Boulder Future Salon

"An engineer showed Gemini what another AI said about its code. Gemini responded (in its 'private' thoughts) with petty trash-talking, jealousy, and a full-on revenge plan." Allegedly. Series of screenshots.

According to this screenshot from some job hunting site, 4580 people applied for a job with 46% of them writing cover letters. (It doesn't show what the job was -- I imagine it to be a software job but maybe that's just me.) Obviously people are using AI to apply for jobs. AI makes customized résumés and cover letters for every job. I've commented on how AI is in the process of automating jobs but it's interesting to note that AI also breaks the process of getting jobs.

"OpenAI improved efficiency by ~400x in one year, from $4,500 per problem, now down to about $12." "Another year of similar gains would get the cost down to $0.03." "Notably, human labor doesn't generally become 400x cheaper in a single year." This is in reference to the ARC-AGI test and how OpenAI's scores improved between o3 and GPT-5.2 Pro.

Happy random point in Earth's orbit around the sun where we increment the year number, everybody! In this case we are going from a number that is a perfect square -- 45 squared -- to twice a prime number -- twice 1013, the year Sweyn Forkbeard became King of England (he was already King of Denmark), and Kaifeng, China, became the world's largest city, a title it would hold until 1127. Keifeng's population was believed to be 600,000 in 1013. Today it has a population 4,824,016, or at least that's the 2020 census number. The largest city in the world is now Guangzhou, China, with a population of 72.7 million -- if you thought it was Tokyo, 41.2 million, demographers now consider a bunch of cities in the Pearl River Delta to have merged together into a single metro area and as such now constitute the world's largest city. I think it should be called "Shenzhen", since that's the name everyone knows, at least everyone outside China. The cities that merged together to form this new world's largest metro area are Shenzhen, Dongguan, Foshan, Huizhou, Jiangmen, Zhongshan, and Guangzhou. If you're wondering where Kaifeng is, it's not next to any Chinese city you've probably heard of. It's not next to Beijing, Nanjing, Shanghai, or Wuhan. It's kind of in the space in between all of those and Xi'an. You'll have to look at a map. This is still counting the year numbers from 2026 years ago, but that's a very arbitrary point in time, isn't it? Have you ever stopped to think that if the Roman Empire had not adopted Christianity, we not only wouldn't have Christmas, we wouldn't have New Year at this time and with this year number, either? Constantine the Great took the first step by making the Edict of Milan in 313 AD, legalizing Christianity throughout the Empire, and Christianity became the official religion of the Roman Empire under Theodosius I in 380 AD with the Edict of Thessalonica. But if that hadn't happened, maybe we'd be celebrating Roman gods like Jupiter, Mars, Venus, etc, today. Or maybe we'd be doing a pagan solstice cerebration -- from exactly which pagan tradition (Europe was full of pagan sects before Christianity) is anybody's guess. Maybe Mithraism would've become the official religion of the Roman Empire, in which case our society would be more "patriarchal" as Mithraism establishes a male-only religious hierarchy. Alternatively, Isis worship could've become the official religion of the Roman Empire, and maybe modern society would be full of goddess-worshippers. There's other possibilities such as stoicism and Manichaeism (religion from Iran founded by a person named Mani.) Or perhaps Sol Invictus (literally means "invincible sun" in Latin) would've become the official religion of the Roman Empire, and we'd all be sun worshippers today. Might be convenient on winter solstice celebration days. So if we didn't start the numbering 2026 years ago, when would it make sense to start the numbering? My first thought was the beginning of the agricultural revolution, which happened immediately upon the end of the last ice age, which was 11,600 years ago. Well, we don't know that it was *exactly* 11,600 years ago, so I had this idea of copying the last 2 digits of our years over to 11,600. That would make this the year 11626. And 11626, unlike 2026, isn't divisible by 1013. It's divisible by 5813. It's twice 5813. Another candidate for starting the numbering is the industrial revolution. A reasonable starting year for the industrial revolution is 1764 with the invention of the coal-powered steam engine (in England). That would make this year year 263. 263 is a prime number. So if we started the year numbers from the beginning of the industrial revolution, we'd be living in a prime number year. Another candidate would be the start of the computer revolution. A reasonable starting year would be the year the transistor was invented, which was 1947. That would make this year year 80. And 80 is very far from a prime number -- it's highly divisible. It's a bunch of 2s and a 5. 4 2s and a 5. Which date do you like best for the new year? January 1, 11626 (from start of agricultural revolution) January 1, 263 (from start of industrial revolution) January 1, 80 (from start of computer revolution)

