For most of history, people living with amyotrophic lateral sclerosis (ALS) and related neurological disorders have faced a grim outlook for their ability to communicate. ALS, which attacks the nerve cells responsible for carrying signals from the brain to the muscles necessary for speech, can make speech slurred, difficult to understand, and eventually impossible for some patients. Over the past several decades, modern assistive communication technology has made major strides toward enabling people with ALS to communicate, but the technology has fallen short of reproducing the ease and spontaneity of natural communication. An experimental AI-powered tool is changing that.

A new AI-powered brain-computer interface (BCI) system developed at UC Davis in collaboration with researchers at Brown University and Mass General Brigham Neuroscience Institute appears to represent a major breakthrough in addressing two of the “key challenges” to the real-world adoption of this emerging BCI technology: independent at-home use and reliable long-term performance. A BCI is a system that measures brain activity and translates it into commands for an external device without relying on muscle movements normally required to operate a computer.

What does this breakthrough mean for the everyday lives of ALS patients experiencing severe paralysis? A significant leap toward independence and more natural communication.

The latest BCI breakthrough enabled study participant Casey Harrell to communicate substantially more independently than before, with the study documenting more than 3,800 hours of at-home use. And while a caregiver helped set up the system, at-home use was not dependent on the researcher supervision his earlier BCI use required. This allows for sustained and far more natural communication with friends, family, and colleagues. The BCI also enabled him to control a computer cursor, allowing him to navigate the internet, send messages, and perform work-related tasks. Together, these capabilities allow Harrell to participate considerably more independently in family life and work.

Using a 125,000-word vocabulary, the BCI demonstrated 99.2 percent word accuracy in a controlled word-copying task, according to a new June 2026 study. And the pace of this innovation is difficult to overstate. Two earlier studies, one published in August 2024 with the same participant and the other in August 2023 involving a different participant, reported 97.5 percent word accuracy and a 23.8 percent word error rate, respectively, under different testing conditions.

In the June 2026 study, Harrell communicated at an average of 56 words per minute (WPM) using a BCI, compared with roughly 6.3 WPM using head-controlled typing, as documented in an earlier study. For context, conversational English is roughly 160 WPM. And while this remains substantially slower than conversational English, it represents a meaningful jump over less than three years.

From a technical standpoint, this BCI works by using implanted electrodes—tiny sensors that record electrical activity in the brain—to send those recordings to AI decoding software capable of translating those signals into text. From there, those words can be displayed or played aloud. This is a break from traditional assistive systems that rely on things like movements of the eyes, head, and other parts of the body to select words and letters.

Recent AI-powered advancements in BCI technology do not stop at helping users communicate with greater speed, accuracy, and independence. Another experimental approach is pushing the boundaries of restoring natural-feeling communication, translating brain activity not only into words, but tone, emphasis, and even song. And it’s doing so in real time.

Harrell also participated in a study involving a brain-to-voice BCI, published in June 2025. While both BCIs use brain signals, this system goes beyond translating attempted speech into text, seeking to restore the expressiveness of natural speech. The study’s results suggest the future of communication for ALS patients could look remarkably different.

To make this possible, the researchers developed what the report calls a “real-time neural decoding pipeline” capable of synthesizing voice from incoming neural signals in under 10 milliseconds as a person attempts to speak. In other words, instead of waiting for an entire word or sentence to be decoded before generating speech, this model enables near-instantaneous speech synthesis more closely resembling the natural flow of speech.

In this study, researchers developed an AI-generated voice resembling Harrell’s using recordings of him speaking before ALS had severely impaired his speech. The BCI’s neural decoder—AI software that translates brain activity into information used to synthesize speech—allowed the system to produce speech from his attempted vocalizations.

The BCI also demonstrated success in reproducing his intended intonation. When he intended to ask a question, for example, the BCI reproduced the rising pitch associated with asking that question.

And this BCI demonstrated the ability to reproduce intended emphasis on words, too. Think about the difference in meaning between “I didn’t say she stole the money” and “I didn’t say she stole the money.” Emphasis may appear to be a small thing on the surface but can go a long way toward making day-to-day communication feel normal again.

And this study’s BCI takes speech restoration yet another step further, reproducing musical pitch. Harrell attempted to sing short melodies consisting of six or seven notes and successfully alternated between pitches classified as low, medium, and high.

The latter BCI study illustrates what is already being made possible by AI-powered research: real-time speech synthesis, intonation, emphasis, and even melody. In controlled trials, the system reproduced intended question intonation with 90.5 percent accuracy and intended word emphasis with 95.7 percent accuracy. Researchers also tested how well human listeners could distinguish musical pitches and understand the speech synthesized by the BCI.

