Boulder Future Salon

"How often do you use artificial intelligence in your role?" Asks Gallup poll. 67% say "never", 5% say "less often than once a year", 2% say "once a year", 7% say "a few times a year", 8% say "a few times a month", 7% say "a few times a week", 4% say "daily". But the same poll shows 1/3rd of organizations are taking action on AI. 44% for "white-collar" jobs. So it looks like leaders want to boost productivity and innovation, but workers are not using AI much and not delivering on that expectation. The 3rd question is, of people who do use AI, what do they use it for? Mostly "to generate ideas" and "to consolidate information or data" -- but leaders and managers more than individual contributors. Next is "to automate basic tasks", which is used more by individual contributors than leaders and managers.

WalkON Suit F1 exoskeleton demonstration. A person unable to walk and in a wheelchair is able to transfer directly into the exoskeleton and walk using the exoskeleton. The WalkON Suit F1 exoskeleton was developed by the Korea Advanced Institute of Science and Technology (KAIST) Exoskeleton Laboratory and Angel Robotics.

A Russian court has fined Google $20 decillion. Because there was a law that said that fines accumulate daily but double weekly. Whoever made that law never heard of the chessboard with the grains of rice. According to the story, some ruler of India many years ago was so delighted with the newly created game of chess that he wanted to reward its creator. The creator asked for 1 grain of rice on the first square of the chessboard on the first day, 2 on the 2nd square of the chessboard on the 2nd day, 4 on the 3rd square of the chessboard on the 3rd day, 8 on the 4th square of the chessboard on the 4th day, and so on -- each day the number of grains of rice doubles. At first the numbers look small but the doubling causes them to eventually become huge -- surpassing the entire world's grain production, and even, by the end of the chessboard, so they say, adding up to a number of grains so huge the pile would be higher than Mount Everest. It's an apocryphal story designed to illustrate the power of exponential growth. In mathematical terms, the number of grains on square x of the chessboard is 2^(x-1) and the total number for the whole chessboard is 2^64 - 1, about 18 followed by 18 0s. If you go thousand, million, billion, trillion, quadrillion (?), what comes after "quadrillion", "quintillion"? Then it's about 18 quintillion. Likewise, here, according to the article, the World Bank estimates global GDP as around $100 trillion, which is 1 followed by 14 0s, but the fine here, $20 decillion, is 2 followed by 34 0s. (1 followed by 38 0s in rubles.) To add to the absurdity, what is Google being fined for? Banning the YouTube channels of 17 Russian TV stations. That's it.

"If you had any idea that satellite connectivity isn't a key part of Apple's strategy, well, the company's satellite partner Globalstar has disclosed changes to its deal with Apple, including a new influx of $1.1 billion from Apple tied to capital improvements, and $400 million in equity, which gives Apple a 20-percent stake in the company." "Apple's been offering satellite connectivity since the introduction of the iPhone 14 line in 2022, which debuted with the Emergency SOS via Satellite feature."

"China adds 160 gigawatts in first 3 quarters of 2024." Of solar power, that is. "It's truly impossible to comprehend the scale of solar power deployment in China these days. When I saw how much solar power China had installed in the first 9 months of the year, I thought I must be reading something wrong. I checked a few times. But, indeed, China's National Energy Administration (NEA) reports that a shocking 160 gigawatts (GW) of new solar power capacity were added in the first three quarters of the year. 160 GW." To put that in perspective, 1 gigawatt is enough power for 750,000 homes. (I assume that number is for homes in the US, as I got it from CNET.) So 160 gigawatts is enough power for 120 million homes. Also remember, it takes 1.21 gigawatts to go... back to the future ;)

"Four futures for cognitive labor." "First: the printing press. If you were an author in 1400, the largest value-add you brought was your handwriting." "With hindsight we see that even as all the terrifying extrapolations of printing automation materialized, the income, influence, and number of authors soared." "Second: the mechanization of farming." "The per-capita incomes of farmers have doubled several times over but there are many fewer farmers, even in absolute numbers." "Third: computers. Specifically, the shift from the job title of computer to the name of the machine that replaced it. " "This industry was replaced by a new industry of people who programmed the automation of the previous one." "Finally: the ice trade. In the 19th and early 20th centuries, before small ice machines were common, harvesting and shipping ice around the world was a large industry employing hundreds of thousands of workers." "By WW2 the industry had collapsed and been replaced by home refrigeration."