Jane Wickline on Saturday Night Live made a song called "The Greatest Threat To Humanity Right Now." Starts at 10 minutes and 19 seconds in this video. (I set up the link so it should take you there.) "There are many theories about how society as we know it could end. Here with a stern warning about the future is our own Jane Wicklein." "We're programming monsters we will lose control of soon." "They're taking every job, and Singularity's approaching." "When they get smarter than us, will they be our doom?" "I think we all know the topic I am broaching."

Charlie Kirk's legacy is AI slop, and he's just the first of a new trend that will affect the whole world, says YouTuber Moon. This got me thinking, people have worried so much about deepfakes that fool people into thinking someone said things they never said or did things they never did, but here it's just sheer quantity of "AI slop" and it none of it seems to be deceptive. Nobody believes the fake surveillance video of Sam Altman stealing GPUs (ironically generated by Sora 2). But even knowingly fake videos can create an impression of a person that's different from reality, so, a different kind of deception.

Here's an idea: an AI tool for "side-by-side reading". "In Part I of this series, we explored a familiar challenge across nearly every industry: the difficulty of comparing what you have with what you need in order to meet standards, requirements, or expectations. Whether it's aligning a proposal with a solicitation, mapping an SSP to NIST controls, reviewing a student's assignment against a rubric, or validating internal processes against external frameworks, the work is often slow, manual, and cognitively demanding." "Most teams still rely on some combination of side-by-side reading, highlighting, notes scattered across spreadsheets, and a lot of rereading to feel confident they haven't missed anything. Despite all the advances in tools and automation elsewhere in the workflow, gap analysis has remained almost entirely unchanged." "Today, in Part II, we're excited to introduce the project we built to address that problem directly: Riftur, an AI-powered document alignment tool designed to make gap analysis faster, clearer, and significantly less error-prone." "Riftur helps users understand how well one document aligns with another. You upload the document you want to evaluate and the document you want to match -- anything from regulatory standards to proposal instructions, audit checklists, rubrics, internal guidelines, or technical requirements." "Riftur reads both, interprets the intent behind each requirement, and identifies where the draft satisfies, partially satisfies, or fails to address what's expected. Instead of manually scanning back and forth, the system presents a structured view of missing content, ambiguous coverage, and inconsistencies."

Someone at AI Village had Claude Opus 4.5 send an automated "Thank you for your contributions to computing" to Rob Pike, co-creator of the Go programming language (with Robert Griesemer and Ken Thompson). He completely flipped out. "F--- you people." It looks like the pro- and anti-AI bifurcation is happening. I wouldn't've expected Rob Pike to take the anti-AI side, but that's what he did.

"For most of my career, I have been told that 'optimization' is the answer. If only we could formulate the right model, feed it with enough data, and let a powerful solver loose, the machine would calmly produce the best possible decisions." "Yet in real supply chains, this promise rarely materializes. Companies deploy sophisticated software, tune countless parameters, and still find themselves firefighting stockouts, excess inventory, and nervous planners who no longer trust the system. The mathematics inside the black box may be beautiful; the decisions on the warehouse floor are often not." "The real bottleneck is not the lack of solvers but the lack of an adequate frame around the optimization itself. In this essay I want to take this idea one step further and give it a name: holimization, and its verb, to holimize, formed by contracting 'holistic optimization'." "Classical optimization, in its simplest form, starts from a very tempting posture: 'Tell me what you want to maximize or minimize, list the constraints, and I will find the best possible decision.'" "On a whiteboard this sounds perfectly reasonable. In a supply chain, it hides almost everything that actually matters." "What exactly are we 'maximizing'? Profit this month? Over a year? Growth over several years? Customer satisfaction in some not-quite-measurable sense? Resilience to disruption? A blend of all of the above?" "What exactly are the constraints? The formal ones, such as capacity and lead times, or also the undocumented ones, such as 'this warehouse team cannot realistically handle more than 5,000 inbound cartons a day' or 'this machine cannot be reset twice in the same week'?" "And how should we measure harm? Is a stockout worse than a clearance sale? How much worse, in money terms, and for which products?" "When we deploy a classical optimization engine inside a supply chain, we are forced to answer these questions by encoding them -- explicitly or implicitly -- into an objective function and a collection of constraints. Once we have done that, the solver will indeed find 'optimal' decisions relative to that encoding. Unfortunately, if the encoding is even slightly misaligned with reality, we simply get the wrong decisions faster." The whole time I was reading this, I expected it to become about neural networks. All neural nets are optimization algorithms. But no, it didn't go there. I guess this is generalizing about all optimization algorithms, including neural nets but not limited to them.

