Autonomous trucking company Plus AI’s DC point person is “cautiously optimistic” that the federal government will soon establish a national regulatory framework for autonomous vehicles.

“The prior administration, my group of folks, we were working to establish a set of guardrails,” Earl Adams Jr., former deputy administrator for the Federal Motor Carrier Safety Administration and now the VP of public policy and regulatory affairs for Plus, said at a June 3 roundtable in Detroit.

“This is maybe the one bipartisan issue that I have found,” he added, “that the current administration is still looking at establishing a set of guardrails around the initial deployment of commercial vehicles.”

Keep reading here.—JG

To go open or closed?

It’s one of the key questions businesses face when building new LLM-based applications. Whether enterprise developers choose to build around open models or plug into proprietary APIs can result in trade-offs around customization, cost, security, and performance.

At New York Tech Week in IBM’s Manhattan offices last week, a panel of experts talked about some of the considerations for businesses building on open models like Meta’s Llama family and Google’s Gemma. The AI Alliance, an IBM- and Meta-backed group that promotes open-source AI, hosted the event.

The panel began with an exchange of definitions; this is important because there’s no fully agreed-upon standard for what is or isn’t an open-source model, though the Open Source Initiative has offered one up. It depends on which of the three broad components—model weights, source code, or training datasets—developers make available.

When asked what type of systems they worked with, a show of hands failed to result in an obvious front-runner—sizable portions of the audience indicated support for open, closed, and hybrid models.

Keep reading here.—PK

AI agents might be taking on more responsibilities at work, but maybe think twice before handing over full access to payments.

A new paper from researchers at Princeton University and the Sentient Foundation found that certain agents—AI systems that can act beyond the realm of a chatbot—could be vulnerable to memory attacks that trick them into handing over cryptocurrency.

Targeting agents created with the platform ElizaOS, the researchers were able to implant false memories or “malicious instructions” that manipulated shared context in a way that could lead to “unintended asset transfers and protocol violations which could be financially devastating.” They wrote that the vulnerabilities point to an “urgent need to develop AI agents that are both secure and fiduciarily responsible.”

Keep reading here.—PK

We were promised a self-driving future years ago. So why aren’t robotaxis everywhere yet? From billion-dollar bets to brutal setbacks, the autonomous vehicle industry has hit some surprising detours. But insiders say a major shift is coming—and it may change how we get around forever.