2026-07-29 02:00:01
In shaping her career, Peru native Mariana Costa has asked herself a question: What can I do to make life better for women in Latin America?
The answer she landed on was training them for tech jobs.
Employer
Laboratoria
Title
Co-founder and president
Alma Maters
London School of Economics; Columbia
Such positions pay well and are in demand. And for too long, women across the region have been locked out of them, she says.
Costa is president of Laboratoria, a U.S.-registered nonprofit based in Miami that she helped found. Laboratoria has trained thousands of women in 11 Latin American countries for technology careers. She has built training centers in the countries and has placed graduates at major companies. Meanwhile, she has become one of the most recognized voices in the region on workforce equity and tech education for women.
IEEE recognized her work with its President’s Award this year for her “distinguished leadership and contributions to the betterment of society.” Recipients of the award are selected by the IEEE president with the consent of the IEEE Board of Directors.
Costa says the recognition came as a surprise because she is not an engineer by training and had never considered becoming affiliated with IEEE.
She was presented with the award at the IEEE Honors Ceremony on 24 April in New York City.
Costa grew up in Lima, Peru’s capital, in a household with no connection to engineering or technology. Her mother was an art historian and professor, and her father was a lawyer. The family was financially comfortable and traveled abroad regularly. Costa attended well-resourced schools.
That economic stability came with a reckoning, Costa says, in that she recognized early on that economic inequality had created separate societies inside Peru. Her parents, she says, made it “clear that my reality wasn’t the reality of most people in my country.”
Lima is a microcosm of the country, she says. The divide in the capital city is visible: A kilometers-long concrete wall topped with barbed wire separates wealthier neighborhoods from shantytowns, where residents lack running water.
Nationally, there are splits along ethnic and geographic lines. The highland and jungle regions remain home to mostly indigenous communities with limited educational access and a deep cultural distance from the Hispanic-dominated coast.
The questions that stirred in her as a child never left, she says.
“Why do I live in a country where so much depends on where you’re born?” she asked herself. “What does it mean to be Peruvian when individual realities are strikingly different?”
Those questions followed her to the London School of Economics, where she studied international relations, graduating with a bachelor’s degree in 2007. She held onto the questions when she moved to Washington, D.C., where she spent the next four years working for the Organization of American States, helping Latin American governments improve public services that fall under the heading of civil registration.
“I said, ‘How can it be? The tech space has so many rich opportunities. Why aren’t any women here?’”
The OAS Universal Civil Identity Program in the Americas provides technical support to national civil registry institutions, modernizing them to foster social inclusion and ensuring the right to civil identity for all people. Without civil identity, a person can’t access education, health care, legal employment, social services, or the right to vote. People without the classification don’t exist in the eyes of the government. They also can’t own property, get married officially, or pass citizenship rights to their children.
Doing that work deepened her concern about the socioeconomic disparities in her homeland, she says. In search of practical solutions to those problems, she went to New York City in 2011 to further her education. She earned a master’s degree in public administration and development from Columbia in 2013.
Technology was not yet part of a solution. But Costa already had met someone who would change that.
While working in Washington, Costa met Herman Marìn, a software engineer who used digital tools in support of social causes. Because he was doing work she had never associated with programmers before, her assumptions about the field dissolved quickly.
“I had a vision of [programmers doing] something not very social—strictly technical,” she says. “And my then-boyfriend, now husband, actually worked for different social movements that used technology to address social causes.”
That realization cracked something open, she says: “I said, ‘Oh! Technology can actually be a tool to address some of the more stubborn problems in our societies.’”
After earning her degree at Columbia, Costa returned to Lima with her husband. She had been abroad for nearly a decade and felt the pull of home.
“The thought of not moving back to my country was something that tormented me a bit,” she says. “I really felt I had to move back, at least to try it out and contribute somehow.”
When Costa, her husband, and a friend from graduate school moved to Lima, they had modest savings and big ambitions. They wanted to build something that combined technology with social impact.
They started with what they had: a small digital services agency, where they built websites for clients.
The business grew, and they hired more employees. Their team expanded to a dozen software engineers. And as it did, Costa noticed three things.
First, there weren’t enough trained developers to meet the demand. Second, many of their best hires did not have traditional computer science degrees. Some had never even finished college.
“There was no other space where you could actually build an amazing career and get a well-paying job without a good degree from a good school,” she says. “The tech world was different. It was open in ways other fields weren’t.”