When asked to identify which note was higher in 189 pairs of synthesized notes, listeners chose correctly 73.02 percent of the time, on average. When asked to identify the correct transcript of synthesized speech from six written sentence options, listeners chose correctly 94.34 percent of the time. Still, these results carry limitations.

Listeners were also asked to transcribe both the synthesized and unaided speech. Transcription, however, is a more demanding measure of intelligibility than choosing from six sentences. The median word error rate for the synthesized speech was 43.75 percent. And while this is a substantially lower error rate than when listeners were asked to transcribe Harrell’s unaided speech (96.43 percent), it remains a ways off from restoring natural conversation. These limitations underscore that while AI is already transforming communication for people living with ALS, accelerating research and innovation could bring us closer to restoring the flow of natural conversation and making these life-changing technologies widely available.

“I do not want to be special any longer,” Harrell wrote in a first-person account published by Springer Nature. “I think this is good enough technology that people who have ALS should have access to it right now. Sadly, that is not the case yet.” Sergey Stavisky, a neuroscientist at UC Davis who helped lead the BCI research, is optimistic about the future. He told Time, “I think motor-speech BCIs will be widely available.”

For patients living with ALS, advancements in AI and related emerging technologies are not merely about economic growth or productivity gains. They are about the promise of being able to communicate ordinarily again. And recent advancements in BCI technology illustrate both what AI is already making possible and what it can make possible if we keep going.

Harrell hopes to no longer be an exceptional case study, but one of many regaining the ability to communicate naturally, including those who may have believed they never would. Throughout history, extraordinary technological achievements have transformed what once seemed impossible into the commonplace. With enough research and innovation, Harrell’s dream may soon be in reach.

Ed Tarnowski is the Founder and Editor of The Compute Optimist. He is also a Resident Fellow, Technology and Innovation at the R Street Institute, a Senior Contributor at Young Voices, and the Washington, DC Regional Director for America’s Future. All opinions expressed are his own.

Of all the critical coverage I’ve seen of Data After Dark so far—a party I was proud to co-host and The Compute Optimist proud to co-present—perhaps my favorite genre is the assertion that a themed party in Washington, DC did not, in a single evening, reverse American public opinion on data centers.

As Krystal Ball of Breaking Points put it, she “can’t imagine a single rural American” who would be persuaded because “some people in DC had a cocktail party.” Her co-host, Saagar Enjeti, added, “Generally, just some advice, that’s not really how you move the needle.”

I appreciate the advice, Saagar, and I’m glad we can at least agree that, as you mentioned on the show, in-person socialization is good. But the value of the party was never that people would hear about a pro-data center party in the nation’s capital and suddenly see the light on the importance of the data center buildout. Nor have we ever argued that data centers belong anywhere and everywhere.

The value of Data After Dark lies in something much deeper.

What started as two friends and me planning a themed house party quickly grew into something far bigger. Within about an hour, my co-hosts Jonas Du, Casey Given, and I posted Data After Dark on Partiful. By morning, about 100 of our friends had RSVP’d.

In the weeks and months leading up to that night, anti-data center fervor had reached a breaking point. Strikingly, a Gallup poll had found seven in ten Americans opposing the construction of “data centers for artificial intelligence in their local area.” Politicians, sensing the changing winds, were quick to respond.

The data center debate was something the three of us had all discussed with our friends countless times, and with great frustration. In my experience, much of the opposition is being driven by false or exaggerated claims, but not all of it. Many are also asking valid community questions, and tech companies will have to make their case in those towns. The issue? Whether rooted in legitimate concerns or misconceptions, many of these objections can be addressed through better information or technological solutions. Yet data center opposition was increasingly fueling support for radical and reactionary proposals like all-out moratoriums.

The first statewide data center moratorium was signed this summer, support for Vermont Sen. Bernie Sanders’ national moratorium expanded beyond its niche progressive origins to include a powerful committee ranking member, and midterm campaign ads were increasingly using past support for data center projects as a political weapon.

On August 20, I posted my frustration on X: “If not, in 30 years, we’ll be watching documentaries about how the Jane Fondas of today destroyed our standing as the world’s compute superpower. People will so obviously realize how wrong they were today.” This was a callback to watching documentaries with my dad as a kid detailing the history of nuclear energy in America. Collectively, those documentaries led me to discover that something I’d opposed out of fear and pessimism wasn’t what I thought it was.

