←Search results

By relevance · Total 593 results Clear search

Thursday

  1. Rohan Paul

    Google DeepMind's new paper: CALLIOPE builds topic trees using keywords, outperforming embedding vectors

    A new paper from Google DeepMind proposes CALLIOPE: it has an LLM tag each document with a small number of keywords plus noise, keeps only high-frequency keywords, and then has the LLM propose topics and classify documents accordingly, thereby generating clearer topic maps under strict privacy constraints. Under the strictest privacy setting, human raters preferred CALLIOPE over the embedding-vector-based URANIA on all 3 datasets, with the highest margin being 76% versus 18%. This method consumes 2 to 5 times as many tokens as the latter.

    A new paper from Google DeepMind proposes CALLIOPE: it has an LLM tag each document with a small number of keywords plus noise, keeps only high-frequency keywords, and then has the LLM propose topics and classify documents accordingly, thereby generating clearer topic maps under strict privacy constraints. Under the strictest privacy setting, human raters preferred CALLIOPE over the embedding-vector-based URANIA on all 3 datasets, with the highest margin being 76% versus 18%. This method consume

    Matched fieldsTitle、Summary、Body

  2. Shao Meng

    Google DeepMind Previews Gemini 4 Carbon, Claiming Leadership in Cybersecurity and Long-Horizon Capabilities

    Google DeepMind has previewed its next-generation frontier model, Gemini 4 Carbon, claiming it achieves SOTA in cybersecurity and long-horizon capabilities, ranking first on the Artificial Analysis Intelligence Index v5.0 with 59 points, while Claude Opus 5.5 scored 58. The model is not yet publicly available; it will first be opened to select cybersecurity defenders and trusted partners in the Fairwind program, and will participate in the U.S. government's voluntary pre-release testing, before gradually being opened to developers, enterprises, and consumers. Introductory pricing is the same as Argon, at approximately $2 input and $10 output per million tokens, rising to approximately $4 input and $20 output after the introductory period.

    Google DeepMind has previewed its next-generation frontier model, Gemini 4 Carbon, claiming it achieves SOTA in cybersecurity and long-horizon capabilities, ranking first on the Artificial Analysis Intelligence Index v5.0 with 59 points, while Claude Opus 5.5 scored 58. The model is not yet publicly available; it will first be opened to select cybersecurity defenders and trusted partners in the Fairwind program, and will participate in the U.S. government's voluntary pre-release testing, before

    Matched fieldsTitle、Summary

  3. The DecoderSelected

    Google DeepMind releases Gemini 4 Carbon, just two weeks after Argon

    Google DeepMind launched Gemini 4 Carbon two weeks after the release of Argon. The model scored 59 on the Artificial Analysis Intelligence Index v5.0, higher than Argon's 50, ranking first. Carbon is designed for long-horizon engineering tasks, rose to 1769 points and fourth place on WebDev Arena, and reduced the attack success rate from 0.7% to 0.0% on the Gray Swan indirect prompt injection benchmark. The model is first being made available to select cybersecurity experts, priced at $2 per million input tokens and $10 per million output tokens, in line with Argon's introductory pricing.

    Google DeepMind launched Gemini 4 Carbon two weeks after the release of Argon. The model scored 59 on the Artificial Analysis Intelligence Index v5.0, higher than Argon's 50, ranking first. Carbon is designed for long-horizon engineering tasks, rose to 1769 points and fourth place on WebDev Arena, and reduced the attack success rate from 0.7% to 0.0% on the Gray Swan indirect prompt injection benchmark. The model is first being made available to select cybersecurity experts, priced at $2 per mil

    Matched fieldsTitle、Summary、Body

  4. Latent SpaceSelected

    Google DeepMind releases Gemini 4 Carbon, topping Artificial…

    Google DeepMind has released Gemini 4 Carbon, which ranks first on the Artificial Analysis Intelligence Index v5 with a score of 59 and leads in 4 of 9 evaluations including HLE-Diamond and TB-Science. The model focuses on cybersecurity and long-horizon tasks, claiming 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and is initially available only to trusted cybersecurity personnel through the Fairwind Program. In terms of specifications, it supports a 1M token context and 1M maximum output, with input covering text, images, video, and speech, and output in text; Artificial Analysis lists a standard price of $4/$20 per million input/output tokens, plus a 50% launch discount.