Thirdly, she noticed that there were no women on the team. In the first six months, Costa says, they didn’t interview a single female developer.
Her colleagues shrugged. It’s just how it is, they told her.
Costa, the outsider, didn’t accept that.
“I said, ‘How can that be? The tech space has so many rich opportunities,’” she says. “‘Why aren’t there any women?’”
In 2014 she decided to launch Laboratoria. The business model was simple: Find talented women who hadn’t yet broken into tech, train them quickly on practical skills, and connect them with employers who needed developers.
Laboratoria started offering a six-month immersive boot camp that covered Web development, UX design, data literacy, strategic use of artificial intelligence, and soft-skills coaching such as interview prep and projecting confidence.
Just as important for career success, Costa says, is a user-centered mindset. She says Laboratoria’s program emphasizes the discipline of keeping the client’s needs in mind when designing the work.
The teaching model has evolved beyond the boot-camp structure, but the organization still focuses on helping Latin American women develop tech skills and land quality jobs in the digital age. These days, the training, conducted via twice-weekly live Zoom sessions, lasts six weeks.
“We needed developers ourselves,” she says of the company’s original logic. “I said, ‘Why don’t we run a program to train women—women who are incredibly talented but haven’t been given a chance yet—and help them gain the skills they need to get a great job as quickly as possible?’”
Mariana Costa [seated, right] poses with Laboratoria co-founder and CEO Gabriela Rocha and co-founder and chief product officer Rodulfo Prieto.Valeria Martens
It worked. Laboratoria expanded from Lima to Santiago, Chile; Mexico City; São Paulo, Brazil; and Bogotá, Colombia. The organization eventually incorporated as a nonprofit in the United States. Today its programs are held remotely in Latin America’s major job markets. So far, Laboratoria has opened the doors to tech careers for more than 3,500 women.
Costa says she believes the most important skills Laboratoria’s graduates need aren’t purely technical. Close behind the growth mindset is self-confidence, she says.
“Knowing who you are, valuing who you are, and learning to trust yourself and your capacities are indispensable traits,” she says.
Networking, she adds, is the third pillar, and often the hardest to build for women without access to elite schools or flexible work schedules.
“When you go out in the market,” she says, “you realize that having a network of people who trust you and know your work is such a valuable and critical asset.”
Costa’s introduction to IEEE came late—but it landed hard.
She is not an IEEE member, so when she was contacted this year about receiving the President’s Award, she did her homework on the organization. What she found, she says, was a public charity whose reach and values aligned with her mission.
“IEEE is about expanding access to opportunities in the world of technology,” she says. “And that’s also the core of what we do at Laboratoria.”
She says she also sees IEEE as a living example of something her company preaches every day: “I was talking about the value of professional networks, and I think IEEE is such an amazing reference in that space. It exemplifies this belief that human connection—not only doing your work but also sharing and learning with others—is at the core of building thriving technology careers.”
The engineering organization found her well after she launched her tech-related career. But it wasn’t too late. She says she intends to make the most of the connection.
2026-07-28 21:00:01
Physicists have been trying to measure the fundamental gravitational constant for well over two centuries. The current accepted value of big G, as it’s known, is 6.67430 × 10-11 cubic meters per kilogram per square second. It also has an uncertainty of ±0.00015 × 10-11 m3/(kg s2). As far as constants of the universe go, that’s very uncertain.
Schlamminger is a physicist at the U.S. National Institute of Standards and Technology.
Stephan Schlamminger recently completed a 10-year effort at the U.S. National Institute of Standards and Technology to replicate an earlier measurement of big G from the International Bureau of Weights and Measures, or BIPM (located near Paris) that’s notably higher than most measurements. He spoke with IEEE Spectrum about why it took so long to get a number—6.67387 x 10-11 m3/(kg s2)—and why it’s notably lower than the BIPM result, to the tune of 0.0235 percent.
Why is it so difficult to measure big G?
Stephan Schlamminger: Gravity is very weak. When you were a kid, you probably played with fridge magnets, and it was a force you could feel. But if you have two coffee cups, you can try all you want—you can’t feel the force between them. It is there, but it’s so, so weak.
How did you attempt to measure big G?
NIST used a torsion balance with a fourfold geometry. This animation shows an exaggerated version of how the outer green masses gravitationally attract the inner blue masses.S. Kelley/NIST
Schlamminger: We used what’s called a torsion balance. The key idea in the torsion balance is that it decouples vertical gravity that you have from Earth from horizontal gravity, and that makes it sensitive to masses that are around the torsion balance but not the Earth below.
