Best AI Models in Brazil - Page 15
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Compare the Top AI Models in Brazil as of July 2026 - Page 15
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1
SWE-1.6
Cognition
SWE-1.6 is an engineering–focused AI model developed by Cognition and integrated into the Devin (Windsurf) environment, designed to optimize both raw intelligence and what the company calls “model UX,” or the overall feel and efficiency of interacting with an AI agent. It represents a new iteration in the SWE model family, improving performance on benchmarks such as SWE-Bench Pro by over 10% compared to SWE-1.5 while maintaining similar underlying capabilities. It was trained from scratch to jointly improve reasoning quality and user experience, addressing issues observed in earlier versions such as overthinking simple problems, taking too many steps, looping in repetitive reasoning, and relying excessively on terminal commands instead of specialized tools. SWE-1.6 introduces behavioral improvements such as more frequent parallel tool usage, faster context retrieval, and reduced need for user input, resulting in smoother and more efficient workflows. -
2
Gemini Robotics-ER 1.6
Google DeepMind
Gemini Robotics-ER 1.6 is a family of AI models developed by Google DeepMind to bring advanced multimodal intelligence into the physical world by enabling robots to perceive, reason, and act in real-world environments. Built on the Gemini 2.0 foundation, it extends traditional AI capabilities by adding physical action as an output modality, allowing robots to interpret visual input and natural language instructions and convert them directly into motor commands to complete tasks. It includes a vision-language-action model that processes images and instructions to execute tasks, as well as a complementary embodied reasoning model (Gemini Robotics-ER) that specializes in spatial understanding, planning, and decision-making within physical environments. These models enable robots to generalize across new situations, objects, and environments, allowing them to perform complex, multi-step tasks even if they were not explicitly trained for them. -
3
GPT-Rosalind
OpenAI
GPT-Rosalind is a purpose-built frontier reasoning model developed by OpenAI to accelerate scientific research across biology, drug discovery, and translational medicine. It is designed specifically for life sciences workflows, where researchers must navigate large volumes of literature, experimental data, and specialized databases to generate and validate new ideas. It combines deep domain understanding in areas such as chemistry, genomics, protein engineering, and disease biology with advanced tool-use capabilities, allowing it to interact with scientific databases, analyze experimental outputs, and support complex, multi-step reasoning tasks. It can assist with evidence synthesis, hypothesis generation, literature review, sequence interpretation, and experimental planning, helping scientists move faster from raw data to actionable insights. GPT-Rosalind transforms complex, time-intensive research processes into more efficient AI-assisted workflows. -
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GLM-Image
Z.ai
GLM-Image is a next-generation, open source image generation model developed by Z.ai, designed to combine deep language understanding with high-fidelity visual synthesis. Unlike traditional diffusion-only models, it uses a hybrid architecture that integrates an autoregressive language model with a diffusion decoder, enabling it to first reason about the structure, meaning, and relationships within a prompt before generating the image itself. This approach allows GLM-Image to excel in scenarios that require precise semantic control, such as generating infographics, presentation slides, posters, and diagrams with accurate embedded text and complex layouts. With a total of around 16 billion parameters, the model achieves strong performance in rendering readable, correctly placed text within images, an area where many image models struggle, while maintaining detailed visual quality and consistency. -
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Qwen3.6
Alibaba
Qwen3.6 is a large language model developed by Alibaba as part of its Qwen AI model family, designed for real-world applications and advanced reasoning tasks. It focuses on improving stability, usability, and performance compared to earlier versions. The model supports multimodal capabilities, allowing it to process and reason across text, images, and other data types. Qwen3.6 is particularly strong in coding and developer workflows, offering improved accuracy for complex programming tasks. It uses a mixture-of-experts architecture, enabling efficient performance while maintaining large-scale model capabilities. The model is designed to be deployable in production environments, including enterprise and cloud-based systems. It can be integrated into applications or run locally using open-weight variants. Overall, Qwen3.6 delivers a powerful, efficient, and versatile AI solution for modern use cases.Starting Price: Free -
