Google DeepMind is funding research into the potential dangers of situations where millions of different AI agents interact with each other online. According to Rohin Shah, who directs the company’s AGI safety and alignment research, the mass-market arrival of agents that can carry out tasks without human oversight and follow instructions given to them by other…

Using AI to build dashboards is genuinely fast and getting faster. But there are watchouts that most teams don’t hit until they’ve already shared an AI-generated view with a stakeholder who asks a question the dashboard can’t answer. We hope this checklist will help you know what to avoid and how you can fix the problems.

Large language models usually generate text one token at a time. While this autoregressive approach delivers strong quality and instruction following, it can be inefficient for local users because GPUs often spend more time moving weights from memory than doing parallel compute. Google DeepMind’s DiffusionGemma takes a different path, generating and refining blocks of tokens […] The...

As AI agents become more capable and autonomous, they also introduce new security challenges. In this 'Fully Connected' episode, Dan and Chris unpack Anthropic’s Zero Trust for AI Agents security framework and what it means for organizations deploying agentic systems. They examine the key security risks facing agentic systems and discuss how organizations can apply Zero Trust principles to...

Reading Time: 2 minutesThe Challenge of Non-Native AS2 Integrations For enterprises exchanging high-value B2B transactions—such as EDI purchase orders, healthcare claims, and financial invoices—the Applicability Statement 2 (AS2) protocol is the industry benchmark for secure, reliable transport. Historically, teams working in BusinessWorks (BW) often had to stitch together external tools,...

New research from SmarterX surfaced not just where B2B marketers are in their AI journey but how they feel about it.

We had a campaign we wanted to get in front of the right people. The problem was familiar: We had a targeted list of business leaders we genuinely thought would benefit from what we were promoting, but no clean process for actually reaching them at scale. And we didn’t have enough time to do it the slow way [read: without AI].

Pharma commercial teams are generating more data than ever, but field intelligence is still arriving too late to change rep behavior before the engagement window closes. In this episode, Damion Nero, Global Head of Statistics at Daiichi Sankyo, joins Emerj editor Yolandi de Weerdt to examine why fragmented data pipelines, not a shortage of data, are the structural root of the gap between...

Enterprise AI agents fail consistently in production, not because of model limitations, but because they lack a live, temporally aware context layer grounded in the actual current state of the business. In this episode, Ravi Marwaha, Chief Operating Officer & Chief Technology Product Officer at Arango, explores how treating context as infrastructure—rather than a data pipeline...

AI tools have gone from “fun to try” to part of the daily workflow. There’s an AI tool for almost everything nowadays, readily accessible for all. The problem is no longer access. It’s choice. Every week, a new tool promises to save time, boost creativity, or replace half your workflow. Most just add another tab […] The post Top 10 AI Engineering Tools Everyone is Using in 2026 appeared...