Boulder Future Salon

"The US military is deploying significant airpower in the Caribbean one week after carrying out an airstrike on what it said was a boat operated by a Venezuelan drug cartel." "MQ-9 Reaper drones have been stationed in Puerto Rico, according to open-source imagery. The Pentagon is also planning to send F-35 Lightning II stealth fighters to the island, US officials said. Numerous C-17 Globemaster III cargo aircraft, as well as KC-135 Stratotanker and KC-46 Pegasus aerial refuelers, have also been flying to bases in the region." "The MQ-9s have been spotted at Rafael Hernández International Airport in Puerto Rico. That airfield is home to Coast Guard Air Station Borinquen, but the Coast Guard does not operate MQ-9s. At least one Reaper was photographed on Sept. 4, and armed with what appeared to be Hellfire air-to-surface missiles, by the news agency Reuters.

Volodymyr Zelenskyy, speaking before the UN, says the world needs global rules for use of AI in weapons. He doesn't elaborate on what these rules should be or how they should be enforced, but instead goes on to say it is cheaper to stop Russia now than to allow the AI weapons arms race to continue and have to protect every school, every piece of critical infrastructure, every port, and every ship from AI weapons.

Newsguard claims: "Despite a year of technical advancements in the AI industry, generative AI tools fail at a nearly doubled rate when it comes to one of the most basic tasks: distinguishing facts from falsehoods. The 10 leading AI tools repeated false information on topics in the news more than one third of the time -- 35 percent -- in August 2025, up from 18 percent in August 2024. When it comes to providing reliable information about current affairs, the industry's promises of safer, more reliable systems have not translated into real-world progress." "The increase reflects a structural tradeoff. As chatbots adopted real-time web searches, they moved away from declining to answer questions. Their non-response rates fell from 31 percent in August 2024 to 0 percent in August 2025."

"SWE-Bench Bash Only -- where models must fix real GitHub issues armed with just shell commands -- is one of the sharpest stress tests for agentic coding. Even the strongest models top out around 67% (Claude 4 Opus). That means on 1 in 3 issues -- or worse -- models fail." "To understand why, we ran Gemini 2.5 Pro, Claude Sonnet 4, and GPT-5 across the full SWE-bench suite, then had professional coders dissect every failed trajectory. One particularly revealing pattern emerged: spiraling hallucination loops, where small deviations from reality quickly spiral into disaster as models build further reasoning on shaky foundations." "Gemini encountered missing information early on. Instead of realizing, it filled in the gaps with assumptions and internal knowledge. These early inaccuracies quickly snowballed into hallucinated classes, methods, even fake terminal outputs. After dozens of turns and hundreds of lines of altered code, it gave up without a fix." "Claude made similar missteps early on. But when it crashed into runtime errors, it recognized the gap between its assumptions and reality, investigated more carefully, and eventually landed on the correct fix." "GPT-5 avoided hallucinations altogether. When it encountered missing context, it explicitly went back to re-check rather than guessing, and solved the problem on its first attempt." "Same task, three trajectories. One spiraled, one slipped and recovered, and one navigated cleanly. What separates them is how they handled missing information and whether they could tell the difference between ground truth (Seen), prior knowledge (Remembered), and unverified guesses (Guessed)." "The bug was simple: When writing an astropyTable to HTML, the formats argument in Table.write() is being ignored. Instead of applying custom column formatting like scientific notation, numbers are being dumped with full precision." "This problem isn't so much about how well models can write new code, it's about how well they can investigate and understand the structure of an existing codebase. In fact, the golden fix is just two lines: pass the columns to the data object and call _set_col_formats()." They go out of their way to say the point isn't ranking models, the point is understanding how models approach real-world problems, but I do think it's interesting that the largest model that also uses the most inference-time computing power -- GPT-5 -- did the best. I don't know why they used the less powerful Claude model, Sonnet 4, instead of Opus 4. Gemini 2.5 Pro is considered one of the best coding models, but maybe it is better at generating code from scratch than understand the structure of an existing codebase and modifying an existing codebase. This could all change by next week, the way these companies are always leapfrogging each other to have bragging rights for the world's best model.

