NVIDIA Quarterly Revenue, $MM Note: Gaming includes PC & console gaming. Other includes Enterprise / Pro Vis, Auto, & OEM / Other. NVIDIA’s fiscal year ends January 31. The figures in the title compare FQ4:25 $0 (Free) / $20 (Plus) / $200 (Pro) per Month xAI Grok $0 (Free) / $3 (Basic) / $8 (Premium) / $40 (Premium+) per Month1 Google Gemini $0 (Free) / $19.99 (AI Pro) / $250 (AI Ultra) per Month (5/25) Anthropic Claude $0 (Free) / $172 (Plus) / $100 (Max) per Month Perplexity $0 (Free) / $20 (Pro) per Month AI – New Entrants = Rapidly Laying Groundwork190 …AI Monetization…Foundation Models =

Target Hardware/Model Options Codegen CPU arm_cpu pixel2 (snapdragon 835), mate10/mate10pro (kirin 970), p20/p20pro (kirin 970) -target=arm64-linux-android -mattr=+neon llvm firefly rk3399, rock960, ultra96

workable state 4. Ch. 11 Enable and Practice Continuous Integration a. Branching – Pros & Cons i. Pro – Allows work in parallel while minimizing potential breaking impacts to trunk ii. Con – Branch work

will also run on Windows, although this configuration is not officially supported or recommended for pro- duction use. Some features are missing on Windows (including multi-process mode) and scalability is oneline: Collapse all runs of whitespace into a single space character, removing all newlines in the pro- cess. Added in version 4.3. 6.2.3 tornado.routing — Basic routing implementation Flexible routing websocket • WebSocketHandler.on_message implementations may now be coroutines. New messages will not be pro- cessed until the previous on_message coroutine has finished. • The websocket_ping_interval and w

Julia programmers may never feel the need to write code that explicitly uses types. Some kinds of pro- gramming, however, become clearer, simpler, faster and more robust with declared types. 12.1 Type Sometimes, you want a container (like an array) that would normally participate in broadcast to be "pro- tected" from broadcast's behavior of iterating over all of its elements. By placing it inside another It is common to want to create a task and schedule it right away, so the macro Threads.@spawn is pro- vided for that purpose — Threads.@spawn x is equivalent to task = @task x; task.sticky = false;

Julia programmers may never feel the need to write code that explicitly uses types. Some kinds of pro- gramming, however, become clearer, simpler, faster and more robust with declared types. 12.1 Type Sometimes, you want a container (like an array) that would normally participate in broadcast to be "pro- tected" from broadcast's behavior of iterating over all of its elements. By placing it inside another It is common to want to create a task and schedule it right away, so the macro Threads.@spawn is pro- vided for that purpose –- Threads.@spawn x is equivalent to task = @task x; task.sticky = false;

Julia programmers may never feel the need to write code that explicitly uses types. Some kinds of pro- gramming, however, become clearer, simpler, faster and more robust with declared types. 12.1 Type Sometimes, you want a container (like an array) that would normally participate in broadcast to be "pro- tected" from broadcast's behavior of iterating over all of its elements. By placing it inside another It is common to want to create a task and schedule it right away, so the macro Threads.@spawn is pro- vided for that purpose –- Threads.@spawn x is equivalent to task = @task x; task.sticky = false;

Julia programmers may never feel the need to write code that explicitly uses types. Some kinds of pro- gramming, however, become clearer, simpler, faster and more robust with declared types. 12.1 Type Sometimes, you want a container (like an array) that would normally participate in broadcast to be "pro- tected" from broadcast's behavior of iterating over all of its elements. By placing it inside another It is common to want to create a task and schedule it right away, so the macro Threads.@spawn is pro- vided for that purpose –- Threads.@spawn x is equivalent to task = @task x; task.sticky = false;

Julia programmers may never feel the need to write code that explicitly uses types. Some kinds of pro- gramming, however, become clearer, simpler, faster and more robust with declared types. 12.1 Type Sometimes, you want a container (like an array) that would normally participate in broadcast to be "pro- tected" from broadcast's behavior of iterating over all of its elements. By placing it inside another It is common to want to create a task and schedule it right away, so the macro Threads.@spawn is pro- vided for that purpose –- Threads.@spawn x is equivalent to task = @task x; task.sticky = false;

Julia programmers may never feel the need to write code that explicitly uses types. Some kinds of pro- gramming, however, become clearer, simpler, faster and more robust with declared types. 11.1 Type Sometimes, you want a container (like an array) that would normally participate in broadcast to be "pro- tected" from broadcast's behavior of iterating over all of its elements. By placing it inside another worker. Note While Julia generally strives for backward compatibility, distribution of code to worker pro- cesses relies on Serialization.serialize. As pointed out in the corresponding documen- tation, this