Trends Artificial Intelligence
for a standalone product (5 days to secure 1MM users). Generative AI = AI that can create content – text, images, audio, or code – based on learned patterns. Source: OpenAI Generative AI – Public Launch per Stanford University *Multimodal = AI that can understand and process multiple data types (e.g., text, images, audio) together. **Open-source = AI models and tools made publicly available for use, modification Strategy 5/24: OpenAI releases GPT-4o, which has full multimodality across audio, visual, & text inputs 7/24: Apple releases Apple Intelligence, an AI system integrated into its devices0 码力 | 340 页 | 12.14 MB | 5 月前3
XDNN TVM - Nov 2019HW Platforms ZCU102 ZCU104 Ultra96 PYNQ Face detection Pose estimation Video analytics Lane detection Object detection Segmentation Models© Copyright0 码力 | 16 页 | 3.35 MB | 6 月前3
OpenAI - AI in the Enterpriseour product data. We knew we had a winner on our hands! Nishant Gupta Senior Director, Data, Analytics and Computational Intelligence Product Note: OpenAI has launched Vision Fine-Tuning to further0 码力 | 25 页 | 9.48 MB | 6 月前3
Google 《Prompt Engineering v7》Engineering February 2025 6 Introduction When thinking about a large language model input and output, a text prompt (sometimes accompanied by other modalities such as image prompts) is the input the model uses Prompt engineering Remember how an LLM works; it’s a prediction engine. The model takes sequential text as an input and then predicts what the following token should be, based on the data it was trained to do this over and over again, adding the previously predicted token to the end of the sequential text for predicting the following token. The next token prediction is based on the relationship between0 码力 | 68 页 | 6.50 MB | 6 月前3
清华大学 DeepSeek+DeepResearch 让科研像聊天一样简单训练 规划执行多步 骤研究流程 实时调整策略 回溯修正错误 文本 PDF 图像 【多格式数据】 支持搜索多格式数据, 整合多模态信息,生 成带引用和思考过程 总结的报告 Text Text Text “引用” DeepResearch:智能协作,自主研究 表现:人类终极考试,准确率突破 26.6% 这项测试包括3000多个多项选择题和简答题, 涵盖了从语言学到火箭科学、古典文学到生态学的100多个学科。0 码力 | 85 页 | 8.31 MB | 8 月前3
DeepSeek-V2: A Strong, Economical, and Efficient
Mixture-of-Experts Language Modela positive and beneficial impact on society. • Currently, DeepSeek-V2 is designed to support the text modality exclusively. In our forward-looking agenda, we intend to enable our model to support multiple C. Foster, J. Phang, H. He, A. Thite, N. Nabeshima, et al. The Pile: An 800GB dataset of diverse text for language modeling. arXiv preprint arXiv:2101.00027, 2020. Google. Introducing gemini: our largest0 码力 | 52 页 | 1.23 MB | 1 年前3
TVM: Where Are We Going= tvm.IRModule([te_add_one]) print(mod[”te_add_one”].args) Use hybrid script as an alternative text format Directly write pass, manipulate IR structures Accelerate innovation, e.g. use (GA/RL/BayesOpt/your0 码力 | 31 页 | 22.64 MB | 6 月前3
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