 So welcome everyone and thank you for joining Kubernetes on the edge day live in Chicago. I'm Steve Wong I'm gonna skip a bio because I've only got 10 minutes And I'll invite you to judge me by what I have to say rather than my bio you can but you can read where I'm from on the screen You saw the official theme when you registered for this event some impressive numbers here edge compute four times larger than cloud generating 75% of data worldwide in Marketing forecasts like these are called a pitch deck if this is what got your boss to okay coming here to this event That's that's great, but Let's be skeptics today and question the likely growth in edge as a thought exercise Why will edge be generating and handling 75% of all data? Why will people decide to increase investments in edge compute? Let me outline a few technology shifts taking place and lay out an idea on what these could lead to Then you can decide for yourself whether that growth forecast is real There are five significant changes going on right now Some things on this list help with remote management of edge workloads at locations with limited physical security and limited or no staff and for greenfield missions New chips reach into places. You couldn't go before with connectivity going increasingly wireless So we're seeing needs for Better energy efficiency and data access governance as well the world is using approaches like get ops and Device twins to manage edge at scale and of course the elephant in the room is AI Chat GBT recently woke the world up as to the potential of AI it learns from text and generates The generative part of its description means that it generates text But chat is not the only application for AI and a central public cloud is not the only place Where this will be useful data is being generated in manufacturing retail and utilities And we have affordable AI technologies to act on this data a recent survey indicated that at edge Generative AI is only 6% of the machine learning tasks that people are looking into These are examples of popular Edge AI use cases You can look at this list and it's quite likely you'll have a few more that aren't included here The majority of data already comes from edge not cloud and it's growing because of cheaper and better sensors cameras and Cheaper and better wireless connectivity Do you want to move all of this growing data up to the cloud? In a blog post earlier this year a former founding engineer of Google's big query dropped the line big data is dead It talks about data sovereignty and privacy challenges along with a re-evaluation of whether hosting a central ocean of data Delivered value to those who amassed it Spoiler alert if you read this the answer was no it's like bringing home a puppy. It has a long-term cost The savings aren't just in cloud storage Moving data incurs latency resiliency capital expense and energy costs and every transit point can Give hackers another bite at the apple AI at edge can be used to reduce the content to actionable events and summaries Excuse me just a minute this coral USB TPU and the wireless Soc in this picture are just a few examples of inexpensive hardware accelerators for edge AI And this is just the tip of the iceberg essentially all the vendors of chips hardware chips for edge are Embedding machine learning acceleration on the software front the frigate nvr project And the upcoming so many Minakura wedge project are some examples of open-source software in this space Don't get me wrong. This is new stuff and it's changing rapidly, but the opportunity is huge The devices aren't multi-million dollar quantum computers So You might want to start looking at this now taking into account Risks in terms of what kinds of things you might want to do as prototype use cases and avenues for proofs of concept Predictive maintenance as an example of something where if it isn't perfect The downside is that maybe it predicted that you needed a you know an oil change or a bearing Replacement earlier than you actually need to needed Needed to and if the AI was wrong it isn't the end of the world so you can find things to use for proof as a concept now AI is going to bring about mass uncertainties and risks for those in competitive businesses that get caught unprepared Every business is going to change whether we like it or not AI will alter your career Maybe sooner than you think now AI is not going to replace engineers But I contend that engineers who know how to deploy AI are going to replace those who don't If you want to use AI at edge, there's more to it than just buying some chips. You're going to need Tools for deployment updates security connectivity and more this stuff is available And that's what we're going to talk about today at this Kubernetes on the edge day event Here are the sessions this morning Please take a look at this list. We're going to be doing for 25 minute sessions covering foundations like Kubernetes service mesh and then look at Trans drilling down into device management web assembly machine learning then after a brief break We'll move on to visit a couple studies that look at lessons learned and best practices Finally, we're going to close with some lightning talks on taking advantage of wireless technology and a use case That's very interesting from the Boston Children's Hospital There are also about seven edge talks in the made cube con event later in the week We had some of these like particularly the AI talks that were deemed by the cube con event as being particularly interesting to the general public so Speakers applied for this event, but they ended up getting shifted into the main cube con event so I'd encourage you to go search the schedule for the word edge and you'll find Edge related talks later in the week finally at the end of the day Tina is going to come up and Follow up with a talk about how we can take advantage of the community along with new technology To make the world a better place AI tech can be an intellectual force multiplier just like the steam engine and electricity were Years ago But suppose that we could have proved the efficiency of a manufacturing or transportation Operation by just 2% These are the kinds of advances that can save resources and improve quality of environment Elevating the standard of living and quality of life for all So that means that this is a critical time to come together to listen and learn from each other and Explore this together to get the most out of this event I suggest that you go beyond passive listening and take advantage of the hallway track meeting with other attendees during the lunch that occurs after this event and We'll carry forward on this as a group activity In the spirit of open-source software communities Finally this event is subsidized by event sponsors that help cover the budget So I want to quickly recognize their support. Thank you spectral cloud for being a diamond sponsor Thank you edge Genesis And thank you audience for coming today. You can get my deck at this link right now