Boulder Future Salon

"Airchat is a new social media app that encourages users to 'just talk.'" "Visually, Airchat should feel pretty familiar and intuitive, with the ability to follow other users, scroll through a feed of posts, then reply to, like, and share those posts. The difference is that the posts and replies are audio recordings, which the app then transcribes." What do y'all think? You want an audio social networking app?

"One of the most common concerns about AI is the risk that it takes a meaningful portion of jobs that humans currently do, leading to major economic dislocation. Often these headlines come out of economic studies that look at various job functions and estimate the impact that AI could have on these roles, and then extrapolates the resulting labor impact. What these reports generally get wrong is the analysis is done in a vacuum, explicitly ignoring the decisions that companies actually make when presented with productivity gains introduced by a new technology -- especially given the competitive nature of most industries." Says Aaron Levie, CEO of Box, a company that makes large-enterprise cloud file sharing and collaboration software. "Imagine you're a software company that can afford to employee 10 engineers based on your current revenue. By default, those 10 engineers produce a certain amount of output of product that you then sell to customers. If you're like almost any company on the planet, the list of things your customers want from your product far exceeds your ability to deliver those features any time soon with those 10 engineers. But the challenge, again, is that you can only afford those 10 engineers at today's revenue level. So, you decide to implement AI, and the absolute best case scenario happens: each engineer becomes magically 50% more productive. Overnight, you now have the equivalent of 15 engineers working in your company, for the previous cost of 10." "Finally, you can now build the next set of things on your product roadmap that your customers have been asking for." Read the comments, too. There is some interesting discussion, uncommon for the service formerly known as Twitter, apparently made possible by the fact that not just Aaron Levie but some other people forked over money to the service formerly known as Twitter to be able to post things larger than some arbitrary and super-tiny character limit.

"Evaluate LLMs in real time with Street Fighter III" "A new kind of benchmark ? Street Fighter III assesses the ability of LLMs to understand their environment and take actions based on a specific context. As opposed to RL models, which blindly take actions based on the reward function, LLMs are fully aware of the context and act accordingly." "Each player is controlled by an LLM. We send to the LLM a text description of the screen. The LLM decide on the next moves its character will make. The next moves depends on its previous moves, the moves of its opponents, its power and health bars." "Fast: It is a real time game, fast decisions are key" "Smart: A good fighter thinks 50 moves ahead" "Out of the box thinking: Outsmart your opponent with unexpected moves" "Adaptable: Learn from your mistakes and adapt your strategy" "Resilient: Keep your RPS high for an entire game" Um... Alrighty then!

"US-based startup RocketStar has successfully demonstrated an electric propulsion unit for spacecraft that uses nuclear fusion-enhanced pulsed plasma." "By introducing boron into the thruster's exhaust, high-speed protons generated from ionized water vapor collide with boron nuclei, triggering a fusion reaction that significantly boosts the thruster's performance. This fusion process, like an afterburner in a jet engine, transforms boron into high-energy carbon, which rapidly decays into three alpha particles. The result? A remarkable 50% improvement in thrust compared to our FireStar Foundation thruster." "This discovery, initially made under an SBIR from AFWERX, has been independently validated. We've witnessed fusion reactions occur in our lab and the result is a 50% jump in thrust performance. 'RocketStar has not just incrementally improved a propulsion system, but taken a leap forward by applying a novel concept, creating a fusion-fission reaction in the exhaust! This is an exciting time in technology developments and I am looking forward to their future innovations,' stated Adam Hecht, Professor of Nuclear Engineering, University of New Mexico." "The FireStar Foundation thruster is ready to ship now. It will fly in July and October 2024 on D-Orbit's proprietary OTV ION Satellite Carrier riding on two SpaceX Transporter missions, proving performance in the ultimate test -- space itself. But get ready, because our FireStar Fusion Drive is headed to the launchpad too, scheduled for in-space testing in February 2025 on Rogue Space System's Barry-2 spacecraft." From what I've been able to figure out, and for those of you who like things expressed in equations (don't worry, for those of you scared by equations I'll describe it in words as well), what they're claiming looks like: proton + 11B -> 12C* -> 3 4He + boatload of energy Boron by definition has 5 protons, add 6 neutrons and we get the 11 isotope of boron. Hit it with a proton and that makes it 6 protons, which makes it carbon by definition. The asterisk indicates the carbon is in an "excited state", which means it has excess energy. It sheds this excess energy by splitting into 3 "alpha particles", also known as 3 helium nuclei (2 protons, 2 neutrons, without the orbiting electrons -- the "4" indicates the 4 isotope). The "boatload of energy" term of the equation increases the velocity of the thrust and cranks up the acceleration that the engine imparts to the spacecraft and the efficiency of the engine. They say, "This discovery, initially made under an SBIR from AFWERX, has been independently validated." SBIR stands for Small Business Innovation Research, a US government funding program, and AFWERX is an agency within the US Air Force for tapping into innovations from startups in the US economy. They say: "As the innovation arm of the Department of the Air Force and powered by the Air Force Research Laboratory (AFRL), AFWERX brings cutting edge American ingenuity from small businesses and start-ups to address the most pressing challenges of the Department of the Air Force." Link to their website below. I wasn't able to find any record of this on their website, but that could be because I don't know how to properly search the website.

