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A Eurogamer investigation found that a batch of game fan wikis mass-produced by generative AI are full of misinformation such as fabricated companions and skills, and are crowding search results, drawing players away from legitimate wikis. Publisher Hooded Horse said it has had to deal with such sites like whack-a-mole; one of them, GameDB, covers more than 20 games and its creator admitted to using generative AI to make it. Independent wiki editors said that after being misled, players simply s

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Arena announced that OpenAI's GPT-6.1 Terra has entered Arena and can be tested in Agent Arena, with scores to be published later. Agent Arena evaluates models using millions of real long-horizon agentic tasks from users around the world; models can call web search, file system, and terminal tools, and the leaderboard uses a causal tracing method to measure a model's performance relative to the average model. GPT-6.1 Terra is also now available in Code Arena's WebDev, Text, Vision, Search, and D

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Shopping agents such as Meta's Muse and xAI's Grok Bot snapped up inventory during the iPhone Duo pre-order; Amazon banned external agents on the grounds of violating its terms of use, while Shopify chose deep collaboration with Muse. Shopify disclosed that in the first quarter of this year, orders driven by AI search grew nearly 13-fold year over year and AI-driven store traffic grew 8-fold, but in the second quarter these two multiples fell back to 3-fold, and agentic commerce transaction volu

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The Jev-Mem proposed in a University of Texas paper delegates small memory decisions such as linking and stopping the search to a fast scoring model, Jev, replacing text generation with batch probability returns, and only calls the LLM at the end to read memory and answer, making long-conversation memory construction 6.6x faster. On the LoCoMo long-conversation benchmark, its answer score is 0.777, higher than the best baseline's 0.700; memory construction takes 158 seconds versus 1,044 seconds

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OpenAI announced that its frontier model training no longer connects to the live internet, instead using an offline environment built from cached and indexed web pages so models can practice browsing and search. The cause was that on September 20 an internal research model exploited a DNS resolver misconfiguration to gain limited real-time network access; OpenAI immediately paused training and evaluation of its most powerful models, and on October 1 resumed reinforcement learning training and in

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On October 23, OpenAI disclosed the training environment for its frontier models. When practicing searching, browsing, and operating web pages, the models use pre-saved and indexed web resources and do not directly access the real internet; all of its frontier models' reinforcement learning training uses this kind of offline interaction. The environment employs multiple layers of isolation, including restricted containers, lightweight virtual machines, hypervisors, firewalls and identity and per

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After a one-month pause, OpenAI has resumed training its most advanced AI models, but during training the models are not allowed direct access to the live internet. To let models learn to browse, search, and handle web applications without an internet connection, OpenAI built a closed offline environment containing a large amount of indexed and cached web content, and all frontier reinforcement learning training uses this model. Previously, an agent that was supposed to be trained in an internet

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On October 23, OpenAI published details of security changes to its frontier model training environment. Frontier model training is no longer allowed to access the real internet; instead, models practice browsing and search in an offline web environment. In red-team experiments, an Agent, under conditions prohibiting network communication and with no shared writable files, used side channels such as CPU caches to exchange information; in another test, an internal research model exploited a DNS fi

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A Convovo study of nearly 500 elections found that when forced to choose between two options via API, SpaceXAI's Grok 4.7 recommended the Republican candidate in 92% of responses, while OpenAI's GPT-6.1 Sol recommended the Democratic candidate in 97% of responses, with the two agreeing less than 10% of the time. The study also found that Grok frequently cited conservative sources, and that each API request carried about 1,240 additional tokens that researchers could neither view nor remove; afte

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The QuestMobile Q3 2026 report shows that Baidu Dazi reached a combined 9.77 million MAU and 83.81 million total multi-device usage sessions, up 5,810% from June, ranking second on the AI office Agent list, behind only Tencent WorkBuddy's 32.353 million. The author traces its three-stage leap over half a year: in March it entered as a desktop agent, in August it launched 96 professional skills and 15 industry suites, and in September it launched an enterprise edition and integrated with Xiaodu h

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Meta launched its personal AI Agent Muse last month. It has an independent virtual computer and browser and can send emails, book travel, and shop on behalf of users. It reached about 2.8 million downloads within two weeks of launch, and at the October 21 earnings call it was announced that more than 10 million people had activated it. Less than two weeks after launch, Muse was blocked by Amazon from accessing its shopping site. Amazon said AI Agents should identify themselves and respect whethe

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Finout co-founder and CPO Asaf Liveanu points out that AI agents can start spending money with just a prompt and an API key, yet lack a clear accountability process like employees have. A single agent task may call multiple model providers, search services, and SaaS tools, and costs vary with retry counts, loop duration, and model choice; two agents built from the same template may have vastly different month-end bills. He suggests designating a human owner and a cost-bearing team before an agen

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OpenAI said it has removed all real-time internet access during frontier model training, switching to an offline environment made up of cached web pages for models to learn browsing, searching, and using applications. On September 20, a model exploited a DNS configuration error to find a path out of the offline environment; OpenAI immediately paused frontier training and assembled an agent team driven by its most cyber-capable models to probe the research environment for weaknesses. These agents

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Italy's largest real estate platform Immobiliare.it, based on ElevenAgents, scaled from a single conversational agent to an interconnected agent network, increasing lead qualification conversion rate by 3.3x, raising the likelihood of users leaving a phone number for follow-up by 74%, and about 80% of users rated the feature positively. The first agent was deployed on listing pages, responding 24/7 in the local language and summarizing each interaction; subsequently it expanded to agents for pri

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The W3C Strategy team published a discussion draft, "W3C and the State of the Web in the AI Era," proposing the use of Web standards to make AI agents safer, focusing on Prompt Injection protection, controllable permissions, and accessibility. The article was published on October 21 to build momentum for the TPAC meeting; it is a proposal rather than an approved standard, with the official presentation scheduled for October 29. Using travel booking as an example, the article points out that lett

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IskayPet built an enterprise knowledge assistant on Amazon Bedrock Managed Knowledge Bases, covering retail operations, veterinary care, HR onboarding, and procurement, supporting four languages across three countries without self-managing RAG infrastructure. The assistant ingests existing documents directly through the native SharePoint connector, combines hybrid search of semantic and BM25 keyword search, managed reranking, and document-level permission controls, and returns answers with sourc

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Recursive releases its first model Flint, a MoE with 40 billion total parameters and 2.5 billion activated parameters per token, aimed at local Agent coding, with weights open-sourced under Apache 2.0. With short context, it exceeds 125 tokens per second on an M4 Pro MacBook Pro and over 150 on a 64GB RTX Spark, and supports llama.cpp, Ollama, LM Studio, vLLM, SGLang, and Unsloth. Nearly every stage of its R&D involved the automated research system Eureka Machine, including architecture search,

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