RAPYD.AI

We help you build amazing AI products faster.

Managing Partner

O'Reilly Media

Author & Online Trainer

Springboard

- Mentoring students who want to switch careers to Data Science / Data Analytics 
- Top Mentor Award in 2021 (Springboard Inspire)

Data Science Mentor

Data Science Dojo

Instructor

Toptal

Freelance

Deutsche Messe AG

Systematic retrieval, analysis and utilization of (unstructured) data from diverse sources to build new products and processes.

- People movement analytics 
- Computer vision with focus on text retrieval

Senior Data Scientist

Building & maintaining predictive models. Generating and communicating insights about customer trends and behavior to product owners and senior management.

- Churn Prediction
- Next Best Offer Recommendations 
- Customer Segmentation
- Visual Analytics

Data Scientist

Leading various international trade show projects in e.g. China, India, Indonesia, Mexico, Myanmar, South Africa, South Korea, Turkey.

Project Director

Deutsche Messe Dubai Branch

Management Trainee

TLDR; I'm a data scientist with high entrepreneurial bias who helps you to learn more about AI/ML so you can build
valuable business use cases. 

As the Managing Partner of RAPYD.AI, a Germany-based startup, I help businesses adopt AI and machine learning faster while delivering relevant business value. I have 15+ years of professional experience working in the corporate world where my responsibilities included building data science use cases, digital B2B products, and developing an enterprise-wide data strategy. 

I'm author of the O'Reilly book AI-Powered Business intelligence (2022) and the weekly newsletter AI4BI.Rocks which is read by over 1,000+ data professionals every week.

Online teaching is my passion. I have helped over 1,000+ students learn data science and analytics via online trainings, webinars, and mentorings for brands such as O'Reilly Media, Data Science Dojo, Knowledgehut, and Springboard.

Technical Skills

Data Science: Python, R, SQL, KNIME

Business Intelligence: Power BI, Tableau, Shiny, Dash

Databases: Microsoft SQL Server, Google Cloud BigQuery, Postgres, Excel ( ;-)

CRM: Salesforce, SAP

Project Management: Agile, Lean, Kanban, Scrum, CRISP-DM

GPT-4 is less than 24 hours old and people go crazy. 

I combed Twitter for the most exciting new use cases. 

Here‘s my top 10 list:


1 Napkin sketch to functional website
https://lnkd.in/e9zCSDKr

2 AI tutor on Khan Academy
https://lnkd.in/eD7ef2jD

3 Build video games from scratch
https://lnkd.in/eZfhN_VK

4 One click lawsuits
https://lnkd.in/edW56cNW

5 Documentation to coding tutorials
https://lnkd.in/eYhPkpKG

6 Consultant in your pocket
https://lnkd.in/ev46hMGJ

7 Check blockchain contracts
https://lnkd.in/epe897aH

8 Explain memes (killer feature)
https://lnkd.in/eSerHkxM

9 Pass exams with top grade performance 
https://lnkd.in/eWgTkkxe

10 Be my AI eyes
https://lnkd.in/ecBrxpZ9


GPT-4 is the next generation of the GPT family of large language models powering chatGPT. 

New capabilities include:
- Multi-modality: read images and answer questions about them
- Increased prompt limit: remembers 25k words instead of just 3k
- Performance: Overall performance improved for security and reliability

Limitations still include:
 - Training data until 2021
- 10x more expensive again
- “Hallucinates” from time to time

More details here: https://lnkd.in/eezDzCtb
   
Can’t wait to try this out even more!

What new use case are you most excited about?

#ai #chatgpt #gpt4 

Tobias Zwingmann

Author of AI-Powered Business Intelligence (O'REILLY) | Founder & Managing Partner at RAPYD.AI - I help you solve real business problems with data and AI, one use case at a time.

Wow, is this a sneak peek into GPT-4? Microsoft Research just dropped a trending repo that shows how the interaction with multimodal models could look like. Visual ChatGPT connects ChatGPT and a set of open source models to send and receive images while chatting. So cool!

Colab: https://lnkd.in/eF2SvCBA
Repo: https://lnkd.in/e_F3Wfgu

#chatgpt #ai #opensource 

graphical user interface, application, Word

Do you know the famous "beer and diapers" case study? I've told it many times. It’s a great example of how one of the most underrated data analytics techniques can be used to drive business value. The story goes like this:

In the 1990s, a large U.S. retail chain wanted to increase sales and attract more customers to its stores.

