Historical Context & Evolution of AI - The field of AI began in 1956 with the vision of simulating human intelligence [1] - AI experienced "AI winters" in the 1970s and 1990s due to unmet promises [3][4] - A turning point arrived in the 2000s with researchers like Jan Leun, Joffrey Inton, and Joshua Benjo, who focused on machine learning from data [6][7] - Alexnet's image recognition capabilities in 2012 marked another significant advancement [10][12] - The release of Chat GPT by Open AI in November 2022 led to rapid adoption, reaching 1 million users in 5 days [15][16] Company's Journey & Business Impact - The company recognized the need to make AI accessible and understandable to a wider audience [2] - Initial challenges included convincing businesses of AI's practical value [6] - The company observed a shift in 2020 when businesses started recognizing AI's potential to save time and money [8] - The company established an AI observatory and witnessed AI transforming from science fiction to a business driver [9] - The company launched the AI week, a European fair for AI, to connect experts and those seeking to understand AI [14] - The company created AI Play, a platform for learning AI in a simple and on-demand manner [18] Current Landscape & Future Outlook - Europe released the AI Act, the first regulation on AI, addressing rights, risks, and opportunities [19][20] - A global race for leadership in AI is underway, involving companies from Silicon Valley, China, and others [20] - The company has evolved into an ecosystem of 20 people, creating content, training individuals, and organizing events [21] - The company acknowledges the ongoing evolution of AI, including robotics, agents, multimodality, and general AI, while emphasizing that no one has all the answers [22] - The company views AI as a tool that is neutral and requires human direction to determine its impact [23][24]

Google announced on Wednesday its plans to sign onto the European Union's "Code of Practice" for artificial intelligence, a set of guidelines on how businesses can follow the rules of the E.U.'s new AI Act. https://t.co/LU17c1Gvka ...

AI Fundamentals & History - AI has been studied for almost a century and integrated into daily life for decades, exemplified by facial recognition and voice assistants [2] - Large language models (LLMs) have driven recent AI advancements, making AI conversational and accessible [5] - AI systems learn from vast amounts of text and other data, enabling them to generate human-like text, but they lack human-level understanding, feelings, and consciousness [8] AI Risks & Ethical Considerations - AI-generated content raises copyright concerns due to the lack of mechanisms to trace the origin of training data and compensate original creators [12] - AI can perpetuate and amplify societal biases present in the data it is trained on, leading to discriminatory outcomes [19] - The use of AI for social scoring, as experimented with in some countries, raises concerns about privacy and restriction of personal freedoms [15] - The European Union's AI Act aims to regulate AI development and usage based on risk levels, prohibiting certain applications like social scoring [16] AI Limitations & Future Directions - AI systems, particularly LLMs, struggle with numerical and spatial reasoning [21][22] - It is crucial to educate and promote conscious development and usage of AI [24] - AI is not a magical solution but a tool that requires human intelligence to understand, regulate, and guide its development [25] - Research efforts, such as the EU-funded Infinity project, focus on improving the quality and representativeness of data used to train AI, particularly in the context of cultural heritage [20]

A surgical pause on the most ambiguous parts of the the EU's AI Act would help make sure that when the rules do arrive, they work, writes @parmy (via @opinion) https://t.co/f4m4ebRAEQ ...