February 2025 14 Let’s use Vertex AI Studio (for Language) in Vertex AI,6 which provides a playground to test prompts. In Table 1, you will see an example zero-shot prompt to classify movie reviews. The table prompts, which also includes writing prompts for returning code. Let’s go to the Vertex AI Studio and test these prompts to look at some coding examples. Prompts for writing code Gemini can also be a developer it’s essential to read and test your code first. The moment we are all waiting for, does it really work? Prompt Engineering February 2025 44 Let’s try it first with a test folder with only a few files

iRobot, TechCrunch, BBC, OpenAI. Data aggregated by BOND. 10/50: Alan Turing creates his Turing Test to measure computer intelligence, positing that computers could think like humans 6/56: into iPhone 4S model one year later 6/14: Eugene Goostman, a chatbot, passes the Turing Test, with 1/3 of judges believing that Eugene is human 6/18: OpenAI releases GPT-1, the Surpassed Human Levels of Accuracy & Realism, per Stanford HAI AI System Performance on MMLU Benchmark Test – 2019-2024, per Stanford HAI Note: The MMLU (Massive Multitask Language Understanding) benchmark

AGIEval, CLUEWSC, CMRC, and CMath. In addition, we perform language- modeling-based evaluation for Pile-test and use Bits-Per-Byte (BPB) as the metric to guarantee fair comparison among models with different MoE # Activated Params - 67B 72B 39B 70B 21B # Total Params - 67B 72B 141B 70B 236B English Pile-test (BPB) - 0.642 0.637 0.623 0.602 0.606 BBH (EM) 3-shot 68.7 59.9 78.9 81.0 78.9 MMLU (Acc.) 5-shot W. Liu, S. Dong, and B. Wang. Cmath: Can your language model pass chinese elementary school math test?, 2023. L. Xu, H. Hu, X. Zhang, L. Li, C. Cao, Y. Li, Y. Xu, K. Sun, D. Yu, C. Yu, Y. Tian, Q. Dong

Copyright 2018 Xilinx Quantization Tool – vai_q ˃ 4 commands in vai_q quantize ‒ Quantize network test ‒ Test network accuracy finetune ‒ Finetune quantized network deploy ‒ Generate model for DPU ˃ increase accuracy decent_q Pre-trained model (fp32) Quantized model (Int16/Int8/...) quantize test finetune needs to increase accuracy deploy Y N Model for DPU Origin training data Calibration

command Step 10: Get the generated .sof file programmed into hardware Step 11: Evaluate the unit test script test_vta_insn.py with python3. Hooray!©2019 HARMAN INTERNATIONAL INDUSTRIES, INCORPORATED ACCELERATED