Trends Artificial Intelligence
digital datasets that have been in the making for over three decades; breakthrough large language models (LLMs) that – in effect – found freedom with the November 2022 launch of OpenAI’s ChatGPT with computers are ingesting massive datasets to get smarter and more competitive. Breakthroughs in large models, cost-per-token declines, open-source proliferation and chip performance improvements are making are racing to build and deploy the next layers of AI infrastructure: agentic interfaces, enterprise copilots, real-world autonomous systems, and sovereign models. Rapid advances in artificial intelligence0 码力 | 340 页 | 12.14 MB | 5 月前3
The Servo Book - 0.0.1Windows (none) AI contributions Contributions must not include content generated by large language models or other probabilistic tools, including but not limited to Copilot or ChatGPT. This policy covers contributions, something that we cannot trust an AI tool to do. Copyright issues: Publicly available models are trained on copyrighted content, both accidentally and intentionally, and their output often includes Ethical issues: AI tools require an unreasonable amount of energy and water to build and operate, their models are built with heavily exploited workers in unacceptable working conditions, and they are being used0 码力 | 107 页 | 2.48 MB | 3 天前3
julia 1.10.10the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled type system • Elegant and extensible conversions and promotions for numeric and other types • Efficient support for Unicode, including but not limited to UTF-8 • Call C functions directly (no wrappers0 码力 | 1692 页 | 6.34 MB | 4 月前3
Julia 1.10.9the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled type system • Elegant and extensible conversions and promotions for numeric and other types • Efficient support for Unicode, including but not limited to UTF-8 • Call C functions directly (no wrappers0 码力 | 1692 页 | 6.34 MB | 4 月前3
Julia 1.11.4the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled type system • Elegant and extensible conversions and promotions for numeric and other types • Efficient support for Unicode, including but not limited to UTF-8 • Call C functions directly (no wrappers0 码力 | 2007 页 | 6.73 MB | 4 月前3
Julia 1.11.5 Documentationthe performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled type system • Elegant and extensible conversions and promotions for numeric and other types • Efficient support for Unicode, including but not limited to UTF-8 • Call C functions directly (no wrappers0 码力 | 2007 页 | 6.73 MB | 4 月前3
Julia 1.11.6 Release Notesthe performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled type system • Elegant and extensible conversions and promotions for numeric and other types • Efficient support for Unicode, including but not limited to UTF-8 • Call C functions directly (no wrappers0 码力 | 2007 页 | 6.73 MB | 4 月前3
Julia 1.12.0 RC1the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled type system • Elegant and extensible conversions and promotions for numeric and other types • Efficient support for Unicode, including but not limited to UTF-8 • Call C functions directly (no wrappers0 码力 | 2057 页 | 7.44 MB | 4 月前3
Julia 1.12.0 Beta4the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled type system • Elegant and extensible conversions and promotions for numeric and other types • Efficient support for Unicode, including but not limited to UTF-8 • Call C functions directly (no wrappers0 码力 | 2057 页 | 7.44 MB | 4 月前3
Julia 1.12.0 Beta3the performance trade-off and provide a single environment productive enough for prototyping and efficient enough for deploying performance-intensive applications. The Julia programming language fills this behavior across many combinations of argument types via multiple dispatch • Automatic generation of efficient, specialized code for different argument types • Good performance, approaching that of statically-compiled type system • Elegant and extensible conversions and promotions for numeric and other types • Efficient support for Unicode, including but not limited to UTF-8 • Call C functions directly (no wrappers0 码力 | 2057 页 | 7.44 MB | 4 月前3
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