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Friday

  1. MarkTechPost

    TinyFish Breaks Down Production-Grade Agent Search Architecture and Deep Research Experience

    TinyFish released two technical guides: one defines a production-grade agent search architecture, and the other summarizes lessons from building a deep research system. The architecture is built on four web primitives—TinySearch, TinyFetch, TinyBrowser, and TinyAgent—and runs a seven-stage control loop around a foundation model, covering task definition, retrieval planning, tool routing, evidence evaluation, and failure retry. In OpenBenchmarks tests with a fixed gpt-5.6-sol model and 100 tasks, TinyFish search plus fetch achieved a 79.0% completion rate, with a median task cost of $0.050 and a runtime of 24 seconds; under a search-only configuration, the completion rate was 59.3%.

    TinyFish released two technical guides: one defines a production-grade agent search architecture, and the other summarizes lessons from building a deep research system. The architecture is built on four web primitives—TinySearch, TinyFetch, TinyBrowser, and TinyAgent—and runs a seven-stage control loop around a foundation model, covering task definition, retrieval planning, tool routing, evidence evaluation, and failure retry. In OpenBenchmarks tests with a fixed gpt-5.6-sol model and 100 tasks,

    Matched fieldsTitle、Summary、Body

    #ai-vertical#Papers/Research#Agents#Search
  2. FactRelated story

    TinyFish releases technical guide for production-grade agent search architecture

    On October 23, 2026, TinyFish released two technical guides: one defines a production-grade agentic search architecture, and the other summarizes lessons learned from building a deep research system. According to a MarkTechPost report, the architecture is built on four web primitives—TinySearch, TinyFetch, TinyBrowser, and TinyAgent—and runs a seven-stage control loop around a foundation model, covering task definition, retrieval planning, tool routing, evidence evaluation, and failure retry. In OpenBenchmarks tests with a fixed gpt-5.6-sol model and 100 tasks, the search-plus-fetch configuration achieved a 79.0% completion rate, with a median task cost of $0.050 and a runtime of 24 seconds; the search-only configuration achieved a 59.3% completion rate. Currently, this event has only the single source report mentioned above, and there have been no subsequent developments.

    Matched fieldsTitle

    View story:TinyFish Releases Technical Guide for Production-Grade Agentic Search Architecture

Thursday

  1. Artificial Analysis

    DeepSeek Search ranks 17th on the Artificial Analysis Search Index

    DeepSeek Search scores 69 on the Artificial Analysis Search Index, ranking 17th among 27 search products, and is the lowest-priced paid search API on the list. It charges $0.75 per 1k searches, with a per-task cost of about $0.032, ranking 5th cheapest among 27 products. On AA-Omniscience its accuracy is 70%, ranking 10th, but on BrowseComp, which requires multi-hop reasoning, it is only 63%, ranking 25th; each search returns about 7k tokens, raising model cost to the 2nd highest on the list.

    Matched fieldsTitle、Summary

    #editorial#Evaluations / benchmarks#Search#DeepSeek
  2. FactRelated story

    Artificial Analysis includes DeepSeek Search in its search index evaluation

    Artificial Analysis has added DeepSeek Search to its search index evaluation. The evaluation results from October 22, 2026 show that DeepSeek Search scored 69 on the index, ranking 17th among 27 search products, and is the lowest-priced paid search API on the list: charging $0.75 per 1k searches, with a cost of about $0.032 per task, making it the 5th cheapest among the 27 products. In terms of accuracy, it scores 70% on AA-Omniscience, ranking 10th, but only 63% on BrowseComp, which requires multi-hop reasoning, ranking 25th. In addition, each search returns about 7k tokens, raising the model cost to the 2nd highest on the list. There are currently no further developments.

    Matched fieldsTitle

    View story:Artificial Analysis Adds DeepSeek Search to Its Search Index Evaluation

Monday

  1. MarkTechPost

    TinyFish Makes Search Free: Breaking Down the Real Cost of AI Agents Reading Web Pages

    TinyFish announced that, within limits, it will waive retrieval fees for Search and Fetch: Search is limited to 30 requests per minute and 500 per hour, while Fetch is limited to 150 URLs per minute and 1,000 per day. The article notes that free retrieval does not eliminate the inference costs of downstream models; the same article of about 4,300 characters returns an estimated 1,184 to 42,774 tokens across different providers, and three pages of unfiltered content can fill a 128K context window. In the September 28, 2026 Artificial Analysis snapshot, TinyFish Search scored 71 at $9.30 per 1,000 tasks, the lowest total cost among the displayed configurations but also the lowest score, with about 59 seconds per task.

