Java Pub House 1x2x21

Yes, this is the great episode where we dive and RUN these crazy LLMs in our own computer, and not just that, we use Java to interact with them! So if you ever wanted to start experimenting with these llms, but didn't know where to start, this is the great episode to dive into! http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/  - https://spring.io/projects/spring-ai  - https://ollama.com/  - https://www.baeldung.com/spring-ai  - https://www.youtube.com/playlist?list=PLZV0a2jwt22uoDm3LNDFvN6i2cAVU_HTH  - https://ollama.com/library/llama3 Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse in Bluesky as well! https://bsky.app/profile/pubhouse.net  

Yes, this is the great episode where we dive and RUN these crazy LLMs in our own computer, and not just that, we use Java to interact with them! So if you ever wanted to start experimenting with these llms, but didn't know where to start, this is the...

Yes, this is the great episode where we dive and RUN these crazy LLMs in our own computer, and not just that, we use Java to interact with them! So if you ever wanted to start experimenting with these llms, but didn't know where to start, this is the...

Allright, it is time to pull the curtain on all this AI stuff and really learn how it works! On this episode we dive deep into AI, and Neural Networks, refinenements, vector databases (and why we need them) so you can understand the underlying...

Allright, it is time to pull the curtain on all this AI stuff and really learn how it works! On this episode we dive deep into AI, and Neural Networks, refinenements, vector databases (and why we need them) so you can understand the underlying...

Allright, it is time to pull the curtain on all this AI stuff and really learn how it works! On this episode we dive deep into AI, and Neural Networks, refinenements, vector databases (and why we need them) so you can understand the underlying principles of AI and LLM! The field is so vast, intersting and more importantly it's going to be here to stay. So take a listen and keep learning on this new tool we should all be familiar with! http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/  - https://ollama.com/library/llama3.1/blobs/f1cd752815fc  - https://onnx.ai/  - https://partee.io/2022/08/11/vector-embeddings/  - https://codelabs.milvus.io/vector-database-101-introduction-to-unstructured-data  - https://www.guru99.com/backpropogation-neural-network.html  - https://deeplearning4j.konduit.ai/  - https://spring.io/projects/spring-ai  - https://medium.com/data-science-at-microsoft/how-large-language-models-work-91c362f5b78f  - https://www.v7labs.com/blog/neural-network-architectures-guide Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse

So we continue to have guests in our show to talk to us about interesting things... This time is about Apache Tika. This is an incredible tool to do search file processing and metadata extraction. Think about that you have tons of unstructured files,...

So we continue to have guests in our show to talk to us about interesting things... This time is about Apache Tika. This is an incredible tool to do search file processing and metadata extraction. Think about that you have tons of unstructured files,...

So we continue to have guests in our show to talk to us about interesting things... This time is about Apache Tika. This is an incredible tool to do search file processing and metadata extraction. Think about that you have tons of unstructured files, like emails, or documents, and you want to extract, index and then search theses. This is Tika's purpose. And who best to walk us through how it does its magic that its Project Management Committee (PMC) Chair, Tim Allison! So take a listen as we go deeper on ingesting tons of content (which is fundamental for things like training LLMs). http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/ Apache Tika * https://tika.apache.org/ OpenSearch Project and OpenSearch Neural Plugin Tutorials * https://opensearch.org/ * https://opensearch.org/docs/latest/search-plugins/neural-search/ * https://opster.com/guides/opensearch/opensearch-machine-learning/how-to-set-up-vector-search-in-opensearch/  * https://opster.com/guides/opensearch/opensearch-machine-learning/opensearch-hybrid-search/ * https://sease.io/2024/01/opensearch-knn-plugin-tutorial.html * https://sease.io/2024/04/opensearch-neural-search-tutorial-hybrid-search.html Selected Advanced File Processing toolkits/services * https://unstructured.io/ * https://aws.amazon.com/textract/ * https://azure.microsoft.com/en-us/products/ai-services/ai-document-intelligence Selected Hybrid Search/RAG toolkits (there are _MANY_ others!) * Haystack: https://haystack.deepset.ai/ * LangChain: https://www.langchain.com/ * LangStream: https://langstream.ai/ Search/Relevance Conferences * https://haystackconf.com/ * https://2024.berlinbuzzwords.de/ * https://mices.co/ Tim's personal project * JavaFX (ahem) tika-config writer UI: https://github.com/tballison/tika-gui-v2 Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse

We have a great time talking to Matt Topol from Voltron Data on one of his Apache Software Foundation projects called Apache Arrow. It's both a spec and implementation of a columnar data format that is not only efficient, but cross-language...

