full duplex conversational AI with "negative latency"—in 6 months with just 4-6 people (while big tech teams had 10-20x the resources) 🧠 Why speech-to-speech models lose intelligence compared to their text counterparts (and what's being done about it) 📱 Pocket TTS: The first voice cloning model that runs on your phone's CPU—not GPU, CPU 🤖 Why robotics and spatial audio represent the next frontier (hint: current voice systems completely break in these environments) 👶 The efficiency gap: Babies learn to speak fluently from <5,000 hours of audio. Current models train on millions of hours. We're doing something wrong. My favorite vision from Neil? The first truly contrarian AI that interrupts you mid-sentence to tell you why you're wrong. Not just more natural conversation—but actually useful for testing ideas and playing devil's advocate. Full episode and detailed blog post linked in the comments 👇 What's your take - will speech-to-speech replace cascaded systems, or will modularity keep cascaded architectures dominant even as naturalness improves?

What if your voice AI could interrupt you the moment it figured out your question - sometimes even before you finished asking it? Last week, I sat down with Neil, CEO of Gradium and co-founder of Kyutai , to talk about the future of speech-to-speech models and why he believes today's cascaded voice systems will soon look "archaic and brittle." Some highlights from our conversation: 🎯 How Kyutai built Moshi—a full duplex conversational AI with "negative latency"—in 6 months with just 4-6 people (while big tech teams had 10-20x the resources) 🧠 Why speech-to-speech models lose intelligence compared to their text counterparts (and what's being done about it) 📱 Pocket TTS: The first voice cloning model that runs on your phone's CPU—not GPU, CPU 🤖 Why robotics and spatial audio represent the next frontier (hint: current voice systems completely break in these environments) 👶 The efficiency gap: Babies learn to speak fluently from <5,000 hours of audio. Current models train on millions of hours. We're doing something wrong. My favorite vision from Neil? The first truly contrarian AI that interrupts you mid-sentence to tell you why you're wrong. Not just more natural conversation—but actually useful for testing ideas and playing devil's advocate. Full episode and detailed blog post linked in the comments 👇 What's your take - will speech-to-speech replace cascaded systems, or will modularity keep cascaded architectures dominant even as naturalness improves?

Brooke Hopkins

13,000 Aufrufe • vor 6 Monaten

📣 Partnership Announcement: Solidus AI Tech and SambaNova Systems ✨ We are excited to announce a strategic partnership with SambaNova, a distinguished Silicon Valley unicorn valued at $5 billion and recognized for developing the world's fastest AI-specialized chips. This collaboration will significantly enhance our AI Marketplace by providing unparalleled AI inferencing and training capabilities, solidifying our position as a leader in industry innovation. SambaNova’s advanced technology will bring several key benefits to our HPC Data Center: 🔹 Powering a significant portion of our infrastructure with their cutting-edge RDUs. 🔹 Achieving up to 80% energy savings compared to traditional systems. 🔹 Supporting AI models with up to 5 trillion parameters per SambaNova Node. 🔹 Setting a new benchmark for AI infrastructure performance.

📣 Partnership Announcement: Solidus AI Tech and SambaNova Systems ✨ We are excited to announce a strategic partnership with SambaNova, a distinguished Silicon Valley unicorn valued at $5 billion and recognized for developing the world's fastest AI-specialized chips. This collaboration will significantly enhance our AI Marketplace by providing unparalleled AI inferencing and training capabilities, solidifying our position as a leader in industry innovation. SambaNova’s advanced technology will bring several key benefits to our HPC Data Center: 🔹 Powering a significant portion of our infrastructure with their cutting-edge RDUs. 🔹 Achieving up to 80% energy savings compared to traditional systems. 🔹 Supporting AI models with up to 5 trillion parameters per SambaNova Node. 🔹 Setting a new benchmark for AI infrastructure performance.

AITECH CLOUD NETWORK

124,303 Aufrufe • vor 1 Jahr

Introducing Lightning V3 - it beats every model we tested against. ElevenLabs, Cartesia, OpenAI. Lightning sets a new SOTA with V3 in conversational text-to-speech. → Highest MOS score for conversational TTS at 3.9 → ~76% win rate vs gpt-4o-mini-tts on naturalness → 15 languages with mid-sentence code-switching → Built from scratch for voice agents, not read-aloud Every TTS model sounds clean in a demo. You type a sentence and you get beautiful audio. Voice agents don't work that way. They stream. They're generating audio in real-time chunks with half the context missing. That's where everything breaks. A great reading voice and a great conversational voice are fundamentally different things. A conversational voice has to sound like it's thinking - with the pauses, the rhythm shifts, the reactions. It has to handle the way real people actually talk, including switching languages mid-sentence. That's what V3 does. V3.1 also ships voice cloning. 5 to 15 seconds of audio, no fine-tuning, production-grade clone across 15 languages. Blog link in the comments.

