📆 Learn to build a fintech chatbot from scratch in 1 - 2 days
Even if you have no deep learning expertise
What do basic SQL skills have to do with building LLM-driven AI applications?
A LOT, it turns out!
Within the 100 Days Of Generative AI Challenge, I’ve been learning lots about how to use foundation model APIs to build AI applications.
Last week I completed the Generative AI with LLMs course and yesterday I finished the course on LangChain for LLM Application Development.
One thing that’s surprised me throughout this learning process is how far you can get with just basic Python and SQL skills!
For example, you can easily augment and improve the results a LLM application provides simply by writing SQL queries to pull data from a relational database! This process is called Retrieval Augmented Generation, by the way, and its hugely useful for overcoming problems with model cut-off and hallucination.
We discussed that in our 100 Days To Generative AI learning community just yesterday! (more on that in a sec)
But first, a poll!
📆 This week on the training calendar: OpenAI for FinTech: Building a
Stock Market Advisor Chatbot
Join us for a live training on building a FinTech chatbot using OpenAI, LangChain & a distributed SQL database!
Back in the good old days (as in, last year! 😂) , it would have taken at least three months to build a predictive chatbot that could advise on stock market trends.
We had to build the predictive engine from scratch, after all.
But with the release of foundation models like OpenAI, and LangChain’s AI application building-blocks, you can get a stock market advising chatbot built and in deployment in as little as 1 or 2 days!
Don’t believe me? You don’t have to!!
Come see for yourself on Wednesday, September 13 at 10 am PDT!
That’s when SingleStore is hosting a beginner-friendly training on how to build your own financial chatbot in as little as one or two days, even if you have no deep learning experience.
Topic: OpenAI for FinTech - Building a Stock Market Advisor Chatbot
In this sweet 60-minute live training, you’ll learn how to build a fintech chatbot application that leverages #Langchain, #OpenAI, and a vector contextual database.
📢 Software engineers, developers, and data analytics professionals: This is your chance to code, converse, and potentially predict the next big market move.
What You’ll Get:
👉 The fundamentals of OpenAI and its application in the FinTech sector.
👉 Step-by-step guide to building a voice-activated stock market advisor chatbot.
👉 Best practices for ensuring your chatbot is both efficient and effective.
👉 Real-world use cases and success stories of AI-driven financial tools.
Join us for a blend of finance, fun, and futuristic tech!
Replays are available to those who sign up now!
This week on LinkedIn
Within our 100 Days To Generative AI learning community, Adam Nelson posted this interesting article about model hallucinations…
Our take is this ^^ is a nothing sandwich. There are already working solutions to the hallucinations issue (RAG and ReAct prompting), so … what’s left to talk about?
If you’d like to weigh in on the conversation and get to know other Gen AI learners inside the community, here’s where you go to join.
This week on the blog
In all honesty, my team and I prepared this blog post for you before the end of the last launch.
Personally, I’ve had a 180-degree change of focus since then, but this blog post is still chaulked full of valuable nuggets on how to choose between MRR and ARR when selecting metrics to describe your startup revenue.
Read the blog: MRR vs ARR: Which Metric to Use for Your Tech Startup?
Building in public update
Last week I delivered over half my lectures for my data strategy course with O’Reilly… and we’ve finally got my LinkedIn Learning course, Python For Data Science Essential Training 1, back in update mode. It looks like I’ll be recording heavily from my home office for the month of Oct. Woohoo!
Also, a little bird told me that it might just be in the cards for me to author an AI strategy and ethics book in 2024! 🙏🙏 I’m so excited about that and am already planning out all of the other AI experts I can work with to make that book as powerful as it possibly can be!
I still have some capacity to take on more projects, so if your company is looking for data project, program, or product support, please reach out!
Yours Truly,
Lillian Pierson
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