Staying updated in the rapidly evolving AI industry can be challenging. To help you stay informed, here is a summary of recent developments in the field of machine learning. SpeedyBrand, a company utilizing generative AI for SEO-optimized content creation, recently emerged and received backing from Y Combinator. However, the rise of generative AI has also led to an increase in low-quality content and misinformation. Newsguard uncovered numerous ad-supported sites using generative AI to create misleading content, causing concerns for advertisers. The scalability of generative AI makes it difficult for search engines and ad platforms to effectively combat this problem. While spammy content is not new, the low barrier to entry and cost involved in generative AI exacerbates the issue. OpenAI launched GPT-4, an advanced text-generating model that outperforms its predecessor, GPT-3.5, by accepting image and text inputs. OpenAI also created a team to develop methods for guiding and controlling “superintelligent” AI systems. New York City implemented a law requiring employers to submit algorithms used in hiring and promotion for an independent audit. Valve clarified its policy on AI-generated assets in games distributed on its Steam platform. Humane unveiled its first product, the Ai Pin, a wearable gadget with AI capabilities. European tech leaders signed an open letter warning against EU laws that could hamper generative AI innovation. Additionally, deepfake scams, AI-generated sex toys, and other machine learning projects were highlighted. Notable projects include a smart intubation device, ETH Zurich researchers’ contribution to animating smoke and fire for a Pixar movie, and the use of AI in archaeology to discover new Nasca lines in Peru. AI is also being employed to predict natural disasters such as wildfires and landslides. Finally, Google is researching “machine unlearning” to prevent ML systems from propagating dangerous or harmful knowledge.