    Google DeepMind has released Gemini 4 Carbon, which ranks first on the Artificial Analysis Intelligence Index v5 with a score of 59 and leads in 4 of 9 evaluations including HLE-Diamond and TB-Science. The model focuses on cybersecurity and long-horizon tasks, claiming 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and is initially available only to trusted cybersecurity personnel through the Fairwind Program. In terms of specifications, it supports a 1M token context and 1

    Matched fieldsTitle、Summary、Body

  5. MarkTechPostSelected

    Google DeepMind releases Gemini 4 Carbon, focused on cybersecurity defense and coding

    Google DeepMind has launched Gemini 4 Carbon, calling it a frontier model for long-horizon agentic coding and cybersecurity defense, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0. The model achieved 96.2% on the GraphWalks long-context test, and 88.2%, 54.8%, and 71.0% on SEC-bench Pro, ExploitGym, and CWE-bench, respectively, but on OSWorld-2.1 it trailed Claude Opus 5.5's 87.2% with 81.5%. Carbon is currently available only to vetted cybersecurity defenders, with introductory pricing of $2 per million input tokens and $10 per million output tokens, later $4 and $20; the timeline for opening it to developers and the public has not been announced.

    Google DeepMind has launched Gemini 4 Carbon, calling it a frontier model for long-horizon agentic coding and cybersecurity defense, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0. The model achieved 96.2% on the GraphWalks long-context test, and 88.2%, 54.8%, and 71.0% on SEC-bench Pro, ExploitGym, and CWE-bench, respectively, but on OSWorld-2.1 it trailed Claude Opus 5.5's 87.2% with 81.5%. Carbon is currently available only to vetted cybersecurity defenders, w

    Matched fieldsTitle、Summary、Body

  6. Leiphone.com

    Leiphone.com's In-Depth Breakdown of Google DeepMind's World Model Genie 4

    Google DeepMind has released Genie 4, a new-generation world model that can generate interactive environments in real time and collaborates with Gemini 3.8 Flash through a division of labor: the latter observes the visuals, decomposes tasks, and adjusts plans. Leiphone.com analyzes its technical challenges from three aspects—dynamic language condition injection, Agent causal hallucination, and dual-model asynchronous collaboration—and notes that DeepMind has not yet disclosed the network architecture or scheduling implementation of Genie 4.

    Google DeepMind has released Genie 4, a new-generation world model that can generate interactive environments in real time and collaborates with Gemini 3.8 Flash through a division of labor: the latter observes the visuals, decomposes tasks, and adjusts plans. Leiphone.com analyzes its technical challenges from three aspects—dynamic language condition injection, Agent causal hallucination, and dual-model asynchronous collaboration—and notes that DeepMind has not yet disclosed the network archite

    Matched fieldsTitle、Summary、Body

Friday

  1. Rohan Paul

    Google DeepMind: Training models to write moral arguments makes them more decisive but does not improve judgment

    A new Google DeepMind paper found that after training Gemma-4 4B with reinforcement learning to write moral arguments, the proportion of cases where the model changed its answer on ambiguous MoralChoice cases due to a swap in option order dropped from 14.3% to 6.6%, but the proportion of sycophantic agreement with users only changed from 45.3% to 44.0%, and accuracy on moral fable questions actually fell from 56.5% to 53.4%. The paper recommends that when evaluating advice or judgment tasks, consistency and correctness be tested separately.

