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Congrats Vaibhav, proud of you.

Thank you so much for this amazing video! Just a quick off-topic question: I have a SafePal wallet with USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). How should I go about transferring them to Binance?

This software has made my life so much easier. Thanks for the recommendation!

This software is a lifesaver. Thanks for the detailed explanation!

You have studied my tecniques? Ok. May I help you?

This is awesome, and it's pretty difficult. I developed something recently for a specific problem, and it's annoying how easy it is to find yourself writing out an ETL pipeline essentially to enable the LLM when the goal was to enable an ensemble of LLMs to "figure it out." You have to constantly push back. It was essentially grabbing a line from a datatable and querying fairly messy data dumped from PDF files and websites, allowing fuzzy matches with a rank, taking a subset, and then comparing the information between these dissimilar documents to find one to three specific pieces of information. It then updates a datatable for machine learning models. It was a challenge and required a more intelligent LLM (unless you're going to be a software engineer for every single step in detail... then why do Agentic at all?). The solution cost about $9 and was pretty slow, but a human would have taken about six months. Do you think there are lots of people that are basically writing entire codebases of SQL queries, where an LLM becomes an unnecessary step or layer in the SQL query that a human spends writing from beginning to end, which is not what they wanted. The programmer becomes the servant to the LLM.

Isn't agent work as pipline?

Any thoughts on Nvidia NIM?

I love how you made your mind map in this video! Could you share the tools or techniques you used to create it? I’d love to make mine look as professional as yours.

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I think Paco makes a very interesting and crucial point at the 30:35 mark. These LLM-powered graph builders are creating graphs from unstructured data, but how much domain knowledge do they possess to build truly sensible and accurate graphs in specific areas? For example, if I work with medical record systems and want to enhance them with data from medical guidelines, how confident can I be that the LLM understands the proper relationships between diseases, symptoms, and medical encodings like ICD-10 to generate a sensible and accurate graph? I know that some SciSpacy models have been trained on biomedical data and could theoretically do a better job of extracting relevant medical entities and relationships. How can this be incorporated into current GraphRAG workflows? I was hoping Paco would discuss this more and possibly explain ways to improve the resultant knowledge graph, either using existing approaches (Microsoft GraphRAG or Neo4J Graph Builder) or other alternative methods.

insightful discussions!

That's a fantastic question from Ben: We can accomplish everything you've outlined using a straightforward software class, without the need for an agent.

Great interview but man, you have to stop cutting your guest off mid sentence. It's rude and it hurts the flow.

Ao

0:25

😕 "promo sm"

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Hello there! I recently stumbled upon your TH-cam-recommended video discussing Data Exchange Podcast. I was thoroughly impressed by your presentation. Your focus on developing self-discipline, staying motivated, and being consistent deeply resonates with the topics I cover on my own channel. Like you, I'm dedicated to empowering and inspiring my audience with practical guidance. Your unique perspective and clear communication style have convinced me to hit that subscribe button. Keep up the great work-you're definitely making a positive difference!

I hope : in oxide or somebody else, ansure all compute, network and storage get its own purposed very specific functions , maybe integrated FPGA alike ??

Really enjoy listening when Dmitriy explains how A.I. is being applied at Ginkgo. He breaks it down into bite-sized pieces that I am able to understand.

"Nothing is better than showing". I could not agree more! I worked two months on an MVP just to be able to show my target audience what I wanted to sell them. I found out someone was already doing what my app did but better. Oh well.

Good quantization and c p.u etc

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it is bit annoying to see the host interrupting the guest so often 😊

Greats guest..

Great discussion.

Very good conversation. Like every other technology, AI requires efforts to make it work. One can’t simply assume that it is like flicking a switch. This realisation is important for us to begin to realise the value at scale. Else there will be disappointment.

Excellent discussion. Totally agree it’s a revolution in communication. Also creation.

I really like that Sudhir showed open-minded opinion about the market trends, not just pitching Neo4j - where in fact Neo4j can be very important player for this wave on AI revolution because of mixing graphs and VBD capabilities.

🎉

Would love more podcasts on navigating, defending against, and combatting next generation identity theft, social engineering, misinformation/disinformation, etc. That’s honestly what keeps me up most at night regarding these rapidly developing technologies.

Great discussion.

Nice

Fascinating. Great listen!

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Really very useful tips,very well done,get going,best wishes

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Very excited to try this. Great discussion.

'Promo sm'

Awesome! Super excited to listen to this!

Really great interview!

great interview. thanks!

It looks Python, it runs like C.

Ok

Bought the book after just a few minutes, in the chat about statistics. Just great! I wish Chris had been my prof at uni! Thank you Ben. Adding real value.

Very informative and interesting podcast. Loved watching, Keep it up👏🙏🙏

AI innovation. Aleph Alpha leads the way. Such a great watch.