YData (acquired by KPMG)

More Changemakers Transforming Our World! Positive impact comes in many forms, from improving healthcare and education to protecting our planet, empowering communities, and creating more inclusive economies. Today we're delighted to announce Etiko 250 · SDG Changemakers 2026-27. Congratulations to the winning changemakers: WASPITO · Jean Lobe Lobe (Cameroon) - Expanding access to healthcare across Africa by connecting patients with doctors, pharmacies, and diagnostic services through a digital health platform. NET2GRID · Mirka Karra (Netherlands) - Accelerating the energy transition by helping utilities and households optimise electricity consumption through AI-powered energy analytics. Red Dot Foundation - Safecity · ElsaMarie D'Silva (India) - Making public spaces safer by empowering individuals to report and map incidents of sexual harassment, driving awareness and systemic change. ChemFORWARD · Stacy Glass (USA) - Advancing safer products and supply chains by providing trusted chemical hazard data to help companies make informed decisions. YData (acquired by KPMG) · Gonçalo (G) Martins Ribeiro (USA) - Enabling organisations to unlock AI innovation through high-quality synthetic data while protecting privacy and reducing bias. tarla.io · Begüm ERİKÇİ, Ph.D. (Turkey) - Empowering farmers with AI-driven agronomic advice to improve crop yields, reduce resource use, and strengthen climate resilience. Each of these changemakers reminds us that meaningful progress starts with bold ideas and determined people. This is only the beginning. The Etiko 250 will be unveiled throughout the year, with more winners announced in July, October, and December 2026, and March and June 2027. Thank you to our sponsor inlea for believing in the idea, our Selection Panel, Dhruv Bhatli, Xavier Simó, Sonia Rodríguez Mayayo, our advisors and everyone who helped make this initiative possible Josep R. Novell LL.M. 🌍 Discover the changemakers: www.etiko-250.com #Etiko250 #SDGChangemakers #SDGs #ESG #Innovation #PositiveImpact #marevaetiko #inlea

In the Iberian Peninsula: Several companies on this map have already been acquired: Argilla (acquired by Hugging Face) YData (acquired by KPMG) Nuclia • The RAG-as-a-Service company (acquired by Progress Software) None of the buyers is from the region. A sign that the infrastructure built here is valuable enough that outside players move to own it early. Submer remains independent and one of the companies worth watching. #exit #data #AI #artificialintelligence #startups

Is 2026 the year of #AIAgents or the year of #Ontology? Databricks just announced their Genie Ontology. Google revealed earlier this year their Knowledge Catalog. Snowflake, Microsoft Fabric and others are also following Palantir Technologies on Ontology and #FDE model. Looks like there's still a lot of foundational work to do before adopting #AgenticAI

Safely building and testing AI agents is a priority to accelerate development cycles. At the upcoming Databricks Data + AI Summit, I’ll be sharing how to design a governed, synthetic Data Lakehouse to create a secure, production-grade testbed for your AI models. Join my session on Wednesday, June 17, at 1:50 p.m. Let's connect and discuss the architecture powering the next generation of AI. KPMG US #DataAISummit #KPMG #data #dataprivacy

We need to stop treating #syntheticdata as a simple shortcut for whenever we need data to feed into lower environments. Right now, most organizations sees synthetic data purely as a compliant placeholder for testing and staging. But this mindset misses its actual potential. Achieving true, comprehensive data diversity using only real-world datasets is often impossible. This makes synthetic data a powerful catalyst for developing a proper epistemic strategy (eg. defining how our models acquire, validate, and expand reliable knowledge beyond the limitations of our existing data silos). I've recently came across a research paper that proves that when engineered correctly, synthetic data doesn't degrade a model's knowledge; it expands it. Here is my take on why a diverse synthetic data strategy is a necessity for AI development: 1️⃣ It is an excellent antidote to "model collapse." There is a persistent myth that synthetic data always leads to heavily biased, repetitive outputs. The research shows that using diverse synthetic data actually mitigates this collapse. 2️⃣ It corrects self-preference bias. AI models naturally favor their own outputs—a massive problem if you want an objective system. Training models on a highly diverse mix of synthetic data from different architectures actively reduces this bias. 3️⃣ It forces us to evolve AI safety. The study found that synthetic fine-tuning can bypass built-in guardrails while keeping output quality deceptively high. This proves just how capable synthetic data is at shaping model behavior. In summary, no , synthetic data isn't just "fake data" for QA. It is a tool for achieving the epistemic diversity so models need can actually understand and operate in the real world. https://lnkd.in/g-26fhC8 #AI #LLMs #SyntheticData #MachineLearning #Datamanagement #ResponsibleAI #Epistemics