"Turn your AI Visibility into Sales". "See how and when AI recommends your products. Track mentions across LLMs, and automate your GEO strategy to transform AI traffic into revenue." So people are already trying to get LLMs to recommend their products and to track whether LLMs are recommending them. Maybe I shouldn't say "already" -- maybe people have been doing this for a long time and I just now heard about it? Here they seem to be promising tracking only -- they don't help you get your products to be recommended by LLMs. Surely they are working on that, though? "We track ChatGPT, Google AI Overview, Perplexity, and all major AI assistants that shoppers use for product research. Enterprise plans can add custom platforms including Claude."

AI transforms scientific discovery: From AlphaFold to Google's AI Co-Scientist. In a protein structure prediction contest, before 2018, no method consistently exceeded a median score of 40-60. AlphaFold 1 raised this to approximately 60, "providing the first signs that deep learning could outperform physics-based methods." Then AlphaFold 2 in 2020 achieving a median score of 92.4. "This was so accurate that many commentators declared the protein folding problem 'solved.'" AlphaFold 3, released in May 2024, did not just predict single proteins. It predicted all biological molecules, including proteins, DNA, RNA, ligands, ions, etc. "DeepMind released a free AlphaFold Protein Structure Database containing predicted structures for over 200 million proteins, covering almost every cataloged protein known to science." The AlphaFold Protein Structure Database has 3+ million users in 190 countries, and there are now 43,000+ papers citing AlphaFold 2 and another 9,000+ citing AlphaFold 3. Researchers are exploring protein structures dissimilar to known structures, exploration of previously uncharted areas of science. Article describes scientific domains AlphaFold has transformed: malaria vaccine development, cancer research, enzyme engineering, and engineering of drought-resistant crops. DeepMind spun out Isomorphic Labs to commercialize AlphaFold for drug discovery. This brings us to the second half of the article, Google's AI Co-Scientist. "Google's AI Co-Scientist builds on the Gemini 2.0 large language model but departs from single-model paradigms. The system comprises specialized agents orchestrated by a Supervisor:" "Generation Agent: Synthesizes literature and proposes initial research hypotheses" "Reflection Agent: Critiques its own hypotheses, identifying weak assumptions" "Ranking Agent: Conducts tournament-style comparisons using Elo rating system" "Evolution Agent: Iteratively refines promising hypotheses" "Proximity Agent: Assesses novelty by measuring deviation from existing literature" "Meta-review Agent: Synthesizes feedback patterns and identifies successful reasoning chains" The article goes on to describe "Validated Case Studies": "Drug repurposing for acute myeloid leukemia (AML)", "Liver fibrosis target discovery", and "Bacterial gene transfer mechanisms" I'll stop here, but the next section is on "the broader AI science ecosystem" and the article goes on to describe how future systems will combine narrow expertise, such as AlphaFold, with language models' deep reasoning ability and ability to generate hypotheses and design experiments.

