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Harald Klinke<p>Neo4j treibt mit GraphRAG, Vektor-Indizes &amp; Agentic RAG die <a href="https://det.social/tags/KI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>KI</span></a>-Entwicklung voran. Ob <a href="https://det.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LangChain</span></a>, <a href="https://det.social/tags/LlamaIndex" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LlamaIndex</span></a>, <a href="https://det.social/tags/SpringAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SpringAI</span></a> oder <a href="https://det.social/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a> – das neue Python-Paket und das Model Context Protocol (MCP) verknüpfen Graphdaten nahtlos mit <a href="https://det.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a>-Anwendungen.<br><a href="https://det.social/tags/Neo4j" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neo4j</span></a> <a href="https://det.social/tags/GenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GenAI</span></a> <a href="https://det.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RAG</span></a> <a href="https://det.social/tags/GraphQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GraphQL</span></a> <a href="https://det.social/tags/Cypher" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Cypher</span></a> <a href="https://det.social/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VectorSearch</span></a> <a href="https://det.social/tags/AgenticAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AgenticAI</span></a><br><a href="https://www.bigdata-insider.de/leistungssprung-bei-graph-datenbanken-mit-ki-integration-cloud-skalierung-und-terabyte-graphen-a-2307ed20cfaf562a1a0094b712b5be95/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">bigdata-insider.de/leistungssp</span><span class="invisible">rung-bei-graph-datenbanken-mit-ki-integration-cloud-skalierung-und-terabyte-graphen-a-2307ed20cfaf562a1a0094b712b5be95/</span></a></p>
Guillaume Laforge<p>During my holidays break I experimented with a <a href="https://uwyn.net/tags/Bluesky" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bluesky</span></a> topic trend visualization with <a href="https://uwyn.net/tags/D3js" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>D3js</span></a> using a <a href="https://uwyn.net/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a> embedding model, DBSCAN clustering to gather common topics, <a href="https://uwyn.net/tags/Gemini" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Gemini</span></a> to summarize clusters of posts.</p><p>All implemented in <a href="https://uwyn.net/tags/java" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>java</span></a> using <a href="https://uwyn.net/tags/langchain4j" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>langchain4j</span></a></p>
Marco Breveglieri - Developer<p>Oggi (giovedì 12) alle 18.30 alle Officine Credem, presso il Tecnopolo Reggio Emilia, il GDG Cloud Modena organizzerà un evento per illustrare *Vertex AI* e la creazione di agenti con questa soluzione by Google. 🪄</p><p>Maggiori dettagli e iscrizione a questo link: <a href="https://gdg.community.dev/events/details/google-gdg-cloud-modena-presents-costruire-agenti-con-vertex-ai-buffet-e-networking/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">gdg.community.dev/events/detai</span><span class="invisible">ls/google-gdg-cloud-modena-presents-costruire-agenti-con-vertex-ai-buffet-e-networking/</span></a></p><p><a href="https://mastodon.uno/tags/Google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Google</span></a> <a href="https://mastodon.uno/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a> <a href="https://mastodon.uno/tags/GDG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GDG</span></a> <a href="https://mastodon.uno/tags/Cloud" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Cloud</span></a> <a href="https://mastodon.uno/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://mastodon.uno/tags/TechEvents" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TechEvents</span></a> <a href="https://mastodon.uno/tags/Networking" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Networking</span></a> <a href="https://mastodon.uno/tags/TecnopoloReggioEmilia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TecnopoloReggioEmilia</span></a> <a href="https://mastodon.uno/tags/OfficineCredem" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OfficineCredem</span></a></p>
Guillaume Laforge<p>Fortunately, the <a href="https://uwyn.net/tags/googlecloud" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>googlecloud</span></a> <a href="https://uwyn.net/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a> embedding model has a new Task Type for code retrieval. </p><p>Enter your query in plain text, get code in return!</p><p>And it's easy to use from <a href="https://uwyn.net/tags/langchain4j" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>langchain4j</span></a></p>
Erik C. Thauvin<p>Lots of new cool Gemini stuff in LangChain4j 0.35.0</p><p><a href="https://mastodon.social/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://mastodon.social/tags/gemini" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gemini</span></a> <a href="https://mastodon.social/tags/google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>google</span></a> <a href="https://mastodon.social/tags/java" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>java</span></a> <a href="https://mastodon.social/tags/lang4chain" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lang4chain</span></a> <a href="https://mastodon.social/tags/vertexai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vertexai</span></a></p><p><a href="https://glaforge.dev/posts/2024/09/29/lots-of-new-cool-gemini-stuff-in-langchain4j/?utm_medium=erik.in&amp;utm_source=mastodon" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">glaforge.dev/posts/2024/09/29/</span><span class="invisible">lots-of-new-cool-gemini-stuff-in-langchain4j/?utm_medium=erik.in&amp;utm_source=mastodon</span></a></p>