25% of code written at Google is produced by AI. The question, well, 2 questions: 1) is this code as good as before, when code was all human-written? And 2) is Google actually making any good products? If not, they're just making products that aren't any good 25% faster. But Google kills lots of products so maybe they can kill products 25% faster, too? I guess Gemini is pretty good -- what's not so good is trying to ram it into everything. I don't know about you but I skip those "AI summaries" in search results -- I go directly to Gemini when I want an "AI summary". Google Search itself doesn't seem to be getting any better, although, I know people say it's getting worse, but to me it seems like it's usually good enough -- I still use it. I'm getting text messages from Gemini on my phone -- it wants to help me write messages. I don't want someone else, AI or no, telling me what to say, tho. Who wants this? If you like and use this stuff, comment below. There's also the issue of the 25% itself. At my work there is tremendous pressure for programmers to vastly increase productivity by using AI tools. Subjectively it seems like the expectation industrywide is about 5x, although at my work nobody has said 5x specifically. 25% is 1.25x, nowhere near 5x.

Export controls not working on semiconductor equipment to China. "Huawei has been able to scoot around TSMC's weak end customer checks and secure thousands of leading edge wafers through Bitmain / Sophgo, and many other established Chinese design firms. While this is a huge failure in enforcement of the export controls, it's also relatively low volume compared to domestic fabrication of the Ascend 910B. Huawei has been relying on primarily Semiconductor Manufacturing International Corporation (SMIC) to produce their domestic AI chip and they have run tens of thousands of wafers of the main compute chiplet on their domestic SMIC N+2 (~7nm) and N+3 (~6nm) process nodes." "SMIC produces 7nm-class chips including the Kirin 9000S mobile system-on-chip (SoC) and Ascend 910B AI accelerator. Two of their fabs are connected via wafer bridge, such that an automated overhead track can move wafers between them. For production purposes, this forms a continuous cleanroom and effectively one fab. But for regulatory purposes, they are separate! One building is entity-listed by the US and working on advanced logic for AI chips, a clear national security concern. The other is free to import 'dual use' tools as it runs only 'legacy processes.' Do you believe they aren't sharing anything over the wafer bridge?" "An isotropic etch chamber, essential to producing the latest 2nm Gate-All-Around transistors, cannot be exported to China from Lam's US factories. This same etch chamber, manufactured in Lam's Malaysia facility, can legally be sold to an advanced logic fab in China if no US persons are involved (in manufacturing, sales, installation, and servicing). This includes even customers on the US entity list. Other companies follow the same playbook, including Applied Materials & KLA with their Singapore facilities." "ChangXin Memory Technologies (CXMT)'s advanced DRAM with 18nm half pitch was subject to the original 2022 export controls. A new method of calculating half-pitch in the 2023 rules put them back above the minimum line for controls. Without changing the underlying process, they went from restricted to not. They also changed the node name from 17nm or 18.5nm to 19nm, to avoid any appearance of impropriety. The subtleties of the rule change that so specifically moved them from under to a literal nanometer or two over the restriction are, at least, very fortunate for CXMT. Lobbying efforts by giants such as Applied Materials who has made over $3 billion from CXMT may be noteworthy." "Pengjin High-Tech, a gallium nitride (GaN) startup that is not entity-listed, is building its cleanroom across the street from entity-listed advanced logic producer Peng Xin Wei (PXW). Pengjin is free to import nearly all advanced Western production equipment, including equipment critical to producing advanced logic at 7nm or below (again the exceptions are a small number of tools on the control list, including extreme ultraviolet (EUV))."

Gerrymandering with simulated annealing with Monte Carlo Markov chains. Found this video from 3 years ago. Basically you randomly flip pixels on a map, then, as your simulated "temperature" decreases, you decrease the randomness of how much you run with the random pixel flips regardless of whether they increase whatever gerrymandering metric you put in, and increase the degree to which the map zeroes in on a solution that's close to optimal. Your optimization function takes into account such things as to what degree funky shapes are allowed, populations of all districts are close, and of course, the degree to which the final outcome of the state is proportional to the population in terms of political parties, or whether it gives one party or the other disproportionate representation.

"Russia says it might build its own Linux community after removal of several kernel maintainers." The Russian Ministry of Digital Development said it is planning to create its own Linux community, which "will unite developers from those countries that are ready to work with Russia." (Me quoting the Google Translate version of the Russian text, see the rbc.ru link below). "Russia's response came after the Linux community blocked 11 Russians from maintaining the Linux kernel -- the operating system's core code -- citing 'various compliance requirements.' Linux creator Linus Torvalds stated that this decision 'is not getting reverted,' adding that as a Finn, he will not 'support Russian aggression.'" (This time quoting the English news article, which provides some context.) "One of the Linux maintainers later explained that the restrictions would apply to developers whose companies are owned or controlled by entities on the US Office of Foreign Assets Control list, designated as involved in activities that 'threaten the national security, foreign policy, or economy' of the country."