The Global Firepower 2024 Military Strength Ranking. I never heard of the Global Firepower Military Strength Ranking before. They say: "The finalized Global Firepower ranking below utilizes over 60 individual factors to determine a given nation's PowerIndex ('PwrIndx') score with categories ranging from quantity of military units and financial standing to logistical capabilities and geography. "Our unique, in-house formula allows for smaller, more technologically-advanced, nations to compete with larger, lesser-developed powers and special modifiers, in the form of bonuses and penalties, are applied to further refine the list which is compiled annually. Color arrows (Green, Gray, and Red) indicate the year-over-year trend comparison (Up, Stable, Down)." "For the 2024 GFP review, a total of 145 world powers are considered." "Note: A perfect PwrIndx score is 0.0000 which is realistically unattainable in the scope of the current GFP formula; as such, the smaller the PwrIndx value, the more 'powerful' a nation's conventional fighting capability is." Apparently with these "PwrIndx" scores, lower is better for some reason. The United States has a score of 0.0699, while Bhutan has 6.3704. According to this ranking, if Moldova (4.2311) went to war against Bhutan (6.3704), Moldova would win. The first three countries are the US, Russia, and China, all nearly tied with scores near 0.07. Make of that what you will.

Creating sexually explicit deepfakes to become a criminal offence in the UK. If the images or videos were never intended to be shared, under the new legislation, the person will face a criminal record and unlimited fine. If the images are shared, they face jail time.