6
Odyssey-2 Max
Odyssey
Odyssey-2 Max is a scaled, real-time world simulation model designed to move beyond traditional generative AI by learning how the physical world behaves and enabling continuous, interactive environments. It represents the third and most advanced model in the Odyssey-2 family, significantly increasing scale with three times the parameters and ten times the training compute compared to Odyssey-2 Pro, which unlocks new emergent behaviors and more stable, realistic simulations. It is built to simulate physics, human motion, interaction, and environmental dynamics in real time, generating continuous streams of visual output that respond instantly to user input instead of producing fixed clips. Unlike conventional video models that generate short, precomputed sequences, Odyssey-2 Max produces long-running simulations that evolve frame by frame, allowing users to interact with the environment as it unfolds. -
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Wan2.7 VideoEdit
Alibaba
Wan2.7 VideoEdit, available in Alibaba Cloud Model Studio, is an instruction-based AI video editing model designed to transform existing video content through natural language commands while preserving the original structure and motion. Instead of generating videos from scratch, it allows users to upload a source clip and describe desired changes such as modifying backgrounds, adjusting lighting, altering colors, applying stylistic transformations, or even changing elements like clothing, enabling iterative refinement without restarting the creative process. As part of the broader Wan2.7 multimedia system, it integrates seamlessly with other capabilities, including text-to-video, image-to-video, and reference-based generation, forming a unified workflow that supports creation, editing, continuation, and reshaping of visual content. The model emphasizes high-quality output with improved motion smoothness, visual coherence, and support for HD formats.Starting Price: $0.1 per second -
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GPT-5.5 Instant
OpenAI
GPT-5.5 Instant is ChatGPT’s updated default model, designed to be smarter and more accurate, with clearer, more concise answers that feel better tailored to each user. Built as a daily driver for hundreds of millions of people, this update makes everyday interactions more useful and enjoyable through stronger and tighter answers across subject areas, a more natural conversational tone, and better use of shared context when personalization can help. GPT-5.5 Instant is more dependable, with significant improvements in factuality, especially in domains where accuracy matters most, including medicine, law, and finance. It is more capable across everyday tasks, with improvements in analyzing photo and image uploads, answering STEM-related questions, and deciding when to use web search to provide a more useful answer. Responses are tighter and more to the point without losing substance, while keeping the warmth and personality that makes ChatGPT enjoyable to use. -
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GPT-5.5-Cyber
OpenAI
GPT-5.5-Cyber is an advanced cybersecurity-focused AI model designed for verified defenders working on authorized security research, vulnerability discovery, and remediation. The model pairs stronger cyber capabilities with more permissive behavior for specialized workflows that require deep analysis across complex software environments. It can help identify security-relevant components, trace vulnerable code paths, validate likely issues in controlled settings, develop and test patches, and prepare evidence for human review. GPT-5.5-Cyber is built to support the full remediation loop rather than simply generating more findings. The model shows stronger benchmark performance than GPT-5.5 on CyberGym, ExploitGym, and SEC-bench Pro, reflecting improvements in vulnerability reproduction, exploit reasoning, and long-horizon security tasks. GPT-5.5-Cyber is intended for advanced, authorized cybersecurity work with verification, monitoring, scoped controls, and review. -
10
Reactor
Reactor
Reactor is building the missing layer for world models and invites users to experience real-time world models through an early preview. Its product direction centers on worlds generated in real time, where pixels, sounds, and actions can be produced on the fly, changing how people interact with software and, eventually, the physical world. The preview is the first step toward that reality, letting users experience AI-generated worlds running on global low-latency infrastructure. Reactor’s work is focused on the next frontier of AI, real-time world models that people, agents, and robots can drive frame by frame. Rather than treating generated video as something passive to watch, Reactor points toward interactive environments that can be inhabited, controlled, and shaped as they generate. Its research and product focus includes real-time interactivity, inference, controllable world models, and systems that make dynamic visual environments responsive enough for live experiences.Starting Price: Free -
