This presentation covers how Artificial intelligence (AI) can be used to help bring public information closer to residents of towns and cities to help communities be more versed in local issues and happenings. It starts with the existing problems and moves to how to use AI to make things just a little bit better for everyone.
From a conceptual perspective it reviews how to grow the people's confidence using publicly available information summarized and presented using basic concepts like bibliographies.
From a technical standpoint the solution involves leveraging Retrieval-Augmented Generation (RAG) to curate and orchestrate public data, its specific attributes, and the possible distribution and consumption models for the public.
Apparently everyone has the word "Agile" on their resume. Not so fast! The spirit of this episode is reviewing the specifics of Agile, Scrum, Kanban, and the history behind them. Also included is the value of each process and when they do well and when they can be a hindrance.
If you have Agile on your resume, please watch. This video will definitely help you better understand what Agile is and why its used.
Engineering is based on forming a hypothesis and testing for failure. If the current generation is less likely to test for failure, they will fail at the scientific method, every time.
Culture, at least in the United States, tends to avoid failure or talking about it.
Early days of computing had more engineers, given they were designing the physical systems that ran the code they were writing. After mainstream computing hit the market, this allowed others, like mathematicians, to write code without designing the computer they ran on.
Engineers embrace failure and use it to create better code. But, that's super boring and people tend to avoid marketing or raising interest on failures, even though it is common knowledge that we learn more from failure than success.
That means success, with an avoidance of discussing failure, became a "thing" that people ended up talking about more. This results in more people wanting to talk about their successes, and being more like people talking about their successes.
And, to make matters worse, theories always sound good if they present hypothetical positive outcomes. They are far easier to sell quickly into others, so we preference that and the cycle continues.
If you want to find the software engineers, look where failures are accepted, scientific methods are embraced, and reliable code is desired. Databases. Flight systems. Robotics. Medical equipment. Space stuff.
The passion for learning, combined with the willingness to acquire new skills, led David to embark on a journey of transformation. David courageously adapted to a completely new working environment and overcame various challenges along the way. However, what is even more important is that by sharing his story, you can inspire and motivate others who may be struggling in their current career or experiencing burnout.
Thank you for sharing this. As someone who is working to learn more about bitmaps, id like to ask how you came across this? Is there a specific community or other that you follow? Thanks!
I think it's fair to say that the use cases for bitmaps have not yet been fully explored. I believe their use in areas of analytics and OLAP/RTOLAP will continue to grow as the desire to infer and target demo's across households increases.
I didn't realize Lucene used their own flavor of roaring bitmaps! Super Cool. I certainly think of search when it comes to Lucene, where as the cited material from Vikram & FeatureBase are targeting more general analytics.
Lucene is fast, but probably can't handle analytical type questions on massive amounts of data as fast as a pure binary index can. I could be wrong about that though. I do know Solr has it because Lucene does...
Sure, I completely get it. However, does that mean bitmaps have been fully explored? For example, OLAP is only growing as a market as the need for realtime analysis on the most fresh data. I mean, we never going to have 'less' data nor are we ever going to seek results 'slower'. Where I am going with this, utilizing technologies like bitmaps in OLAP services is an area I believe will see continued growth. While Lucene is a known commodity, I think we can agree it hasn't solved the sector, right?
video link: starts at 103 seconds (1:43) - https://www.youtube.com/watch?v=I_8M9feh_KA&t=103s
This presentation covers how Artificial intelligence (AI) can be used to help bring public information closer to residents of towns and cities to help communities be more versed in local issues and happenings. It starts with the existing problems and moves to how to use AI to make things just a little bit better for everyone.
From a conceptual perspective it reviews how to grow the people's confidence using publicly available information summarized and presented using basic concepts like bibliographies.
From a technical standpoint the solution involves leveraging Retrieval-Augmented Generation (RAG) to curate and orchestrate public data, its specific attributes, and the possible distribution and consumption models for the public.