23政企、创业者必读 DeepSeek的出现验证了我们的预判 而DeepSeek的创新更具颠覆性 24政企、创业者必读 DeepSeek是完美的颠覆式创新  技术创新——让过去做不到的事情可以做到  体验创新——让使用起来很难很复杂的东西变得很简单易用  市场推广创新——让过去很难得到的东西可以得到  商业模式创新——让过去很昂贵的东西变得很便宜甚至免费 DeepSeek正是符合这四种创新模式的完美例子 DeepSeek在用户体验上实现了三件事  更加理解用户需求，降低Prompt要求  直接呈现思维过程，展现像真人一样思考的能力  可实时联网，把搜索能力与推理能力结合 DeepSeek颠覆式创新——用户体验 具备强大推理能力，思维过程更加缜密，智能性提升 用起来更像真人，写作能力更强，想象力更丰富 31政企、创业者必读 DeepSeek-R1用户体验改善的作用  R1在零 中国可能成为全球AI普及率、渗透率最高的国家， 加速了中国爆 发AI产业革命的步伐 DeepSeek颠覆式创新——用户体验 32 ——掀起新一轮AI科普教育 认知决定行动，这场全民AI科普对推动中国AI发展功不可没政企、创业者必读 开源改变行业格局，建立强大生态  开源战胜闭源，促使全球公司、开发者等转到开源  建立强大生态，成为全球人工智能根技术，无推广情况下各国 政府、企业、云厂商纷纷接入，获得全球最大影响力

io/trpl- zh-cn/ 在线阅读，PDF 版本请下载 Rust 程序设计语言 简体中文版.pdf） 本书也有由 No Starch Press 出版的纸质版和电子版。 🚨 想要具有互动性的学习体验吗？试试 Rust Book 的另一个版本，其中包括测验、 高亮、可视化等功能：https://rust-book.cs.brown.edu 5/562Rust 程序设计语言 简体中文版 前言 底层的控制往往是难以兼得 的；而 Rust 则试图挑战这一矛盾。通过平衡强大的技术能力与优秀的开发者体验，Rust 为你 提供了控制底层细节（如内存使用）的选项，而无需承受通常与此类控制相关的所有繁琐细 节。 Rust 适合哪些人 Rust 因多种原因适合许多人。让我们看看几个最重要的群体。 开发者团队 Rust 已被证明是一个对于具有不同系统编程知识水平的大型开发团队协作而言，非常高效的 工具。底层代码容易出现各种微妙的错误，在大多数其他语言中，这些错误只能通过广泛的测 试和经验丰富的开发者的仔细审核代码来捕捉。在 Rust 中，编译器充当了守门员的角色，拒 绝编译包含这些难以察觉的错误的代码，包括并发错误。通过与编译器合作，团队可以将时间 集中在程序逻辑上，而不是追踪 bug。 Rust 也为系统编程世界带来了现代化的开发工具： • Cargo 是内置的依赖管理器和构建工具

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64}) @assert length(DX) == length(DY) n = length(DX) incx = incy = 1 product = @ccall "libLAPACK".ddot( n::Ref{Int32}, DX::Ptr{Float64}, incx::Ref{Int32} (u::Vector) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds @simd for i in 1:n #by asserting that `u` is a `Vector` we can assume it has 1-based indexing �→ u[i] = sin(2pi*dx*i) end end function (u::Vector, du) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds du[1] = (u[2] - u[1]) / dx @fastmath @inbounds @simd for i in 2:n-1 du[i] = (u[i+1] - u[i-1]) / (2*dx) end @fastmath @inbounds du[n]

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64}) @assert length(DX) == length(DY) n = length(DX) incx = incy = 1 product = @ccall "libLAPACK".ddot( n::Ref{Int32}, DX::Ptr{Float64}, incx::Ref{Int32} (u::Vector) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds @simd for i in 1:n #by asserting that `u` is a `Vector` we can assume it has 1-based indexing �→ u[i] = sin(2pi*dx*i) end end function (u::Vector, du) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds du[1] = (u[2] - u[1]) / dx @fastmath @inbounds @simd for i in 2:n-1 du[i] = (u[i+1] - u[i-1]) / (2*dx) end @fastmath @inbounds du[n]

