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At 8:30 p.m. on 16 May 1916, John J. Carty banged his gavel at the Engineering Societies Building in New York City to call to order a meeting of the American Institute of Electrical Engineers. This was no ordinary gathering. The AIEE had decided to conduct a live national meeting connecting more than 5,000 attendees in eight cities across four time zones. More than a century before Zoom made virtual meetings a pedestrian experience, telephone lines linked auditoriums from coast to coast. AIEE members and guests in Atlanta, Boston, Chicago, Denver, New York, Philadelphia, Salt Lake City, and San Francisco had telephone receivers at their seats so they could listen in.

The AIEE, a predecessor to the IEEE, orchestrated this event to commemorate recent achievements in communications, transportation, light, and power. The meeting was a triumph of engineering, covered in newspapers in many of the host cities. The Atlanta Constitution heralded it as “a feat never before accomplished in the history of the world.” According to the Philadelphia Evening Ledger, the telephone connections involved traversed about 6,500 kilometers (about 4,000 miles) across 20 states, held up by more than 150,000 poles running through 5,000 switches. It’s worth noting that the first transcontinental phone call had been achieved only a year earlier.

Carty, president of the AIEE, led the meeting from New York, while section chairmen directed the proceedings in the other cities. First up: roll call. Each city read off the number of members and guests in attendance—from 40 in Denver, the newest section of the institute, to 1,100 at AIEE headquarters in New York. In all, more than 5,100 members attended.

Due to limited seating in New York and Philadelphia, members were allowed only a single admission ticket, and ladies were explicitly not invited. (Boo.) In Atlanta, Boston, and Chicago, members received two tickets each, and in San Francisco members received three; women were allowed to attend in all of these cities. (The AIEE didn’t admit its first woman until 1922, and only as an associate member; Edith Clarke was the first woman to publish a paper in an AIEE journal, in 1926.)

These six cities were the only ones officially participating in the meeting. But because the telephone lines ran directly through both Denver and Salt Lake City, AIEE sections in those cities opted to listen in, although they were kept muted; during the meeting, they sent telegrams to headquarters with their attendance and greetings. In a modern-day Zoom call, these notes would have been posted in the chat.

The first virtual meeting had breakout sessions

Once everyone had checked in and confirmed that they all could hear, Carty read a telegram from U.S. President Woodrow Wilson, congratulating the members on this unique meeting: “a most interesting evidence of the inventive genius and engineering ability represented by the Institute.”

Alexander Graham Bell then gave a few words in greeting and remarked that he was glad to see how far the telephone had gone beyond his initial idea. Theodore Vail, first president of AT&T and one of the men who was instrumental in establishing telephone service as a public utility, offered his own congratulations. Charles Le Maistre, a British engineer who happened to be in New York to attend the AIEE Standards Committee, spoke on behalf of his country’s engineering societies. Finally, Thomas Watson, who as Bell’s assistant was the first person to hear words spoken over a telephone, welcomed all of the electrical engineers scattered across the country.

At precisely 9:00 p.m., the telephone portion of the meeting was suspended for 30 minutes so that each city could have its own local address by an invited guest. Let’s call them breakout sessions. These speakers reflected on the work and accomplishments of engineers. Overall, they conveyed an unrelentingly positive attitude toward engineering progress, with a few nuances.

In Boston, Lawrence Lowell, president of Harvard University, said the discovery and harnessing of electricity was the greatest single advancement in human history. However, he admonished engineers for failing to foresee the subordination of the individual to the factory system.

In Philadelphia, Edgar Smith, provost of the University of Pennsylvania, noted that World War I was limiting the availability of certain materials and supplies, and he urged more investment in developing the United States’ natural resources.

Charles Ferris, dean of engineering at the University of Tennessee, praised the development of long-distance power distribution and the positive effects it had on rural life, but worried about the use of fossil fuels. His chief concern was running out of coal, gas, and oil, not their negative impacts on the environment.

More than a century before Zoom made virtual meetings a pedestrian experience, telephone lines linked auditoriums from coast to coast for the AIEE’s national meeting.

On the West Coast, Ray Wilbur, president of Stanford, argued for the value of dissatisfaction, struggle, and unrest on campus as spurs to growth and innovation. I suspect many university presidents then and now would disagree, but student protests remain a force for change.

