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Draft:Thinking Machines Data Science

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Thinking Machines Data Science
Type of businessPrivate
Founded2015; 10 years ago (2015)
Headquarters
Taguig
,
Philippines
Founder(s)
  • Stephanie Sy
CEO
  • Stephanie Sy
URLwww.thinkingmachin.es

Thinking Machines Data Science is a technology consultancy specializing in data science, artificial intelligence, and analytics solutions for organizations.[1] The company develops custom AI systems and data platforms to solve problems for clients across various sectors throughout Southeast Asia. Thinking Machines is headquartered in Taguig, Philippines, with offices in Singapore and Bangkok, Thailand.

History

Thinking Machines Data Science was founded in 2015. According to the company, it aims to transform complex data into interpretable insights by combining quantitative analysis with qualitative methods to support organizational decision-making that affects communities and businesses.[2] The company also assists companies to adopt generative AI by creating frameworks[3] and building applications in retail[4] and financial services[5] sectors.

The company has expanded its regional presence across Southeast Asia, operating from locations in the Philippines, Singapore, and Thailand.[6] Thinking Machines has expanded its operations to become a multinational technology consulting firm, serving diverse clients, including major regional corporations, international nonprofit organizations, and recognized media companies.[7]

Stephanie Sy is the founder of Thinking Machines. Stephanie was recognized by Forbes Asia 30 Under 30 in 2018[8] for enterprise technology and serves as part of the AI advisory board of the Philippine Department of Science and Technology PCIEERD division.[9]

Significant Projects

Thinking Machines has contributed academic papers to machine learning conferences, including KDD[10], IJCAI[11],and ICML.[12] In 2020, the company won the best paper award at NeurIPS ML4D (Machine Learning for Development)[13] for its work on poverty mapping using social media data, satellite images and geospatial information.[14]

In 2021, in partnership with Asian Development Bank, the company used machine learning together with open-source data to map digital poverty in the Philippines.[15]

In 2022, Thinking Machines, in partnership with EpiMetrics, Manila Observatory, and The Philippine Action for Community-led Shelter Initiatives (PACSII), was selected as a Lacuna Fund Climate and Health Awardee[16] to develop Project CCHAIN: an open-source public health dataset. Completed in 2024, the dataset measures 20 years (2003-2022) of health, climate, environment, and socioeconomic variables at the barangay level across 12 Philippine cities.[17]

In partnership with UNICEF Venture Fund, Thinking Machines developed the AI4D (Artificial Intelligence for Development) Research Bank, a platform designed to facilitate the development of machine learning models for development purposes across Southeast Asia.[18] The project aims to address data accessibility challenges faced by development sector organizations, providing datasets for monitoring air quality and poverty mapping.[19] This platform also included Geowrangler, a Python package to simplify the process of preparing geodata for analysis.[20]

Thinking Machines also collaborated with Arizona State University and Conservation International on a Climate Change AI Innovation Grant project.[21] This initiative used machine learning and satellite imagery to identify shrimp farms that could potentially be converted to alternative farming methods. The stated objectives of the project include mangrove ecosystem conservation and addressing climate vulnerabilities in coastal communities.[22] [23]

References

  1. ^ "About Us". Thinking Machines Data Science. Thinking Machines Data Science. Retrieved 3 April 2025.
  2. ^ Sawhney, Vasundhara. "This Data Scientist Left Silicon Valley to Start Her Own Company in the Philippines". Havard Business Review. Havard Business Review. Retrieved 3 April 2025.
  3. ^ "The Enterprise GenAI App Builder's Model Evaluation Framework". Thinking Machines Data Science. Thinking Machines Data Science. Retrieved 14 April 2025.
  4. ^ "Introducing Focus Global's GenAI Customer Success App ChAI: White Glove Customer Interactions at Scale". Thinking Machines Data Science. Thinking Machines Data Science. Retrieved 14 April 2025.
  5. ^ "From Policy to Practice: How BPI Transformed Branch Operations with GenAI for 3x Faster & Better Responses". Thinking Machines Data Science. Thinking Machines Data Science. Retrieved 14 April 2025.
  6. ^ "Thinking Machines accelerates growth with new office in Bangkok". Thinking Machines Data Science. Thinking Machines Data Science. Retrieved 3 April 2025.
  7. ^ "[Press Resources] Thinking Machines One Pager". Google Docs. Thinking Machines Data Science. Retrieved 3 April 2025.
  8. ^ "30 Under 30 Enterprise Technology". Forbes. Forbes. Retrieved 3 April 2025.
  9. ^ Sy, Stephanie. "Stephanie Sy". LinkedIn. Retrieved 14 April 2025.
  10. ^ "Fragile Earth: Data Science for a Sustainable Planet". AI4Good. AI4Good. Retrieved 3 April 2025.
  11. ^ "IJCAI workshop on AI and the United Nations SDGs". Knowledge 4 All. Knowledge 4 All. Retrieved 14 April 2025.
  12. ^ "Accepted Papers". AI for Social Good. AI for Social Good. Retrieved 3 April 2025.
  13. ^ "Thinking Machines wins Best Paper Award at NeurIPS 2020 ML4D Workshop". Thinking Machines Data Science. Thinking Machines Data Science. Retrieved 3 April 2025.
  14. ^ Ledesma, Chiara; Garonita, Oshean Lee; Flores, Lorenzo Jaime; Tingzon, Isabelle; Dalisay, Danielle (27 Nov 2020). Interpretable Poverty Mapping using Social Media Data, Satellite Images, and Geospatial Information. Canada: NeurIPS 2020 Workshop. Retrieved 14 April 2025.
  15. ^ Araneta, Anica; Carrasco, Bruno; Rahemtulla, Hanif; Sy, Stephanie (22 February 2021). "Mapping digital poverty in PH". Philippine Daily Inquirer. Philippine Daily Inquirer. Retrieved 16 April 2025.
  16. ^ "Announcing Awards for Climate Datasets: Health and Energy". Lacuna Fund. Lacuna Fund. Retrieved 3 April 2025.
  17. ^ "Lacuna Fund Releases 18 New AI Datasets Empowering Local Communities to Tackle Challenges in Agriculture, Climate, Health and Language". Lacuna Fund. Lacuna Fund. Retrieved 14 April 2025.
  18. ^ "Thinking Machines to build Southeast Asia AI Research Bank for Development (AI4D)". UNICEF Venture Fund. UNICEF Venture Fund. Retrieved 14 April 2025.
  19. ^ "AI4D ML Web Catalogue". Thinking Machines. Thinking Machines. Retrieved 14 April 2025.
  20. ^ "Data-Driven Insights for Humanitarian Impact: Geowrangler provides scientists with consistent access to high-quality humanitarian geospatial data and the tools to analyze it". UNICEF. UNICEF Innovation. Retrieved 16 April 2025.
  21. ^ Klemmer, Konstantin. "Announcing the Climate Change AI Innovation Grants 2022 winners". Climate Change AI. Climate Change AI. Retrieved 3 April 2025.
  22. ^ Lujan, Milthon. "How to detect and classify aquaculture ponds with artificial intelligence?". Aquahoy. Aquahoy. Retrieved 16 April 2025.
  23. ^ Cortez, Joshua; Goto, Garrett. "Using Machine Learning to Integrate Mangrove Restoration with Sustainable Aquaculture Intensification". Climate Change AI. Climate Change AI. Retrieved 14 April 2025.
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