Excited to be speaking at Data + AI Summit on building governed synthetic data lakehouses with AI agents—hope to see you there! Thank you for the opportunity KPMG US. #DataAISummit #Databricks #Data #syntheticdata #KPMG https://lnkd.in/gQKvUd6w

𝗦𝘆𝗻𝘁𝗵𝗲𝘁𝗶𝗰 𝗗𝗮𝘁𝗮 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗠𝗮𝗿𝗸𝗲𝘁 𝗦𝗶𝘇𝗲 𝘁𝗼 𝗥𝗲𝗮𝗰𝗵 𝗨𝗦𝗗 𝟯.𝟳𝟵 𝗕𝗶𝗹𝗹𝗶𝗼𝗻 𝗯𝘆 𝟮𝟬𝟯𝟮 𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝘁𝗵𝗲 𝗦𝗮𝗺𝗽𝗹𝗲 𝗥𝗲𝗽𝗼𝗿𝘁: https://lnkd.in/dWkFMnbH The Synthetic Data Generation Market size was USD 0.29 billion in 2023 and is expected to reach USD 3.79 billion by 2032 and grow at a CAGR of 33.05% over the forecast period of 2024-2032. The Synthetic Data Generation Market is experiencing a robust expansion due to the escalating need for data privacy and the ever-growing volume of big data. Organizations are increasingly adopting synthetic data solutions to mitigate the risks associated with using real datasets, thus ensuring compliance with stringent regulatory frameworks such as GDPR and CCPA. This burgeoning market is driven by advancements in machine learning algorithms, which enhance the fidelity and utility of synthetic datasets. The technology finds applications across diverse sectors including finance, healthcare, autonomous vehicles, and retail, providing significant benefits like cost efficiency and scalability while maintaining privacy integrity. Key players in this arena are leveraging artificial intelligence to generate high-quality data outputs that approximate real-world datasets without compromising sensitive information. These developments indicate a promising growth trajectory for stakeholders aiming to harness AI-driven insights while upholding ethical standards of data usage. 𝗞𝗘𝗬 𝗣𝗟𝗔𝗬𝗘𝗥𝗦:  • Amazon  • Microsoft   • Gretel  • YData (acquired by KPMG)  • MOSTLY AI  • DataGen Technologies,   • NVIDIA  • CVEDIA  • Synthesis AI  • IBM  • MDClone #SyntheticData #SyntheticDataGeneration #ArtificialIntelligence  #CloudComputing #BigData #AITraining #SimulationTechnology #PrivacyPreservingAI #DataScience #DigitalTransformation #TechInnovation 

𝗦𝘆𝗻𝘁𝗵𝗲𝘁𝗶𝗰 𝗗𝗮𝘁𝗮 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗠𝗮𝗿𝗸𝗲𝘁 𝘁𝗼 𝗛𝗶𝘁 𝗨𝗦𝗗 𝟯.𝟳𝟵 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 𝗯𝘆 𝟮𝟬𝟯𝟮 𝗚𝗲𝘁 𝗳𝗿𝗲𝗲 𝘀𝗮𝗺𝗽𝗹𝗲 𝗣𝗗𝗙: https://lnkd.in/gkmEMFdS The Synthetic Data Generation Market is expanding rapidly, driven by growing concerns around data privacy and the need for high-quality datasets in AI model training. It enables organizations to simulate real-world scenarios without exposing sensitive information, supporting secure and efficient data-driven decision-making. Advancements in technologies like GANs and reinforcement learning are enhancing the quality and diversity of synthetic datasets across industries such as healthcare, finance, and autonomous systems. Regulatory pressures around data protection are further encouraging adoption. Companies are investing in research and strategic collaborations to strengthen their capabilities and global presence. As industries prioritize innovation and cybersecurity, the market is expected to witness sustained growth. 𝗞𝗲𝘆 𝗣𝗹𝗮𝘆𝗲𝗿𝘀: • Amazon • Microsoft • Gretel Labs • YData (acquired by KPMG) • MOSTLY AI • Datagen • NVIDIA • CVEDIA • Synthesis AI • IBM • MDClone • Hazy • Mostly Synthetic • Statice • SELDON TECHNOLOGIES LIMITED • Parallel Domain #SyntheticData #ArtificialIntelligence #MachineLearning #DataScience #DataPrivacy #AIInnovation #BigDataAnalytics #DigitalTransformation #DataSecurity #FutureOfAI #DeepLearning #TechTrends