Grunty is a "self-hosted desktop app to have AI control your computer, powered by the new Claude computer use capability. Allow Claude to take over your laptop and do your tasks for you (or at least attempt to, lol). Written in Python, using PyQt." "If it wipes your computer, sends weird emails, or orders 100 pizzas... that's on you."

"GenAI's dirty secret: It's set to create a mountainous increase in e-waste." The study, which looks at the rate AI servers are being introduced to datacenters, claims that a realistic scenario indicates potential for rapid growth of e-waste from 2.6 kilotons each year in 2023 to between 400 kilotons and 2.5 million tons each year in 2030, when no waste reduction measures are considered. The team "considered four scenarios with varying degrees of generative AI production and application, ranging from an aggressive scenario with widespread applications to a conservative scenario with more specific applications."

"Trump Media & Technology Group, which operates the Truth Social social-media network and trades under the symbol 'DJT,' has a market capitalization of approximately $9.48 billion, allegedly higher than X, the company formerly known as Twitter, which allegedly has a valuation of $9.4 billion." "Industry analysts believe the jump in TMTG's stock price reflects growing enthusiasm among its investors that Trump will win the 2024 presidential election over VP Kamala Harris."

"TSMC isn't a pure monopsony in the wafer fab equipment market. Intel and Samsung are still buying tools, just not as often as wafer fab equipment manufacturers would like. Memory manufacturers also buy wafer fab equipment tools, and trailing-edge foundries do too." "Monopsony refers to a market in which there is only a single buyer, i.e., producers cannot find alternative buyers of their product." "Monopsony permits the buyer to establish prices, terms and conditions that are quite different from those that would result from a market structure in which there were many competing buyers and sellers." The only seller the article mentions is ASML. Single-seller market, too? At least when it comes to high-numeric-aperture (high-NA) extreme ultraviolet (EUV) lithography tools. "When there are only a few buyers, it's an oligopsony. Given the consolidated nature of the semiconductor industry, most markets within the semiconductor supply chain are already oligopsonistic."

OpenAI o1 isn't as good as an experienced professional programmer, but... "the set of tasks that O1 can do is impressive, and it's becoming more and more difficult to find easily demonstrated examples of things it can't do." "There's a ton of things it can't do. But a lot of them are so complicated they don't really fit in a video." "There are a small number of specific kinds of entry level developer jobs it could actually do as well, or maybe even better, than new hires." Carl of "Internet of Bugs" recounts how he spent the last 3 weeks experimenting with the o1 model to try to find its shortcomings. / "I've been saying for months now that AI couldn't do the work of a programmer, and that's been true, and to a large extent it still is. But in one common case, that's less true than it used to be, if it's still true at all." "I've worked with a bunch of new hires that were fresh out with CS degrees from major colleges. Generally these new hires come out of school unfamiliar with the specific frameworks used on active projects. They have to be closely supervised for a while before they can work on their own. They have to be given self-contained pieces of code so they don't screw up something else and create regressions. A lot of them have never actually built anything that wasn't in response to a homework assignment. "This o1 thing is more productive than most, if not all, of those fresh CS graduates I've worked with. "Now, after a few months, the new grads get the hang of things, and from then on, for the most part, they become productive enough that I'd rather have them on a project than o1." When I have a choice, I never hire anyone who only has an academic and theoretical understanding of programming and has never actually built anything that faces a customer, even if they only built it for themselves. But in the tech industry, many companies specifically create entry-level positions for new grads." "In my opinion, those positions where people can get hired with no practical experience, those positions were stupid to have before and they're completely irrelevant now. But as long as those kinds of positions still exist, and now that o1 exists, I can no longer honestly say that there aren't any jobs that an AI could do better than a human, at least as far as programming goes." "o1 Still has a lot of limitations." Some of the limitations he cited were writing tests and writing a SQL RDBMS in Zig.

"Colossal released a progress report on the work involved in resurrecting the thylacine, also known as the Tasmanian tiger, which went extinct when the last known survivor died in a zoo in 1936. Marsupial biology has some features that may make de-extinction somewhat easier, but we have far less sophisticated ways of manipulating it compared to the technology we've developed for working with the stem cells and reproduction of placental mammals. But, based on these new announcements, the technology available for working with marsupials is expanding rapidly." "Colossal has obtained a nearly complete genome sequence from a thylacine sample that was preserved in ethanol a bit over a century ago. According to Pask, this sample contains both the short fragments typical of older DNA samples (typically just a few hundred base pairs long), but also some DNA molecules that were above 10,000 bases long."