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\n <\/picture>\u201cAI is the tech wave of the moment,\u201d says Rodolfo Azevedo, a computer scientist who heads the Technologies and Innovation Partnerships department at FAPESP and is a professor at the Institute of Computing at UNICAMP. FAPESP, he explains, is funneling much of its grants to projects developing new ways to leverage these technologies. \u201cIt\u2019s also important that startups focus their innovation efforts on lowering costs and making processes scalable. By doing so, they are more likely to make a meaningful impact on people\u2019s lives,\u201d says Azevedo.<\/p>\n
He notes that many startups follow a similar path of using well-established architectures or algorithms and extracting new insights by applying them to proprietary datasets or integrating new solutions, like NeuralMind\u2019s search engine, which integrates with GPT. \u201cCompanies typically spend most of the PIPE grant period training personnel in AI, a field in which there is still a very limited skilled workforce, as well as fine-tuning AI models for specific applications,\u201d he adds.<\/p>\n
\u201cThe growth seen in recent years mirrors the broader expansion of AI startups in Brazil and globally,\u201d notes Eduardo de Rezende Francisco, a computer scientist at Funda\u00e7\u00e3o Getulio Vargas (FGV) in S\u00e3o Paulo. According to the Emerging Tech Report 2024<\/a> from Brazilian-based startup platform Distrito, 45% of the 2,252 emerging tech startups in Latin America are focused on AI, followed by the Internet of Things (IoT) at 16%, and datafication\u2014the conversion of information into digital data\u2014at 12%. Brazil leads the Latin American AI market with 74% of the region\u2019s AI startups.<\/p>\n Latin American startups exploring emerging technologies have attracted US$3.8 billion in seed funding, according to the report, with the AI sector accounting for 60% of this at US$2.4 billion. \u201cNonrepayable grant programs like PIPE play a key role in funding research and innovation with less constraints, especially in the field of AI,\u201d Francisco notes.<\/p>\n Globally, the AI market was valued at US$196.6 billion in 2023, according to market intelligence firm Grand View Research<\/a>, with the dominant players being the US, China, the European Union, and the UK. In 2022, private investment in AI reached US$92 billion\u201418 times higher than in 2013\u2014as per the AI Index Report 2023<\/a> from Stanford\u2019s Institute for Human-Centered Artificial Intelligence (HAI).<\/p>\n Tracking sleep and climate<\/strong> The insomnia section features chatbot-guided conversations, while a sleep apnea test uses smartphone sensors\u2014such as the camera, accelerometer, and microphone\u2014to detect physical and behavioral signs of the disorder. \u201cOur goal is to make sleep health more accessible, especially in Brazil, where access to treatment and specialized labs is limited. Eventually, we hope to integrate with the national healthcare system (SUS),\u201d explains psychologist Laura Castro, a cofounder and currently head of psychology and research at the company.<\/p>\n The algorithm for the sleep apnea module\u2014the latest feature on the app\u2014was developed, trained, and validated as part of an ongoing Phase 2 PIPE project. The goal is to help detect symptoms indicating a potential risk of developing the disorder; based on the results, the tool may suggest the user seek specialized medical attention, for instance.<\/p>\n Meanwhile, S\u00e3o Paulo-based startup MeteoIA, another PIPE grant recipient, developed a neural network-based system to generate customized models for predicting long-term climate risks. These models have a wide range of applications, such as forecasting landslides on highway slopes or predicting climate anomalies that could affect agricultural yields.<\/p>\n In the energy sector, MeteoIA created a model for hydroelectric plants, trained as part of two PIPE projects between November 2020 and April 2024, to forecast rainfall in watersheds hosting hydroelectric dams within the National Grid (SIN). \u201cThe system forecasts rainfall anomalies over the next 12 months with 70% accuracy. It doesn\u2019t predict the exact day the rainfall will occur, but it identifies the months when higher-than-expected precipitation is more likely,\u201d explains Thomas Martin, a scientist and cofounder of the startup.<\/p>\n The story above was published with the title “Innovative applications<\/strong>” in issue 344 of October\/2024.<\/p>\n Projects
\nVigilantes do Sono, a startup incubated at S\u00e3o Paulo\u2019s Hospital Israelita Albert Einstein, received FAPESP funding to create an app that uses machine learning to suggest strategies for improving sleep quality. Its main features include an insomnia treatment protocol based on cognitive-behavioral therapy and a screening tool for sleep apnea.<\/p>\n
\n1.<\/strong> Validation of NeuralSearchX for searching tax databases and integration with MS Office (n\u00b0 22\/13727-5<\/a>); Grant Mechanism<\/strong> Innovative Research in Small Businesses (PIPE); Principal Investigator<\/strong> Roberto de Alencar Lotufo (NeuralMind); Investment<\/strong> R$431,363.96.
\n2.<\/strong> QUEST \u2012 System for searching and aggregating information based on Zero-Shot techniques (n\u00b0 22\/01640-2<\/a>); Grant Mechanism<\/strong> Innovative Research in Small Businesses (PIPE); Principal Investigator<\/strong> Rodrigo Frassetto Nogueira (NeuralMind); Investment<\/strong> R$1,048,816.23.
\n3.<\/strong> Intelligent system for case law analysis using modern deep learning with natural language processing (n\u00b0 20\/09753-5<\/a>); Grant Mechanism<\/strong> Innovative Research in Small Businesses (PIPE); Principal Investigator<\/strong> Rodrigo Frassetto Nogueira; Investment<\/strong> R$431,078.52.
\n4.<\/strong> Robust reading of registration documents using deep learning (n\u00b0 19\/06667-3<\/a>); Grant Mechanism<\/strong> Innovative Research in Small Businesses (PIPE); Principal Investigator<\/strong> Roberto de Alencar Lotufo (NeuralMind); Agreement<\/strong> Sebrae-SP; Investment<\/strong> R$662,802.81.
\n5.<\/strong> System for robust reading of text in images using deep learning (n\u00b0 18\/01188-7<\/a>); Grant Mechanism<\/strong> Innovative Research in Small Businesses (PIPE); Principal Investigator<\/strong> Roberto de Alencar Lotufo (NeuralMind); Investment<\/strong> R$410,479.61.
\n6.<\/strong> Intelligent phenotyping with machine learning for therapeutic personalization in digital sleep improvement program (n\u00b0 21\/12139-0<\/a>); Grant Mechanism<\/strong> Innovative Research in Small Businesses (PIPE); Principal Investigator<\/strong> Laura de Siqueira Castro (Vigilantes do Sono); Investment<\/strong> R$957,782.71.
\n7.<\/strong> MIA: Artificial intelligence system for subseasonal forecasting of hydrometeorological variables in Brazil (n\u00b0 20\/00566-8<\/a>); Grant Mechanism<\/strong> Innovative Research in Small Businesses (PIPE); Principal Investigator<\/strong> Thomas Christian Marcel Martin (Meteoia Datascience); Investment<\/strong> R$457,307.60.
\n8.<\/strong> MIA: Artificial intelligence system for subseasonal forecasting of hydrometeorological variables in Brazil (n\u00b0 21\/14700-0<\/a>); Grant Mechanism<\/strong> Innovative Research in Small Businesses (PIPE); Principal Investigator<\/strong> Thomas Christian Marcel Martin (Meteoia Datascience); Investment<\/strong> R$583,435.78.<\/p>\n