🤖Send Your Digital Twin to Zoom Meetings, Nvidia Unveils New Tech, AI Automates Job Hunting & More!

Two Malaysians, Zila Abka and Amirul Shah, are disputing the authorship of a viral AI-generated image of Gaza. Abka, a science teacher and pro-Palestinian activist, created and shared the image using Microsoft's AI tool in February. Shah, a college student, later edited and reposted a similar image, which went viral on Instagram. Despite the similarities, Shah denies copying Abka’s work. This incident highlights the challenges of authorship and ownership in the era of AI-generated content. Google and other tech giants are grappling with similar issues, as AI continues to impact content creation and distribution.

Google will reduce AI-generated summaries in search results after issues like advising users to add glue to pizza and spreading a racist conspiracy theory. The company will limit responses from its AI Overviews service for nonsensical or satirical queries and pause answers on health-related topics. Google admitted some inaccuracies in its AI Overviews but emphasized ongoing improvements. The decision follows a series of problematic AI product launches by major tech firms. Google's adjustments include better detection of nonsensical queries, limiting user-generated content, refining health-related responses, and avoiding AI Overviews for hard-news topics.

In a conversation with Zoom CEO Eric Yuan, he discussed Zoom's evolution from a videoconferencing app to a comprehensive enterprise software platform. Yuan envisions Zoom competing with Microsoft and Google by integrating productivity tools like email, documents, and AI features. He highlighted the potential of AI to create "digital twins," avatars that can attend meetings and make decisions on behalf of users. While acknowledging the technological challenges and the need for responsible AI use, Yuan remains optimistic about the future, emphasizing Zoom's commitment to innovation and customer satisfaction. He also touched on the importance of hybrid work and maintaining a balance between in-person and virtual interactions.

OpenAI has raised significant funds to develop AI technologies but struggles with understanding how its models work. At the International Telecommunication Union AI for Good Global Summit, CEO Sam Altman admitted they haven't solved AI interpretability, making it hard to trace AI outputs to their origins. Despite assurances of safety, this issue highlights a major challenge in AI research. Other companies, like Anthropic, are also investing in interpretability to improve safety but acknowledge the complexity and cost. This problem is critical given the risks of AI, and while Altman reassures investors about safety, the core issues remain unresolved.

Retrieval-augmented generation (RAG) is transforming AI by combining large language models (LLMs) with external data sources for improved accuracy and reduced misinformation. This approach is gaining traction as companies develop software to facilitate integration. RAG is expected to become a standard feature in AI models, influencing their design and training. While RAG shows promise, challenges like handling conflicting information remain. Researchers are actively working on refining RAG to enhance the accuracy and reliability of AI systems.

Asset managers are increasingly utilizing artificial intelligence (AI) to enhance investment strategies. JPMorgan is expanding its "Moneyball" AI tool to help portfolio managers identify potential biases and improve decision-making. Voya Investment Management employs a virtual analyst to monitor stock risks alongside human research. Legalist utilizes an AI-powered search tool to identify promising litigation finance targets. Despite these advancements, skepticism remains regarding AI's ability to drive long-term returns, with some experts arguing that AI primarily focuses on short-term gains rather than accurately predicting future earnings potential.