And now, behind the scenes is where Werner is going (albeit 15 minutes late - it wouldn't be a Vogels keynote without running long!). And that's the last AWS re:Invent for this year. Thanks for following along with me.
Have pride in your work: most people will never see the majority of your effort, which goes on behind the scenes.
The fifth quality of the Renaissance developer: they must be a polymath - someone whose knowledge spans many subjects.
Werner encourages us to keep doing person to person code reviews. AI will change many things, but the craft of software is still learned person to person.
(On that topic, if you're using AI, you still need to own the outcomes. The work is yours, not the tool's)
The fourth quality of the Renaissance Developer: they are an owner. They own the quality of their software.
(Taking a detour via Kiro to highlight the importance of communication when talking to the AI about how it should build your software)
The third quality of a Renaissance Developer is that they communicate clearly.
The second quality The Renaissance Developer has is that they think in systems. Not computer systems per se, but other systems of interconnected things.
Werner shares some of the learnings he's come to, travelling the world, meeting customers, and seeing people change the world using their skills.
Werner's attempting to define "The Renaissance Developer". His first suggestion, a developer must by curious. I agree entirely, curiosity leads to learning.
Bezos believes we're at the convergence point of multiple golden ages, in AI, robotics, space travel, and development in each area accelerates the others. Werner reckons the other era this reminds him of is the renaissance. Ok, let's see where he's going with this.
We've had assembly, compilers, structured programming, object oriented programming, monolithic architectures, service-oriented architectures. Things have always changed, the new shift in focus to AI is no different.
But where AI might make some *jobs* obsolete, it won't make *you* obsolete, if you evolve.
The other elephant in the room: Will AI take my job? Werner's answer? Maybe. Some tasks will be automated, some skills made obsolete.
Werner starts by addressing the elephant in the room: Werner has given re:Invent keynotes since 2012, but this is his last one. He's not leaving Amazon, but he believes after so many years, the keynote audience deserves a fresh new set of AWS voices.
Lots of Amazon frugality on show in this particular video!
As is traditional, we're starting with some nerd wish fulfillment video content. In previous years, this has seen Werner starring in something like The Matrix, or Fear & Loathing. This time... Back To The Future.
Ok, @topper.me.uk here for the final AWS re:Invent keynote of the year. This one is Werner Vogels, CTO of Amazon.com, and unusually it's just an hour long - which is probably for the best, because it's pretty late here in the UK.
The closing keynote from Werner Vogels is just an hour long this year, and kicks off at 11.30pm London time. I'll see you back here for that.
And after a demo of "live visual intelligence", applying AI models to live content, we're done. This keynote always pushes my geek buttons, there are some very smart people doing some very cool things inside AWS.
In Q1, Trainium will be becoming PyTorch native, so that you don't have to learn a new platform in order to make use of Trainium hardware. Just target 'neuron' instead of 'cuda' in that code.
Compared with Trainium 2, the Trainium 3 chip can process 5 times the number of tokens per megawatt. This performance was recorded using the aforementioned profiling tools.
Trainium has on-chip capabilty for profiling workloads, without impacting performance. Neuron Explorer is a tool for reporting on those performance stats.
Now, the toolchain: Generally Available in Q1, the Neuron Kernel Interface (NKI). This provides direct access to AWS Trainium NeuronCore instruction set architecture, supporting Trainium 3.
Trainium chips have a number of micro-optimisations, built with real world AI workloads specifically in mind - not just benchmarks.
The Elastic Fabric Adapters in on these sleds provides high throughput networking across the whole UltraServer cluster.
The server sleds in these UltraServers use all three AWS hardware platforms: Nitro, Graviton, and Trainium. Everything on this sled is "top servicable", which means they can be assembled robotically, and that when they need maintenance, this can be performed quickly and efficiently.
Trainium chips provide efficient hardware for training models. A Trainium UltraServer provides 144 Trainium3 Chips across two racks, with dedicated "neuron switches" providing networking optimsed for model training workloads.
Customer TwelveLabs on stage now, talking about how they use AWS' s3 vector capabilites to build models that understand video in the way that humans do, providing plain text search for that video content.
