The winter solstice is weeks away, but on a recent sunny October day at a Ford facility in Southeast Michigan, it was already here.

At least, it felt that way in a so-called “soak room” at the automaker’s Drivability Testing Facility, where temperatures plunge as low as -40 degrees Fahrenheit. Here, engineers recreate winter conditions as part of extensive testing to validate that in-development vehicles are prepared for basically any scenario they might encounter in the real world.

Every vehicle model is tested not only to meet federal safety requirements, but so that manufacturers can catch issues before the vehicles go into mass production and thereby avoid costly fixes once they’re on the market. Tests touch on fuel efficiency, vehicle weight, heating and cooling systems, and much more.

Tech Brew got a behind-the-scenes look at some of Ford’s processes, which use continuously evolving technologies to make sure that vehicles are safe, durable, and perform well in a variety of conditions. These methods are adapting to meet some of the unique characteristics—and challenges—of electric vehicles.

“Historically, everything’s been combustion engines. That’s what this place was built for, and every other test facility,” Wind Tunnel Engineer Doug Olson told us. “Battery vehicles, they behave differently in the cold…So, we’ll develop different testing to see how much the battery may degrade parked overnight in the cold.”

“They’re pretty different vehicles,” he added, “so we end up doing a lot of different tests.”

Keep reading here.—JG

In part two of our conversation with Rishi Bommasani, society lead at the HAI’s Center for Research on Foundation Models, we discuss where AI is actually proving most dangerous, why openness is important, and how regulators are thinking about the open–closed divide.

This conversation, the second of two parts, has been edited for length and clarity, and contains references to materials related to child abuse.

I want to ask about the benefits. As OpenAI has moved toward a more closed model, and some of these other big companies have become more closed as more money has gone into the AI race, is there still a robust open foundation model ecosystem?

It’s definitely been true for a while—and I would say it’s still true—that if you only care about raw capabilities, the most capable models are still on the closed side. Both the open developers and the closed developers are constantly improving capabilities…and right now, what you would see is that the open developers are closer to the closed ones than they have been in the past. But I think this also reflects that we don’t have great benchmarks for really revealing the most capable models, like a lot of things are saturating at the moment.

The other thing I would say, though, is where open models are doing very well is really not [in] just broad capabilities, but the capabilities-to-cost tradeoff, which is ultimately what most businesses will care about. And this appears in a few different ways.

Keep reading here.—PK

Don’t expect tech giants to shut their checkbooks any time soon when it comes to AI.

That was one message from last week’s quarterly earnings reports as Meta, Microsoft, and Alphabet each forecast big spending on data center infrastructure and other AI-related expenses continuing into the coming year. Those numbers, as well as a predicted slowing of cloud growth at Microsoft, seemed to distract investors from earnings beats as Meta and Microsoft stocks dipped on Thursday.

But what else is new? Wall Street has been antsy about AI spending for months now, the companies have continued to post strong results bolstered by cloud and ad revenues, and execs have attempted to reassure investors that the returns will come eventually.

“This part of the formula around building out the infrastructure is maybe not what investors want to hear in the near term, that we’re growing it out,” Meta CEO Mark Zuckerberg said. “But I just think that the opportunities here are really big. We’re going to continue investing significantly in this.”

Keep reading here.—PK