The 2024 AI Index Report from Stanford's Human-Centered Artificial Intelligence lab. It says between 2010 and 2022, the number of AI research papers per year nearly tripled, from 88,000 to 240,000. So if you're wondering why I'm always behind in my reading of AI research papers, well, there's your answer. Besides that, I'm just going to quote from the highlights in the report itself, because it seems I can't improve on them, at least not in short order and I've decided I'd like to get this report out to you all quickly. I'll continue browsing through the charts & graphs in all the chapters, but for now I'll just give you their highlights and you can decide if you want to download the report and read it or part of it more thoroughly. "Chapter 1: Research and Development" "1. Industry continues to dominate frontier AI research. In 2023, industry produced 51 notable machine learning models, while academia contributed only 15. There were also 21 notable models resulting from industry-academia collaborations in 2023, a new high." "2. More foundation models and more open foundation models. In 2023, a total of 149 foundation models were released, more than double the amount released in 2022. Of these newly released models, 65.7% were open-source, compared to only 44.4% in 2022 and 33.3% in 2021." "3. Frontier models get way more expensive. According to AI Index estimates, the training costs of state-of-the-art AI models have reached unprecedented levels. For example, OpenAI's GPT-4 used an estimated $78 million worth of compute to train, while Google's Gemini Ultra cost $191 million for compute." "4. The United States leads China, the EU, and the UK as the leading source of top AI models. In 2023, 61 notable AI models originated from US-based institutions, far outpacing the European Union's 21 and China's 15." "5. The number of AI patents skyrockets. From 2021 to 2022, AI patent grants worldwide increased sharply by 62.7%. Since 2010, the number of granted AI patents has increased more than 31 times." "6. China dominates AI patents. In 2022, China led global AI patent origins with 61.1%, significantly outpacing the United States, which accounted for 20.9% of AI patent origins. Since 2010, the US share of AI patents has decreased from 54.1%." "7. Open-source AI research explodes. Since 2011, the number of AI-related projects on GitHub has seen a consistent increase, growing from 845 in 2011 to approximately 1.8 million in 2023. Notably, there was a sharp 59.3% rise in the total number of GitHub AI projects in 2023 alone. The total number of stars for AI-related projects on GitHub also significantly increased in 2023, more than tripling from 4.0 million in 2022 to 12.2 million." "8. The number of AI publications continues to rise. Between 2010 and 2022, the total number of AI publications nearly tripled, rising from approximately 88,000 in 2010 to more than 240,000 in 2022. The increase over the last year was a modest 1.1%." "Chapter 2: Technical Performance" "1. AI beats humans on some tasks, but not on all. AI has surpassed human performance on several benchmarks, including some in image classification, visual reasoning, and English understanding. Yet it trails behind on more complex tasks like competition-level mathematics, visual commonsense reasoning and planning." "2. Here comes multimodal AI. Traditionally AI systems have been limited in scope, with language models excelling in text comprehension but faltering in image processing, and vice versa. However, recent advancements have led to the development of strong multimodal models, such as Google's Gemini and OpenAI's GPT-4. These models demonstrate flexibility and are capable of handling images and text and, in some instances, can even process audio." "3. Harder benchmarks emerge. AI models have reached performance saturation on established benchmarks such as ImageNet, SQuAD, and SuperGLUE, prompting researchers to develop more challenging ones. In 2023, several challenging new benchmarks emerged, including SWE-bench for coding, HEIM for image generation, MMMU for general reasoning, MoCa for moral reasoning, AgentBench for agent-based behavior, and HaluEval for hallucinations." "4. Better AI means better data which means ... even better AI. New AI models such as SegmentAnything and Skoltech are being used to generate specialized data for tasks like image segmentation and 3D reconstruction. Data is vital for AI technical improvements. The use of AI to create more data enhances current capabilities and paves the way for future algorithmic improvements, especially on harder tasks." "5. Human evaluation is in. With generative models producing high-quality text, images, and more, benchmarking has slowly started shifting toward incorporating human evaluations like the Chatbot Arena Leaderboard rather than computerized rankings like ImageNet or SQuAD. Public sentiment about AI is becoming an increasingly important consideration in tracking AI progress." "6. Thanks to LLMs, robots have become more flexible. The fusion of language modeling with robotics has given rise to more flexible robotic systems like PaLM-E and RT-2. Beyond their improved robotic capabilities, these models can ask questions, which marks a significant step toward robots that can interact more effectively with the real world." "7. More technical research in agentic AI. Creating AI agents, systems capable of autonomous operation in specific environments, has long challenged computer scientists. However, emerging research suggests that the performance of autonomous AI agents is improving. Current agents can now master complex games like Minecraft and effectively tackle real-world tasks, such as online shopping and research assistance." "8. Closed LLMs significantly outperform open ones. On 10 select AI benchmarks, closed models outperformed open ones, with a median performance advantage of 24.2%. Differences in the performance of closed and open models carry important implications for AI policy debates." "Chapter 3: Responsible AI" "1. Robust and standardized evaluations for LLM responsibility are seriously lacking. New research from the AI Index reveals a significant lack of standardization in responsible AI reporting. Leading developers, including OpenAI, Google, and Anthropic, primarily test their models against different responsible AI benchmarks. This practice complicates efforts to systematically compare the risks and limitations of top AI models." "2. Political deepfakes are easy to generate and difficult to detect. Political deepfakes are already affecting elections across the world, with recent research suggesting that existing AI deepfake methods perform with varying levels of accuracy. In addition, new projects like CounterCloud demonstrate how easily AI can create and disseminate fake content." "3. Researchers discover more complex vulnerabilities in LLMs. Previously, most efforts to red team AI models focused on testing adversarial prompts that intuitively made sense to humans. This year, researchers found less obvious strategies to get LLMs to exhibit harmful behavior, like asking the models to infinitely repeat random words." "4. Risks from AI are becoming a concern for businesses across the globe. A global survey on responsible AI highlights that companies' top AI-related concerns include privacy, data security, and reliability. The survey shows that organizations are beginning to take steps to mitigate