Introducing Lightning V3 - it beats every model we tested against. ElevenLabs, Cartesia, OpenAI. Lightning sets a new SOTA with V3 in conversational text-to-speech. → Highest MOS score for conversational TTS at 3.9 → ~76% win rate vs gpt-4o-mini-tts on naturalness → 15 languages with mid-sentence code-switching → Built from scratch for voice agents, not read-aloud Every TTS model sounds clean in a demo. You type a sentence and you get beautiful audio. Voice agents don't work that way. They stream. They're generating audio in real-time chunks with half the context missing. That's where everything breaks. A great reading voice and a great conversational voice are fundamentally different things. A conversational voice has to sound like it's thinking - with the pauses, the rhythm shifts, the reactions. It has to handle the way real people actually talk, including switching languages mid-sentence. That's what V3 does. V3.1 also ships voice cloning. 5 to 15 seconds of audio, no fine-tuning, production-grade clone across 15 languages. Blog link in the comments.

Sudarshan Kamath

71,298 Aufrufe • vor 5 Monaten

How can LLMs help improve local government services? This is the end of “Please listen closely as our menu options may have changed”: Lizzie Siegle’s team built a superset of San Francisco’s 311 service - which routes all residents through a massive, confusing and slow phone tree - all replaced by a simple natural language phone call with an AI agent as first line of response. voice to text, text to voice, all in a one day hackathon. Para Español, no necesita oprima numero dos.

How can LLMs help improve local government services? This is the end of “Please listen closely as our menu options may have changed”: Lizzie Siegle’s team built a superset of San Francisco’s 311 service - which routes all residents through a massive, confusing and slow phone tree - all replaced by a simple natural language phone call with an AI agent as first line of response. voice to text, text to voice, all in a one day hackathon. Para Español, no necesita oprima numero dos.

swyx

134,498 Aufrufe • vor 2 Jahren

World Labs CEO Dr. Fei-Fei Li says AI must change how we teach and evaluate students: "AI must change learning. AI must change K-16 learning." "The most precious resource of our entire world is human capital." "When we have gotten the technology that can answer standardized tests... when AI can do better than an average human, it's not about humans are bad. It's about we need to change the education system." "We need to change how we evaluate. We need to change the way we empower teachers to educate the next generation of students where they can use these tools, be empowered, and do things that we can never imagine." "All of the kids today should not be scared of AI. They should feel the human agency to lead AI, to use AI in the right way, and to use AI to make the impact that they want to make for the world." Fei-Fei Li at Bloomberg Tech live with Emily Chang

World Labs CEO Dr. Fei-Fei Li says AI must change how we teach and evaluate students: "AI must change learning. AI must change K-16 learning." "The most precious resource of our entire world is human capital." "When we have gotten the technology that can answer standardized tests... when AI can do better than an average human, it's not about humans are bad. It's about we need to change the education system." "We need to change how we evaluate. We need to change the way we empower teachers to educate the next generation of students where they can use these tools, be empowered, and do things that we can never imagine." "All of the kids today should not be scared of AI. They should feel the human agency to lead AI, to use AI in the right way, and to use AI to make the impact that they want to make for the world." Fei-Fei Li at Bloomberg Tech live with Emily Chang

a16z

81,845 Aufrufe • vor 2 Monaten

How did a tiny, scrappy team build one of the most powerful AI voice models? In a deep dive with Sesame CTO Ankit Kumar and a16z's Anjney Midha, we explore how Sesame is pushing the boundaries of AI conversation, why it open-sourced its speech generation model, and the power of small teams to outdo much larger AI labs on product focus. A part of their secret: a relentless focus on real-time, natural conversations over raw intelligence, and a deep commitment to voice, personality, and user experience. By opening up its speech generation model, Sesame is paving the way for even more breakthroughs in AI-native conversation 👇

How did a tiny, scrappy team build one of the most powerful AI voice models? In a deep dive with Sesame CTO Ankit Kumar and a16z's Anjney Midha, we explore how Sesame is pushing the boundaries of AI conversation, why it open-sourced its speech generation model, and the power of small teams to outdo much larger AI labs on product focus. A part of their secret: a relentless focus on real-time, natural conversations over raw intelligence, and a deep commitment to voice, personality, and user experience. By opening up its speech generation model, Sesame is paving the way for even more breakthroughs in AI-native conversation 👇

a16z

29,930 Aufrufe • vor 1 Jahr

🤖Neurai AI Chat: New version We have updated our AI chat to improve its performance with mobiles and tablets. It has also been updated with a free LLM selector. With a mobile phone, a chrome based browser and by selecting llama 3.2 1B, it is possible to have an AI in your pocket. ✨Why is an AI chat necessary for Neurai? The value of running an AI locally is very important to avoid exposing our information to large corporations and allows autonomy to anyone. With a cell phone it is possible to improve in programming, translate between languages, find information without advertising and have a small AI agent in your pocket. ✨Integration at Neurai In the future, we will add a feature that will allow to anchor a Neurai wallet to the chat and extend the information between different devices such as IoT equipment through the blockchain's own encryption systems. #Neurai #XNA #AI #IoT #DePin #RWA If you want to try our chat on your cell phone, the link is in the next post 👇👇👇