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64}) @assert length(DX) == length(DY) n = length(DX) incx = incy = 1 product = @ccall "libLAPACK".ddot( n::Ref{Int32}, DX::Ptr{Float64}, incx::Ref{Int32} (u::Vector) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds @simd for i in 1:n #by asserting that `u` is a `Vector` we can assume it has 1-based indexing �→ u[i] = sin(2pi*dx*i) end end function (u::Vector, du) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds du[1] = (u[2] - u[1]) / dx @fastmath @inbounds @simd for i in 2:n-1 du[i] = (u[i+1] - u[i-1]) / (2*dx) end @fastmath @inbounds du[n]

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64}) @assert length(DX) == length(DY) n = length(DX) incx = incy = 1 product = @ccall "libLAPACK".ddot( n::Ref{Int32}, DX::Ptr{Float64}, incx::Ref{Int32} (u::Vector) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds @simd for i in 1:n #by asserting that `u` is a `Vector` we can assume it has 1-based indexing �→ u[i] = sin(2pi*dx*i) end end function (u::Vector, du) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds du[1] = (u[2] - u[1]) / dx @fastmath @inbounds @simd for i in 2:n-1 du[i] = (u[i+1] - u[i-1]) / (2*dx) end @fastmath @inbounds du[n]

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64}) @assert length(DX) == length(DY) n = length(DX) incx = incy = 1 product = @ccall "libLAPACK".ddot( n::Ref{Int32}, DX::Ptr{Float64}, incx::Ref{Int32} (u::Vector) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds @simd for i in 1:n #by asserting that `u` is a `Vector` we can assume it has 1-based indexing �→ u[i] = sin(2pi*dx*i) end end function (u::Vector, du) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds du[1] = (u[2] - u[1]) / dx @fastmath @inbounds @simd for i in 2:n-1 du[i] = (u[i+1] - u[i-1]) / (2*dx) end @fastmath @inbounds du[n]

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64}) @assert length(DX) == length(DY) n = length(DX) incx = incy = 1 product = @ccall "libLAPACK".ddot( n::Ref{Int32}, DX::Ptr{Float64}, incx::Ref{Int32} (u::Vector) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds @simd for i in 1:n #by asserting that `u` is a `Vector` we can assume it has 1-based indexing �→ u[i] = sin(2pi*dx*i) end end function (u::Vector, du) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds du[1] = (u[2] - u[1]) / dx @fastmath @inbounds @simd for i in 2:n-1 du[i] = (u[i+1] - u[i-1]) / (2*dx) end @fastmath @inbounds du[n]

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64}) @assert length(DX) == length(DY) n = length(DX) incx = incy = 1 product = @ccall "libLAPACK".ddot( n::Ref{Int32}, DX::Ptr{Float64}, incx::Ref{Int32} (u::Vector) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds @simd for i in 1:n #by asserting that `u` is a `Vector` we can assume it has 1-based indexing �→ u[i] = sin(2pi*dx*i) end end function (u::Vector, du) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds du[1] = (u[2] - u[1]) / dx @fastmath @inbounds @simd for i in 2:n-1 du[i] = (u[i+1] - u[i-1]) / (2*dx) end @fastmath @inbounds du[n]

function compute_dot(DX::Vector{Float64}, DY::Vector{Float64}) @assert length(DX) == length(DY) n = length(DX) incx = incy = 1 product = @ccall "libLAPACK".ddot( n::Ref{Int32}, DX::Ptr{Float64}, incx::Ref{Int32} (u::Vector) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds @simd for i in 1:n #by asserting that `u` is a `Vector` we can assume it has 1-based indexing �→ u[i] = sin(2pi*dx*i) end end function (u::Vector, du) n = length(u) dx = 1.0 / (n-1) @fastmath @inbounds du[1] = (u[2] - u[1]) / dx @fastmath @inbounds @simd for i in 2:n-1 du[i] = (u[i+1] - u[i-1]) / (2*dx) end @fastmath @inbounds du[n]