After the city breakout sessions, everyone reconnected by telephone, and the host cities took turns calling out their greetings, along with some engineering boasts.

“Atlanta, located in the Piedmont section of the southern Appalachians, among their racing rivers and roaring falls, whose energy has been dragged forth and laid at her doors through high-tension transmission and in whose phenomenal development no factor has been more potent than the electrical engineers, sends greetings.”

“Boston sends warmest greetings to her sister cities. The telephone was born here and here it first spoke, but its sound has gone out into all lands and its words unto the ends of the world.”

“San Francisco hails its fellow members of the Institute…. California has by the pioneer spirit of domination created needs which the world has followed—the snow-crowned Sierras opened up the path of gold to the path of energy, which tonight makes it possible for us on the western rim of the continent of peace to be in instant touch with men who have harnessed rivers, bridled precipices, drawn from the ether that silent and unseen energy that has leveled distance and created force to move the world along lines of greater civilization by closer contacts.”

That last sentence, my editor notes, is 86 words long, but we included it for its sheer exuberance.

Maybe all tech meetings should have musical interludes

The meeting then paused for a musical interlude. I find this idea delightfully weird, like the ballet dream sequence in the middle of the Broadway musical Oklahoma! Each city played a song of their choosing on a phonograph, to be transmitted through the telephone. From the south came strains of “Dixie,” countered by “Yankee Doodle” in New England. New York and San Francisco opted for two variations on the patriotic symbolism of Columbia: “Hail Columbia” and “Columbia the Gem of the Ocean,” respectively. Philadelphia offered up the “Star-Spangled Banner,” and although it wasn’t yet the national anthem, audience members in all auditoriums stood up while it played.

For the record, the AIEE in those days took entertainment very seriously. Almost all of their conferences included a formal dinner dance, less-formal smokers, sporting competitions, and inspection field trips to local sites of engineering interest. There were even women’s committees to organize events specifically for the ladies.

I suspect no one in attendance would have predicted that in the 21st century, people groan at the thought of another virtual meeting.

After the music, Michael Pupin delivered an address on “The Engineering Profession,” a topic that was commonly discussed in the Proceedings of the AIEE in those days. Remember that electrical engineering was still a fairly new academic discipline, only a few decades old, and working engineers were looking to more established professions, such as medical doctors, to see how they might fit into society. Pupin had made a number of advancements in the efficiency of transmission over long-distance telephone, and in 1925 he served as the president of the AIEE.

The meeting concluded with resolutions, amendments, acceptances, and seconding, following Robert’s Rules of Order. (IEEE meetings still adhere to the rules.) In the last resolution, the participants patted themselves on the back for hosting this first-of-its-kind meeting and acknowledging their own genius that made it possible.

The Proceedings of the AIEE covered the meeting in great detail. Local press accounts offered less detail. I’ve found no evidence that they ever tried to replicate the meeting. They did try another experiment in which a member read the same paper at meetings in three different cities so that there could be a joint discussion about the contents. But it seems they returned to their normal schedule of annual and section meetings with technical paper sessions and discussion.

And nowhere have I found answers to some of the basic questions that I, as a historian 100 years later, have about the 1916 event. First, how much did this meeting cost in long-distance fees and who paid for it? Second, what receivers did the audience members use and did they work? And finally, what did the members and guests think of this grand experiment? (My editor would also like to know why no one took a photo of the event.)

But in the moment, rarely do people think about what later historians may want to know. And I suspect no one in attendance would have predicted that in the 21st century, people groan at the thought of another virtual meeting.

Nvidia, Oracle, Google, Dell and 13 other companies reported how long it takes their computers to train the key neural networks in use today. Among those results were the first glimpse of Nvidia’s next generation GPU, the B200, and Google’s upcoming accelerator, called Trillium. The B200 posted a doubling of performance on some tests versus today’s workhorse Nvidia chip, the H100. And Trillium delivered nearly a four-fold boost over the chip Google tested in 2023.

The benchmark tests, called MLPerf v4.1, consist of six tasks: recommendation, the pre-training of the large language models (LLM) GPT-3 and BERT-large, the fine tuning of the Llama 2 70B large language model, object detection, graph node classification, and image generation.