Ours had a fourfold geometry. It has a very thin torsion strip, then four cylinders in a “plus sign” arrangement. All of this is inside a vacuum. Outside, we have four larger cylinders that gravitationally attract the four smaller masses to them. If I move the outer masses just a tiny little bit, the plus sign will rotate, and we measure that angle that it moves. That angle is proportional to the gravitational torque.
Why try to replicate the BIPM value?
Schlamminger: We could move the field forward. The measurements have been plagued with inconsistencies, so by redoing an experiment, we hoped to shed light on the inconsistencies.
We did not find a smoking gun, so there’s no single reason why it’s different—our value versus their value. It’s still a big question mark.
What was it like spending 10 years on this?
Schlamminger: It’s a bit like herding cats. I’ve measured other fundamental constants, like Planck’s constant, and for most experiments, they have some sort of self-calibration built in. But with the gravitational constant, you have to keep track of every single mass that moves—where they are, how big they are, and weigh them.
How does your result compare to the rest?
Schlamminger: Our result is a little bit below the standard accepted literature value. I was disappointed because it doesn’t agree with the BIPM value, nor with the literature value. If there’s something wrong with the BIPM experiment, then the literature value—which includes that result—probably ought to come down a bit. But that is not for me to say. I think somebody else, independent, should figure out what the new mean value ought to be.
2026-07-28 01:54:07
An overview of how mode-agile threats challenge static library radar/EW systems, and how AI/ML cognitive architectures enable adaptive, real-time countermeasures.
What Attendees will Learn
2026-07-25 21:00:01
Already, I’ve almost forgotten rain;
I know I will never know that again.
I move forward with the powers you gave me
to live up to my name, Curiosity.
This is a land without leaves, fronds, or spines.
If there are plants, they are small and supine,
dust hidden, like light here, filtered and sand
softened, at home in the thin air, thousands
of motes so small they seem to be fluid,
more fog than firmament. Shadows, few and
far from here, I know I must go to them
to see if they hold order or mayhem
or just another common rock or two.
If a machine can miss the Earth, I do.
2026-07-25 02:00:01
Unlike many budding engineers, K.J. Ray Liu wasn’t inspired to enter the field by tinkering with electronics or following in the footsteps of a family member. Growing up in Taichung, Taiwan, he answered his government’s call for students to become electrical engineers to help manufacture semiconductors in the 1970s, when the country’s economy was struggling.
“Students who were good in math, science, and physics all wanted to be an electrical engineer because that was the top priority of the government,” Liu says. “That’s how I got into engineering. Now Taiwan is a world leader in semiconductors.”
Occupation
Retired professor of information technology and a digital signal processing researcher at the University of Maryland in College Park
Member grade
Fellow
Alma maters
National Taiwan University; University of Michigan; UCLA
But by the time he graduated from university in 1983, semiconductor facilities were still under construction, so there were no jobs available.
Instead, he went on to have a successful career as an educator and entrepreneur in the United States.
For 31 years, he was a professor of information technology and a digital signal processing researcher at the University of Maryland in College Park until he retired in 2021.
Liu was the chairman, CEO, and CTO of Origin Wireless, a startup he founded in Rockville, Md. Origin, which was acquired by ADT in February, pioneers artificial intelligence for wireless sensing and indoor tracking.
Liu, an IEEE Fellow, is an active IEEE volunteer who served as the organization’s president in 2022.
IEEE honored him with this year’s Haraden Pratt Award for “transformative and impactful leadership.”
Liu is credited with increasing the diversity of nominees for IEEE’s Fellow program, which is the highest level of membership. He also led the effort to realign the organization’s regions geographically to ensure more equitable global representation on the IEEE Board of Directors.
He received the Pratt honor on 24 April during a ceremony in New York City. The IEEE Foundation sponsored the Board-level award.
“More than anything, I share the honor with the volunteers and staff I had the privilege to work alongside,” he says. “Our hard work is fueled by our shared devotion to this professional home we love and care for so much.”
In the 1970s, Taiwan’s policymakers decided to improve the country’s economy by pivoting from making products such as shoes and umbrellas to manufacturing electronics.