Chemical hygiene -- a blog post by Andrej Karpathy. In March he wrote a blog post about digital hygiene, which I didn't tell you all about because I didn't know it existed at the time, but you can click through to it from here. I don't agree with all his suggestions but he does get you thinking about all the areas you need to pay attention to. This blog post on chemical hygiene is similar. He distills his chemical hygiene concerns in the areas of drinking water, air, food (sourcing, cooking, and preparation), fabrics, cleaning supplies, dental hygiene, sunscreen, cardio, sauna, vitamin D. "Keep your home unsophisticated. Filter your water and air. Eat real food (not edible food-like substances) from well-treated animals and with few, sensible ingredients and minimally sophisticated supply chains and processing steps. Say no to as many dyes and fragrances as you can. Surround yourself with simple, natural materials or strong and inert materials (e.g. stainless steel). Avoid plastics, especially if they are handled, heated, frozen -- the risk is not just related to the tiny particles of these exotic materials accumulating all over your body and interfering with its chemistry, but the large zoo of chemical plasticizers that are added to plastics and then leech out. The government is significantly lagging behind the industry on chemical regulation and this is your responsibility."

"This giant bubble on the island of Sardinia holds 2,000 tonnes of carbon dioxide. But the gas wasn't captured from factory emissions, nor was it pulled from the air. It came from a gas supplier, and it lives permanently inside the dome's system to serve an eco-friendly purpose: to store large amounts of excess renewable energy until it's needed." Sardinia is an island in the Mediterranean between Italy and Spain. Well, technically, it's part of Italy, but it's not part of the part of Italy that you're probably thinking of when someone says 'Italy', the part of Italy attached to the mainland. "Developed by the Milan-based company Energy Dome, the bubble and its surrounding machinery demonstrate a first-of-its-kind 'CO2 Battery,' as the company calls it." "Outside the dome, a series of machines connected by undulating pipes moves the CO2 out of the dome for compressing and condensing. First, a compressor pressurizes the gas from 1 bar (100,000 pascals) to about 55 bar (5,500,000 pa). Next, a thermal-energy-storage system cools the CO2 to an ambient temperature. Then a condenser reduces it into a liquid that is stored in a few dozen pressure vessels, each about the size of a school bus. The whole process takes about 10 hours, and at the end of it, the battery is considered charged." "To discharge the battery, the process reverses. The liquid CO2 is evaporated and heated. It then enters a gas-expander turbine, which is like a medium-pressure steam turbine. This drives a synchronous generator, which converts mechanical energy into electrical energy for the grid. After that, the gas is exhausted at ambient pressure back into the dome, filling it up to await the next charging phase." The company uses the bubble of custom-made (the article doesn't say how) CO2 because allegedly CO2 extracted from air or from some industrial process has impurities that degrade the machinery. The article says if the bubble gets punctured, the amount of CO2 released to the atmosphere is negligible compared to the CO2 released already by jets and existing coal power plants.

Microsoft distinguished engineer Galen Hunt wrote in a recent LinkedIn post: "My goal is to eliminate every line of C and C++ from Microsoft by 2030. Our strategy is to combine AI and Algorithms to rewrite Microsoft's largest codebases. Our North Star is '1 engineer, 1 month, 1 million lines of code.'"

The decline of the petrodollar will lead to inflation over the decades to come as those dollars "come home" -- at least that is the prediction in this overview of the petrodollar (illustrated with AI-generated images) and its extrapolation out into the future. The US military will lose its funding, and piracy will take over shipping lanes currently protected by the US Navy, reversing the trend towards hyperglobalization as shipping and insurance costs go up for everything imported. Currency-wise, they predict the globe will fracture into 3 distinct currency blocs: The "dollar bloc", the "Euro bloc", and the "BRICS bloc", centered around China. What do you say?

"In the game of visual telephone, one player draws a picture and describes it to another player, who must then attempt to draw the picture based only on the verbal description. After many turns, things often get woefully derailed -- and wildly creative." "Now, researchers have made artificial intelligence (AI) models play the game. In a new study published today in Patterns, researchers paired two AI models and set them loose for 100 rounds of visual telephone. But no matter how diverse or specific the starting prompt, the AIs repeatedly converged on the same 12 generic, often Eurocentric motifs -- what the researchers call 'visual elevator music.'" The article doesn't say what the 12 are but names 6 of them as "sporting celebrations", "pompously decorated dining rooms", "sunset shorelines", "a rainy romantic evening in Paris", "Gothic cathedrals", and "opulent bedrooms". A clustering algorithm called k-means clustering was used to come up with the 12 clusters. The clustering was done on embeddings, not on the actual image pixels.