Cheuk Ting Ho

"This talk will explore AI's dual role, starting with its proven excellence in coding, fueled by extensive open-source training data and models tailored for efficient, profitable business use cases. We will then examine AI's powerful capability to find code vulnerabilities at high speed, acting as an expert across multiple technical fields simultaneously. However, this proficiency introduces significant dangers; we will examine the Anthropic cybersecurity evaluations incident as a primary case study to illustrate the risks associated with autonomous vulnerability discovery. The presentation will shift to the crucial topic of "gatekeeping" these advanced cybersecurity tools, discussing projects like Claude Mythos and Project Glasswing, addressing the complex question of who should have access, and evaluating the role of government and regulatory oversight in controlling these tools. Finally, we will analyze the evolving asymmetry in cybersecurity - the balance between defense and offense - and how AI is fundamentally changing the game. Ultimately, AI is a double-edged sword that demands careful handling and responsible deployment."

告白します、私はキャリアの半分を`print`を誤って使うことに費やしました。このトークは、Pythonでのデバッグにおいて`print`に頼るという一般的でありながら、最終的には限界のある習慣に取り組む、私自身の個人的な道のりから生まれました。アプリケーションの複雑さが増すにつれて、なぜこの習慣が非効率的で扱いにくくなるのかを、私自身のプロフェッショナルな経験から得た苦い教訓を基に探ります。 概要: * 「print」を使わないのはなぜか？ * デバッグに「print」を使える状況 * 「print」の使用が役立たない状況 * Pythonで使われるデバッガー *...

Python has become the most widely used language in scientific computing and data science due to its approachable syntax, vast ecosystem of libraries, and rapid prototyping capabilities.

[Preflight check]: You may want to have a look at the repo and pre-download some libraries or models in advance: https://github.com/Cheukting/lighteval-exercises Large Language Models (LLMs) are becoming central to modern applications, yet effectively evaluating their performance remains a...

Free-threaded Python aims to significantly improve performance, allowing multiple native threads to execute Python bytecode concurrently. In this talk, we will explore the current state of Python's free-threading initiative and assess its practical readiness for widespread adoption.

Free-threaded Python aims to significantly improve performance, allowing multiple native threads to execute Python bytecode concurrently. In this talk, we will explore the current state of Python's free-threading initiative and assess its practical readiness for widespread adoption.

AI is a double-edged sword in cybersecurity. This talk explores its dual role. Why AI excels: Vast open-source training data and profit-driven, coding-optimized models make AI a fast, multi-domain expert at writing and finding vulnerabilities in code. Gatekeeping: Projects like Claude Mythos and...

When I started learning Python, there wasn't much interest in typing in Python. However, as Python is being used in many companies, the community needs a universal typing protocol. Typing in Python starts to take shape via many PEPS and we are going to explore the evolution of it. In this talk,...

Part of the reason why we would want to write Rust code for a Python library is for speed, another is to unlock the power of multithreading. In this workshop, we will look into advanced topics in PyO3 regarding support async in Python and how to do multithreading with PyO3. ## Prerequsit Please...

A lot of you have heard of the famous (or infamous) Python GIL, but do you know why it was there in the first place? And now there exists a no-GIL Python 3.13, what difference does it make without the GIL? Let's find out in this talk. In this talk, we will start with explaining concurrency in...

Nowadays coding assistants are everywhere, many IDEs are offering them as plugins, and are becoming more and more powerful. But it prompts us questions, is coding assistant as good as we want it to be?

In this talk, we will have a deeper technical look at AI coding agents, their design, and how they can carry out coding tasks with the support of large language models. We will look at the journey from the user entering a prompt to how it converts to actions in completing the task.

While Polars is written in Rust and has the advantages of speed and multi-threaded functionalities., everything will slow down if a Python function needs to be applied to the DataFrame. To avoid that, a Polar extension can be used to solve the problem.

Like it or not, AI technology is going to be part of our life, just like any technology, it can be used to do good or harm. While we are conscious of this new technology, let's look at how we can use it to our benefit and help with a constant battle in our community: diversity and inclusion.

Part of the reason why we would want to write Rust code for a Python library is for speed, another is to unlock the power of multithreading. In this workshop, we will look into advanced topics in PyO3 regarding support async in Python and how to do multithreading with PyO3.

While Polars is written in Rust and has the advantages of speed and multi-threaded functionalities., everything will slow down if a Python function needs to be applied to the DataFrame. To avoid that, a Polar extension can be used to solve the problem. In this workshop, we will look at how to do...

In this workshop, we will cover the very basic of using PyO3 - rust library that package rust crates into Python modules. This is the most popular tool in terms of creating Python libraries with Rust. In recent years, Rust has been getting more and more popular over other similar programming...

