If the tech industry is to be believed, an army of chatty computerized coworkers is headed to your office, in the form of AI agents. Within individual companies or industries, they may already be there.

But just like on-boarding a human hire usually involves many new logins, these digital drudges aren’t much use without access to at least some of the constellation of platforms that make up a modern workplace. And while they won’t be rehashing last night’s game at the watercooler, they do still need to talk to each other.

These are the kinds of problems that emerging industry standardization efforts are trying to tackle. Model Context Protocol (MCP), first introduced by Anthropic, is designed to plug agents into various software tools and data sources. Google’s Agent2Agent (A2A) protocol, which debuted this April, aims to let agents communicate, even across different vendors.

Like any attempt to coordinate among varying companies, these cross-compatibility efforts can involve a tricky balance of different needs and interests. And while MCP and A2A are among the most popular at the moment, other options exist, like IBM’s Agent Communication Protocol or Oxford University’s Agora.

While it’s still very early days for these frameworks, experts said some form of communication and coordination will be needed for companies to realize their ambitions for agentic workplaces.

It's been three years since ChatGPT first thrust LLMs into the mainstream. As part of Morning Brew’s Quarter Century Project, we opted to take a look at why many businesses see these agent networks as the next big phase of AI in the workplace.

Rao Surapaneni, VP of Google Cloud’s business application platform, said A2A is meant to give agents a common language to communicate and share information.

“As a customer, when I’m deploying these platforms, how do I not reinvent the wheel and still be able to leverage expertise from different vendors and different agents?” Surapaneni explained to Tech Brew. “We designed the Agent2Agent protocol to leverage that, where the customer can retain their secure data, keep their business logic, but still expose the outcomes via agents.”

Keep reading here.—PK

Waymo has been trying to crack the code on fully self-driving vehicles for over 15 years now.

After years of gradual progress, the Alphabet-owned robotaxi startup is picking up the pace. This year, Waymo made a slew of announcements about market expansions. By the end of next year, its leaders want the company to be offering 1 million rides per week, co-CEO Tekedra Mawakana said at a TechCrunch event in October.

Most recently, Waymo announced the launch of fully autonomous robotaxis in Miami and said it would soon debut operations in four additional US cities—Dallas, Houston, Orlando, and San Antonio—before opening rides to the public in those locations next year.

In a blog post, the company laid out its “consistent” approach to expanding in a growing roster of cities with their own quirks.

“We compare our driving performance against a proven baseline to validate the performance of the Waymo Driver and identify any unique local characteristics. As needed, we then refine the Waymo Driver’s AI to navigate these local nuances—which are becoming fewer with every city,” according to the company.

Keep reading here.—JG

Are robotics about to go mainstream?

Humanoid robots are making headlines. This new generation of robotics could theoretically change how we live and work—provided we deal with security issues like surveillance and data privacy. For example, The Wall Street Journal reported that 1X Technologies’ robot, Neo, sold as an autonomous housekeeper, can be remotely controlled by a human, raising privacy concerns.

But these worries may not impact how organizations adopt robots, especially when added human control could help with certain workplace scenarios, such as supporting doctors in a hospital setting.

Ryan Steelberg, the chairman and CEO of Veritone, which builds enterprise AI solutions, said that as more companies train AI models on audio and video, robotics and autonomous-vehicle companies are “obsessed” with the “amazing amounts of training data [it takes] for us to understand the physical world with movement.”

Steelberg expects Veritone to sell indexed audio and video to train models used by autonomous vehicle and robotics companies.

“You’re seeing a rebirth in hardware,” Steelberg said. “You’re seeing a rebirth in devices at the edge. Groups have to take advantage of that.”

How human do you want this thing to look? Alamgir Karim, the University of Houston’s Dow Chair and Welch Foundation professor of chemical and biomolecular engineering, told IT Brew that sometimes humanoid robots could prove vital for certain tasks.

Keep reading here.—CN