11
Lumen Outpost
Cosine
Lumen Outpost is Cosine’s targeted post-trained coding model, benchmarked against Kimi K2.6, its base model, GPT-5.5, GPT-5.4, and Gemini 3.1 Pro on highly complex, long-horizon coding tasks across 13 programming languages. The model is specialized not only for raw coding accuracy, but also for behavioral signals that matter in professional engineering workflows, including agent initiative, planning, scope discipline, action alignment, concise updates, and useful communication. Cosine’s benchmark report shows that highly targeted post-training transformed the base model’s capabilities, with Lumen Outpost outperforming Kimi K2.6 across Niche-Bench, Slop-Bench, Vibe-Bench, and cost per successful task. On Niche-Bench, an internal evaluation for niche, legacy, and environment-constrained programming languages, Lumen Outpost achieved a 53.9% score and led or tied in 9 of 13 assessed languages, with notable gains in Fortran, ABAP, Java, and Rust.Starting Price: $20 per month -
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MiniMax Speech 2.8
MiniMax
MiniMax Speech 2.8 is a next-generation AI speech model built to make synthetic voice feel alive, expressive, and deeply human. It focuses on performance in real-world voice agent scenarios, combining ultra-fast response, richer emotional expression, cleaner audio, and stronger cross-lingual performance for products that need natural spoken interaction. Speech 2.8 is designed to reduce the distance between AI voice and real human communication, giving developers and creators more control over how a voice sounds, reacts, and carries meaning. It supports flexible emotion control, allowing users to shape delivery with moods, tone, and expressive direction instead of relying on flat or robotic speech. It can produce speech with more natural pauses, cadence, emphasis, and emotional texture, helping AI characters, assistants, narrators, and interactive agents sound more believable across longer conversations. -
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MiniMax Music 2.6
MiniMax
MiniMax Music 2.6 is an AI music generation model designed to help users create expressive, controlled, and production-ready music from natural language prompts. Instead of presenting the model only through technical specs, MiniMax describes Music 2.6 through real creative scenarios: a flamenco dancer building a solo track with dramatic pauses, an indie game developer scoring a boss fight with powerful low-end, a cafe owner creating a playlist with the right mood, and a daughter making a personalized cover version of a familiar song. It focuses on musical details that matter in real use, including tension, silence, rhythm, emotional build, low-frequency impact, imperfect vocals, melody feel, and genre transformation. Music 2.6 improves instruction control so users can include BPM, key, song structure, emotional arc, and specific creative direction directly in a prompt, with the model following those requirements more accurately. -
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CogVideoX-3
Z.ai
CogVideoX-3 is a video generation model with new frame generation capabilities that significantly improve image stability and clarity. It delivers superior performance when handling subjects with significant movement, better adheres to instructions, and provides more realistic simulations. It supports image, text, and start-and-end-frame inputs, with video as the output modality, making it useful across text-to-video, image-to-video, and transition-based video workflows. CogVideoX-3 can be used for advertising and marketing by inputting product images or copy to quickly generate dynamic ads in multiple styles, supporting scene transitions and realistic lighting rendering. It also supports short video creation by converting single-frame images or text scripts into smooth, naturally animated short videos, covering both realistic and 3D styles. For tourism promotion, users can upload scenic spot photos and promotional text to generate immersive short videos.Starting Price: $0.2 per video -
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Ray3.2
Luma AI
Ray3.2 transforms creative intent into scalable video workflows with richer control, continuity, and cinematic direction. Built to help teams direct any frame and finish every cut, Ray3.2 brings direction, performance, transformation, motion, and finish into a single model at cinematic-grade quality. Multi-Keyframe lets users set up to 16 keyframes inside a single clip, directing what changes, what holds, and how the story lands, frame by frame. Modify Video V2 reshapes existing footage into new stories, allowing teams to swap the wall, the world, or the wardrobe while lighting holds and performance survives, with up to 20 seconds at 1080p. Reframe helps create once and deliver everywhere, handling every aspect ratio, while improved Motion Transfer keeps choreography and Expressive Facial Performance preserves the actor’s read. Ray3.2 can transfer movement and dynamics across characters, objects, and materials; transfer cinematic camera moves across scenes, worlds, and styles.Starting Price: $30 per month -
