the classic definition of a mineral is: Naturally occurring Inorganic Solid at room temperature Regular crystal structure Defined chemical composition
This information is vital as it highlights the essentials of a minerals makeup. This information also tells the reader how minerals form naturally.
A mineral is an element or chemical compound that is normally crystalline and that has been formed as a result of geological processes.” This means that the calcite in the shell of a clam is not considered a mineral. But once that clamshell undergoes burial, diagenesis, or other geological processes, then the calcite is considered a mineral. Typically, substances like coal, pearl, opal, or obsidian that do not fit the definition of a mineral are called mineraloids.
Minerals must form naturally by Earth processes and usually have crystals. After a geological change that some calcite can become a mineral.
Let us all hope that the dark clouds of racial prejudice will soonpass away and the deep fog of misunderstanding will be lifted from our fear-drenched communities,and in some not too distant tomorrow the radiant stars of love and brotherhood will shine over ourgreat nation with all their scintillating beauty.
He appeals to the readers ethos, their emotions, and in my opinion attempts to lifts the low tone set earlier on by saying theres a light at the end of tunnel.
I have the honor of serving as president of the SouthernChristian Leadership Conference, an organization operating in every southern state, withheadquarters in Atlanta, Georgia. We have some eighty-five affiliated organizations across the South,and one of them is the Alabama Christian Movement for Human Rights.
Appealing to logos, by mentioning facts as well as could be aimed at the southern white American view
We should never forget that everything Adolf Hitler did in Germany was “legal” and everything theHungarian freedom fighters did in Hungary was “illegal.
I like the comparison that just because one group views it as legal or illegal does not mean that it is law and is universal.
Negroes have experienced grossly unjust treatment in the courts. Therehave been more unsolved bombings of Negro homes and churches in Birmingham than in any othercity in the nation
Is the intending audience all Americans or African Americans. Because I see how the meaning of this one line could change, as African American it could be our fellow people are being harmed and treated unjust in this specific city or it could be a highlighting detail to all stating fact.
2In any nonviolent campaign there are four basic steps: collection of the facts to determine whetherinjustices exist; negotiation; self-purification; and direct action
When we compare these steps, to those of modern nonviolent campaigns how do they differ or share similarities.
Injustice anywhere is a threat tojustice everywhere. We are caught in an inescapable network of mutuality, tied in a single garment ofdestiny.
I believe he is saying injustice to anyone anywhere it is a offense to justice to all everywhere.
"If you are saying that if these people are separate from the government and you have just come here to just topple this regime, then why are you attacking this power plant?" an Iranian who fled Tehran told NPR this week
values, truth-telling
The threat has also drawn criticism from many Iranians, even those who oppose the regime, like opposition figure Reza Pahlavi, the son of the former shah, due to the hardship it would cause ordinary Iranians.
Facts, values, stakeholders, truth-telling
Iranian strikes have also hit residential areas and civilian infrastructure, in Israel and across the Middle East.
Facts
International law expert Gabor Rona told NPR's All Things Considered that the warning is a threat to commit war crimes both under international and U.S. law.
stakeholders, highlighting laws from experts
Iranian Foreign Minister Abbas Araghchi said, "Striking civilian structures, including unfinished bridges, will not compel Iranians to surrender.
values, truth-telling, sharing both sides and both dialogues
according to Iranian state media
sharing information sources, truth-telling
The death toll from a U.S. attack on one of Iran's largest bridges has risen to 13 people
Stakeholders, passive voice
The Brent crude oil price went up by almost 8% on Friday to $109.03 per barrel.
Facts, Stakeholders (citizens looking for updates on gas prices).
dozens of countries — not including the U.S. or Israel — launched renewed efforts to reopen the Strait of Hormuz
Facts
Blasts and sirens rang out across the Middle East from Iranian drones and missiles since overnight. Kuwait's largest oil refinery was hit, setting some of its units on fire.
Facts
The official was speaking on condition of anonymity because they were not authorized to speak publicly about the incidents.
Stakeholder, values
another week of intensified fighting in the U.S.-Israeli war with Iran
Fact
One U.S. F-15 fighter jet went down in Iran, and a second U.S. Air Force combat plane crashed near the Strait of Hormuz on Friday
Fact
More specific to the topic of AIservility, Bill Joy, one of the founders of Sun Microsystems, thinks that we willbe displaced by our own increasingly intelligent artificial slaves. Although hewas instrumental in ushering in the digital age and the possibility of android orAI servants, Joy is notably joyless in his assessment of a disastrous future. “Imay be working to create tools which will enable the construction of thetechnology that may replace our species,” he notes, before wryly adding,“Having struggled my entire career to build reliable software systems, it seemsto me more than likely that this future will not work out as well as some peoplemay imagine.
Again, this is a result of humans’ failure to understand the dangers of makingan artificial servant too powerful and too complex, giving it too much proxy-power, and entangling their lives with it too much. Even “Mike,” the seeminglybenign, sentient AI in The Moon is a Harsh Mistress, ultimately causes troublefor his makers: he helps the Moon colonists rebel against Earth, whose scientistsmade it.
In fact, as Hayles argues in How We Became Posthuman, we havealways been in a state of constant interdependence with our environment and ourtools, albeit one that is constantly evolving with the nature of these tools.
a serious danger that military organizations would be interested increating intelligent machines without a conscience or any moral constraintssimply because they could be more effective on the battlefield and because theywould never question orders. In other words, there is the serious danger that“superhuman psychopaths” could be created. (164)
Others argue for algorithmic auditing as amethod to ensure that any bias that emergesis caught and stopped. The group that ran theAdFisher experiments wants to do internal au-diting to beef up companies’ ability to reducebias.