If you'd asked me when humans began talking, I've heard that "humans" have existed as a species for somewhere between 200,000 and 300,000 years ago, so I would've guess sometime in that timeframe. But I found this podcast (from 2023 -- sorry for the lack of timeliness, but I just discovered this existed today) where a linguist (John McWhorter) recounts evidence that language goes back much further -- and that there may have been other species that had language -- species closely related to humans, namely neanderthals and homo erectus -- actually homo erectus isn't a separate species but a direct ancestor of us, homo sapiens. He cites evidence going progressively back in time, starting with caves, but it gets more interesting when he starts talking about genetics. Humans and neanderthals share genes related to language, and he highlights one in particular called FOXP2. Neanderthals were masterful hunters, suggesting they hunted in teams, which suggests they used language to plan. They also had rituals for the dead, which species without language (such as hyenas?) tend to not have. He then goes back to homo heidelbergensis (thought to be the last common ancestor between humans, neanderthals, and denisovans, though he does not mention this) who were hunter/gatherers who had carpentry 500,000 years ago. If the ability to make cave paintings 50,000 years ago counts as evidence a species (us) had language, carpentry 500,000 years ago ought to count, too. He then goes back to homo erectus. Homo erectus crossed "big water." Erectus did this a lot. Erectus got to Crete (an island in the eastern Mediterranean -- Greece is the closest modern country), and Secotra (off of Yemen -- actually you have to head off straight off into open ocean to find it -- it's in a different direction from the coast of Yemen to get to the horn of Africa, which is the modern-day country of Somalia). Erectus went from One Indonesian island to another. He cites Flores, an island that, while being part of a string of islands (the Lesser Sunda Island chain), he says the currents are "nasty", and that you have to teach people how to sail, you have to build the vessels, and travel to new places and settle them. "Were these people not talking?" he asks. He thinks they could talk. He pushes the date of the beginning of language back to 2 million years ago. The relevance of this to futurology (besides being interesting and different from what I thought), is that it challenges the notion of exponential change. We're so used to living in a world of exponential change and project this back into the past, and think that since the beginning of language, the exponential change trend that we are immersed in today began. At least that was kind of my thinking until recently. Now it looks like, actually, evolution invented language, and primates used it to survive as hunter/gatherers for millions of years, without exponential change. Exponential change began with the end of the last ice age, because that's when the agricultural revolution began. But even then, not really, until the invention of writing, which in this podcast, John McWhorter places at 5,500 years ago. But even then, not really until the invention of the printing press, which really kicked off the scientific revolution which ultimately led to the industrial revolution. We don't see exponential growth in the human population until the 1300s, and even then, not really until the 1800s when the industrial revolution really kicked in. Today, fertility rates are falling everywhere in the world, as if in anticipation of artificial intelligence taking over the planet. We see exponential growth in the capabilities of semiconductors and the sheer quantity of semiconductors on this planet. (Maybe you all are starting to see why I call semiconductors "solid state life".) The exponential growth has to stop at some point -- the laws of physics only allow semiconductors to get so small, and there are a limited number of atoms on this planet. So we are all living in a unique and anomalous period of exponential change.

An AI dashcam for truck drivers. It "combines more than ten distraction and drowsiness indicators. Among the inattention indicators the system tracks are head nodding or tilting, yawning, change in eye blink rate, long eyelid closures (indicating something called microsleeps), and gaze drifting from the road for extended periods (what happens when people text and drive). If a pedestrian enters the crosswalk and the driver is awake, alert, and not driving too fast, the system will remain silent under the assumption that the driver will slow down or stop so the person on foot can cross the street without incident. But if it notices that the driver is scrolling on their phone, it will sound an alarm -- and perhaps trigger a visual warning too -- in time to avoid causing injury." Apparently one of the keys to the system is not issuing "false positive" warnings or drivers get "alert fatigue" and start ignoring the alerts. Also note that it's not drivers, but supervisors, who pay for the system, and are the primary beneficiaries. Supervisors get notified when a driver is driving badly so supervisors can deal with them.

The TRLC-DK1 is "an open source dev kit for AI-native robotics." It includes all necessary parts, including robotic leader arm and cameras, takes about 2 hours to assemble, costs about $3,000, and connects with USB-C to Linux, MacOS, and Windows. Takes under a day to deploy reinforcement learning policies.

"Spotify peeved after 10,000 users sold data to build AI tools." Basically, about 10,000 Spotify users formed a "collective" to sell their data to make a better "Wrapped" feature, but Spotify's terms and conditions prohibits using any Spotify data for building machine learning or AI models. I wonder if it would actually be smarter for Spotify to just charge a reasonable licensing fee and let people have at it.

ARM says they have a new CPU for mobile devices for AI. They call it Lumex. "Up to 5x uplift in AI performance." "4.7x lower latency for speech-based workloads." "2.8x faster audio generation." Basically the idea here is, instead of adding a(nother) GPU to your phone for AI, to add instructions to the CPU. The new instruction set is called "SME2" (which stands for "Scalable Matrix Extension 2"), and provides new instructions for matrix multiplication and various other vector calculations, and built-in support for the "compressed, low-precision" floating-point number formats used in neural networks, especially neural networks "compressed" to run on mobile devices instead of on powerful machines in data centers.

"ChatGPT is calling the police on users". That's what sensationalistic headlines say, but what OpenAI actually said that is behind the headlines is: "When we detect users who are planning to harm others, we route their conversations to specialized pipelines where they are reviewed by a small team trained on our usage policies and who are authorized to take action, including banning accounts. If human reviewers determine that a case involves an imminent threat of serious physical harm to others, we may refer it to law enforcement." There is speculation this decision is in response to a news report of violence committed by a person who had an "AI psychosis" situation involving OpenAI's chatbot, but OpenAI does not mention any such thing in their blog post.

