AI Research
How One Technologist is Empowering Tomorrow’s AI Leaders One Platform at a Time
AI is often framed as the preserve of elite research labs and billion-dollar corporations, where progress emerges behind closed doors. To counteract this, there must be a new kind of tech leader — one who not only understands the complexity of this technology but also knows how to encourage others to advance in this field by equipping them with the right tools.
A clear example of this shift is Saptarshi Banerjee, a technologist, researcher, author, and global AI speaker whose career illustrates how open knowledge, community engagement, and shared platforms can influence the future of generative AI. Saptarshi’s work, spanning competitive hackathons, international judging panels, public mentorship, and forthcoming academic texts, aims to show his belief that AI should be built out in the open, with contributions from a diverse and global community of builders.
How Saptarshi Understood the Value of Competition
While studying computer science at Illinois Tech in Chicago, Saptarshi began assisting hackathons across the United States, earning national recognition at events such as CalHacks and HackIllinois. One winning project, a real-time ‘Uber for Healthcare’ system that connected patients with available healthcare providers, foreshadowed how urgent care delivery could harness AI well before telemedicine became mainstream.
These experiences highlighted the potential of spaces that encourage rapid feedback and prototyping, as well as how they could be a dynamic and effective solution to solving technical gaps in technological devices. More importantly, they shaped Saptarshi’s conviction that technical leadership should not be confined to theory or corporate research, but tested and shared through collective challenges that democratize participation.
This ethos carried into his later career as he architected AI for different companies. Specifically, he’s focused on building agents which can automatically take care of specific tasks for companies. He’s dealt with not only building them but enhancing them using technologies like retrieval-augmented generation techniques to offer these agents access to third-party data in real-time, or Model Context Protocols (MCPs) which provide a standardise interface to connect fragmented platforms.
But over time, more so than the technical kinks of AI and how it could have wider enterprise implementations, Saptarshi’s enduring interest became developing strategies to provide students, researchers, and early-career engineers access to the knowledge and platforms to apply them.
Judging at the Frontlines of New Ideas
Today, Saptarshi acts as a recurring judge at many global AI hackathons sponsored by corporations like Google DeepMind, Perplexity AI, AWS, Y Combinator, and Anthropic.
These have included an MCP-focused edition hosted on AWS with support from Perplexity, where participants explored the ways in which agents can communicate through shared protocols, an AI-Agents sprint held alongside NVIDIA’s GTC conference, and a Global Agent Hackathon that invited developers to build quality assistants that can provide outputs with greater context and inference. He’s also evaluated projects for the QS Reimagine Education Awards, a platform that has been described as the ‘Oscars of EdTech’.
But he doesn’t just focus on existing competitions. He’s also assisted in developing his own. In 2025, he helped organise one of the largest AI hackathons in the Bay Area, which brought together hundreds of participants, $50,000 in prizes, and sponsorships from leading companies in cloud and security.
For Saptarshi, these types of events allow collaboration to bloom across disciplines and demographics, producing networks as valuable as the prototypes themselves. He describes them as ‘sandboxes for the future’, spaces where promising engineers can refine their talents, risk-taking is encouraged, and problems are tackled without the weight of corporate bureaucracy. Judging, for him, is less about identifying winners and more about giving promising ideas their necessary space to develop and grow.
By helping shape the criteria of these competitions, Saptarshi is focusing not only on who gets industry acclaim but also which underlying values are rewarded in this growing ecosystem. In this way, his presence on judging panels signals a rebalancing of incentives toward opening the entry barrier for AI into broader communities.
His Belief in Open Knowledge as a Public Good
Saptarshi also serves as an active speaker on multiple platforms, where he’s gone deep into how to further expand AI’s technical foundation. He has presented at conferences like BrightTalk, SCSP + AI Summit, the KubeFM podcast, and the IEEE Cloud Summit, where he has discussed topics related to how to deploy AI on the cloud.
In addition, Saptarshi is sharing his knowledge through two upcoming books with Springer Nature: Agentic AI: Architecting Autonomous Systems for the Enterprise and Scaling and Integrating Generative AI Across Enterprise Systems. Both works synthesize years of research and apply said research to real operations, which allows him to present strategies for operationalising AI without skimping on transparency or effectiveness.
Through these initiatives, Saptarshi Banerjee is showing how AI can only progress when it’s accessible and open to experimentation and collaboration. His work shows how community-driven initiatives can expand participation and serve as the groundwork for more promising outcomes and products, setting a future where the success of AI will be based on how effectively the ecosystem nurtures the builders of tomorrow.
If you want to keep up with Saptarshi Banerjee’s work, connect with him on LinkedIn.
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A few minutes after losing to Jannik Sinner at the US Open 2025 with a convincing score against him, Alexander Bublik reacted on social media to the incredible performance of the world number one. The Kazakh player commented on a picture with the result: “AI,” once again referring to the Italian as Artificial Intelligence, always as a compliment to his amazing level on the court.
