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InfoQ Podcast Discusses 2026 AI, ML, and Data Engineering Trends
Key points
- Shift from large to small language models and rise of reasoning models.
- AI agents are a major trend, moving from personal to organizational use.
- System One models like TypeSafe AI’s Jev gaining adoption for faster inference.
- Significant developments in physical AI, connecting software to physical machines.
Overview of InfoQ Trends Report
InfoQ's AI, ML, and Data Engineering editorial team, along with an external guest, discussed the 2026 trends in AI and ML. This podcast is part of InfoQ's regular features, which provide overviews of topics in software development. The discussion supplements a written report and trends graph.
Key AI and ML Trends for 2026
Language models are shifting from large-scale models to smaller, more specialized versions, alongside the emergence of reasoning models capable of solving logic and math problems. AI agents are identified as a significant trend, expanding from individual use to team and organizational applications. System One models, such as TypeSafe AI’s Jev, are expected to see increased adoption due to their faster inference and lower operational costs compared to traditional large language models.
Developments in AI Evaluation and Physical AI
AI evaluations have received considerable attention, focusing on ensuring agents perform tasks correctly. Physical AI has also seen developments in 2026, involving the integration of software intelligence with machines that can perceive and interact with the physical world.
Panelists' Predictions for the Coming Year
Panelists predict more innovations from US-based robotics companies, along with the development of cheaper and faster AI models. They also anticipate limitations on AI due to energy and infrastructure constraints. Other predictions include the incorporation of Jev-like models into AI agents, applications using smaller specialized agents for mixed models, and AI becoming a larger part of daily life, with niche areas identified where AI provides value while still requiring human intelligence.
✨ This summary was generated by AI from the outlets' reporting listed below. It is not independently verified and may contain errors — check the original sources. How BrevFeed works →
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Reporting from
An InfoQ podcast featuring its AI and ML editorial staff and guests discussed current trends in AI, ML, and data engineering for 2026. The discussion covered shifts from large to small language models, the rise of AI agents, and developments in physical AI. Key predictions include increased adoption of System One models and more innovations in US-based robotics.