Fear and pessimism are the right words. Fear of the unknown and pessimism about what emerging technologies could mean for the future. It’s a tale as old as time, with America’s data center and broader AI buildout as the latest iteration.

The exhaustion with the prevailing climate of fear and pessimism is, in my view, the spark that made Data After Dark go viral. When Jonas and I posted the party on X, we were having fun with it. And we both knew those exhausted by the constant and growing negativity surrounding what they understand to be critical infrastructure would get a kick out of the themed party. We just didn’t realize quite how much of a kick.

With the screenshot of the Partiful invite, Jonas posted “Who wants to come to my pro-data center party in DC” to which I immediately reposted with “Yes, we’re hosting a pro-data center party in DC next month… Yes, we will be serving Loudoun County Ice Teas.” It didn’t take long for both posts to catch fire, with Jonas’s post drawing more than 322,000 views and mine more than 52,000.

“Based on the replies this is becoming the event of the season,” said Taylor Lorenz. “lfg. I’m there,” posted @/ira_quint. “Flying back to DC for this,” stated Nahom Sisay.

It quickly became clear that Jonas’s 900-square-foot DC row house, where we initially planned to co-host the party, was not going to fit everyone who wanted to come.

Among the responses were tech startup builders and nonprofits graciously jumping in to offer their support. We had clearly tapped into something, and they wanted to make sure capacity wouldn’t keep it confined to a row house.

That something was a yearning for optimism. AI is poised to deliver immense value for humanity, and those who recognize it are increasingly fatigued not only by the continuing proliferation of fear-based doomerism, but by how open excitement about technological progress is often met with scolding and unfounded accusations ranging from disregarding the environment to “shilling for big tech.” In a way, for many, that optimism was becoming a form of rebellion.

“It really is our generation’s Industrial Revolution, but bigger,” I told VICE in an interview about the party last week. “The risk of slowing down is far greater than pushing forward.” And this is the greater point. In throwing this party, our message was simple: You’re allowed to be excited and optimistic about the remarkable and innovative things happening in American tech right now. What Data After Dark revealed was that the doomers do not have a monopoly on the energy and sentiment toward tech. There is a robust constituency for techno-optimism, and that constituency is hungry to express it.

The tech and politico worlds came together in a novel way that Saturday night: not over stuffy Hill meetings, rubber-chicken dinners, or a name-tagged networking event, but in the whisky lounge, over live jazz, and while dancing under a flag with the words “Come And Take It” beneath the image of a data center server.

While the typical DC crowd was certainly represented, Data After Dark was far from limited to it. I should know—I organize monthly happy hours and policy panels in the city. It enabled communicators, policy wonks, and startup builders to converge outside the usual professional circles. Not merely to “network,” but to get to know one another, celebrate optimism for the future, and yes, have fun.

No one in that room needed convincing that data centers have a PR problem. What they needed was to know one another. Professionals approaching the issue from different parts of the tech and policy worlds, who might otherwise never have met, are now acquainted. And from my conversations with friends, old and new, those relationships are already continuing and evolving beyond the party.

Finally, while much of the media coverage carried a negative flavor, the party provided a platform for getting out our message about optimism and innovation. If the SMRtini, named after small modular reactors (SMRs) to highlight one answer to data center grid concerns, or the Closed-Loop Spritz, named after closed-loop cooling systems to highlight how innovation is enabling data centers to recycle and reuse water, prompted even one conversation about these solutions, I’d call that a win. And when it came to optimism, one moment captured the contrast perfectly.

The protesters who stormed the stage put the divide between optimism and pessimism on full display. When the crowd broke into chants of “USA!” in response, I quickly joined my friend Jonas on the stage to help carry the chant. Photos and videos captured the two of us holding the microphone, smiling, laughing, and chanting alongside the crowd. Next to us, a protester shouted back at the attendees, at one point giving them the finger.

And that’s the contrast. The techno-optimists are having fun. And optimism is how we win.

Ed Tarnowski is the Founder and Editor of The Compute Optimist. He is also a Resident Fellow, Technology and Innovation at the R Street Institute, a Senior Contributor at Young Voices, and the Washington, DC Regional Director for America’s Future. All opinions expressed are his own.

Location, location, location. And I’m not talking real estate.

When it comes to serious disease, location is an often underappreciated factor in mapping out treatment. This became a sobering fact of life when my mom, while in her mid-50s, was diagnosed with stage IV ovarian cancer in the latter half of 2024.

