Machine Learning Singapore

This month's event comes in the wake of Google's newest Gemini updates and Agent framework announcements. Here is your chance to get hands-on with this technology (warts and all)!

NOTE: MUST BRING YOUR LAPTOP TO THE SESSION!

Sessions (with additional expert help from Hassan Abid):

"Introductory Hands-on Generative AI Lab with Gemini" - Matthias Baetens
Hands-on code lab on Generative AI using Gemini to prepare audience with the coding environment, knowledge about Gemini and LLM in general, and key features from Gemini like structured output, files API, function calling, long context window and more with real examples. We are very grateful for Matthias Baetens, who has agreed to step into Guan Wang's shoes for this presentation.

"Building Agents with Gemini" - Sam Witteveen

In this session, Sam will cover Google's new Agent Development Kit and do a practical walkthrough of how it can be used to create various agents using the Gemini models, as well as how they can be extended with Google Cloud platform's Agent Engine and A2A protocol.

"Vibe Coding" - Martin Andrews

Going beyond simply code assistants, there has been an upsurge of developers showing how the latest generations of models can enable a new mode of creating applications : "Vibe Coding". This session will probably include some chaos - but in the spirit of the subject, we'll welcome that!

Google will be providing food starting at 12:30pm. Talks will start around 1:00pm and end around 4:30pm (with some breaks in between).

This month's event has a bit of a Nature twist : The evolution of programs; and using programs to help design medicines.

Talks:

"Evolving GPU Kernels" - Martin Andrews

As mentioned at our last meetup, AMD is currently running a competition to create high-performance GPU kernels (along the lines of DeepSeek's open source releases for Nvidia). In his talk, Martin will discuss some of the complexities of kernel programming, and whether Gemini Pro can tackle the task. Then, taking it a step further, we'll look at how a Quality/Diversity evolutionary process could power the search for effective solutions.

"A Deep Learning Approach for Nanomedicine Design" - Alvin Chan

The success of COVID-19 mRNA vaccines is driven by a new class of medicine based on Lipid nanoparticles (LNPs), but designing these multi-component drug delivery systems is still a major challenge. In this talk, Alvin will share how COMET (a transformer-based deep learning model) was built. By capturing the molecular structures, ratios, and synthesis parameters of LNPs, COMET can predict their efficacy and accelerate the design of next-generation RNA medicines.

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Talks will start at 7:00pm and end at around 8:45pm, at which point people normally come up to the front for a bit of a chat with each other, and the speakers.

As always, we're actively looking for more speakers - both '30 minutes long-form', and lightning talks. For the lightning talks, we welcome folks to come and talk about something cool they've done with keras, PyTorch, JAX and/or Deep Learning for 5-10mins (so, if you have slides, then #max=10). We believe that the key ingredient for the success of a Lightning Talk is simply the cool/interesting factor. It doesn't matter whether you're an expert or an enthusiastic beginner: Given the responses we have had to previous talks, we're sure there are lots of people who would love to hear what you've been playing with. If you're interested in talking, please just introduce yourself to Martin at one of the events.