The industry got its start in 1976 when RCA, a major electronics company at the time, agreed to transfer licensed semiconductor processes to Taiwan’s Industrial Technology Research Institute. ITRI spun off several semiconductor-related companies including the Taiwan Semiconductor Manufacturing Co. TSMC, launched in 1987, is the world’s largest dedicated semiconductor foundry.
Liu graduated in 1983 with a bachelor’s degree in electrical engineering from National Taiwan University, in Taipei. At the time, there were no semiconductor companies to work for, he says.
“Nowadays, many of the country’s university graduates go right to TSMC to get a job,” he says. “But back then, there was no real job market.
“Most of my classmates—including me—came to the U.S. for graduate studies. Many of us stayed and, over the last three to four decades, contributed to the development of electronic computer communication technology in the U.S.”
Liu left Taiwan after a two-year mandatory stint in the Republic of China Armed Forces to attend the University of Michigan, in Ann Arbor, where in 1987 he earned a master’s degree in electrical engineering.
“If I can help make IEEE a better professional home for future members, that is something that I can pay back to IEEE.”
He went on to earn a Ph.D. in electrical, electronics, and communications engineering in 1990 from the University of California, Los Angeles. His interest in digital signal processing and very-large-scale integration (VLSI) was sparked while at UCLA. Today VLSI powers all modern electronics.
“When I was a graduate student, there was no wireless communication. Everybody had a landline,” he explains.
VLSI was an important, active research field at the time.
“My research interest was digital signal processing,” he says. “One day I saw a book on VLSI signal processing on my professor’s bookshelf. I immediately thought to myself: That is the field I want to pursue.
“VLSI is one lane, digital signal processing is the other, and there is a bridge linking the two. I was interested in both areas, so I did my Ph.D. thesis on VLSI signal processing.”
After graduating, Liu joined the University of Maryland, where he is credited with establishing its signal processing research program.
In addition to teaching, he conducted research on a broad range of signal processing and communication aspects. The topics include bioinformatics, game theory, signal processing algorithms and architectures, and wireless sensing and communications.
He has authored more than 10 books and 900 papers, and he holds 250 patents. You can find his research papers in the IEEE Xplore Digital Library.
Liu is considered to be a pioneer in the field of ambient sensing. The technology gathers environmental data and is used in security systems and health-monitoring devices.
He came up with the idea, he says, while working on a project in 2009 for the U.S. Navy. He was trying to solve a problem the Navy was having with the wireless communication systems used in its submarines. Because submarines are made of metal, radio waves were unable to penetrate the vessels’ compartments and instead bounced around, creating interference, he says.
His solution was to use a relatively unknown concept in physics: time-reversal signal processing. The technique captures waves, such as sound and electromagnetic signals, and sends them back through the same medium in reverse, flipping the signal from last-in to first-out, and re-emits them.
“By using time-reversal feed, we could increase the signal-to-noise ratio by four times,” he says. “That improved performance dramatically.”
He became fascinated by the physics of time-reversal signal processing, he says, and wondered how he could apply the concept to serve society. After three years of research, he came up with the idea of using wireless sensing applications through ambient radio waves from surrounding Wi-Fi networks.
“I learned to turn Wi-Fi networks into sensing networks that decipher our activities,” he says. “We could know everything happening around us—our motions, breathing, heartbeat, even fall detection—without any wearables.”
Through the university’s incubator, which encourages faculty to work on projects with an impact on society, he launched Origin in 2013. The company’s Wi-FI and AI sensing technology enables accurate indoor tracking, motion detection, and health monitoring without the need for wearable devices or cameras. Its products, including its remote patient monitoring, received three innovation awards at the 2020 and 2021 Consumer Electronics shows, including one for best innovation.
Liu joined IEEE in 1986 as a graduate student to access its research papers, he says.
“If you didn’t join an IEEE society, you didn’t get its journal—which meant that you couldn’t read the most up-to-date research papers,” he says. “So, I joined the IEEE Signal Processing Society. When I attended my first signal processing conference, I knew I had found a professional home. I met many like-minded people, and together, we built a professional home for our members worldwide.”
He became an active volunteer, holding top leadership positions including 2012–2013 president of the Signal Processing Society and 2016–2017 director of IEEE Division IX, which covers societies focused on signal processing, data transmission, navigation, and transportation. In 2019 he was vice president of the Technical Activities Board.
In 2022 he served as IEEE president and CEO. The three accomplishments during his term he says he is most proud of are increasing the prize money for the IEEE Medal of Honor, overseeing the realignment of IEEE regions, and establishing greater financial transparency.
