user interface. In addition, relatively new AI company founders have been especially aggressive about innovation / product releases / investments / acquisitions / cash burn and capital raises. At the can make. The magic of watching AI do your work for you feels like the early days of email and web search – technologies that fundamentally changed our world. The better / faster / cheaper impacts of 5x Faster vs. Google Note: Dashed-line bars are for years where Google did not disclose annual search volumes. Source: Google public disclosures, OpenAI (12/24). ChatGPT figures are estimates per company

for debugging and reviewing code 48 What about multimodal prompting? 54 Best Practices 54 Provide examples 54 Design with simplicity 55 Be specific about the output 56 Use Instructions over Constraints attempts 64 Summary 66 Endnotes 68 Prompt Engineering February 2025 6 Introduction When thinking about a large language model input and output, a text prompt (sometimes accompanied by other modalities Token Limit 1024 Top-K 40 Top-P 0.8 Prompt I want you to act as a travel guide. I will write to you about my location and you will suggest 3 places to visit near me. In some cases, I will also give you the

instructions= tools=[get_weather], ) , "Weather agent" "You are a helpful agent who can talk to users about the weather.", 7 A practical guide to building agents Selecting your models Different models have executing the workflow. Query transaction databases or systems like CRMs, read PDF documents, or search the web. Action Enable agents to interact with systems to take actions such as adding new information return "File saved" search_agent = Agent( name= , instructions= tools=[WebSearchTool(),save_results], ) "output" "timestamp" "Search agent" "Help the user search the internet and save

Stanley is a relationship business. Not surprisingly, there were some questions across the business about how AI could add value to the highly personal and sensitive nature of the work. The answer was use OpenAI every day; access to documents has jumped from 20% to 80%, with dramatically reduced search time; and advisors spend more time on client relationships, thanks to task automation and faster Solutions To find out more, watch Morgan Stanley: Shaping the Future of Financial Services and ask us about our Eval Frameworks. 7 AI in the EnterpriseEvals defined Evaluation is the process of validating

framework for deep learning.TVM Stack High-Level Differentiable IR Tensor Expression and Optimization Search Space LLVM, CUDA, Metal VTA Edge FPGA Cloud FPGA ASIC Optimization AutoTVM Device FleetExisting Credit: Logan WeberuTVM upcoming: Self Hosted Runtime Credit: Logan WeberDesigned for Accelerators(NPU)Search Space for TPU-like Specialized Accelerators Tensor Compute Primitives Unified Buffer Acc FIFO IRModule Custom codegenTimeline RFC: now Main area of focus in next 3-4 month More updates about tensor-level IR at the TVM conferenceCommunityOpen Source Community Open source: ~280 contributors

Comparison Between MLA and MHA . . . . . . . . . . . . . . . . . . . . . . . . . 31 E Discussion About Pre-Training Data Debiasing 32 F Additional Evaluations on Math and Code 33 G Evaluation Formats It has a total of 15.7B parameters, where 2.4B are activated for each token. Detailed descriptions about DeepSeek-V2-Lite can be found in Appendix B. In the rest of this paper, we first provide a detailed corpus to mitigate the data bias introduced from specific regional cultures. A detailed discussion about the influence of this filtering strategy is presented in Appendix E. 11 We adopt the same tokenizer

with WMMA API “Unified matmul schedule for GPU 。 Maintainability & Common Optimization Sharing 。 Search across the entire space (TensorCore + non-TensorCore) Our >olution 1

life. In order to meet the strong demand for further improving its electrochemical performance, the search for sustainable anode materials that provide lithium-ion batteries with safe and stable cyclic

Infrastructure o_ Supports the ability to handle nested division and modulus o_ Improves the ability to reason about and optimize loops e Support for different integer division modes, floor division and truncating