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Ant inclusionAI has open-sourced Zooming without Zooming v2 (ZwZ2), trained on Qwen3.5-4B/9B and Qwen3.6-27B using GRPO reinforcement learning, with training data consisting of 20.4K multi-region VQA samples validated across models. The models are trained on full images and require no zooming tools at inference time, and can be transferred to perception, spatial reasoning, long-context understanding, and multimodal agent tasks. The code, data synthesis, and evaluation pipeline are all released u

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OpenAI has released GPT-6.1 Terra, with API pricing at $1 per million input tokens and $5 per million output tokens, down 50% and about 58% respectively from the previous generation, and half the price of GPT-6.1 Sol. OpenAI says its task completion rate on Terminal-Bench 4.0 rose from 21.5% to 50.3%, and its error rate at the highest reasoning level on difficult factual tests dropped to 4.3%. Third-party organization Artificial Analysis measured an intelligence index of 48 points, lower than So

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On October 26, 2026, Anthropic submitted an S-1 to the SEC, planning to list on Nasdaq under the ticker "ANT" with a target valuation of approximately $2 trillion and plans to raise up to $100 billion, with its annualized revenue run rate surpassing $65 billion. On the same day, OpenAI released GPT-6.1 Terra, with standard API pricing at $1 per million input tokens and $5 per million output tokens, half that of GPT-6.1 Sol. Meta, meanwhile, launched an equity financing of up to $95 billion to su

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OpenAI has released GPT-6.1 Terra, with API pricing at $1 per million input tokens and $5 per million output tokens, representing a 50% and approximately 58% decrease in input and output prices respectively compared to the previous generation, and only half that of GPT-6.1 Sol. The company claims its task completion rate on Terminal-Bench 4.0 increased from 21.5% to 50.3%, and it scored 60.0% on Agents' Last Exam, close to Claude Opus 5.5's 63.2%. Artificial Analysis measured an intelligence ind

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OpenAI has released GPT-6.1 Terra, an upgraded version of GPT-5.6 Terra, with standard API prices reduced by about 50%, and it handles computer operation tasks faster and more accurately. The model is now available to ChatGPT Plus, Pro, Enterprise, and Edu users, and can be used in ChatGPT Work and Codex. On Terminal-Bench 4.0, at the highest reasoning effort, the task resolution rate is 50.3%, higher than the previous generation's 21.5%; however, OpenAI says that in nearly 30% of simulated runs

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Goldman Sachs Chief Economist Jan Hatzius said that the year-over-year change in hyperscale data center AI investment as a share of U.S. GDP is expected to peak in the fourth quarter of 2026 at about 1.5%. AI infrastructure capital expenditure by Amazon, Microsoft, Alphabet, Meta, Oracle and SpaceX this year is expected to reach about $725 billion to $800 billion, up 64% from 2025, and to push U.S. investment-grade bond issuance up to $1.76 trillion. Goldman Sachs also estimates that if the data

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Databricks' Lakeflow Connect offers native, fully managed connectors for sources such as Atlassian (Jira, Confluence), Microsoft SharePoint, Google Workspace (Drive, Outlook, Gmail), GitHub, and OpenAI, Anthropic, with data landing directly in Unity Catalog. Unstructured files, pages, and emails land as governed tables, with no need to build or maintain data pipelines, and can be used for enterprise knowledge bases, AI agents, and developer productivity dashboards. Toyota Finance Australia uses

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Redwood Research argues that AI's conceptual reasoning capabilities should be accelerated differentially—that is, tasks that resemble philosophy, lack verifiable standards, and rely on a priori argumentation. The organization believes such capabilities are crucial for safety work such as alignment, yet are neglected by AI companies because of their low value for AI R&D and commercial applications, with currently insufficient investment. Its preliminary work shows that basic steering methods such