    A new Google DeepMind paper found that after training Gemma-4 4B with reinforcement learning to write moral arguments, the proportion of cases where the model changed its answer on ambiguous MoralChoice cases due to a swap in option order dropped from 14.3% to 6.6%, but the proportion of sycophantic agreement with users only changed from 45.3% to 44.0%, and accuracy on moral fable questions actually fell from 56.5% to 53.4%. The paper recommends that when evaluating advice or judgment tasks, con

    Matched fieldsTitle、Summary、Body

  2. Ethan Mollick

    Ethan Mollick on DeepMind's intelligence economics research: agent coordination capability is the key to economic transformation

    Ethan Mollick commented on Google DeepMind's "The Economics of Intelligence" research, pointing out that an organization is not merely the sum of its best individuals, so a single agent becoming stronger will not change the economy on its own; only agents that can work in coordination may bring about transformation. The research, released by Alex Imas, Andrew Koh, and Shane Legg, proposes two thresholds of economic capability—capability and coordination—and argues that economic transformation depends on whether AI becomes a super-strong individual, super-strong collaboration, or both.

    Ethan Mollick commented on Google DeepMind's "The Economics of Intelligence" research, pointing out that an organization is not merely the sum of its best individuals, so a single agent becoming stronger will not change the economy on its own; only agents that can work in coordination may bring about transformation. The research, released by Alex Imas, Andrew Koh, and Shane Legg, proposes two thresholds of economic capability—capability and coordination—and argues that economic transformation de

    Matched fieldsTitle、Summary

  3. Rohan Paul

    Google DeepMind paper proposes measuring AGI's economic impact using two thresholds: competence and coordination

    Google DeepMind has released the paper "The Economics of Intelligence," proposing the use of two thresholds—competence (single-task capability) and coordination (agent collaboration capability)—to characterize AGI's impact on the economy. The authors argue that AI has already shown changes in leaner startups, flatter organizational structures, and slower hiring for some entry-level positions, but that mass unemployment has not yet occurred; most benchmarks test only a single model, whereas firms compete as teams. The paper also cites a 100-person test in which groups paired for complementarity outperformed randomly paired groups by 32%, showing that AI models sharing the same weaknesses may lose to well-coordinated human teams even if they beat every individual one-on-one.

    Google DeepMind has released the paper "The Economics of Intelligence," proposing the use of two thresholds—competence (single-task capability) and coordination (agent collaboration capability)—to characterize AGI's impact on the economy. The authors argue that AI has already shown changes in leaner startups, flatter organizational structures, and slower hiring for some entry-level positions, but that mass unemployment has not yet occurred; most benchmarks test only a single model, whereas firms

    Matched fieldsTitle、Summary、Body

Wednesday

  1. The Rundown AI

    Google DeepMind releases the Genie 4 world model, which can generate sound effects and converse with characters in the scene

    Google DeepMind has released Genie 4, a new-generation world model that can turn prompts into explorable, realistic scenes in real time, and for the first time the Genie model itself generates background sounds and music, while characters in the scene can also hold real-time conversations. Users move via the keyboard and use text prompts to modify content in the scene instantly, with the scene remaining coherent across multiple inputs. In the demo, a simulated Apptronik Apollo robot plays checkers, with each move planned by Gemini 4 Argon, pointing to Genie's future use in robot training.

    Google DeepMind has released Genie 4, a new-generation world model that can turn prompts into explorable, realistic scenes in real time, and for the first time the Genie model itself generates background sounds and music, while characters in the scene can also hold real-time conversations. Users move via the keyboard and use text prompts to modify content in the scene instantly, with the scene remaining coherent across multiple inputs. In the demo, a simulated Apptronik Apollo robot plays checke

    Matched fieldsTitle、Summary、Body

  2. MarkTechPost

    Google DeepMind Releases Genie 4 Real-Time World Model with Native Audio Generation

    Google DeepMind has released the Genie 4 world model as a research preview to trusted testers; it can generate explorable worlds in real time from text and image prompts, and natively generate ambient sound, music, and character dialogue. The model introduces Gemini 3.8 Flash as a planner within the simulation loop, responsible for breaking down goals, inspecting frames, and replanning, which DeepMind calls an early step toward hybrid world models. Genie 4 is hosted only on Google's platform and will later be opened to AI Ultra users and Gemini API partners; all video and audio carry SynthID watermarks.