The reason for increasing the prize for IEEE’s highest award—from US $50,000 to $2 million—in 2025, he says, was to underscore the importance of the technologies the IEEE community develops. Those innovations include semiconductors, the Internet, and the GPU. The money for the Medal of Honor now exceeds that of the Nobel Prize, which carries an award of roughly $1 million.
“We need the whole world to understand the IEEE community has made the most impact on society in the last century,” Liu says. “Nevertheless, we did not receive the attention and respect we deserved, so we needed to help ourselves. We want the whole world to know what our contributions are.”
His next achievement was realigning IEEE’s regions. During the past several years, membership in Region 10, which covers countries in Asia and the Pacific, has grown from 10 percent of total membership to nearly 40 percent, he says. It is the largest and most populous of IEEE’s geographic areas, but its members were not equitably represented on the Board of Directors. Each region had one representative on the Board.
“The region has 40 percent of the members but only makes up 10 percent of the Board,” Liu says. “That didn’t make sense to a lot of us.”
The IEEE Board in 2022 approved region realignment. The total number of regions remains at 10, but their organization is changing. Effective 1 January 2028, the six U.S.-based regions will be consolidated into five, and Region 10 will be split into two. IEEE will no longer use the Region 1 designation. The new Region 2 will represent the Northeastern and Eastern U.S. Region 10 will cover North Asia, and the new Region 11 will represent South Asia and the Pacific.
Liu also succeeded in leading a movement that persuaded the IEEE Board to invest in a better financial reporting system to have a clearer understanding of the organization’s finances. A more modern system now tracks banking transactions, contracts, expense reports, and other spending.
“Now we know exactly where the money comes from and where it is spent,” he says, “so that we can make more informed decisions.
“If I can help make IEEE a better professional home for future members, that is something that I can pay back to IEEE,” he adds. “I truly appreciate what IEEE offered me. From student to professor to an established leader, at every stage, it offered me different opportunities to grow. That is why I worked very hard when I was president to make sure everybody realizes it is a professional home for our entire career.”
2026-07-23 02:00:01
One summer day in 1941, a British radio operator was monitoring German military frequencies and heard something unexpected in her headphones. A later report called it “strange new music.” Sounding unlike the familiar Morse dit-dit-dah of enciphered messages sent over the German Enigma network, the “new music” was a rhythmic warble of binary teletype code being transmitted at high speed.
Germany’s wartime engineers had developed a radically new encryption and transmission system. It was way more advanced than Enigma, which was patented in 1920.
To break the complex new cipher, engineer Tommy Flowers built Colossus, the world’s first large-scale programmable electronic digital computer. Flowers previously built Enigma-related codebreaking equipment for Alan Turing, the British mathematician.
Colossus was installed in the British codebreaking headquarters at Bletchley Park, about 80 kilometers from London. The room-size machine weighed around a tonne.
The computer is being commemorated as an IEEE Milestone. The dedication ceremony is scheduled to be held 29 September at Bletchley Park.
Britain’s top codebreakers were quickly all over the new “music” being picked up by the intercept stations. Identifying it as encrypted teletype code was the easy part. The real problem was figuring out how the encryption machine worked. Its manufacturer was discovered at the end of the war: Berlin engineering firm C. Lorenz.
But in 1941, the Lorenz machine was just a black box to the British. They codenamed it “Tunny,” a British term for tuna fish. The Enigma breakers had set a precedent for using piscine codenames such as Dolphin, Lumpsucker, and Porpoise.
Enigma had three or four encrypting wheels. The codebreakers guessed that the Tunny machine also used a system of rotating wheels to encrypt messages. An important clue was that all the intercepted messages shared a curious feature: Each began with an uncoded list of 12 common German names, including Anton, Bertha, Conrad, and Dora. The codebreakers guessed that Tunny had 12 wheels and that the 12 names and their order somehow told the receiving operator which combination they should twist the wheels to before decrypting the message.
Then the British had an extraordinary piece of good fortune. John Tiltman, head of the research section at Bletchley Park, started analyzing a pair of intercepted messages, each around 1,200 characters long. Unusually, both began with the same sequence of names. The second message turned out to be a retype of the first, with minor differences in punctuation, a few abbreviations, and other small divergences. Tiltman managed to decrypt the two ciphertexts using a mixture of educated guesswork and intuition. The resulting 1,200 or so pairings of ciphertext and plaintext characters proved to be enough information to deduce the workings of the Tunny machine.