Guillaume Laforge<p>First, I take advantage of <a href="https://uwyn.net/tags/Gemini" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Gemini</span></a>'s intrinsic training knowledge to do sentiment analysis (zero-shot), then I use a few-shot prompting technique to give the model examples of classification.</p><p>Then, I use an Embedding Models based approach to calculate vector embeddings of labeled samples, to compare them with the text to classify, thanks to <a href="https://uwyn.net/tags/langchain4j" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>langchain4j</span></a>'s EmbeddingModelTextClassifier class.</p><p>I used <a href="https://uwyn.net/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a>'s embedding model to compute vectors, and <a href="https://uwyn.net/tags/Gemini" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Gemini</span></a> to prepare some sample data.</p>
Guillaume Laforge<p>I updated my <a href="https://uwyn.net/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a> token visualization application with the latest <a href="https://uwyn.net/tags/googlecloud" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>googlecloud</span></a> <a href="https://uwyn.net/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a> preview embedding models<br><a href="https://tokens-lpj6s2duga-ew.a.run.app/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">tokens-lpj6s2duga-ew.a.run.app</span><span class="invisible">/</span></a></p>
Новини Українською<p>Google наділила Gemini 1.5 Pro «вухами» та запустила конструктор ботів Vertex AI <a href="https://itc.ua/ua/novini/google-nadilyla-gemini-1-5-pro-vuhamy-ta-zapustyla-konstruktor-botiv-vertex-ai/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">itc.ua/ua/novini/google-nadily</span><span class="invisible">la-gemini-1-5-pro-vuhamy-ta-zapustyla-konstruktor-botiv-vertex-ai/</span></a> <a href="https://mastodon.social/tags/%D0%A8%D1%82%D1%83%D1%87%D0%BD%D0%B8%D0%B9%D1%96%D0%BD%D1%82%D0%B5%D0%BB%D0%B5%D0%BA%D1%82" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Штучнийінтелект</span></a> <a href="https://mastodon.social/tags/%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D0%B8%D0%B9%D0%A8%D0%86" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ГенеративнийШІ</span></a> <a href="https://mastodon.social/tags/Gemini1" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Gemini1</span></a>.5Pro <a href="https://mastodon.social/tags/%D0%9D%D0%B5%D0%B9%D1%80%D0%BE%D0%BC%D0%B5%D1%80%D0%B5%D0%B6%D1%96" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Нейромережі</span></a> <a href="https://mastodon.social/tags/%D0%A2%D0%B5%D1%85%D0%BD%D0%BE%D0%BB%D0%BE%D0%B3%D1%96%D1%97" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Технології</span></a> <a href="https://mastodon.social/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a> <a href="https://mastodon.social/tags/%D0%A7%D0%B0%D1%82%D0%B1%D0%BE%D1%82%D0%B8" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Чатботи</span></a> <a href="https://mastodon.social/tags/%D0%9D%D0%BE%D0%B2%D0%B8%D0%BD%D0%B8" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Новини</span></a> <a href="https://mastodon.social/tags/Gemini" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Gemini</span></a> <a href="https://mastodon.social/tags/Google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Google</span></a> <a href="https://mastodon.social/tags/%D0%A1%D0%BE%D1%84%D1%82" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Софт</span></a></p>
Erik C. Thauvin<p>Gemini Function Calling</p><p><a href="https://mastodon.social/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a> <a href="https://mastodon.social/tags/gemini" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gemini</span></a> <a href="https://mastodon.social/tags/google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>google</span></a> <a href="https://mastodon.social/tags/java" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>java</span></a> <a href="https://mastodon.social/tags/vertexai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vertexai</span></a></p><p><a href="https://glaforge.dev/posts/2023/12/22/gemini-function-calling/?utm_medium=erik.in&amp;utm_source=mastodon" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">glaforge.dev/posts/2023/12/22/</span><span class="invisible">gemini-function-calling/?utm_medium=erik.in&amp;utm_source=mastodon</span></a></p>
Anna Nicholson<p>… You guessed it, we’re helping train the AI behind Alphabet’s self-driving cars! 😱</p><p>And if you want a (slightly scary) insight into where Alphabet/Google are going next with their pattern-recognition models, here’s their latest announcement on Vertex AI: <a href="https://cloud.google.com/blog/products/ai-machine-learning/vertex-ai-next-2023-announcements" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">cloud.google.com/blog/products</span><span class="invisible">/ai-machine-learning/vertex-ai-next-2023-announcements</span></a></p><p>(This thread may be old news to many of you, but I haven’t been paying enough attention! 😉)</p><p>end/🧵</p><p><a href="https://eldritch.cafe/tags/captcha" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>captcha</span></a> <a href="https://eldritch.cafe/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://eldritch.cafe/tags/reCaptcha" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>reCaptcha</span></a> <a href="https://eldritch.cafe/tags/AutonomousVehicles" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AutonomousVehicles</span></a> <a href="https://eldritch.cafe/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VertexAI</span></a> <a href="https://eldritch.cafe/tags/AlphabetInc" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphabetInc</span></a></p>