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We also have a great deal of machine learning technology that can benefit machine scientists and developers working outside Amazon. Last week, I wrote a blog about helping the machine learning scientist community select the right deep learning framework from among many we support on AWS such as MxNet, TensorFlow, Caffe, etc.
Central engineering teams provide paved paths (secure, vetted and supported options) and guard rails to help reduce variance in choices available for tools and technologies to support the development of scalable technical architectures. If you would like to be part of our small, impactful, and collaborative team?—?come come join us.
Fast-forward 30 years, and website technology has changed significantly — we have images, stylesheets, JavaScript, streaming video, AJAX, animation, WebSockets, WebGL, rounded corners in CSS — the list goes on. In the 2000s we had a showdown of two popular blog publishing platforms — MovableType in 2001 and WordPress in 2003.
Linux has been adding tracing technologies over the years: kprobes (kernel dynamic tracing), uprobes (user-level dynamic tracing), tracepoints (static tracing), and perf_events (profiling and hardware counters). And namespaces, used for Linux containers, are also a relevant technology. I think that is a weakness of Linux.
I also learned a lot about how to work directly with customers, when to shut up and let the sales guy drive the conversation, and generally how technology sales works. I saw Erik Fisher last time I was in Budapest, and Constantin Gonzalez later became one of the first AWS solutions architects in Germany, too many names to mention.
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