That was thanks to Bill Tutte, a quiet young codebreaker who spent weeks poring over the pairings. One day, he shyly announced to his superiors how Tunny worked. His description was uncannily accurate.
The next step in the Tunny machine’s downfall was achieved by Turing, fresh from his successes against Enigma.
Knowledge of how the Tunny machine worked was not enough to decrypt the messages. Codebreakers also required detailed information about how the wheels of the sender’s machine had been set up. There were adjustable pins around the circumference of each wheel: In one of its two possible positions, a pin would contribute a 1 to the encryption process, and in the other, a 0. The pins were reset from time to time.
The codebreakers also needed to know the wheels’ positions at the start of the message—which the German operators gave away in the list of 12 names.
Turing invented a tricky method, called “Turingery,” that enabled codebreakers to deduce the positions of the pins from nothing but intercepted ciphertext.
After that, the message could be decrypted, using the list of names and a British replica of the Tunny machine.
The basis of Turingery was a procedure that Turing introduced, called “delta-ing” (from the Greek letter delta). Also known as “differencing,” the process used “sideways” addition: To delta the four letters ABCD, you add (at the bit level) A to B, B to C, and C to D. Turing used delta-ing to reveal information about the wheels.
Tunny messages, often signed by Adolph Hitler himself, turned out to be pure gold for the Allies. The machine was used in Berlin by the Armed Forces High Command to communicate with front-line generals directing the war in the Eastern and Western theaters.
Once the system was broken, the Allies could eavesdrop on lengthy back-and-forth communications between the architects of Germany’s battle plans.
Turingery was the codebreakers’ only weapon against Tunny for a year, during which they managed to decrypt 1.5 million letters of ciphertext.
But everything changed when those helpful lists of names at the start of each message disappeared.
At the same time, Turingery was becoming less effective. Turing’s method depended on the German sender mistakenly using the same wheel settings to encrypt two differing messages. As security tightened across the Tunny network, the blunder became rarer.
Fortunately, Tutte had been at work devising a different decryption method, based on Turing’s delta-ing but taking a novel approach.
Tutte had found a way of deducing wheel information from ciphertext, with no list of names or blunders by the German operators required. His method made use of statistical properties of the Tunny machine itself.
At first, it wasn’t clear how to apply his statistical method, however. The Tunny breakers worked by hand. Applying Turingery to a message was like solving a monster Sudoku or crossword puzzle.
Tutte’s statistical method required scads of routine binary math, as well as a colossal amount of counting long binary sequences. If the process were done by hand, one message could take months to decrypt. What was needed was a machine to automate the process.
Engineer Thomas H. Flowers developed Colossus to break a complex new German cipher.Pictorial Press/Alamy
The first plan was to build a machine from electromagnetic relays, adding a couple of dozen vacuum tubes to speed up the counting. Electronic tubes were much faster than electromagnetic relays, which had slow-moving metal components. Problems with the circuit design bedeviled the machine’s relay-based logic unit, however.
Flowers was recommended by Turing and brought in to troubleshoot. He was on loan to Bletchley Park from the Post Office Research Station in London, where he had spent the prewar years designing experimental switching equipment involving thousands of vacuum tubes.
At the time, it was commonly believed that tubes could not be used in large numbers because each one contained a hot filament. This meant tubes were prone to sudden death. In a large installation, it would not be long before one tube blew and things stopped working properly.
Flowers discovered that switching tubes on and off stressed them, but leaving them on continuously made them more reliable than relays. He offered to build Bletchley Park a high-speed, all-electronic machine containing around 2,000 tubes.
Bletchley Park’s advisors rejected the idea, convinced that such a machine would never work reliably. But Flowers, confident of his proposed design, retreated to his London laboratory and quietly built the electronic machine that he believed the codebreakers needed. He and his small team of engineers worked day and night for 10 months to create Colossus.
In January 1944 some of his engineers showed up at Bletchley Park with the world’s first large-scale programmable electronic digital computer packed onto the back of a truck. Colossus was reassembled and functional in about two weeks, and it notched up its first German message on 5 February 1944.
The machine read the input—Tunny ciphertext—photoelectrically from a large loop of punched paper tape. The output—information about the wheels—went to a primitive printer that Flowers’ engineers had created from a manual typewriter, fitting relays to automate the keys. Once Colossus had cracked enough of the Tunny machine’s wheels, the information was passed on to the hand-breakers, who took over.