They analyzed their sales data and noticed an interesting pattern: on Friday evenings, sales of beer and diapers spiked in their stores.

At first, they thought it was just a coincidence, but after some research, they discovered that this pattern was recurring in many of their stores.

Intrigued by the phenomenon, the marketing team decided to get to the bottom of it.

They analyzed their sales data using a technique called association rule learning, which looks for patterns and relationships in customers' buying behavior.

What they found was surprising: sales of beer and diapers were indeed correlated, but mostly for small basket sizes.

The explanation was as follows: When people (especially young fathers) were in a hurry and needed to get just a few missing items for the weekend, they were more likely to buy both beer and diapers at the same time. However, this association did not hold true for larger shopping carts where customers were stocking up for the week.

With this insight in hand, the grocery chain adjusted its strategy.

They placed beer and diapers in close proximity, especially in areas where quick purchases were more likely. They also made sure that beer and diapers were sold at full price on Fridays.

The results were impressive - beer sales increased significantly.

The "beer and diapers" case study is a classic example of how data analytics and association rule learning can reveal unexpected insights and lead to more successful business outcomes - even if it's more of a great fable rather than an accurate report. 


PS: If you want to learn how to apply association rule learning to a real-world use case yourself, check out the latest edition of my newsletter: https://ai4bi.rocks

Everyone's crazy about the new chatGPT API. 

I just pulled a 1,000+ words blog post about it. 

Here are 4 use case types I see happening now:


1. Integrate ChatGPT into other applications

If you've used ChatGPT before, you can now integrate it directly into your favorite software. (No, this was not easily possible before.) This will happen in some of the most popular software categories out there, especially those with a thriving ecosystem - like Wordpress: https://lnkd.in/ecakD4s8

2. Make existing chatbots more powerful

If you've already built a chatbot with GPT-3 under the hood, switching that connection to the new ChatGPT API will most likely produce more natural conversations, be faster, and way cheaper as described here: https://lnkd.in/egUXyg3K

3. Innovate new apps & businesses

The possibilities are endless. Since most people don't want to do prompt engineering, you can literally build ANY application layer around the chatGPT API that takes some user input, translates it into a good prompt, and then returns the results in a nice way. Masterclass lesson here: https://tome.app/ 

Just be aware: The competition here is extremely high and your individual competitive advantage is rather low. You need either a very good niche or a very good marketing / distribution strategy to survive.

4. Enterprise use cases

Sending data to OpenAI servers in the US is still the main bottleneck for many enterprise use cases, especially with GDPR relevance (tip: try https://lnkd.in/eHd8sqBy from Germany instead). Even though data usage policies are stricter with the new chatGPT API (delete after 30 days), data is still being thrown over the fence. 

I still see a huge opportunity for text-to-sql plugins in BI applications. The new chatGPT API allows for even more conversational style workflows. Who hasn't wanted to chat with their dashboard before?

Overall, this is just the beginning. 

I don't really expect a big bang, but countless of micro-relevant use cases for every business niche.

The general idea of providing natural language interfaces to enterprise software alone is huge!

If you like to learn more, you can read the full post here: https://lnkd.in/e_VDyJNX

#ai #chatgpt #api

I recently gave a presentation on AI at #domotex, the world's leading carpet and flooring event. What the hell does AI have to do with carpets? Well, quite a lot!

This slide shows a high-level comparison between a traditional (carpet) design process and an AI-powered design process at different stages.

Yes, you should care about AI. 

Even - or I should say especially - if you're not in tech.

Today's AI systems are not like the robots you see in Hollywood movies.

It's a practically invisible, horizontal technology that's coming to every industry.

If handmade carpets aren't safe from AI, then what is?

In reference to a well-known quote:

AI won't threaten your business.

A competitor using AI will.

How do you set up your business for AI?

#ai #business #industry  

ChatGPT enthusiasts are reaching out to Himanshu and me these days. It’s always the same question: “How can I leverage ChatGPT for my business?”. TBH: There’s no one answer. But we want to help. So we partnered up:


There’s no doubt that technology like ChatGPT is changing the way we do business forever. 

To help you figure out what that means for your business, Himanshu and I are giving away short meetings to answer your ChatGPT-related use cases.

Just the three of us, in a Zoom call, discussing YOUR ideas together. 

Obviously, slots are limited.

First come, first served!

Sign up here: https://lnkd.in/eKuk8Mvv

#chagpt #ai # #business

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