Today is Pythagorean Triple Square Day. Well sort of. You have to leave the "20" off "2025" and write it with the month first to get 09/16/25. Then each number is a "square" number, and the square roots are 3-4-5 which happen to be a Pythagorean triangle. If you keep the "2025", the article doesn't mention it but as luck would have it, 2025 is also a square number (it's 45 times 45). So it's still a square day, just not a Pythagorean square day, because 3-4-45 isn't a Pythagorean triangle. Also, the next year that's a square number is 46 times 46 which is 2116. I probably won't be alive that year.

Barbara F. Walter commented on the Charlie Kirk assassination. Barbara F. Walter is the author of a book called How Civil Wars Start (which I haven't read, but maybe I should), based on a research project for the CIA where a team of researchers from the University of California at San Diego (UCSD) analyzed 38 factors that were thought to correlate with civil war in countries other than the US. They found that there were only two factors that predicted civil war: when the government is neither a democracy nor an autocracy, but in an in-between state, which she calls "anocracy", and when people organize around identity rather than ideology. Civil wars do not happen in healthy democracies and they do not happen in full autocracies. They happen in this middle zone where a country is a partial democracy, with some elements of democracy and some elements of autocracy, especially if that state is in flux. A rapidly declining democracy is at risk of political violence, and likewise, an autocracy that's rapidly democratizing -- think about Yugoslavia in the 1990s -- is at risk of political violence. The second factor is, do citizens choose who to vote for based on ideology -- such as liberal or conservative policies -- or do they choose who to vote for based on their race or ethnic group? Those two features in combination -- a partial democracy combined with identity-based political parties -- that puts the country at high risk for political violence, instability, and civil war. Does she consider the US at risk of civil war? Spoiler: The US meets the criteria, especially the "anocracy" factor -- the US has definitely entered the "in-between zone" between democracy and autocracy. As for the second factor, US political parties are defined by ideology but there is now a significant racial dimension to determining which party people vote for. Despite this, she does not think civil war will break out right this minute, but she considers the US to be "in a really very tough bad spot", and in the years ahead, the upcoming elections could be bad. The US has extremely close elections that feel "zero sum". There's a discussion here about how social media plays a role in amplifying distrust in people in the opposing party and distrust in the democratic system itself. Towards the end, she claims everyone knows what needs to be changed to make the US a more democratic system: gerrymandering has to be eliminated, the Senate has to be reformed (she does not elaborate on what this means -- maybe you have to buy the book for that), the electoral college has to be eliminated, and "big money" has to be taken out of politics. According to her, the Republican party has no incentive to make these changes because they benefit disproportionately from the current system, and the Democratic party is either unwilling or unable to make any of these changes, even when they have control of all three branches of government. Note: The video has two ad breaks that are very long, so get your fast-forward finger ready. Also note: In the comments many people objected to her saying 80% of white people voted for Trump. She probably just flubbed this and got it backwards: In the last election, 80% of Trump voters were white, but that doesn't mean 80% of white people voted for Trump. You can't reverse that statistic and make it the other way around.

Stability AI has produced a music-generating model, but it's not an open source model that you can just go and download. It has an "enterprise license". Without the "enterprise license", you have to interact with it on the website or through an API, like closed-source models.

The 1 trillion parameter threshold was crossed by Alibaba with a new Qwen-3 model... but the same article goes on to say that OpenAI's GPT-5 model is believed to be the largest in the world with an estimated 5 to 7 trillion parameters. Details of GPT-5 are not public, so I don't think anybody (outside OpenAI) actually knows.

"Four research volunteers will soon participate in NASA's year-long simulation of a Mars mission inside a habitat at the agency's Johnson Space Center in Houston." My first thought was, "Are they going to simulate the communication delays?" Depending on where Mars is in its orbit, the length of time it takes a radio signal to travel from Mars to Earth can range from 3.1 to 22.2 minutes, with the same amount of time required again for the reply back. Around that maximum time, Mars can go (close enough to) behind the sun (from the vantage point of Earth, from Mars it is the other way around and Earth that goes "behind the sun") and communication can be blocked entirely. (This is called Mars solar conjunction.) (Mars doesn't usually go completely behind the sun, but if it's close enough that the sun's corona, which is ionized plasma, interferes with radio signals, then radio communication is impossible.) Every 25 months, approximately, it's impossible to communicate with Mars from Earth for a few days. "The team will live and work like astronauts for 378 days, concluding their mission on Oct. 31, 2026." "The crew will undergo realistic resource limitations, equipment failures, communication delays, isolation and confinement, and other stressors, along with simulated high-tempo extravehicular activities." "Crew members will carry out scientific research and operational tasks, including simulated Mars walks, growing a vegetable garden, robotic operations, and more. Technologies specifically designed for Mars and deep space exploration will also be tested, including a potable water dispenser and diagnostic medical equipment."

"OpenAI is backing 'Critterz,' an AI-generated animated film designed to prove AI can create cinema-quality content faster and cheaper than Hollywood." "In a collaboration with London-based Vertigo Films and Los Angeles AI studio Native Foreign, the team plans to complete the movie in just nine months on a budget under $30 million. This ambitious experiment is a direct challenge to conventional filmmaking and a high-stakes demonstration of AI's creative potential for a skeptical industry."