these risks. Globally, however, most companies have so far only mitigated a small portion of these risks." "5. LLMs can output copyrighted material. Multiple researchers have shown that the generative outputs of popular LLMs may contain copyrighted material, such as excerpts from The New York Times or scenes from movies. Whether such output constitutes copyright violations is becoming a central legal question." "6. AI developers score low on transparency, with consequences for research. The newly introduced Foundation Model Transparency Index shows that AI developers lack transparency, especially regarding the disclosure of training data and methodologies. This lack of openness hinders efforts to further understand the robustness and safety of AI systems." "7. Extreme AI risks are difficult to analyze. Over the past year, a substantial debate has emerged among AI scholars and practitioners regarding the focus on immediate model risks, like algorithmic discrimination, versus potential long-term existential threats. It has become challenging to distinguish which claims are scientifically founded and should inform policymaking. This difficulty is compounded by the tangible nature of already present short-term risks in contrast with the theoretical nature of existential threats." "8. The number of AI incidents continues to rise. According to the AI Incident Database, which tracks incidents related to the misuse of AI, 123 incidents were reported in 2023, a 32.3 percentage point increase from 2022. Since 2013, AI incidents have grown by over twentyfold. A notable example includes AI-generated, sexually explicit deepfakes of Taylor Swift that were widely shared online." "9. ChatGPT is politically biased. Researchers find a significant bias in ChatGPT toward Democrats in the United States and the Labour Party in the UK. This finding raises concerns about the tool's potential to influence users' political views, particularly in a year marked by major global elections." "Chapter 4: Economy" "1. Generative AI investment skyrockets. Despite a decline in overall AI private investment last year, funding for generative AI surged, nearly octupling from 2022 to reach $25.2 billion. Major players in the generative AI space, including OpenAI, Anthropic, Hugging Face, and Inflection, reported substantial fundraising rounds." "2. Already a leader, the United States pulls even further ahead in AI private investment. In 2023, the United States saw AI investments reach $67.2 billion, nearly 8.7 times more than China, the next highest investor. While private AI investment in China and the European Union, including the United Kingdom, declined by 44.2% and 14.1%, respectively, since 2022, the United States experienced a notable increase of 22.1% in the same time frame." "3. Fewer AI jobs in the United States and across the globe. In 2022, AI-related positions made up 2.0% of all job postings in America, a figure that decreased to 1.6% in 2023. This decline in AI job listings is attributed to fewer postings from leading AI firms and a reduced proportion of tech roles within these companies." "4. AI decreases costs and increases revenues. A new McKinsey survey reveals that 42% of surveyed organizations report cost reductions from implementing AI (including generative AI), and 59% report revenue increases. Compared to the previous year, there was a 10 percentage point increase in respondents reporting decreased costs, suggesting AI is driving significant business efficiency gains." "5. Total AI private investment declines again, while the number of newly funded AI companies increases. Global private AI investment has fallen for the second year in a row, though less than the sharp decrease from 2021 to 2022. The count of newly funded AI companies spiked to 1,812, up 40.6% from the previous year." "6. AI organizational adoption ticks up. A 2023 McKinsey report reveals that 55% of organizations now use AI (including generative AI) in at least one business unit or function, up from 50% in 2022 and 20% in 2017." "7. China dominates industrial robotics. Since surpassing Japan in 2013 as the leading installer of industrial robots, China has significantly widened the gap with the nearest competitor nation. In 2013, China's installations accounted for 20.8% of the global total, a share that rose to 52.4% by 2022." "8. Greater diversity in robot installations. In 2017, collaborative robots represented a mere 2.8% of all new industrial robot installations, a figure that climbed to 9.9% by 2022. Similarly, 2022 saw a rise in service robot installations across all application categories, except for medical robotics. This trend indicates not just an overall increase in robot installations but also a growing emphasis on deploying robots for human-facing roles." "9. The data is in: AI makes workers more productive and leads to higher quality work. In 2023, several studies assessed AI's impact on labor, suggesting that AI enables workers to complete tasks more quickly and to improve the quality of their output. These studies also demonstrated AI's potential to bridge the skill gap between low- and high-skilled workers. Still, other studies caution that using AI without proper oversight can lead to diminished performance." "10. Fortune 500 companies start talking a lot about AI, especially generative AI. In 2023, AI was mentioned in 394 earnings calls (nearly 80% of all Fortune 500 companies), a notable increase from 266 mentions in 2022. Since 2018, mentions of AI in Fortune 500 earnings calls have nearly doubled. The most frequently cited theme, appearing in 19.7% of all earnings calls, was generative AI." "Chapter 5: Science and Medicine" "1. Scientific progress accelerates even further, thanks to AI. In 2022, AI began to advance scientific discovery. 2023, however, saw the launch of even more significant science-related AI applications-- from AlphaDev, which makes algorithmic sorting more efficient, to GNoME, which facilitates the process of materials discovery." "2. AI helps medicine take significant strides forward. In 2023, several significant medical systems were launched, including EVEscape, which enhances pandemic prediction, and AlphaMissence, which assists in AI-driven mutation classification. AI is increasingly being utilized to propel medical advancements." "3. Highly knowledgeable medical AI has arrived. Over the past few years, AI systems have shown remarkable improvement on the MedQA benchmark, a key test for assessing AI's clinical knowledge. The standout model of 2023, GPT-4 Medprompt, reached an accuracy rate of 90.2%, marking a 22.6 percentage point increase from the highest score in 2022. Since the benchmark's introduction in 2019, AI performance on MedQA has nearly tripled." "4. The FDA approves more and more AI-related medical devices. In 2022, the FDA approved 139 AI-related medical devices, a 12.1% increase from 2021. Since 2012, the number of FDA-approved AI-related medical devices has increased by more than 45-fold. AI is increasingly being used for real-world medical purposes." "Chapter 6: Education" "1. The number of American and Canadian CS bachelor's graduates continues to rise, new CS master's graduates stay relatively flat, and PhD graduates modestly grow. While the number of new American and Canadian bachelor's graduates has consistently risen for more than a decade, the number of students opting for graduate education in CS has flattened. Since 