Page 302 +448% -9% 1/18 4/25 Source: University of Maryland’s UMD-LinkUp AIMaps (in collaboration with Outrigger Group) (5/25) Change in USA IT Job Postings, Indexed to 1/18 (AI = Blue, Non-AI = Green) performance per chip Performance of Leading AI Supercomputers (FLOP/s) – 2019-2025, per Epoch AI18 …167% Annual Growth Over Four Years in… Number of Powerful AI Models *As of 4/25, ‘Large-Scale AI Years (2024) vs. Google’s 11 Years (2009) 0 2,500 5,000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Google Search ChatGPT Years Since Public Launch (Google = 9/98, ChatGPT

17 4.3 Evaluation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 4.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 (16) k?,? = [k? ?,?; k? ? ], (17) o?,? = ?∑︁ ?=1 Softmax?( q? ?,?k?,? √︃ ?ℎ + ?? ℎ )v? ?,?, (18) u? = ??[o?,1; o?,2; ...; o?,?ℎ], (19) where ??? ∈ R?? ℎ ?ℎ×?′ ? and ? ?? ∈ R?? ℎ ×? are matrices and fused 12 1K 12K 24K 35K 47K 58K 70K 81K 93K 104K 116K 128K Context Length (#Tokens) 0 9 18 27 36 45 55 64 73 82 91 100 Document Depth Percent (%) Pressure Testing DeepSeek-V2 Base

13 General prompting / zero shot 13 One-shot & few-shot 15 System, contextual and role prompting 18 System prompting 19 Role prompting 21 Contextual prompting 23 Table of contents Step-back prompting or unexpected, but that the model should still be able to handle. Prompt Engineering February 2025 18 System, contextual and role prompting System, contextual and role prompting are all techniques used Bash. LLMs can help with translating code from one language to another. See the example in Table 18: Prompt Engineering February 2025 47 Name 1_python_rename_files Goal Write a prompt to translate Bash

Italian agent 18 A practical guide to building agents For example, here’s how you could implement this pattern in the Agents SDK: Python 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 that handles both sales and support: Python 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 from agents import Agent, Runner technical_support_agent guardrails when using the Agents SDK: Python 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 from import from import class str async def ( "Churn

. . . . . . . . . . . . . 17 3.2.2 使用 phi-3 . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.3 总结 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2 4 零代码搭建本地 AI 前端 lobechat 中使用，进入主页后，在最上面一行，选择模型 phi-3- mini，然后就能直接提问了，这种界面会更加友好，如图 18所示。关于如何安 装 lobechat，会在下面一节讲解。 Figure 18: lobechat 使用 phi-3 模型，进行智能问答 18 3.3 总结 Llama3 本地部署大模型，这是最精简的一种方法，推荐大家先按照此方法去实 践，如图 19所示，其实这个

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Customize and fine-tune your models 13 Get AI in the hands of experts 16 Unblock your developers 18 Set bold automation goals 21 Conclusion 22 More resources 24 2 AI in the EnterpriseA new way 
 without having to get into the source code. Security, guardrails, and routing logic are all built in. 18 AI in the EnterpriseAs a result, AI app development has accelerated dramatically, helping Mercado Libre

增长  大模型能以更少的参数量达到更高的性能  360联合北大研发：5%参数量逼近Deepseek-R1满血性能 18政企、创业者必读 DeepSeek出现之前的十大预判 之六 成本越来越低  过去一年，大模型成本「自由落体」  国外：GPT-4等效智能在过去18个月内价格下降240倍  国内：大模型「亏本」卖，可以「白嫖」大模型API能力 19政企、创业者必读 DeepSeek出现之前的十大预判

Pooling/ EWA© Copyright 2018 Xilinx Xilinx Edge DPU IP (DPUv2) Source: Published results from Huawei 18% 13% 14% 40% 24% 23% 85% 51% 52% 0% 20% 40% 60% 80% 100% VGG16 ResNet-50 GoogleNet-V3

大模型）、中科院 （紫东太初大模型）、百川智能（百川大模 型）、商汤（日日新大模型）、MiniMax （ABAB 大模型）、上海人工智能实验室（书 生通用大模型）、腾讯（混元大模型，9月15 日通过）。 18 / 32 大模型应用现状：知名大模型应用 LLM 已经在多种应用场景中得到了应用，包括文本生成、机器翻译、问答、自然语言推理 等。 以 为代表的文本生成应用， 为代表的图片生成 应用，以