Training GPT-3 is such a mammoth task that it’d be impractical to do the whole thing just to deliver a benchmark. Instead, the test is to train it to a point that experts have determined means it is likely to reach the goal if you kept going. For Llama 2 70B, the goal is not to train the LLM from scratch, but to take an already trained model and fine-tune it so it’s specialized in a particular expertise—in this case, government documents. Graph node classification is a type of machine learning used in fraud detection and drug discovery.

As what’s important in AI has evolved, mostly toward using generative AI, the set of tests has changed. This latest version of MLPerf marks a complete changeover in what’s being tested since the benchmark effort began. “At this point all of the original benchmarks have been phased out,” says David Kanter, who leads the benchmark effort at MLCommons. In the previous round it was taking mere seconds to perform some of the benchmarks.

Performance of the best machine learning systems on various benchmarks has outpaced what would be expected if gains were solely from Moore’s Law [blue line]. Solid line represent current benchmarks. Dashed lines represent benchmarks that have now been retired, because they are no longer industrially relevant.MLCommons

According to MLPerf’s calculations, AI training on the new suite of benchmarks is improving at about twice the rate one would expect from Moore’s Law. As the years have gone on, results have plateaued more quickly than they did at the start of MLPerf’s reign. Kanter attributes this mostly to the fact that companies have figured out how to do the benchmark tests on very large systems. Over time, Nvidia, Google, and others have developed software and network technology that allows for near linear scaling—doubling the processors cuts training time roughly in half.

First Nvidia Blackwell training results

This round marked the first training tests for Nvidia’s next GPU architecture, called Blackwell. For the GPT-3 training and LLM fine-tuning, the Blackwell (B200) roughly doubled the performance of the H100 on a per-GPU basis. The gains were a little less robust but still substantial for recommender systems and image generation—64 percent and 62 percent, respectively.

The Blackwell architecture, embodied in the Nvidia B200 GPU, continues an ongoing trend toward using less and less precise numbers to speed up AI. For certain parts of transformer neural networks such as ChatGPT, Llama2, and Stable Diffusion, the Nvidia H100 and H200 use 8-bit floating point numbers. The B200 brings that down to just 4 bits.

Google debuts 6th gen hardware

Google showed the first results for its 6^th generation of TPU, called Trillium—which it unveiled only last month—and a second round of results for its 5^th generation variant, the Cloud TPU v5p. In the 2023 edition, the search giant entered a different variant of the 5^th generation TPU, v5e, designed more for efficiency than performance. Versus the latter, Trillium delivers as much as a 3.8-fold performance boost on the GPT-3 training task.

But versus everyone’s arch-rival Nvidia, things weren’t as rosy. A system made up of 6,144 TPU v5ps reached the GPT-3 training checkpoint in 11.77 minutes, placing a distant second to an 11,616-Nvidia H100 system, which accomplished the task in about 3.44 minutes. That top TPU system was only about 25 seconds faster than an H100 computer half its size.

A Dell Technologies computer fine-tuned the Llama 2 70B large language model using about 75 cents worth of electricity.

In the closest head-to-head comparison between v5p and Trillium, with each system made up of 2048 TPUs, the upcoming Trillium shaved a solid 2 minutes off of the GPT-3 training time, nearly an 8 percent improvement on v5p’s 29.6 minutes. Another difference between the Trillium and v5p entries is that Trillium is paired with AMD Epyc CPUs instead of the v5p’s Intel Xeons.

Google also trained the image generator, Stable Diffusion, with the Cloud TPU v5p. At 2.6 billion parameters, Stable Diffusion is a light enough lift that MLPerf contestants are asked to train it to convergence instead of just to a checkpoint, as with GPT-3. A 1024 TPU system ranked second, finishing the job in 2 minutes 26 seconds, about a minute behind the same size system made up of Nvidia H100s.

Training power is still opaque

The steep energy cost of training neural networks has long been a source of concern. MLPerf is only beginning to measure this. Dell Technologies was the sole entrant in the energy category, with an eight-server system containing 64 Nvidia H100 GPUs and 16 Intel Xeon Platinum CPUs. The only measurement made was in the LLM fine-tuning task (Llama2 70B). The system consumed 16.4 megajoules during its 5-minute run, for an average power of 5.4 kilowatts. That means about 75 cents of electricity at the average cost in the United States.

While it doesn’t say much on its own, the result does potentially provide a ballpark for the power consumption of similar systems. Oracle, for example, reported a close performance result—4 minutes 45 seconds—using the same number and types of CPUs and GPUs.

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