2018, the number of CS master's and PhD graduates has slightly declined." "2. The migration of AI PhDs to industry continues at an accelerating pace. In 2011, roughly equal percentages of new AI PhDs took jobs in industry (40.9%) and academia (41.6%). However, by 2022, a significantly larger proportion (70.7%) joined industry after graduation compared to those entering academia (20.0%). Over the past year alone, the share of industry-bound AI PhDs has risen by 5.3 percentage points, indicating an intensifying brain drain from universities into industry." "3. Less transition of academic talent from industry to academia. In 2019, 13% of new AI faculty in the United States and Canada were from industry. By 2021, this figure had declined to 11%, and in 2022, it further dropped to 7%. This trend indicates a progressively lower migration of high-level AI talent from industry into academia." "4. CS education in the United States and Canada becomes less international. Proportionally fewer international CS bachelor's, master's, and PhDs graduated in 2022 than in 2021. The drop in international students in the master's category was especially pronounced." "5. More American high school students take CS courses, but access problems remain. In 2022, 201,000 AP CS exams were administered. Since 2007, the number of students taking these exams has increased more than tenfold. However, recent evidence indicates that students in larger high schools and those in suburban areas are more likely to have access to CS courses." "6. AI-related degree programs are on the rise internationally. The number of English-language, AI-related postsecondary degree programs has tripled since 2017, showing a steady annual increase over the past five years. Universities worldwide are offering more AI-focused degree programs." "7. The United Kingdom and Germany lead in European informatics, CS, CE, and IT graduate production. The United Kingdom and Germany lead Europe in producing the highest number of new informatics, CS, CE, and information bachelor's, master's, and PhD graduates. On a per capita basis, Finland leads in the production of both bachelor's and PhD graduates, while Ireland leads in the production of master's graduates." "Chapter 7: Policy and Governance" "1. The number of AI regulations in the United States sharply increases. The number of AI-related regulations has risen significantly in the past year and over the last five years. In 2023, there were 25 AI-related regulations, up from just one in 2016. Last year alone, the total number of AI-related regulations grew by 56.3%." "2. The United States and the European Union advance landmark AI policy action. In 2023, policymakers on both sides of the Atlantic put forth substantial proposals for advancing AI regulation The European Union reached a deal on the terms of the AI Act, a landmark piece of legislation enacted in 2024. Meanwhile, President Biden signed an Executive Order on AI, the most notable AI policy initiative in the United States that year." "3. AI captures US policymaker attention. The year 2023 witnessed a remarkable increase in AI-related legislation at the federal level, with 181 bills proposed, more than double the 88 proposed in 2022." "4. Policymakers across the globe cannot stop talking about AI. Mentions of AI in legislative proceedings across the globe have nearly doubled, rising from 1,247 in 2022 to 2,175 in 2023. AI was mentioned in the legislative proceedings of 49 countries in 2023. Moreover, at least one country from every continent discussed AI in 2023, underscoring the truly global reach of AI policy discourse." "5. More regulatory agencies turn their attention toward AI. The number of US regulatory agencies issuing AI regulations increased to 21 in 2023 from 17 in 2022, indicating a growing concern over AI regulation among a broader array of American regulatory bodies. Some of the new regulatory agencies that enacted AIrelated regulations for the first time in 2023 include the Department of Transportation, the Department of Energy, and the Occupational Safety and Health Administration." "Chapter 8: Diversity" "1. US and Canadian bachelor's, master's, and PhD CS students continue to grow more ethnically diverse. While white students continue to be the most represented ethnicity among new resident graduates at all three levels, the representation from other ethnic groups, such as Asian, Hispanic, and Black or African American students, continues to grow. For instance, since 2011, the proportion of Asian CS bachelor's degree graduates has increased by 19.8 percentage points, and the proportion of Hispanic CS bachelor's degree graduates has grown by 5.2 percentage points." "2. Substantial gender gaps persist in European informatics, CS, CE, and IT graduates at all educational levels. Every surveyed European country reported more male than female graduates in bachelor's, master's, and PhD programs for informatics, CS, CE, and IT. While the gender gaps have narrowed in most countries over the last decade, the rate of this narrowing has been slow." "3. US K12 CS education is growing more diverse, reflecting changes in both gender and ethnic representation. The proportion of AP CS exams taken by female students rose from 16.8% in 2007 to 30.5% in 2022. Similarly, the participation of Asian, Hispanic/Latino/Latina, and Black/African American students in AP CS has consistently increased year over year." "Chapter 9: Public Opinion" "1. People across the globe are more cognizant of AI's potential impact--and more nervous. A survey from Ipsos shows that, over the last year, the proportion of those who think AI will dramatically affect their lives in the next three to five years has increased from 60% to 66%. Moreover, 52% express nervousness toward AI products and services, marking a 13 percentage point rise from 2022. In America, Pew data suggests that 52% of Americans report feeling more concerned than excited about AI, rising from 38% in 2022." "2. AI sentiment in Western nations continues to be low, but is slowly improving. In 2022, several developed Western nations, including Germany, the Netherlands, Australia, Belgium, Canada, and the United States, were among the least positive about AI products and services. Since then, each of these countries has seen a rise in the proportion of respondents acknowledging the benefits of AI, with the Netherlands experiencing the most significant shift." "3. The public is pessimistic about AI's economic impact. In an Ipsos survey, only 37% of respondents feel AI will improve their job. Only 34% anticipate AI will boost the economy, and 32% believe it will enhance the job market." "4. Demographic differences emerge regarding AI optimism. Significant demographic differences exist in perceptions of AI's potential to enhance livelihoods, with younger generations generally more optimistic. For instance, 59% of Gen Z respondents believe AI will improve entertainment options, versus only 40% of baby boomers. Additionally, individuals with higher incomes and education levels are more optimistic about AI's positive impacts on entertainment, health, and the economy than their lower-income and less-educated counterparts." "5. ChatGPT is widely known and widely used. An international survey from the University of Toronto suggests that 63% of respondents are aware of ChatGPT. Of those aware, around half report using ChatGPT at least once weekly."

