 Trends Artificial Intelligence
acceleration. Google’s TPU (Tensor Processing Unit) and Amazon’s Trainium chips are now core components of their AI stacks. Amazon claims its Trainium2 chips offer 30-40% better price-performance than • Imagen 4 • Veo 3 • Lyria 2 • Flow TV • Project Moohan • Glasses with Android XR • Magentic-UI • Copilot Studio multi-agent orchestration • GitHub Copilot asynchronous functioning • Azure AI0 码力 | 340 页 | 12.14 MB | 4 月前3 Trends Artificial Intelligence
acceleration. Google’s TPU (Tensor Processing Unit) and Amazon’s Trainium chips are now core components of their AI stacks. Amazon claims its Trainium2 chips offer 30-40% better price-performance than • Imagen 4 • Veo 3 • Lyria 2 • Flow TV • Project Moohan • Glasses with Android XR • Magentic-UI • Copilot Studio multi-agent orchestration • GitHub Copilot asynchronous functioning • Azure AI0 码力 | 340 页 | 12.14 MB | 4 月前3
 普通人学AI指南非常简单,基本都是下一步。注意在安装过程中,我们需要确 保”Use WSL 2 instead of Hyper-V (recommended)” 这一功能被启用。 docker 有 UI 界面,如图 22所示: 21 Figure 22: docker 在 mac 下的 UI 界面 如何验证 docker 是否安装成功,只需要运行下面命令: docker run hello-world 如果返回消息中带有:成功,表明安装成功。0 码力 | 42 页 | 8.39 MB | 8 月前3 普通人学AI指南非常简单,基本都是下一步。注意在安装过程中,我们需要确 保”Use WSL 2 instead of Hyper-V (recommended)” 这一功能被启用。 docker 有 UI 界面,如图 22所示: 21 Figure 22: docker 在 mac 下的 UI 界面 如何验证 docker 是否安装成功,只需要运行下面命令: docker run hello-world 如果返回消息中带有:成功,表明安装成功。0 码力 | 42 页 | 8.39 MB | 8 月前3
 OpenAI 《A practical guide to building agents》agents Agent design foundations In its most fundamental form, an agent consists of three core components: 01 Model The LLM powering the agent’s reasoning and decision-making 02 Tools External functions {{help_center_doc}}” 12 A practical guide to building agents Orchestration With the foundational components in place, you can consider orchestration patterns to enable your agent to execute workflows effectively execution between agents. Regardless of the orchestration pattern, the same principles apply: keep components flexible, composable, and driven by clear, well-structured prompts. 17 A practical guide to building0 码力 | 34 页 | 7.00 MB | 6 月前3 OpenAI 《A practical guide to building agents》agents Agent design foundations In its most fundamental form, an agent consists of three core components: 01 Model The LLM powering the agent’s reasoning and decision-making 02 Tools External functions {{help_center_doc}}” 12 A practical guide to building agents Orchestration With the foundational components in place, you can consider orchestration patterns to enable your agent to execute workflows effectively execution between agents. Regardless of the orchestration pattern, the same principles apply: keep components flexible, composable, and driven by clear, well-structured prompts. 17 A practical guide to building0 码力 | 34 页 | 7.00 MB | 6 月前3
 OpenAI - AI in the EnterpriseAutomating software testing and QA using Operator to interact with web apps like a real user, flagging any UI issues. Updating systems of record on behalf of users, without technical instructions or API connections0 码力 | 25 页 | 9.48 MB | 5 月前3 OpenAI - AI in the EnterpriseAutomating software testing and QA using Operator to interact with web apps like a real user, flagging any UI issues. Updating systems of record on behalf of users, without technical instructions or API connections0 码力 | 25 页 | 9.48 MB | 5 月前3
 Google 《Prompt Engineering v7》when it would prompt me for file names, ideally it should work as a separate application with an UI. As a starting point, Python would be a better language for a (web) application than Bash. LLMs can0 码力 | 68 页 | 6.50 MB | 6 月前3 Google 《Prompt Engineering v7》when it would prompt me for file names, ideally it should work as a separate application with an UI. As a starting point, Python would be a better language for a (web) application than Bash. LLMs can0 码力 | 68 页 | 6.50 MB | 6 月前3
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