🤖Neurai AI Chat: New version We have updated our AI chat to improve its performance with mobiles and tablets. It has also been updated with a free LLM selector. With a mobile phone, a chrome based browser and by selecting llama 3.2 1B, it is possible to have an AI in your pocket. ✨Why is an AI chat necessary for Neurai? The value of running an AI locally is very important to avoid exposing our information to large corporations and allows autonomy to anyone. With a cell phone it is possible to improve in programming, translate between languages, find information without advertising and have a small AI agent in your pocket. ✨Integration at Neurai In the future, we will add a feature that will allow to anchor a Neurai wallet to the chat and extend the information between different devices such as IoT equipment through the blockchain's own encryption systems. #Neurai #XNA #AI #IoT #DePin #RWA If you want to try our chat on your cell phone, the link is in the next post 👇👇👇

NeurAI Project / XNA

13,561 Aufrufe • vor 1 Jahr

Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬 We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. The key contributions of our work are: 🕹️ Enables the exploration of different training algorithms for AI Research Agents such as RL 🛠️ Provides a flexible evaluation framework that can accommodate different artifacts such as models, algorithms, or predictions 🤖 Allows researchers to evaluate any model without the need to develop a custom agentic harness 🎯 Introduces 13 diverse open-ended AI Research tasks for evaluating AI Research Agents on a wide range of domains such as computer vision, natural language processing, reinforcement learning, game theory, and logical reasoning. 📈 Proposes a new evaluation metric for AI Research Agents MLGym makes it easy to: 1) Add new tasks 2) Evaluate new models 3) Integrate new agents Check out a video of the MLGym Agent to see how it performs the full pipeline of idea generation💡, implementation 👩‍💻, experimentation 👩‍🔬, and iteration 🔄 to improve on ML tasks. Huge thanks to the exceptionally talented Deepak Nathani who led this work and to all the other amazing collaborators who made this possible 🙏🫶🚀

Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬 We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. The key contributions of our work are: 🕹️ Enables the exploration of different training algorithms for AI Research Agents such as RL 🛠️ Provides a flexible evaluation framework that can accommodate different artifacts such as models, algorithms, or predictions 🤖 Allows researchers to evaluate any model without the need to develop a custom agentic harness 🎯 Introduces 13 diverse open-ended AI Research tasks for evaluating AI Research Agents on a wide range of domains such as computer vision, natural language processing, reinforcement learning, game theory, and logical reasoning. 📈 Proposes a new evaluation metric for AI Research Agents MLGym makes it easy to: 1) Add new tasks 2) Evaluate new models 3) Integrate new agents Check out a video of the MLGym Agent to see how it performs the full pipeline of idea generation💡, implementation 👩‍💻, experimentation 👩‍🔬, and iteration 🔄 to improve on ML tasks. Huge thanks to the exceptionally talented Deepak Nathani who led this work and to all the other amazing collaborators who made this possible 🙏🫶🚀

Roberta Raileanu

105,104 Aufrufe • vor 1 Jahr

Text to Sound Effects is here. Our newest AI Audio model generates sound effects, short instrumental tracks, soundscapes, and a wide variety of character voices, all from a text prompt. Available now for all users. Everyone from content creators, video game developers, to film and television studios, uses sound effects to create rich and immersive content. Now, in addition to AI voiceovers, you can generate all of the sounds you need with just a prompt. Everything you hear in this video was generated by ElevenLabs sound and voice models. In this thread, we shared some additional clips that help show off the range of this new model.

Text to Sound Effects is here. Our newest AI Audio model generates sound effects, short instrumental tracks, soundscapes, and a wide variety of character voices, all from a text prompt. Available now for all users. Everyone from content creators, video game developers, to film and television studios, uses sound effects to create rich and immersive content. Now, in addition to AI voiceovers, you can generate all of the sounds you need with just a prompt. Everything you hear in this video was generated by ElevenLabs sound and voice models. In this thread, we shared some additional clips that help show off the range of this new model.

ElevenLabs

450,763 Aufrufe • vor 2 Jahren