AI is simultaneously overhyped and underhyped, alleges Dagogo Altraide, aka "ColdFusion" (technology history YouTube channel). For AI, we're at the "peak of inflated expectations" stage of the Garter hype cycle. At the same time, tech companies are doing mass layoffs of tech workers, and it's not because of overhiring during the pandemic any more, and it's not the regular business cycle -- companies with record revenues and profits are doing mass layoffs of tech workers. "The truth is slowing coming out" -- the layoffs are because of AI, but tech companies want to keep it secret. So despite the inflated expectations, AI isn't underperforming when it comes to reducing employment.

Will AI combined with the mathematics of category theory enable AI systems to have powerful and accurate reasoning capabilities and ability to explain their reasoning? While I'm kind of doubtful, I'm not well-versed in category theory to be able to have an opinion. I tried to read the research paper, but I didn't understand it. I think one needs to be well-versed on category theory before reading the paper. I have the YouTube video of a discussion with one of the researchers (Paul Lessard) below, which I actually stumbled upon first. And I also have an introductory video to category theory. Apparently they have gotten millions of dollars in investment for a startup to bring category-theory-based AI to market, which surprises me because it seems so abstract, I would not expect VCs to understand it and become strong enough believers in it to make millions in investments. Then again, maybe VCs see their job as taking huge risks for potentially huge returns, in which case, if this technology is successful and successfully takes over the AI industry, they win big. As best I understand, set theory, which most of us learned (a little bit of) in school, and group theory (which we didn't learn in school, most of us) are foundations of category theory, which uses them as building blocks and extends the degree of abstraction out further. Set theory has to do with "objects" being members of "sets", from which you build concepts like subsets, unions, intersections, and so on. Group theory is all about symmetry, and I have this book called "The Symmetry of Things", which is absolutely gorgeous, with pictures of symmetrical tiling on planes and spheres using translation, reflection, rotation, and so on. The first half introduces a notation you can use to represent all the symmetries, and that part I understood, but the second half abstracts all that and goes deep into group theory, and it got so abstract that I got lost and could not understand it. From what I understand, group theory is incredibly powerful, though, such that, for example, all the computer algebra systems that perform integrals of complex functions symbolically do it with group theory, not with trial-and-error or exhaustive brute-force-search or any of the ways you as a human would probably try to do it with pencil and paper and tables of integrals from the back of your calculus book. Category theory I have not even tried to study, and it is supposed to be even more abstract than that. Anyway, I thought I would pass this along on the possibility that some of you understand it and on the possibility that it might revolutionize AI as its proponents claim. If it does you heard it from me first, eh?

