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AI Singapore’s Open Source AI Bricks: a 20-Year Personal Journey

This past two weeks AI Singapore announced the release of two free and open-source AI Bricks:

  1. PeekingDuck – a computer vision (CV) framework for inference that allows ANYONE with basic scripting and CV skills to quickly build up an end-to-end CV pipeline in as little as 4 lines of code. See PeekingDuck: A Computer Vision Framework | AI Singapore
  2. SG-NLP – a series of Natural Language Processing (NLP) tools based on research done by Singapore NLP research groups from our institutes of higher learning (IHL) and research institutes (RI). See SG-NLP is Launched! | AI Singapore

Both are available under the business-friendly open-source Apache license, and can be downloaded from Github or simply with a simple Python pip install command.

This is in addition to AI Singapore’s earlier released open-sourced RPA tool – TagUI (TagUI | AI Singapore) – the world’s most popular open-source and free RPA tool with more than 80,000 downloads worldwide, being used in more than 100 countries and 4000+ stars on Github.

Other tools and frameworks in our roadmap include Federated Learning and AI/MLOps which will be released in the next few months.

While the availability of freely available open-source tools is not new, what is new is that these are the first open-source tools released targeting industry adoption, instead of just academic publication and research, that is funded by the Singapore government through the AI Singapore’s AI Makerspace initiative.

These tools were built based on the engagement of more than 500 organizations in Singapore in the last 4 years, working on more than 75 real-world AI projects through the 100Experiements programme and having deployed more than 30 of them to date. We distilled the common requests, repeatedly required features and looked at ways to automate and simplify so that we can help our SMEs in particular to accelerate their adoption of AI.

This has been a personal two decade-long journey to get the Singapore government to adopt open-source, not just as a consumer, but as a producer of open-source tools for, not just the Singapore industry, but for the world.

As a Singaporean entrepreneur, whether I was working in a large local enterprise, small-medium company or my own startup, I wanted to make use of the research generated by our Singapore researchers. The research was paid for by Singaporean tax dollars, and I believed we should have easy access to them, instead of having to pay again through complicated license agreements and fees.

I remember having multiple conversations with IHLs and RIs the last twenty years to have them open-source their tools and research and make them readily available to our SMEs and start-ups, but often the response was – it was not their KPI and they need to execute a license agreement, charge a fee and have a record of who is using their tools and research.

Do not get me wrong, I wholely believe in sharing the upside with the researchers, IHLs and RIs, if the venture making use of their research output generated handsome rewards. This could be through revenue share, royalties etc, after I had the opportunity to use and deploy the research into the global market, sell, generated revenue but not before I even started. There are several examples of such license which basically says “please go ahead and use our research, code, data but if you make more than $500,000, you will have to sign a commercial agreement with us and pay us $50,000 per year”.

The complex license agreement and sometimes high (by a start-up standard) license fees required upfront made using our Singapore research difficult. Even more challenging was that most of the research was hidden behind a proprietary license where only a compiled binary was provided with no access to the source code. This did not allow my engineering team to enhance the code or fix any bugs and we need to go back to the original researcher in the IHL or RI.

It did not help that these IHL and RI do not and cannot offer any service level agreement (SLA) when it comes to when the code could be fixed. So if I license their research and implement their code into a customer’s system, and if things break, there is no way I can get a guaranteed fix in a reasonable amount of time. It was “best effort and depends on our researcher’s availability”.

Fast forward to 2016, when I was offered a role in AI Singapore, one of the things I recommended and asked for was the mandate to open-source the tools we built and share them freely and openly with the industry under a license like the Apache license. I was fortunate to have strong support from the National Research Foundation (NRF) team, as they wanted to explore more innovative means to get our industry to adopt NRF funded research.

TagUI, PeekingDuck and SG-NLP are just the beginning. We have a talented and dedicated AI Engineering team in AI Singapore today. Many of them coming through our AI Apprenticeship Programme (AIAP) – another innovation we created in AI Singapore to groom the next generation of Singaporeans in AI and open-source development.

We are planning on more tools developed by AI Singapore’s AI Engineering team. We will also be launching new programmes and initiatives to raise the standard of AI and cloud computing and encourage more open-source development in the local community. Watch this space.


Author

  • Passionate about growing our own timber. I am currently the Director for AI Industry Innovation and AI Makerspace in AI Singapore.

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