We have a great time talking to Matt Topol from Voltron Data on one of his Apache Software Foundation projects called Apache Arrow. It's both a spec and implementation of a columnar data format that is not only efficient, but cross-language...

We have a great time talking to Matt Topol from Voltron Data on one of his Apache Software Foundation projects called Apache Arrow. It's both a spec and implementation of a columnar data format that is not only efficient, but cross-language compatible. We walk through the scenarios that it covers and how is becoming more and more pivotal for things like ML and LLMs. So come listen to this JPH episode on one of the best and free ways to distribute data and integrate services working on top of that data! http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/  - Apache Arrow Project (https://arrow.apache.org/)  - Java implementation (https://arrow.apache.org/docs/java/index.html)  - In-Memory Analytics with Apache Arrow (https://www.oreilly.com/library/view/in-memory-analytics-with/9781801071031/)  - Matt Topol X (Twitter!) (https://twitter.com/zeroshade)  -  Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse

Ok, so it's an incredible time to be in the Java Ecosystem, and one of the biggest frameworks out there just dropped their three-point-oh version! That's right! So Spring Boot is not officially 3.0, and it has as a Baseline Java 17! (oohh!!). So we...

Ok, so it's an incredible time to be in the Java Ecosystem, and one of the biggest frameworks out there just dropped their three-point-oh version! That's right! So Spring Boot is not officially 3.0, and it has as a Baseline Java 17! (oohh!!). So we...

Ok, so it's an incredible time to be in the Java Ecosystem, and one of the biggest frameworks out there just dropped their three-point-oh version! That's right! So Spring Boot is not officially 3.0, and it has as a Baseline Java 17! (oohh!!). So we brought in the big guns to talk about what does it mean to Spring Boot 3, and what are the new cool toys we can expect from that upgrade!  In all, an amazing interview full of great things that are available NOW (so whatcha waiting for! Upgrade!) http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/  - Dan Vega's own What's new in Spring Boot 3 (https://www.danvega.dev/newsletter/whats-new-spring-boot-3/)  - Official Spring Framework 6 Wiki (https://github.com/spring-projects/spring-framework/wiki/What's-New-in-Spring-Framework-6.x)  - Spring Boot 3, and Spring Framework 6, What's new? (https://www.baeldung.com/spring-boot-3-spring-6-new)  - Spring Boot 3 goes GA (https://spring.io/blog/2022/11/24/spring-boot-3-0-goes-ga)  - Preparing for Spring Boot 3 (https://spring.io/blog/2022/05/24/preparing-for-spring-boot-3-0)  -  Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse

Whew! So we took a big break over summer (like Bob said, we were just swamped with work.. oof), but we are BACK! and like always we are ready to explore even deeper Java topics for the professional developer. This time we set our sights in Apache...

Whew! So we took a big break over summer (like Bob said, we were just swamped with work.. oof), but we are BACK! and like always we are ready to explore even deeper Java topics for the professional developer. This time we set our sights in Apache...

Whew! So we took a big break over summer (like Bob said, we were just swamped with work.. oof), but we are BACK! and like always we are ready to explore even deeper Java topics for the professional developer. This time we set our sights in Apache Kafka, one of the (if not THE) dominant distributed messaging framework / broker. If you have been integrating webservices, you might have been running into message brokers (and applying Enterprise Integration Patterns), well if so, you most likely have run into Kafka.  We dive into "What does Kafka Solve", into what it is (and isn't), and why you should use it (or not use it), and how it differs from traditionalling Messaging systems. In all, this is another episode of "Cloud stuff", and, like you know, that's where everything interesting is at! So have a listen!  http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/ Apache Kafka https://kafka.apache.org/ Kafka Quick Start https://developer.confluent.io/quickstart/kafka-on-confluent-cloud/ What IS Apache Kafka https://developer.confluent.io/what-is-apache-kafka/ Apache Kafka Quickstart (With Tim Berglund, Hi!!!) https://kafka.apache.org/quickstart  Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse  

Yeah! so we have been working with the cloud for a while, like K8s, EC2, Route53, BlobData, CLI has been swinged around... and is a little mysterious, and sometimes looks like a black box where you just click buttons, add things, type commands,...

Yeah! so we have been working with the cloud for a while, like K8s, EC2, Route53, BlobData, CLI has been swinged around... and is a little mysterious, and sometimes looks like a black box where you just click buttons, add things, type commands,...