releases GPT-1, the first of their large language models 6/20: OpenAI releases GPT- 3, an AI tool for automated conversations; Microsoft exclusively licenses the model 11/22: OpenAI releases – 2024 AI Development Trending = UnprecedentedAI Performance = Increasingly Realistic Audio Translation / Generation… 46 Note: China data may be subject to informational limitations due to government in that language. Each speaker’s original voice is isolated and cloned before generating the translation to make sure they sound the same in every language. - ElevenLabs Press Release, 1/24 Global

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello end bad_read2(a) # it is NOT safe to access `a` here Using locks to avoid data-races An important tool to avoid data-races, and thereby write thread-safe code, is the concept of a "lock". A lock can be

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello end bad_read2(a) # it is NOT safe to access `a` here Using locks to avoid data-races An important tool to avoid data-races, and thereby write thread-safe code, is the concept of a "lock". A lock can be

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello end bad_read2(a) # it is NOT safe to access `a` here Using locks to avoid data-races An important tool to avoid data-races, and thereby write thread-safe code, is the concept of a "lock". A lock can be

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello end bad_read2(a) # it is NOT safe to access `a` here Using locks to avoid data-races An important tool to avoid data-races, and thereby write thread-safe code, is the concept of a "lock". A lock can be

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello end bad_read2(a) # it is NOT safe to access `a` here Using locks to avoid data-races An important tool to avoid data-races, and thereby write thread-safe code, is the concept of a "lock". A lock can be

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello end bad_read2(a) # it is NOT safe to access `a` here Using locks to avoid data-races An important tool to avoid data-races, and thereby write thread-safe code, is the concept of a "lock". A lock can be

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello end bad_read2(a) # it is NOT safe to access `a` here Using locks to avoid data-races An important tool to avoid data-races, and thereby write thread-safe code, is the concept of a "lock". A lock can be

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello end bad_read2(a) # it is NOT safe to access `a` here Using locks to avoid data-races An important tool to avoid data-races, and thereby write thread-safe code, is the concept of a "lock". A lock can be

internals of a program and its types just like any other data. Warning Metaprogramming is a powerful tool, but it introduces complexity that can make code more difficult to understand. For example, it can quoted return expression using the function macroexpand (important note: this is an extremely useful tool for debugging macros): julia> ex = macroexpand(Main, :(@sayhello("human")) ) :(Main.println("Hello declare an isbits struct type and use that instead. Unnamed structs are not possible in the translation to Julia. Packed structs and union declarations are not supported by Julia.CHAPTER 27. CALLING