    Google DeepMind has released the Genie 4 world model as a research preview to trusted testers; it can generate explorable worlds in real time from text and image prompts, and natively generate ambient sound, music, and character dialogue. The model introduces Gemini 3.8 Flash as a planner within the simulation loop, responsible for breaking down goals, inspecting frames, and replanning, which DeepMind calls an early step toward hybrid world models. Genie 4 is hosted only on Google's platform and

    Matched fieldsTitle、Summary、Body

  3. Ayi AI Notes

    Google DeepMind Releases World Model Genie 4

    Google DeepMind has released the world model Genie 4, which supports real-time text-based scene modification, native ambient sound, and interactive dialogue, with Gemini 3.8 Flash serving as the real-time director in the background. The author says it no longer pre-renders video, but instead simulates physical collisions in real time and dynamically loads scenes as the player acts. Currently, the limit for a single simulation is about two minutes; over time, details will drift, and it is only a research preview available to a small number of testers.

    Google DeepMind has released the world model Genie 4, which supports real-time text-based scene modification, native ambient sound, and interactive dialogue, with Gemini 3.8 Flash serving as the real-time director in the background. The author says it no longer pre-renders video, but instead simulates physical collisions in real time and dynamically loads scenes as the player acts. Currently, the limit for a single simulation is about two minutes; over time, details will drift, and it is only a

    Matched fieldsTitle、Summary、Body

  4. AYi AI Notes

    Google DeepMind releases the world model Genie 4, supporting real-time text-based scene changes and native ambient sound

    Google DeepMind has officially released the world model Genie 4, which supports real-time text-based scene changes, comes with native ambient sound and interactive dialogue, and has Gemini 3.8 Flash serving as the behind-the-scenes director. Unlike pre-rendered video models, Genie 4 simulates physical collisions in real time as the player acts within the scene, and a single simulation can remain continuously stable for about two minutes. The author believes its real purpose is to provide a low-cost physical training ground for embodied agents, but it is currently still a research preview available to only a few testers, and details drift over time.

    Google DeepMind has officially released the world model Genie 4, which supports real-time text-based scene changes, comes with native ambient sound and interactive dialogue, and has Gemini 3.8 Flash serving as the behind-the-scenes director. Unlike pre-rendered video models, Genie 4 simulates physical collisions in real time as the player acts within the scene, and a single simulation can remain continuously stable for about two minutes. The author believes its real purpose is to provide a low-c

    Matched fieldsTitle、Summary、Body

  5. Demis Hassabis

    DeepMind Releases Interactive World Model Genie 4

    Demis Hassabis shared Google DeepMind's interactive world model Genie 4, saying it integrates real-time physics, reasoning, and audio capabilities. The official Google DeepMind account called it its most realistic and interactive world model to date, allowing real-time exploration of dynamic environments and observation of how scenes respond, produce sound, and how the people within them move, react, and speak. Hassabis also mentioned simulations nested within simulations.

    Matched fieldsTitle、Summary

  6. Google AI

    Google DeepMind Releases Genie 4 World Model

    Google DeepMind has released the Genie 4 world model, which the company calls its most realistic and interactive world model to date. Users can control scenes and soundscapes in real time using natural language, for example by changing the weather, moving the camera, or adding new elements; Gemini acts as the simulation's "brain" behind the scenes, responsible for turning requests into actions, planning complex events, and tracking changes in the scene. Genie 4 also adds ambient sound effects and interactive voice dialogue that can be adjusted in real time.

    Google DeepMind has released the Genie 4 world model, which the company calls its most realistic and interactive world model to date. Users can control scenes and soundscapes in real time using natural language, for example by changing the weather, moving the camera, or adding new elements; Gemini acts as the simulation's "brain" behind the scenes, responsible for turning requests into actions, planning complex events, and tracking changes in the scene. Genie 4 also adds ambient sound effects an

    Matched fieldsTitle、Summary、Body

  7. 36Kr · AISelected

    Google DeepMind releases the world model Genie 4, natively generating sound and dialogue for the first time

    Google DeepMind has released Genie 4, a new-generation general-purpose world model. For the first time in the Genie series, it natively generates ambient sound and improvised character dialogue, doubles the duration of a single coherent world to about 2 minutes, and renders real-machine footage at about 24 frames per second. The model uses Gemini 3.8 Flash to perform multi-step reasoning and control in the background and Gemini 4 Argon to break down action instructions, forming a hybrid world model architecture. It has opened beta applications to Google AI Ultra users and is also available in the Gemini API and Google AI Studio.