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Starchild-1
Odyssey
Starchild-1 is the first real-time multimodal world model, built to simulate both the visuals and sounds of the world in real time. Unlike language models, which learn from text, world models learn directly from the world itself through pixels, motion, and actions encoded in large-scale video, becoming capable of understanding and simulating an approximation of the world as it evolves. Starchild-1 goes beyond traditional world models, which have mostly focused on visual generation alone, by autoregressively generating synchronized audio and video while continuously responding to streaming user input. Instead of producing a fixed offline clip, it predicts the next audio and video state of a world based on past observations and live inputs, enabling environments, conversations, ambient sound, and world dynamics to change interactively. Users can stream text, speech, and action inputs into the model during rollout, dynamically altering what is seen and heard in real time. -
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Agora-1
Odyssey
Agora-1 is a multi-agent world model that enables multiple participants, human or AI, to share and interact within the same world simulation in real time. It is the first in a series of multi-agent world models exploring how world models can enable new shared experiences across gaming, robotics, defense, education, foundation models, and more. World models generate high-fidelity simulations of arbitrary environments, but until now, they have largely been limited to a single active participant inside those simulated worlds. Agora-1 introduces multi-agent world simulations by allowing up to four players to interact in the same generated world at once. Players are matched into a shared deathmatch simulation, where every participant interacts with the same world simultaneously while the model simulates player actions, maintains shared world state, and streams generated pixels to each player. -
18
Grok Imagine Video 1.5
SpaceXAI
Grok Imagine Video 1.5 is xAI’s improved image-to-video model, built for better quality at faster speeds. Now generally available on the Imagine API as grok-imagine-video-1.5, it gives creators and developers a way to start from an image, describe the motion, and choose the resolution and duration for the generated video. Grok Imagine Video 1.5 and Video 1.5 Fast are described as xAI’s best image-to-video models yet, with better motion, better physics, better audio, and faster generation for real creative work. Audio and speech are generated in the same pass as the visuals, so sound effects, ambience, and dialogue land on the action, while speech is clearer and better synchronized. Motion and physics are also improved, helping movement hold together across the length of a clip with fewer warps and more believable weight and momentum. Grok Imagine Video 1.5 Fast almost doubles generation speed, producing 6-second, 720p videos in about 25 seconds. -
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Sakana Fugu Ultra
Sakana AI
Sakana Fugu Ultra is the higher-performance version of Sakana Fugu, built to coordinate a deeper pool of expert AI agents for demanding, high-stakes tasks. The model operates through a single OpenAI-compatible API while dynamically orchestrating multiple powerful models behind the scenes. It is designed to maximize answer quality for complex workflows such as coding, code review, paper reproduction, cybersecurity analysis, scientific reasoning, patent investigation, and autonomous research. Fugu Ultra uses learned orchestration techniques to assemble, route, and coordinate agents instead of relying on hand-designed workflows or a single frontier model. Users can access advanced multi-agent intelligence without manually managing separate models, prompts, or collaboration patterns. Sakana Fugu Ultra is built for teams that need stronger performance, deeper reasoning, and more reliable results on difficult multi-step problems.Starting Price: $20 per month -
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Mistral OCR 4
Mistral AI
Mistral OCR 4 is a document extraction and understanding model built for enterprise search, RAG, domain-specific retrieval pipelines, and production-grade document intelligence. It extracts and structures content from a wide range of documents, moving beyond clean text and tables to return a structured representation of each page. Alongside extracted text, OCR 4 provides bounding boxes, typed-block classification, and inline confidence scores, helping downstream systems understand not only what the document says, but where each element sits, what role it plays, and how confident the model is in each region. Bounding boxes make in-context highlighting and reliable data pipelines possible, while block types and confidence scores support source-grounded citations, redactions, and human-in-the-loop verification. OCR 4 accepts common enterprise formats, including PDF, DOC, PPT, and OpenDocument, and supports 170 languages across 10 language groups.Starting Price: $2 per 1000 pages -
