NEWS IN BRIEF: AI/ML FRESH UPDATES

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Tech Hurdles: Government AI Struggles

The Public Accounts Committee warns of risks to government efficiency from outdated technology and digital skills shortages. Over 20 legacy IT systems still lack funding for improvement, hindering AI integration efforts.

Unlocking the Potential of Multimodal AI

Artificial intelligence advancements, like OpenAI's GPT-4o models, show potential in understanding and analyzing various images. Tests reveal impressive capabilities in processing complex visual data, offering a glimpse into the future of AI applications.

Create Your Own AI Coding Assistant in JupyterLab

Jupyter AI integrates generative AI capabilities into JupyterLab, offering a local coding assistant for developers. The tool, compatible with Jupyter notebooks and Google Colaboratory, simplifies setup with access to various model providers.

Labour MP warns No 10 on AI concerns

Chi Onwurah calls for AI safety bill amid concerns of government prioritizing Trump over regulation. The bill would mandate tech companies to submit large language models for testing in the UK.

AI: The Ultimate Intelligence Amplifier

Reid Hoffman, co-founder of LinkedIn, believes AI can empower society, as detailed in his book Superagency. Despite economic interests, he advocates for ethical use of technology and transparent communication.

Apple's Siri Misstep: Rushed AI Mania

Apple unveiled its unique take on AI at WWDC: "Apple Intelligence" - a collection of features for iPhone 15 Pro users. The move surprised the tech industry amidst the ChatGPT hype, showcasing Apple's distinctive approach to the technology.

Google's Data Science Agent: Job Threat?

Google's Data Science Agent in Colab simplifies data analysis with Gemini, automating tasks and providing customizable plans. It offers end-to-end execution and autocorrection, potentially reshaping data science workflows.

AI Revolutionizing Product Operating Models

Empowered product teams evolve to meet AI challenges with the 3-in-a-box model: product management, design, and engineering. Historical context and key phases in team composition highlight the importance of core competencies for successful AI-powered products.