Andrew Ng just released a 1-hour course on building agentic knowledge Graphs from scratch:
• 00:00 - Introduction to agentic knowledge Graphs
• 03:07 - Construction of agentic Graphs
• 14:00 - Architecture of multi-agent systems
• 23:00 - Building agentic graphs with Google ADK
• 01:06:03 - Why Graphsare the future of agentic AI
Worth more than 10 articles on loop engineering.
Watch it today, then read how to become a graph engineer in the article below.
Prof. Donald Knuth opened his new paper with "Shock! Shock!"
Claude Opus 4.6 had just solved an open problem he'd been working on for weeks — a graph decomposition conjecture from The Art of Computer Programming.
He named the paper "Claude's Cycles."
31 explorations. ~1 hour. Knuth read the output, wrote the formal proof, and closed with: "It seems I'll have to revise my opinions about generative AI one of these days."
The man who wrote the bible of computer science just said that. In a paper named after an AI.
Paper: https://t.co/juSOmK9vOt
Just wrapped up a hands-on #AWS workshop covering S3, Lambda, DynamoDB & more — all with Java + CLI!
Full recap, code & slides:
https://t.co/ToK6Fj4jbj
#Java#CloudComputing#AWSWorkshop
My free “Functional Programming in Depth” video course is now available:
https://t.co/H1OEu5yRVS
As always, I thank @zivergetech for sponsoring these courses so they can be free for everyone! 🙏🥳
Comparing Approaches to Structured Concurrency by @_JamesWard and @adamhearn from @AWSCloud is available on YouTube!
Get your ticket for #LambdaConf2025 here:
https://t.co/iliCuXjItr
Watch NOW:
https://t.co/CCY2LViXJD
GPT-4o is now available in the API. It’s as smart as GPT-4 Turbo, has improved vision capabilities, and is much more efficient—2x faster, 50% cheaper, 5x rate limits. It supports text and vision today, with audio and video coming soon. Details in thread 🧵
https://t.co/JT3VmueGEQ
I’m excited to kick off the first of our short courses focused on agents, starting with Building Agentic RAG with LlamaIndex, taught by @jerryjliu0, CEO of @llama_index.
This covers an important shift in RAG (retrieval augmented generation), in which rather than having the developer write explicit routines to retrieve information to feed into the LLM context, we instead build a RAG agent that that has access to tools for retrieving information. This lets the agent decide what information to fetch, and enables it to answer more complex questions using multi-step reasoning.
In detail, you'll learn about:
- Routing: Where your agent will use decision-making to route requests to multiple tools.
- Tool Use: Where you'll create an interface for agents to select what tool (function call) to use as well as generate the right arguments.
- Multi-step reasoning with tool use: Where you'll use an LLM to carry out multiple steps of reasoning, while retaining memory throughout the process.
You’ll also learn how to step through what your agent is doing to debug and improve it iteratively.
It’s an exciting time to build agents. Sign up and get started here! https://t.co/sHhzRRJG0l
To make it easier than ever to get started with #FunctionalProgramming, the PDF version of “Learn Functional Programming The Fast Way!” is now free. 🥳
Learn about #Scala error-handling data types (Option, Try, and Either), and get started with ZIO!
https://t.co/oJ81HrAJPE
Introducing ChatQA-1.5, a family of models that surpasses GPT-4-0613 and Command-R-Plus on RAG and conversational QA.
ChatQA-1.5 has two variants:
Llama3-ChatQA-1.5-8B, https://t.co/RAYM8AsSMX
Llama3-ChatQA-1.5-70B, https://t.co/INv0ygbjvM
We also open source our instruction tuning data, offer the ChatRAG Bench for evaluation, and provide a fine-tuned multi-turn QA retriever for the community.
For more details, visit the following links:
https://t.co/wWG3wSo8gG
@alvinalexander Have been Scala advocate since its early days, TBH it’s not doing good. I still use it personally but projects using tyoesafe stack has dried up in my company.
Chandrayaan-3 Mission:
🇮🇳Vikram soft-landed on 🌖, again!
Vikram Lander exceeded its mission objectives. It successfully underwent a hop experiment.
On command, it fired the engines, elevated itself by about 40 cm as expected and landed safely at a distance of 30 – 40 cm away.
Importance?: This 'kick-start' enthuses future sample return and human missions!
All systems performed nominally and are healthy. Deployed Ramp, ChaSTE and ILSA were folded back and redeployed successfully after the experiment.
#Chandrayaan_3
#Ch3
Best explanation why distributed systems are complex I've seen is from Peter Alvaro's (@palvaro) keynote "Outwards from the Middle of the Maze"
It's a great talk, you should watch
https://t.co/U4P6LkIpSg