And post-match he was very quick to insist on his point. https://t.co/qjuPPcHxif pic.twitter.com/7B1rhCUWUH
— José Morgado (@josemorgado) September 2, 2025
This news is an automatic translation. You can read the original news, Bublik reacciona en redes sociales tras perder contra Sinner: “Es Inteligencia Artificial”
Artificial Intelligence (AI) could help Indonesia achieve its vision of Golden Indonesia 2045 with the right strategy and governance, according to Minister of Communication and Digital Affairs, Meutya Hafid.
Stating this in her forward to Indonesia’s National AI Roadmap White Paper, she said the AI roadmap would provide policy direction to accelerate AI ecosystem development to ensure the country was not to be left behind in a field increasingly dominated by advanced countries and global tech giants.
The White Paper, drafted by the AI Roadmap Task Force, a 443-member body representing government, academia, industry, civil society, and the media, was launched by the Ministry of Communication and Digital in early August.
It has been envisaged as a strategic document that would serve as the country’s reference for adopting and developing AI technology in a more focused, inclusive, and ethical manner. The document has been circulated for public consultation to gather wider input from stakeholders.
This initiative builds on the National AI Strategy 2020-2045, which was an initial framework developed by the Collaborative Research and Industrial Innovation in AI (KORIKA), an organisation formed by scientists, technocrats and industry leaders to accelerate the AI ecosystem in Indonesia.
However, that strategy has struggled to keep up with the rapid breakthroughs in generative AI (GenAI) since late 2022.
Three major action plans
The national AI roadmap outlines three main action plans: AI ecosystems, AI development priorities, and AI financing – all anchored in ethical guidance and regulation.
This roadmap also breaks down the action plan into three-time horizons: short term (2025-2027), medium term (2028-2035) and long term (2035-2045).
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Indonesia’s AI ecosystem development would focus on three main pillars.
The first pillar was talent development.
Indonesia aimed to nurture a large pool of skilled professionals who could both use and create AI innovation.
The roadmap sets an ambitious target of producing 100,000 AI talents annually. Around 30 per cent would be developers, divided further into AI specialists (30 per cent) and practitioners (70 per cent), and the remaining 70 per cent would be AI end-users.
The government also aimed to ensure 20 million citizens are AI-literate by 2029.
The next pillar was research and industrial innovation.
The roadmap emphasised advanced, relevant, and sustainable AI research that delivered real benefits to society.
To achieve this, the government would encourage agencies, universities, and industries to strengthen AI programmes in priority sectors.
A cross-sectoral open sandbox platform would also be developed to support experimentation and collaboration.
The last pillar in Indonesia’s AI ecosystem was infrastructure and data.
To foster domestic AI innovation, the government planned to expand digital infrastructure, including high-performance computing, GPUs/TPUs, and a national cloud hosted in sovereign data centres to ensure secure and regulated data management.
The white paper also outlined plans to promote the development of green data centres through public–private partnerships.
Strategic priorities in AI development
The roadmap focuses on developing AI for strategic use cases, ensuring that AI adoption delivers meaningful and sustainable impact.
These priorities closely align with the country’s national development agenda and President Prabowo’s Asta Cita vision.
The priority sectors for AI include food security, healthcare, education, economy and finance, bureaucratic reform, politics and security, energy, environment, housing, transport and logistics, as well as arts, culture, and the creative economy.
Public services were also identified as an immediate priority for the 2025–2027 term. In healthcare, AI would be applied for early disease detection, remote patient monitoring, and optimising the distribution of medicines and vaccines.
In education, the focus would be on adaptive learning and digital platforms for personalised teaching materials. The government also plans to develop automated evaluation systems to ease assessment processes in schools.
In governance, AI applications would centre on intelligent chatbots for public services and data-driven policy analytics.
For transport and mobility, development would be directed towards smart traffic systems, public transport management, and the optimisation of national logistics.
Financing the national AI agenda
The roadmap outlined a phased financing strategy, combining state budget allocations, private sector contributions, and external partnerships through bilateral and multilateral collaborations.
Over the next two decades, the government aimed to establish a sustainable financing ecosystem driven by industry participation and international investment. To achieve this, Indonesia will expand fiscal incentives to encourage AI-related investments.
A notable feature of the roadmap was the role of Danantara, Indonesia’s newly established sovereign wealth fund, which has been tasked with spearheading AI financing.
Danantara would design innovative financial instruments, establish a Sovereign AI Fund, and develop blended financing models for the country’s strategic AI projects.
In the initial phase, financing would target fundamental research, pilot projects in the public sector, and the development of data and computing infrastructure.
Subsequent stages would extend funding to industries, research institutions, universities, and domestic AI start-ups, with the goal of strengthening Indonesia’s AI ecosystem and boosting its global competitiveness.
AI Research
MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists
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