At stage IV, there is little time to waste. Thankfully, after the initial diagnosis, my mom was able to get into surgery in just two weeks through the Dana-Farber Cancer Institute in Boston, Massachusetts, one of the best cancer hospitals in the world. I asked her what it meant to be able to get into surgery so quickly. She said: “It helped relieve the fear to tackle it right away instead of waiting while it continued to spread. It took the fear out of me.”

Following the surgery, which went remarkably well, she completed chemotherapy and is now in remission. Still, this wasn’t quite the end of the road.

Her type of cancer carries a high risk of recurrence, and she remains on Lynparza, a PARP inhibitor designed to reduce or delay the risk of disease progression or recurrence. Because Lynparza can come with taxing side effects and regular recurrence testing remains necessary, so does ongoing monitoring. On a regular basis, she and my dad wake up around 3:30 a.m., drive to Boston before work for testing, and return to Rhode Island to head to work for the day. Up in Boston, she gets same-day results and, in turn, more peace of mind.

This isn’t their first rodeo. My mom first had a different cancer earlier in life. Dana-Farber doctors saved her life then, as my mom puts it. She feels comfortable there and trusts their facilities. Had they been further from a state-of-the-art cancer hospital, the speed, quality, and routine of treatments may have looked very different.

Not everyone lives in such close proximity to world-class medical facilities like Dana-Farber. An experimental, AI-powered breakthrough in surgical procedures may be laying the groundwork for making geography matter less.

2022 marked the first time autonomous robotic surgery was performed on a live animal. It was carried out by the Smart Tissue Autonomous Robot (STAR), a device developed by roboticist Axel Krieger. The laparoscopic surgery, involving reconnecting two ends of the small intestine, was no small feat. It is described by the 2022 report as being particularly challenging because soft tissue moves and deforms, unlike rigid anatomy including bones.

Impressively, STAR autonomously completed the surgery on four live pigs, and, according to Krieger, “produced significantly better results than humans performing the same procedure.” Still, STAR came with its limitations. It required marked tissue, worked in a highly controlled environment, and was guided by a predetermined plan. Just three years later, in July 2025, Krieger’s work in surgical robotics demonstrated a break from many of these limitations with the AI-powered hierarchical surgical robot transformer (SRT-H).

SRT-H, trained on videos of surgeries, is described by a Johns Hopkins report as an evolution from robots being able to merely execute surgical tasks to being capable of adapting, making quick decisions, and self-correcting in real time. Krieger compared STAR to teaching a robot to drive along a carefully mapped route. He compared SRT-H to “teaching a robot to navigate any road, in any condition, responding intelligently to whatever it encounters.” Characterized as incorporating the same “learning architecture” as large language models (LLMs), SRT-H can additionally understand and respond to spoken commands.

To prepare SRT-H for surgery, researchers trained the robot on 17 hours of recorded surgical demonstrations performed on 34 gallbladders. For testing, SRT-H was then given eight ex-vivo pig gallbladders (gallbladders removed from dead pigs) that the robot had not been previously trained on. Without human intervention, it achieved a 100 percent success rate across the eight cases, completing all 17 surgical tasks. This included identifying and grasping ducts and arteries, placing clips, and making necessary cuts, all part of a key phase of cholecystectomy, or gallbladder removal surgery. Notably, cholecystectomy is a surgery the study points out as “a common laparoscopic procedure performed over 700,000 times annually in the United States.”

Researchers even deliberately introduced SRT-H to conditions requiring adaptability. “The robot performed flawlessly across anatomical conditions that weren’t uniform, and during unexpected detours—such as when the researchers changed the robot’s starting position and when they added blood-like dyes that changed the appearance of the gallbladder and surrounding tissues.” And while it did not conduct the surgical tasks as fast as a human surgeon, the Johns Hopkins report states that the results were “comparable to an expert surgeon.” Jeff Jopling, a co-author on the study, compared this to surgical residents mastering their craft at different paces.

The implications of these advances in AI-powered robotics are not going unnoticed. In an announcement just this week, the Defense Advanced Research Projects Agency (DARPA), an independent research and development agency within the U.S. Department of Defense, is betting millions in hopes of accelerating the technology.

The DARPA announcement notes traumatic injuries, particularly in combat operations, as a critical threat, making the point that otherwise survivable injuries can end fatally simply because service members may lack access to specialized surgeons. The competition seeks to “spur the development of robotics systems that can act as skilled, reliable partners to human surgeons.” In March 2027, it will award $1.5 million for capabilities in surgical collaboration, $1.5 million for capabilities in surgical independence, and $500,000 to be “distributed to top performers in the individual sub-component capabilities.” And lacking access to specialized surgical care is not a problem confined to the battlefield.

