Enterprise ai

⚡️Every product of the future will be a living system  — Ronak Malde, Trajectory.ai

⚡️Every product of the future will be a living system — Ronak Malde, Trajectory.ai

Ronuk Malde, CEO of Trajectory.ai, discusses his journey from building AI coding agents at Windsurf to his current focus on continual learning for enterprise AI. He shares insights on leveraging real-world user data, the unique challenges of model acquisition, and how Trajectory.ai's platform, powered by innovations like scaled SDPO and a novel training stack, enables dynamic, always-learning AI models for diverse industries from legal to finance.

6 Things to Know about AIE World's Fair 2026

6 Things to Know about AIE World's Fair 2026

Discover the AI Engineering World's Fair 2026, the largest iteration yet, offering an unparalleled deep dive into AI engineering with expanded tracks on auto research, GPU specialization, and new verticals like finance and healthcare. Highlights include an innovative expo experience, exclusive leadership initiatives like the "Token Billionaires Program," and unique side events fostering community, including "Posters on AI" where attendees can defend their tweets. This event is designed to be a curated hub for practical, cutting-edge insights and networking in the AI/ML professional landscape.

Stop Making Models Bigger, Make Them Behave — Kobie Crawdord, Snorkel

Stop Making Models Bigger, Make Them Behave — Kobie Crawdord, Snorkel

Snorkel.ai's research demonstrates how a 4-billion-parameter model, fine-tuned with Reinforcement Learning for under $500, significantly outperformed a 235-billion-parameter model on financial analysis tool-use tasks. The key was cultivating 'tool discipline' and error correction capabilities, rather than relying on sheer model size or deeper reasoning. Single-table training generalized effectively to harder multi-table problems, emphasizing the importance of targeted behavioral fixes identified through detailed evaluation rubrics.

Why AI Agents Break Zero Trust at the Last Mile

Why AI Agents Break Zero Trust at the Last Mile

AI agents introduce a critical security gap when connecting to legacy enterprise systems, known as the 'agentic last mile identity problem'. This summary explains how losing user identity, context, and delegation breaks zero-trust principles and outlines a solution using a policy-driven vault to manage access and issue short-term credentials.

AI skills security, Open AI Deployment Company & zero days

AI skills security, Open AI Deployment Company & zero days

This discussion explores IBM Research's MELLEA, a skills compiler designed to secure AI agents by transforming natural language skills into verifiable Python programs. It also analyzes OpenAI's new consulting venture, the "Deployment Company", and debates the future of AI in consulting. Finally, it delves into the escalating AI-driven cybersecurity arms race, highlighted by Google's discovery of an AI-found zero-day, and wraps with insights from the Red Hat Summit on enterprise AI transformation being a cultural challenge before a technological one.

Physical AI Forum | Builders Reveal the New Moat & Playbook | Creator & Founder's Cut | Mar 2026 |4K

Physical AI Forum | Builders Reveal the New Moat & Playbook | Creator & Founder's Cut | Mar 2026 |4K

In a live panel at the Physical AI Builders Forum, founders and operators in computer vision, robotics, and multimodal AI share their 2026 playbooks. The discussion covers the architectural differences between physical and generative AI, the strategic shift from frame AI to scene AI for enterprise value, and the critical skills needed to build and scale a modern AI business.