According to God of Prompt (@godofprompt), the AI Skills 2026 conference is set to bring together 8,000 AI builders for over four hours of actionable strategy sessions focused on practical applications and business growth opportunities in artificial intelligence. The event, highlighted by its zero-cost registration and access to session recordings, positions itself as a must-attend for professionals aiming to stay competitive in the rapidly evolving AI industry (Source: https://x.com/godofprompt/status/2014016730087964992). The conference emphasizes real-world use cases, market trends, and networking, creating a unique platform for AI practitioners and companies looking to leverage AI for scalable solutions.

According to Andrew Ng (@AndrewYNg), improving large language models (LLMs) currently relies on a piecemeal, data-centric process rather than sweeping breakthroughs. Ng highlights that while LLMs demonstrate greater generality than prior AI systems, their ability to learn and adapt is still limited compared to humans. For specific applications—such as programming in niche languages or delivering accurate healthcare and finance insights—AI teams must curate, clean, and generate specialized data sets, often involving labor-intensive tasks like deduplication and paraphrasing (source: deeplearning.ai/the-batch/issue-332). Additionally, enabling LLMs to handle complex tasks such as web browsing requires building simulated environments for reinforcement learning. This data-centric approach shapes current AI development and signals significant business opportunities for firms specializing in domain-specific data engineering, annotation, and AI infrastructure. Ng forecasts that ongoing incremental improvements, rather than rapid leaps toward AGI, will continue to drive practical AI adoption and market growth in the coming years.

According to Jeff Dean (@JeffDean) on Twitter, his team is actively pushing the boundaries of machine learning, a trend that reflects the ongoing drive for innovation in AI research and development. This commitment to advancing machine learning techniques is fueling new business opportunities in sectors like healthcare, finance, and autonomous systems, as organizations seek to leverage the latest AI breakthroughs for practical applications and competitive advantage (source: https://twitter.com/JeffDean/status/1983388997515915732).