    Google DeepMind has released Genie 4, a new-generation general-purpose world model. For the first time in the Genie series, it natively generates ambient sound and improvised character dialogue, doubles the duration of a single coherent world to about 2 minutes, and renders real-machine footage at about 24 frames per second. The model uses Gemini 3.8 Flash to perform multi-step reasoning and control in the background and Gemini 4 Argon to break down action instructions, forming a hybrid world mo

    Matched fieldsTitle、Summary、Body

  8. The New Stack

    Google DeepMind releases the Genie 4 world model, providing AI agents with an interactive testing environment

    Google DeepMind has released the Genie 4 world model, which can render interactive environments in real time with simulated physics, human motion, and native audio, with Gemini Omni shaping the scenes and Gemini 3.8 Flash planning the next steps. Genie 4 lets developers generate testing environments on demand, for scenarios such as the Apptronik Apollo humanoid robot playing checkers, but Google acknowledges that its physics is not always accurate, and objects may shift or behave abnormally during long runs. Google has not yet published benchmark data for Genie 4 in repeated agent testing, including whether the same prompt can produce consistent results.

    Google DeepMind has released the Genie 4 world model, which can render interactive environments in real time with simulated physics, human motion, and native audio, with Gemini Omni shaping the scenes and Gemini 3.8 Flash planning the next steps. Genie 4 lets developers generate testing environments on demand, for scenarios such as the Apptronik Apollo humanoid robot playing checkers, but Google acknowledges that its physics is not always accurate, and objects may shift or behave abnormally duri

    Matched fieldsTitle、Summary、Body

  9. Google DeepMindSelected

    Google DeepMind releases world model Genie 4, supporting native audio and real-time interaction

    Google DeepMind has released the world model Genie 4, which can generate interactive worlds in real time and, for the first time, natively generate ambient sound and character dialogue. The model builds on capabilities from the Gemini series; Gemini 3.8 Flash breaks down goals in a loop and checks frames to maintain causal coherence across multi-step events, and Gemini 4 Argon has also been used for joint simulation tasks with Gemini Robotics. The company says it remains an early experimental model: over long runs, object permanence and complex physical interactions still drift, all generated content carries a SynthID watermark, and it is currently available in preview to trusted testers first.

    Google DeepMind has released the world model Genie 4, which can generate interactive worlds in real time and, for the first time, natively generate ambient sound and character dialogue. The model builds on capabilities from the Gemini series; Gemini 3.8 Flash breaks down goals in a loop and checks frames to maintain causal coherence across multi-step events, and Gemini 4 Argon has also been used for joint simulation tasks with Gemini Robotics. The company says it remains an early experimental mo

    Matched fieldsTitle、Summary

Tuesday

  1. Google BlogSelected

    Google DeepMind releases world model Genie 4, supporting real-time interactive simulation and native audio

    Google DeepMind releases the world model Genie 4, focused on real-time interactive simulation and introducing native audio for the first time in the series. The model is built on capabilities from the Gemini family: Gemini Omni is responsible for making simulations match the appearance and behavior of the real world, while other Gemini models provide the complex reasoning needed to maintain simulation coherence. Users can control scenes in real time using natural language, such as moving the camera, changing the weather, or introducing new characters, and each world also generates ambient sound, music, and interactive dialogue on the fly.

    Google DeepMind releases the world model Genie 4, focused on real-time interactive simulation and introducing native audio for the first time in the series. The model is built on capabilities from the Gemini family: Gemini Omni is responsible for making simulations match the appearance and behavior of the real world, while other Gemini models provide the complex reasoning needed to maintain simulation coherence. Users can control scenes in real time using natural language, such as moving the cam

    Matched fieldsTitle、Summary、Body