21
Ling 2.6
Ant Group
Ling 2.6 is a general-purpose large language model series independently developed and open-sourced by Ant Group, built on a Mixture of Experts architecture and designed for inference efficiency, long context modeling, training technology, and AI Agent collaborative reasoning. Ling’s MoE architecture routes each token to activate only the most relevant expert subnetworks, compressing actual computation to a minimal fraction while maintaining large-scale model capacity. The Ling 2.6 series further advances long-sequence modeling, with Ling-2.6-1T supporting up to a 1M native context window and the official API exposing a 256K context window, while Ling-2.6-flash provides a native 256K context window capable of processing approximately 200,000 characters of long-form input. The models are designed for reliable long-range information retrieval, with no noticeable degradation whether information appears at the beginning, middle, or end of the context.Starting Price: $0.0028 per 1M tokens -
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Ling 2.6 Flash
Ant Group
Ling 2.6 Flash is the latest cost-effective model in the Ling series, built on a Mixture of Experts architecture with 104B total parameters and 7.4B activated parameters. It is designed to achieve an optimal balance between inference performance and compute cost, making it suitable for general-purpose scenarios where strong reasoning capability, high throughput, and efficient deployment matter. Ling’s MoE architecture routes each token to activate only the most relevant expert subnetworks, compressing actual computation to a minimal fraction while maintaining large-scale model capacity. Ling 2.6 Flash provides a native 256K context window and can process approximately 200,000 characters of long-form input, with reliable long-range information retrieval whether key information appears at the beginning, middle, or end of the context. Its aggregate benchmark performance is comparable to or exceeds 40B-class Dense models.Starting Price: $0.00037 per 1M tokens -
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Ring 2.6
Ant Group
Ring is a trillion-parameter thinking model from Ant Group, designed for real-world Agent workflows. It uses the same Mixture of Experts architecture as Ling, activating about 63B parameters per inference, and focuses on coding agents, tool use, multi-tool collaboration, engineering development, research analysis, and long-horizon task execution. Rather than only pursuing “smarter” results, Ring is built to consistently complete complex tasks at reasonable cost, balancing quality, speed, and execution efficiency in production environments. Ring-2.6-1T introduces an adjustable Reasoning Effort mechanism with high and xhigh reasoning intensity levels, using adaptive reasoning budget allocation based on task complexity. High mode is designed for high-frequency Agent workflows, lower token cost, faster multi-step execution, multi-turn interaction, tool collaboration, and task decomposition.Starting Price: $0.0028 per 1M tokens -
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Grok Speech to Text (STT)
SpaceXAI
Grok Speech to Text is a standalone audio API built to help developers integrate fast, accurate transcription into any application. Built on the same stack that powers Grok Voice, Tesla vehicles, and Starlink customer support, the API is designed for use cases such as voice agents, real-time transcription tools, accessibility solutions, podcasts, meeting capture, telephony, and interactive audio experiences. Grok STT can generate transcripts from large audio files through a REST API or transcribe speech in real time through a low-latency WebSocket API. It includes word-level timestamps, speaker diarization, multichannel support, and intelligent Inverse Text Normalization that converts spoken language into properly formatted structured output for numbers, dates, currencies, and more. Grok Speech to Text is evaluated across phone calls, meetings, video and podcast content, and telephony, with strong performance in entity recognition and business use cases. -
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Inkling
Thinking Machines Lab
Inkling is an open-weights multimodal AI model from Thinking Machines designed as a customizable foundation model for developers, researchers, and enterprises. The model is a Mixture-of-Experts transformer with 975 billion total parameters, 41 billion active parameters, and support for context windows up to 1 million tokens. Inkling was trained from scratch on text, images, audio, and video, giving it native capabilities across reasoning, coding, agentic tool use, vision, audio, factuality, and instruction following. It is built with controllable thinking effort so users can balance performance, latency, and token efficiency for different workloads. The model is available for fine-tuning on Tinker, with playground access, API availability through ecosystem partners, and full weights published on Hugging Face. Built for customization, Inkling gives teams an open-weights base model for building domain-specific AI systems, multimodal agents, coding workflows, research tools, and more.Starting Price: Free -
