RO AI Alliance

⚡ 𝗖𝗮𝗻 𝗔𝗜 𝗱𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗔𝗜 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗰𝗼𝗲𝘅𝗶𝘀𝘁? Startups move fast and break things. Corporations scale big and optimize. Who’s actually driving AI forward? 🎤 Hear Luca S., Paul Muntean, Andrei Petreanu, and Tudor-Gabriel Predună share real-world insights on 𝘪𝘯𝘯𝘰𝘷𝘢𝘵𝘪𝘰𝘯 and 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘪𝘰𝘯. ⌛ Join us on Feb 13, 18:30 Lenovo HQ for a high-energy debate with AI founders and industry experts! 🚀💡 𝗥𝗦𝗩𝗣 now to secure your spot

It’s easier to walk on already-paved roads than to forge a new path and AI development is no exception. The recent discussion around DeepSeek is the perfect evidence for this. Moreover, while they’ve built on a foundation of open-source models and innovation, the nuances of true openness remain complex. Is it truly open source (yes, there is a DeepSeek github) if their claims can’t be fully validated without access to their specific hardware architecture? One thing is certain: the conversation around open-source is evolving. We look forward to diving deeper into these topics at the upcoming RO AI Alliance meet-ups starting in February. Let’s engage in meaningful discussions about the future of AI! 🚀

🚨𝗥𝗲𝗺𝗲𝗺𝗯𝗲𝗿 𝘄𝗵𝗲𝗻 𝘄𝗲 𝘁𝗮𝗹𝗸𝗲𝗱 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗘𝗨 𝗔𝗜 𝗔𝗰𝘁? The EU AI Act, set to become the global gold standard for AI regulation, introduces a risk-based approach to ensure trustworthy AI while fostering innovation. But as this ambitious framework unfolds, challenges for stakeholders are becoming clearer and clearer:  → 𝗦𝘁𝗮𝗿𝘁𝘂𝗽𝘀: Can they afford the cost of compliance without stifling innovation?  → 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀𝗲𝘀: Will navigating risk categories slow AI integration?  → 𝗥𝗲𝗴𝘂𝗹𝗮𝘁𝗼𝗿𝘀: Can enforcement keep the pace with rapid AI advancements?  → 𝗖𝗼𝗻𝘀𝘂𝗺𝗲𝗿𝘀: Will transparency build trust or overwhelm them? 𝗪𝗵𝘆 𝗜𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀: The EU AI Act is more than a regulatory framework, it’s a blueprint for how societies worldwide might manage AI’s transformative power. From banning harmful AI applications (e.g social scoring and subliminal manipulation) to requiring human oversight for high-risk systems, the Act strives to safeguard fundamental rights. 𝗛𝗼𝘄𝗲𝘃𝗲𝗿,... As Philipp Justus, Google’s Vice President for Central Europe, said: “It’s a bit like creating traffic laws before we’ve even built the first car.” 𝙃𝙤𝙬 𝙙𝙤 𝙬𝙚 𝙚𝙣𝙨𝙪𝙧𝙚 𝙘𝙤𝙢𝙥𝙡𝙞𝙖𝙣𝙘𝙚 𝙬𝙞𝙩𝙝𝙤𝙪𝙩 𝙨𝙩𝙞𝙛𝙡𝙞𝙣𝙜 𝙞𝙣𝙣𝙤𝙫𝙖𝙩𝙞𝙤𝙣? . . . 𝘐𝘮𝘢𝘨𝘦 𝘴𝘰𝘶𝘳𝘤𝘦: 𝘩𝘵𝘵𝘱𝘴://𝘭𝘯𝘬𝘥.𝘪𝘯/𝘦𝘡𝘚7𝘠𝘔𝘠𝘟

We need Ethical Media. Now. https://lnkd.in/eb6RuHJp

We need to talk about what happened over the last few weeks! While we have tried to steer away from any political content, we feel it is our responsibility, in this community, to understand what are the mechanisms for manipulation and disinformation that many of you can come across online. So we're going to do this our way. Who's interested in a talk about about ethical media, bots, identity verification, deepfakes? Is AI the solution or the problem? Is it both? Lets meet next week with a very special guest. More details coming tomorrow. PS : this image is generated by AI to draw attention to this post. Lets keep things fun, in the spirit of celebrating a crazy 2024. #machinelearning #community #deepfakes #bots #ethicalmedia

There's a new learning path on Google Cloud Skills Boost: Integrate generative AI into your data workflow. In this collection of courses, hands-on labs, and skill badges, you'll learn how to use BigQuery Machine Learning for inference, work directly with Gemini models in BigQuery, and enhance your data team’s efficiency with Gemini's assistance.

Not everyone is convinced of generative AI’s return on investment. But many investors are, judging by the latest figures from funding tracker PitchBook. In Q3 2024, VCs invested $3.9 billion in generative AI startups across 206 deals, per PitchBook. (That’s not counting OpenAI‘s $6.6 billion round.) And $2.9 billion of that funding went to U.S.-based companies across 127 deals.

Being fluent in AI is “important for employability”, according to a top tech executive with a leading French unicorn. Aymeric Augustin, CTO of Qonto, a French business banking fintech, says that more than half of Qonto’s 1,600 staff are using GenAI as a work tool, increasing from zero use to over 50 percent in around four months. Augustin says it will help its employees be more employable in the future.

In the early years, getting AI models like ChatGPT or its rival Cohere to spit out human-like responses required vast teams of low-cost workers helping models distinguish basic facts such as if an image was of a car or a carrot. But more sophisticated updates to AI models in the fiercely competitive arena are now demanding a rapidly expanding network of human trainers who have specialized knowledge -- from historians to scientists, some with doctorate degrees.

A three-lens approach–on adoption, creation, and energy–is required to assess Europe’s competitiveness in the emerging generative AI (gen AI) economy. While much of the current discourse centers around large language models (LLMs), European policy makers and business leaders must look beyond LLMs. Adopting a holistic approach to capitalize fully on gen AI’s potential could boost European labor productivity by up to 3 percent annually through 2030.