DARPA rightfully recognizes the civilian benefits of propelling this technology too, remarking that the agency “expects the technologies developed under this competition to offer profound dual-use benefits for civilian healthcare—from expanding specialist access in rural communities to bolstering disaster response capabilities.” And there is research to back up the need for better access to specialized care.

A 2025 JAMA study found that in 2020, nearly 60 percent of rural Medicare patients undergoing high-risk surgeries traveled over an hour for care. This could mean long, burdensome drives to reach necessary medical expertise not available closer to home. In natural disasters, it can be even more difficult to reach essential care. After Hurricane Helene hit North Carolina in 2024, washed-out roads cut off both patients and hospital staff from Mission Hospital, then the only Level II trauma center in western North Carolina. The resulting disruption reportedly led to surgical delays.

But what if it were different?

Innovative, AI-powered robotics like those demonstrated by SRT-H could eventually mean a very different future for those lacking ready access to specialized surgical expertise today. While this kind of technology has not yet been tested on humans and it will likely be some time before that happens, it is nevertheless rapidly advancing. In just three years, Krieger’s robotics work evolved from following a predetermined surgical plan in a controlled environment to demonstrating adaptive autonomy in executing a complex, critical phase of surgery across eight cases. If this can be extended across procedures, and eventually be used on people, it could be scaled to fill in critical gaps in places that need it most.

Instead of requiring patients to travel long distances for surgical expertise, a robust, autonomous surgical robotics industry could mean specialized care traveling to patients and their communities. It could mean rural hospitals and emergency trauma centers becoming equipped with certain specialized surgical capabilities when a human specialist is not physically present. Realizing that potential will require continued experimentation, investment, and development.

We are not there yet. My parents are lucky enough to be able to fit the early-morning trips to Boston into their schedules. In a world where this technology progresses from the laboratory to widespread human use, future families may not have to be.

Ed Tarnowski is the Founder and Editor of The Compute Optimist. He is also a Resident Fellow, Technology and Innovation at the R Street Institute, a Senior Contributor at Young Voices, and the Washington, DC Regional Director for America’s Future. All opinions expressed are his own.

Today’s rapidly evolving technologies hold immense potential to advance once-unimaginable breakthroughs in human progress. From medicine to robotics to space, artificial intelligence (AI) and the compute that powers it provide an exceptional opportunity to reshape our lives for the better. These engineering feats are no accident. They are being powered by free markets, private-sector innovation, competition, and the risk-taking all three encourage.

Despite this, tech doomerism is seemingly everywhere right now. This publication is your place to follow and learn more about the possibilities of these emerging technology frontiers.

Just as fear swirled around the once-emerging technologies of flight, textile automation, and electric lighting, growing alarmism is currently capturing the American psyche around AI and its surrounding infrastructure.

In many ways, this anxiety is understandable. Some of the biggest names in AI have loudly floated apocalyptic scenarios resulting from the technologies they are developing—like vast job losses, unchecked cyberattacks, and even the end of the world. These predictions unsurprisingly catch like wildfire in the media. After all, negativity sells. None of this is novel, but that doesn’t make it any more true. Many of these claims have been substantially softened, particularly relating to job losses, with several of the big AI labs publicly walking back past catastrophic predictions. And while motivations behind all of this may vary, so far, much of the evidence also cuts against the alarmism.

When the news Americans consume is saturated with sensationalized, often misguided coverage of new technologies not yet fully understood, telling them these tools will eliminate the jobs enabling them to put food on the table tonight, it is no surprise to see many turning against those technologies. This is nothing to discount and must be meaningfully addressed, not mocked.

The disinformation problem must also be confronted, and nothing demonstrates this more than today’s conversation around data centers. This publication will cover them under a section called Supercomputers (thank you for proposing this rename, Neil Chilson), a name that accurately captures the hardware carrying out quadrillions of operations to train and run the most advanced AI models ever built. Recent polling found 71 percent of Americans oppose local construction of data centers for AI. Importantly, this opposition is largely being fueled not by general opposition to AI or anti-tech sentiment, but by local environmental and quality-of-life concerns, many of which are exaggerated, unfounded, or controllable.

Politicians are taking note of this rising unpopularity. Populist, anti-market policy is on the rise in response, with proposals targeting data centers ranging from tying up companies in uncertain permitting limbo to outright moratoriums gaining steam. Some of these politicians were enthusiastic about encouraging more of this investment in their states less than a year ago.