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Mercury 2
Inception
Mercury 2 is the first reasoning model fast enough to pick up the phone, a reasoning diffusion language model built for real-time voice agents. Instead of making callers wait through seconds of dead air while an autoregressive model generates thinking tokens one by one, Mercury 2 uses a diffusion large language model architecture to generate tokens in parallel, decoding 1000+ tokens per second on standard NVIDIA GPUs. That speed is fast enough to run a full reasoning pass and start speaking within the latency budget of a natural conversation, reducing the cost of reasoning from seconds of silence to roughly 300 milliseconds. Mercury models work by corrupting clean text into noise, then training a standard Transformer to reverse the process and predict clean text across all positions simultaneously. Because each denoising pass touches many tokens, generation uses the GPU more efficiently than one-token-at-a-time decoding, making custom-silicon-like speed possible on NVIDIA H100s. -
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Grok 4.6
SpaceXAI
Grok 4.6 is an upcoming AI model from xAI with 2 trillion parameters expected to continue the Grok model family’s focus on advanced reasoning, coding, agentic workflows, and knowledge work. While xAI has not yet published a full official product page for Grok 4.6, public reporting indicates that Elon Musk confirmed the model is in development. Grok 4.6 is likely to build on the capabilities introduced in Grok 4.5, which xAI describes as its smartest model for coding, agentic tasks, and knowledge work. The broader Grok platform supports chat, coding, image creation, real-time answers from the web and X, and API access for developers. For businesses and builders, Grok 4.6 may become relevant for software engineering, research, automation, AI agents, and productivity workflows once details are released. Built for users who want access to xAI’s newest frontier models, Grok 4.6 represents the next expected step in the company’s fast-moving AI roadmap. -
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LUIS
Microsoft
Language Understanding (LUIS): A machine learning-based service to build natural language into apps, bots, and IoT devices. Quickly create enterprise-ready, custom models that continuously improve. Add natural language to your apps. Designed to identify valuable information in conversations, LUIS interprets user goals (intents) and distills valuable information from sentences (entities), for a high quality, nuanced language model. LUIS integrates seamlessly with the Azure Bot Service, making it easy to create a sophisticated bot. Powerful developer tools are combined with customizable pre-built apps and entity dictionaries, such as Calendar, Music, and Devices, so you can build and deploy a solution more quickly. Dictionaries are mined from the collective knowledge of the web and supply billions of entries, helping your model to correctly identify valuable information from user conversations. Active learning is used to continuously improve the quality of the models. -
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OpenAI Whisper
OpenAI
Whisper is an automatic speech recognition (ASR) system developed by OpenAI for converting spoken language into text. It is trained on 680,000 hours of multilingual and multitask audio data collected from the web. The model is designed to handle diverse accents, background noise, and technical language with high accuracy. Whisper supports transcription in multiple languages as well as translation into English. It uses an encoder-decoder Transformer architecture to process audio inputs and generate text outputs. The system can also perform tasks like language identification and timestamp generation. Overall, Whisper enables developers to build robust voice-enabled applications with ease. -
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Sparrow
DeepMind
Sparrow is a research model and proof of concept, designed with the goal of training dialogue agents to be more helpful, correct, and harmless. By learning these qualities in a general dialogue setting, Sparrow advances our understanding of how we can train agents to be safer and more useful – and ultimately, to help build safer and more useful artificial general intelligence (AGI). Sparrow is not yet available for public use. Training a conversational AI is an especially challenging problem because it’s difficult to pinpoint what makes a dialogue successful. To address this problem, we turn to a form of reinforcement learning (RL) based on people's feedback, using the study participants’ preference feedback to train a model of how useful an answer is. To get this data, we show our participants multiple model answers to the same question and ask them which answer they like the most.