The codebreakers were astonished by Colossus.
“I don’t think they understood very clearly what I was proposing until they actually had the machine,” Flowers said in a 1977 interview. “They just couldn’t believe it!”
Colossus was described in almost loving terms in a since-declassified report written at Bletchley Park in 1945:
It is regretted that it is not possible to give an adequate idea of the fascination of a Colossus at work: its sheer bulk and apparent complexity; the fantastic speed of thin paper tape round the glittering pulleys; the childish pleasure of not-not, span, print main heading and other gadgets; the wizardry of purely mechanical decoding letter by letter (one novice thought she was being hoaxed); the uncanny action of the typewriter in printing the correct scores without and beyond human aid; the stepping of display; periods of eager expectation culminating in the sudden appearance of the longed-for score; and the strange rhythms characterizing every type of run: the stately break-in, the erratic short run, the regularity of wheel-breaking, the stolid rectangle interrupted by the wild leaps of the carriage-return, the frantic chatter of a motor run, even the ludicrous frenzy of hosts of bogus scores.
Bletchley Park’s managers, no longer leery of Flowers’s ideas, soon wanted additional Colossi. He finished building the second one in June 1944, days before D-Day and the Allied invasion of Europe. With 2,400 vacuum tubes—around 800 more than in Colossus I—Colossus II processed Tunny messages at an eye-watering speed of 25,000 characters per second.
Its maximized timing-pulse rate was not far short of the performance of the first Intel microprocessor chip from the 1970s, more than 30 years later.
Flowers conceded that “Colossus bore about as much resemblance to a modern computer as Stephenson’s [1829] Rocket locomotive did to the Royal Scot,” a state-of-the-art 20th-century train operating between London and Glasgow. But he emphasized that, nevertheless, Colossus “embodied all the basic features of a modern computer.” In Colossus, Flowers had pioneered clock pulses, bit-stream generators, control circuits, loops, counters, shift registers, interrupts, parallel processing, and more.
As the Allies slowly fought their way toward Germany, the Colossi poured out wheel information, and the codebreakers provided the military with an unparalleled view of German strategies, strengths, weaknesses, and tactical intentions.
Even with that mass of detailed intelligence, it took the Allies almost a year to move from Northern France to the German heartland. No one can say for sure how much longer the fighting would have lasted if the intelligence breakthrough had not occurred. But if Colossus and the codebreakers shortened the war even by only six months, the number of lives saved was in the millions.
There were 10 Colossi at Bletchley Park by the end of the war, housed in two vast, steel-frame, bombproof buildings, running day and night. Although concealed behind a thick veil of secrecy, Bletchley Park accommodated the world’s first electronic computing facility. It was directed by Max Newman, the mathematician who mentored Turing in prewar Cambridge.
I don’t think they understood very clearly what I was proposing until they actually had the machine. They just couldn’t believe it!”—Tommy Flowers
When the fighting ended, authorities decided that ultrasecrecy must be maintained, and orders were issued to break up the Colossi. Only two were spared.
“All that was left were the deep holes in the floor where the machines had stood,” Colossus operator Dorothy Du Boisson recalled in an interview for the book Colossus: The Secrets of Bletchley Park’s Codebreaking Computers. Norman Thurlow, one of Flowers’s engineers who was also interviewed, remembered being told in a staff memo that if the secrecy was ever lifted, he and his colleagues might be able to tell their grandchildren about Colossus and “the tapes that span on silver wheels.”
The Milestone plaque recognizing Colossus is to be displayed outside Block H at Bletchley Park, near Milton Keynes, England.
The plaque is to read:
Six Colossus codebreaking computers operated in this building in 1944–1945. Designed by Thomas H. Flowers of the British Post Office, they enabled deciphering of encrypted radio messages transmitted between German commands across occupied Europe, North Africa, and the Soviet Union. The resulting military intelligence saved countless lives and helped shorten World War II. As the first successful large-scale application of digital electronics to computing, Colossus anticipated subsequent computer developments.
The IEEE United Kingdom and Ireland Section sponsored the nomination.
Reviewed by the IEEE History Committee and awarded by the IEEE Board of Directors, IEEE Milestones recognize outstanding technical developments around the world that are at least 25 years old. The Milestone program is administered by the IEEE history and heritage group.
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