This suggests that despite many of these politicians understanding the economic benefits these data center projects offer to communities and the general importance of American AI innovation, they are caving to what polling has picked up as a snapshot of passion, frozen in time. Rather than reasoning with voters and combating disinformation with the truth, better ideas, and results, they are contributing to a growing sentiment and advancing policies that risk causing lasting damage to America’s ability to remain technologically dominant and competitive.

While no one should be naive enough to presume none of this disinformation has spread organically, there is growing evidence that America’s adversaries are actively working to drum it up. The X Safety Team recently identified a suspected Chinese bot farm of 200,000 accounts, 200 of which were “posting in a manner that could manipulate a legitimate debate about American AI and energy policy. These posts contained claims that AI data centers are driving up household electricity prices and straining the grid. Others included AI-generated cartoons that depicted data-center operators enriching themselves at the public's expense.”

This is just one reported example of suspected foreign efforts to sow discord among Americans over AI and the infrastructure behind it. It is unlikely to be the last, and should come as no surprise. American AI innovation is not only essential to national security in the most obvious sense—as part of a general defense strategy in a global, ever-evolving technological landscape—but also as a modern economic engine. Advanced AI is poised to offer one of the most significant wealth creation opportunities in history, and if America hamstrings itself on this front, our adversaries will continue marching forward anyway.

The national security risks posed by falling behind in the global AI competition make proposals like data center moratoriums, a legislative ban on supposed “superintelligence,” and the growing chorus of calls for a pause on American advanced AI development all the more dangerous. Even if proponents of these radical policies were to succeed in their efforts to cripple America’s private sector AI industry, our adversaries would not follow our lead. China, for example, fully grasps the weight of this moment and is steaming forward to expand its own AI capabilities. Whoever leads in AI will wield a commanding advantage in everything from economic growth to military power. Do we want to live in a world where China sets the terms? Or will America meet the moment?

The purpose of this publication is not to suggest that AI comes with no risks. It is to assert that the risk of suppressing AI development is far higher than the risk of forging ahead. It also aims to build a well-rounded, evidence-based understanding of the profound good these technologies have the potential to unlock and the consequences of allowing fear to drive us. Yes, the transition will bring real disruption, just as in other times of historic technological progress. That disruption deserves serious attention, including job training to help workers in impacted industries adapt.

Nevertheless, periods of transformative progress—driven by markets and a robust private sector—have left humanity overwhelmingly better off. They’ve turned luxuries, from air travel to automobiles to antibiotics, into normal parts of everyday life. They’ve created not only more jobs in place of those made obsolete, but jobs enabling a far better quality of life. Just as we don’t look back and wish the gaslight companies had successfully defeated the adoption of electric lighting, as they fought hard to do, history is unlikely to look fondly on those who try to strangle the innovation behind the light bulbs and telephones of today. And there is no shortage of equivalent examples.

AI is already supercharging the fight against cancer, democratizing knowledge and expertise, and yes, creating new jobs while transforming others—and not just in Silicon Valley. It is spurring rapid advancements in robotics designed to help people with mobility issues, how we fight wildfires, and commercial autonomous driving proven to result in far fewer crashes.

The question before us is not whether or not this frontier technology will continue evolving, but whether or not those who believe in the Western project will be the ones driving that evolution. For many, the scale of this transformation is frightening, and understandably so. The consequences are immense. But fear will not prepare us for this moment. Leading can. And this moment is only the tip of the iceberg. The AI revolution is here, it’s happening, and it has the power to do tremendous good for humanity—perhaps far more than the Industrial Revolution.

Much like the hysteria of the 1970s that helped smother the nuclear energy buildout, a buildout that might have left us with both a far cleaner and more independent energy grid, today’s alarmism threatens to constrain technological progress on an even greater scale. The speed and scope of today’s innovation boom—driven primarily by the private sector—much more closely resemble a transition into a new technological era than a bubble waiting to burst. AI provides us an extraordinary opportunity to push the boundaries of human prosperity, but only if we allow it to. More institutions are necessary to fill the gap in covering this revolution. I’m founding The Compute Optimist to begin filling that gap.

Ed Tarnowski is the Founder and Editor of The Compute Optimist. He is also a Resident Fellow, Technology and Innovation at the R Street Institute, a Senior Contributor at Young Voices, and the Washington, DC Regional Director for America’s Future. All opinions expressed are his own.