The EU Commission is likely to vote on the Cyber Resilience Act (CRA) later this year. In this talk we will look at the timeline for the new legislation, any critical discussions happening around implementation and most importantly, the new responsibilities outlined by the CRA.

The EU Commission is likely to vote on the Cyber Resilience Act (CRA) later this year. The CRA is an ambitious step towards protecting consumers from software security issues by creating a new list of responsibilities for software developers and providers.

In this workshop, we will cover the very basic of using PyO3 - rust library that package rust crates into Python modules. This is the most popular tool in terms of creating Python libraries with Rust.

The EU Commission is likely to vote on the Cyber Resilience Act (CRA) later this year. The CRA is an ambitious step towards protecting consumers from software security issues by creating a new list of responsibilities for software developers and providers.

As there are more regulations regarding AI and Data, OSI is leading a conversation regarding the definition of open source AI. In this unconference session, we will have a look at what has been in the discussion and how we can chim in for our opinions.

The Python community has been making efforts in improving the diversity and representation among its members. There are examples of success stories such as PyCon US Charlas, PyLadies, Djangonaut, and Django Girls.

Python is one of the programming languages that has a huge open-source supply chain. There are over 400,000 Python packages on Python Package Index (PyPI) and many more on other registries like conda-forge, mostly for scientific libraries.

For the third year in a role, the PyLadies Panel at PyCon PyData engages with a broader audience on critical issues related to gender disparities, ethics, and the ongoing importance of women-focused tech groups.

The Python community has been making efforts in improving the diversity and representation among its members. There are examples of success stories such as PyCon US Charlas, PyLadies, Djangonaut, and Django Girls.

In this interactive workshop, we will cover the very basics of using PyO3. There will be hands-on exercises to go from how to set up the project environment to writing a "toy" Python library written in Rust using PyO3.

We don’t need AI for writing better code! Formators like Black and PyBetter have been automatically refactoring messy code way before AI agents claim to help you write codes. In this talk, we are going to explore how formatters analyse and manipulate the CST of your code to make it nicer.

In this workshop, we will introduce Numba - a JIT compiler that is designed to speed up numerical calculations. Most people found all of it is like a mystery - It sounds like magic, but how does it work?

When handling a large amount of data, memory profiling the data science workflow becomes more important. It gives you insight into which process consumes lots of memory.

The European Parliament proposed a Cyber Resilience Act - basically wants all software to have an “EC” stamp on it. There is a non-commercial craft out but it is still not enough to make sure open-source projects with limited resources are exempted from the Act.

In this talk, we will be exploring what memory profiling is, and how it can help with data science work. We will start the talk with a basic explanation of how Python arrange memories for various objects. This lays the foundation explanation of why we need a special tool to memory profile Python...

Mozilla has been promoting WASM for years, on the other hand, HTMX is gaining attraction. Question is, do we want more frontend or more backend? Do we still need to write JavaScripts?

When handling a large amount of data, memory profiling the data science workflow becomes more important. It gives you insight into which process consumes lots of memory.

Last year, Sam Gross, the author of nogil fork on Python 3.9, demonstrates the GIL can be removed. For scientific programs which use heavy CPU-bound processes, it could be a huge performance improvement.

When handling a large amount of data, memory profiling the data science workflow becomes more important. It gives you insight into which process consumes lots of memory.

Recently Sam Gross, the author of nogil fork on Python 3.9, demonstrates the GIL can be removed. For scientific programs which use heavy CPU-bound processes, it could be a huge performance improvement. In this talk, we will see if this is true and compare the nogil version to the original.

Ok, I lied, I still write tests. But instead of the example-based tests that we normally write, have you heard of property-based testing? By using Hypothesis, instead of thinking about what data I should test it for, it will generate test data, including boundary cases, for you.

Recommendation algorithms are the driving force of many businesses: e-commerce, personalized advertisement, on-demand entertainment. Computer algorithms know what you like and present you with things that are customized for you.

Recently, a paper titled [Trojan Source](https://trojansource.codes/) is published to demonstrate how a visibly valid contribution can contain malicious code by exporting the Unicode control characters. Some of these have been tested on Python and it works. How can it happen? Shall the Python...

Python community cares about diversity. So do we still have a problem in, especially gender, diversity? We will look at some data and see if there’s a true problem, discuss what the problem may be and how to fix it.

Now we can talk to our gadgets as if it’s a real human. It makes you wonder when you chat with the “customer service” online, is that a real person or a robot on the other side? I built a chatbot, and here’s 3 things that I discovered.

By engaging in the revolution of AI and deep learning, reinforcement learning has also evolved from being able to solve simple game puzzles to beating human records in Atari games. It has also opened up the possibility of using reinforcement learning in making real life decisions.