    TinyFish announced that, within limits, it will waive retrieval fees for Search and Fetch: Search is limited to 30 requests per minute and 500 per hour, while Fetch is limited to 150 URLs per minute and 1,000 per day. The article notes that free retrieval does not eliminate the inference costs of downstream models; the same article of about 4,300 characters returns an estimated 1,184 to 42,774 tokens across different providers, and three pages of unfiltered content can fill a 128K context window

    Matched fieldsTitle、Body

    #ai-vertical#Product updates#Search#English text is being prepared.
  2. FactRelated story

    TinyFish makes search and scraping free

    TinyFish announced that it will waive retrieval fees for Search and Fetch within the limits. According to a MarkTechPost report, Search's free limit is 30 requests per minute and 500 per hour, while Fetch's is 150 URLs per minute and 1,000 per day. The report also notes that free retrieval does not eliminate the inference costs of downstream models: the same article of about 4,300 characters returns an estimated 1,184 to 42,774 tokens across different providers, and three pages of unfiltered content could fill a 128K context window. In the September 28, 2026 Artificial Analysis snapshot, TinyFish Search scored 71 at $9.30 per 1,000 tasks, the lowest total cost among the displayed configurations but also the lowest score, with each task taking about 59 seconds. There are currently no subsequent developments.

    Matched fieldsTitle

    View story:TinyFish makes Search and Fetch free

Wednesday

Sunday

  1. Phoenix Technology

    OpenAI discloses offline training environment for frontier models; two isolated AIs communicate via CPU cache

    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 permission management, and monitoring and suspension mechanisms, but OpenAI still retains some external connections for collecting metrics, logging, and managing authentication. In experiments specifically testing the effectiveness of the isolation, OpenAI had two AIs attempt to pass messages to each other through the CPU cache; in most tests, researchers had given hints about the communication direction or encoding rules; OpenAI said it has patched the issues found and added monitoring for these communication methods.

    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

    Matched fieldsSummary、Body

    #chinese#Safety / alignment#Agents#OpenAI
  2. Story1 reports · 1 facts

    TinyFish Releases Technical Guide for Production-Grade Agentic Search Architecture

    On October 23, 2026, TinyFish released two technical guides: one defines a production-grade agentic search architecture, and the other summarizes lessons learned from building a deep research system. According to a MarkTechPost report, the architecture is built on four web primitives—TinySearch, TinyFetch, TinyBrowser, and TinyAgent—and runs a seven-stage control loop around a foundation model, covering task definition, retrieval planning, tool routing, evidence evaluation, and failure retry. In OpenBenchmarks tests with a fixed gpt-5.6-sol model and 100 tasks, the search-plus-fetch configuration achieved a 79.0% completion rate, with a median task cost of $0.050 and a runtime of 24 seconds; the search-only configuration achieved a 59.3% completion rate. Currently, this event has only the single source report mentioned above, and there have been no subsequent developments.

    On October 23, 2026, TinyFish released two technical guides: one defines a production-grade agentic search architecture, and the other summarizes lessons learned from building a deep research system. According to a MarkTechPost report, the architecture is built on four web primitives—TinySearch, TinyFetch, TinyBrowser, and TinyAgent—and runs a seven-stage control loop around a foundation model, covering task definition, retrieval planning, tool routing, evidence evaluation, and failure retry. In

    Matched fieldsTitle

Wednesday

  1. AWS Machine Learning

    AWS Publishes Agent Registry Runtime Tool Discovery Practice

    AWS introduces the Agent Registry runtime tool discovery approach: agents use hybrid semantic and keyword search to find approved MCP servers and A2A agents, then instantly build clients from descriptors to execute requests. The sample code is based on Amazon Bedrock AgentCore Gateway and runtime, integrates an order management MCP server and two A2A agents for pricing and customer service, and demonstrates a return and refund scenario using pure semantic matching. The registry returns only connection metadata; invocation credentials must be obtained separately through Cognito OAuth or IAM, and new capabilities require no changes to orchestrator code.

    Comparison of hardcoded tool endpoints versus runtime discovery with AWS Agent Registry

    AWS introduces the Agent Registry runtime tool discovery approach: agents use hybrid semantic and keyword search to find approved MCP servers and A2A agents, then instantly build clients from descriptors to execute requests. The sample code is based on Amazon Bedrock AgentCore Gateway and runtime, integrates an order management MCP server and two A2A agents for pricing and customer service, and demonstrates a return and refund scenario using pure semantic matching. The registry returns only conn

    Matched fieldsSummary、Body

    #lab#Tutorials / practice#Agents#English text is being prepared.

Friday

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Monday

Saturday

  1. Story1 reports · 1 facts

    Artificial Analysis Adds DeepSeek Search to Its Search Index Evaluation

    Artificial Analysis has added DeepSeek Search to its search index evaluation. The evaluation results from October 22, 2026 show that DeepSeek Search scored 69 on the index, ranking 17th among 27 search products, and is the lowest-priced paid search API on the list: charging $0.75 per 1k searches, with a cost of about $0.032 per task, making it the 5th cheapest among the 27 products. In terms of accuracy, it scores 70% on AA-Omniscience, ranking 10th, but only 63% on BrowseComp, which requires multi-hop reasoning, ranking 25th. In addition, each search returns about 7k tokens, raising the model cost to the 2nd highest on the list. There are currently no further developments.

    Artificial Analysis has added DeepSeek Search to its search index evaluation. The evaluation results from October 22, 2026 show that DeepSeek Search scored 69 on the index, ranking 17th among 27 search products, and is the lowest-priced paid search API on the list: charging $0.75 per 1k searches, with a cost of about $0.032 per task, making it the 5th cheapest among the 27 products. In terms of accuracy, it scores 70% on AA-Omniscience, ranking 10th, but only 63% on BrowseComp, which requires mu

    Matched fieldsTitle

Sunday