David Graeber was right about BS jobs, says Max Murphy. Basically, our economy is bifurcating into two kinds of jobs: "essential" jobs that, despite being "essential", are lowly paid and unappreciated, and "BS" (I'm just going to abbreviate) jobs that are highly paid but accomplish nothing useful for anybody. The surprise, perhaps, is that these BS jobs, despite being well paid, are genuinely soul-crushing. My question, though, is how much of this is due to technological advancement, and will the continued advancement of technology (AI etc) increase the ratio of BS jobs to essential jobs further in favor of the BS jobs?

"Who would really win a civil war?", ponders "Monsieur Z". Before I reveal what he says, let me preface it by saying in my mind, I always figured if there was a civil war in this country between the liberal and conservative sides (which sadly seems increasingly likely over the years), the liberal side would win. The "logic" behind this prediction, such as it is, is simply that all the economic growth for the last several decades has been concentrated in the tech companies and major cities of the liberal side, and economic growth ultimately determines the winner. That's not to say that a civil war couldn't be extremely bloody and worth avoiding because of the loss of life it would cause. Ok, having said that, I never encountered this YouTube channel before, and I get the impression this guy is a conservative, since he seems to sympathize more with the conservative side. If you're familiar with this channel feel free to chime in. (Hopefully sharing a link to this channel won't get you in trouble -- I think YouTube keeps track of who watches disapproved channels.) It seems he's some sort of military historian. Anyway, he predicts a win for the liberal side. The greatest advantage the conservative side has, supposedly, is they control the food supply, but at a practical level, they cannot cut off the food supply to liberals because that would also cut off the food supply to each other in the process. More generally, the conservative side is too fractured and distrustful to organize into a combat force that could successfully take on the US military, even as a guerrilla combat force, and the military will, he predicts, be successful at purging conservative sympathizers from their ranks.