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During the 2026 NYC Climate Week, MIT organized 14 sessions that attracted more than 700 participants, with topics covering data centers, super pollutants, agriculture, and education. Evelyn Wang, MIT's Vice President for Energy and Climate, discussed AI and the climate equation at the opening session, and MIT also co-hosted a climate innovation event with the Bezos Earth Fund. Aaron Krol, editor of the MIT Climate Change Engagement Program, moderated the "Climate Communication for Impact" sessi

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OpenAI has launched GPT-6.1 Terra, a new model in the GPT-6 series positioned as an efficient model for high-throughput professional work, with strong image analysis and computer operation capabilities. The system card addendum states that under the Preparedness Framework, the model is rated Critical in the cybersecurity domain and High in the biological and chemical domains, using the same set of safeguards as GPT-6.1 Sol and GPT-6 Astra. On Production Benchmarks, its safety performance is on p

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OpenAI has released GPT-6.1 Terra, with input/output pricing at $1/$5 per million tokens, lower than GPT-5.6 Terra's $2/$12, with cache writes reduced to $1.25 and cached input reduced to $0.05. Artificial Analysis measured that at maximum effort, the model's intelligence index is 6 points higher than GPT-5.6 Terra, with per-task cost of $0.40 versus $1.40, and gains of 7 to 13 points at the low effort tier. In AA-Omniscience, the model's guessing rate on questions where it does not know the ans

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AWS released a solution that uses AWS CDK to deploy enterprise-grade agentic retrieval on a managed Amazon Bedrock Knowledge Base: the reasoning agent invokes two knowledge bases as MCP tools through AgentCore Gateway, and AgenticRetrieveStream performs multi-turn planning, internal reranking, and returns answers with citations. The managed knowledge base (Type: MANAGED) takes over ingestion, storage, indexing, and retrieval, eliminating the need to build your own OpenSearch Serverless collectio

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Vapi has introduced a traffic splitting feature that can allocate inbound and outbound call traffic to different versions of voice agents at ratios such as 0.1%, 1%, or 5%, before a full release once validated. The feature supports maintaining version stickiness by caller identity, and the official recommendation is to start with a two-way split, changing only one variable at a time. Previously, releasing a new version would immediately switch 100% of traffic over, so teams did not dare to itera

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In 2026, Sakana AI launched products including Sakana Chat, Sakana Marlin, Sakana Fugu, and Sakana Translate. Its GTM team was formally established in September 2026, led by Vice President Hidekazu Kakishima. The team adopts a "product-led GTM" model and hires Forward Deployed Engineers (FDEs) to feed customer on-site experience back into product improvements. Kakishima previously served as head of the strategic accounts team at AWS Japan, a founding member of SORACOM, and in a related role at S

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Browser Use published a tutorial introducing a workflow for extracting structured data across multiple websites using a single JSON Schema: static pages are scraped to Markdown and then filled in by an LLM, while pages requiring login or clicks are handed off to a browser agent. The article provides a reliability checklist, including enabling structured output, validating with Pydantic or Zod, returning null for missing fields, preserving source url and original-text citations, deduplicating by

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Text-to-speech (TTS) works in two stages: the front end first normalizes the text and converts it into tokens and vector representations, and then the back end uses a neural model to generate acoustic representations, which are output as speech waveforms through a vocoder. In the article, ElevenLabs uses "Mr. Ríos paid $11 on 10/06" as an example to demonstrate the complete pipeline from normalization, tokenization, and prosody to the acoustic model and vocoder, and mentions that pronunciation d

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OpenAI released GPT-6.1 Terra, with input/output prices of $1/$5 per million tokens, lower than GPT-5.6 Terra's $2/$12. On the Artificial Analysis Intelligence Index, at the highest effort level it scores 6 points higher than GPT-5.6 Terra, with a cost per task of $0.40 versus $1.40; at the low and medium effort levels it sits at the frontier of intelligence and cost. On the AA-Omniscience benchmark, the model's guess rate when it does not know the answer dropped from 88% to 38%, while accuracy

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