"Humane AI Pin review: A $700 gamble," says David Pierce (Vergecast). The hardware is pretty good but the AI slow enough and error-prone enough to be frustrating. I guess the dream of the "linguistic user interface" is not here yet.

"AI could actually help rebuild the middle class," says David Autor. "Artificial intelligence can enable a larger set of workers equipped with necessary foundational training to perform higher-stakes decision-making tasks currently arrogated to elite experts, such as doctors, lawyers, software engineers and college professors. In essence, AI -- used well -- can assist with restoring the middle-skill, middle-class heart of the US labor market that has been hollowed out by automation and globalization." "Prior to the Industrial Revolution, goods were handmade by skilled artisans: wagon wheels by wheelwrights; clothing by tailors; shoes by cobblers; timepieces by clockmakers; firearms by blacksmiths." "Unlike the artisans who preceded them, however, expert judgment was not necessarily needed -- or even tolerated -- among the 'mass expert' workers populating offices and assembly lines." "As a result, the narrow procedural content of mass expert work, with its requirement that workers follow rules but exercise little discretion, was perhaps uniquely vulnerable to technological displacement in the era that followed." "Stemming from the innovations pioneered during World War II, the Computer Era (AKA the Information Age) ultimately extinguished much of the demand for mass expertise that the Industrial Revolution had fostered." "Because many high-paid jobs are intensive in non-routine tasks, Polanyi's Paradox proved a major constraint on what work traditional computers could do. Managers, professionals and technical workers are regularly called upon to exercise judgment (not rules) on one-off, high-stakes cases." Polanyi's Paradox, named for Michael Polanyi who observed in 1966, "We can know more than we can tell," is the idea that "non-routine" tasks involve "tacit knowledge" that can't be written out as procedures -- and hence coded into a computer program. But AI systems don't have to be coded explicitly and can learn this "tacit knowledge" like humans. "Pre-AI, computing's core capability was its faultless and nearly costless execution of routine, procedural tasks." "AI's capacity to depart from script, to improvise based on training and experience, enables it to engage in expert judgment -- a capability that, until now, has fallen within the province of elite experts." Commentary: I feel like I had to make the mental switch from expecting AI to automate "routine" work to "mental" work, i.e. what matters is mental-vs-physical, not creative-vs-routine. Now we're right back to talking about the creative-vs-routine distinction.

"The rise of generative AI and 'deepfakes' -- or videos and pictures that use a person's image in a false way -- has led to the wide proliferation of unauthorized clips that can damage celebrities' brands and businesses." "Talent agency WME has inked a partnership with Loti, a Seattle-based firm that specializes in software used to flag unauthorized content posted on the internet that includes clients' likenesses. The company, which has 25 employees, then quickly sends requests to online platforms to have those infringing photos and videos removed." This company Loti has a product called "Watchtower", which watches for your likeness online. "Loti scans over 100M images and videos per day looking for abuse or breaches of your content or likeness." "Loti provides DMCA takedowns when it finds content that's been shared without consent." They also have a license management product called "Connect", and a "fake news protection" program called "Certify". "Place an unobtrusive mark on your content to let your fans know it's really you." "Let your fans verify your content by inspecting where it came from and who really sent it." They don't say anything about how their technology works.

"Sonauto: Create hit songs with AI". Another AI music generator. I listened to Blue Scooby Doo ft. AI Beatles and Thanks Hacker News, done in the style of a country song. Pretty impressive. Give a listen. Check out the "Top of Week" and "Top of All Time" categories. I haven't had time to actually try creating a song, but if you do, let me know how it goes.

"Texas will use computers to grade written answers on this year's STAAR tests." STAAR stands for "State of Texas Assessments of Academic Readiness" and is a standardized test given to elementary through high school students. It replaced an earlier test starting in 2007. "The Texas Education Agency is rolling out an 'automated scoring engine' for open-ended questions on the State of Texas Assessment of Academic Readiness for reading, writing, science and social studies. The technology, which uses natural language processing, a building block of artificial intelligence chatbots such as GPT-4, will save the state agency about $15 million to 20 million per year that it would otherwise have spent on hiring human scorers through a third-party contractor." "The change comes after the STAAR test, which measures students' understanding of state-mandated core curriculum, was redesigned in 2023. The test now includes fewer multiple choice questions and more open-ended questions -- known as constructed response items."