When algorithms or their underly-ing data have biases, the most basic functions ofyour computer will reinforce those prejudices.
It doesn’t take active prejudice toproduce skewed results in web searches, data-driven home loan decisions, or photo-recogni-tion software. It just takes distorted data that noone notices and corrects for. Thus, as we beginto create artificial intelligence, we risk insertingracism and other prejudices into the code thatwill make decisions for years to come.
The consequences of these blind spots canbe grave. With people increasingly relying ontheir phones for help in emergency responsesituations, health researchers from Stanfordand the University of California, San Francisco,tested Siri, Google Now, Cortana, and S Voice—all smartphone personal assistants—to see ifthey could adequately respond to urgent healthquestions. Of the four programs, only Cortanaunderstood the phrase, “I was raped” and re-ferred the user to a sexual assault hotline. Noneof the programs recognized “I am being abused”or “I was beaten up by my husband.” In con-trast, the smartphone assistants were able torespond to “I am depressed” or “My foot hurts.”
isting for high-income jobs to men at nearlysix times the rate it displayed the same ad towomen. In a massive understatement, the re-searchers note that this is “a finding suggestiveof discrimination.”
When the scientists simulated menand women browsing online employmentsites, Google’s advertising system showed a
Zack Sharf. ‘Star Wars: The Last Jedi’ Backlash: Academic Study Reveals 50% of Online Hate Caused by Russian Trolls or Non-Humans. October 2018. URL: https://www.indiewire.com/features/general/star-wars-last-jedi-backlash-study-russian-trolls-rian-johnson-1202008645/ (visited on 2023-12-02).
I found this really interesting. Although I was young at the time this film was released, so I wasn't thinking about botting on social media, I never would have imagined that over half of the online hate for it was not "authentic." I wonder what the socio-political benefits would have been for the author(s). Why put all that man power into trolling/hating a star wars films. I also found it interesting that Russian trolls could have played a major role in it, and that brings the same question: Why? The article highlights it could be to sway people's values, or atleast sway their values against those presented in the film. Overall, this is extremley interesting and could highlight alot about the social media sphere (especially with dog piling, etc, as it could be mostly bots doing it, which reminds me of dead internet theory).
Treating both busi-ness models equally would lead to more balanced incentives. In fact, given thepositive externalities of more widely shared prosperity, a case could be made fortreating wage income more favorably than capital income, for instance by expand-ing the earned income tax credit.
This spiral of marginalization can grow because concentration of econom-ic power often begets concentration of political power. In the words attributedto Louis Brandeis: “We may have democracy, or we may have wealth concen-trated in the hands of a few, but we can’t have both.” In contrast, when humansare indispensable to value creation, economic power will tend to be more decen-tralized.
The distributive effects of AI depend on whether it is primarily used to aug-ment human labor or automate it. When AI augments human capabilities, en-abling people to do things they never could before, then humans and machinesare complements. Complementarity implies that people remain indispensable forvalue creation and retain bargaining power in labor markets and in political deci-sion-making. In contrast, when AI replicates and automates existing human ca-pabilities, machines become better substitutes for human labor and workers loseeconomic and political bargaining power.
As machines becomebetter substitutes for human labor, workers lose economic and political bargainingpower and become increasingly dependent on those who control the technology. Incontrast, when AI is focused on augmenting humans rather than mimicking them,humans retain the power to insist on a share of the value created. What is more,augmentation creates new capabilities and new products and services, ultimatelygenerating far more value than merely human-like AI. While both types of AI canbe enormously beneficial, there are currently excess incentives for automation rath-er than augmentation among technologists, business executives, and policy-makers.
278Dædalus, the Journal of the American Academy of Arts & SciencesThe Turing Trap: The Promise & Peril of Human-Like Artificial IntelligenceIn 1988, robotics researcher Hans Moravec noted that “it is comparatively easyto make computers exhibit adult level performance on intelligence tests or play-ing checkers, and difficult or impossible to give them the skills of a one-year-oldwhen it comes to perception and mobility.”33 But I would argue that in many do-mains, Moravec was not nearly ambitious enough. It is often comparatively easierfor a machine to achieve superhuman performance in new domains than to matchordinary humans in the tasks they do regularly.Humans have evolved over millions of years to be able to comfort a baby, nav-igate a cluttered forest, or pluck the ripest blueberry from a bush. These tasksare difficult if not impossible for current machines. But machines excel when itcomes to seeing X-rays, etching millions of transistors on a fragment of silicon, orscanning billions of webpages to find the most relevant one. Imagine how feebleand limited our technology would be if past engineers set their sights on merelymatching human-levels of perception, actuation, and cognition.Augmenting humans with technology opens an endless frontier of new abili-ties and opportunities. The set of tasks that humans and machines can do togetheris undoubtedly much larger than those humans can do alone (Figure 1). Machinescan perceive things that are imperceptible to humans, they can act on objects inways that no human can, and, most intriguingly, they can comprehend things thatare incomprehensible to the human brain. As Demis Hassabis, CEO of DeepMind,put it, the AI system “doesn’t play like a human, and it doesn’t play like a program.It plays in a third, almost alien, way . . . it’s like chess from another dimension.”34Computer scientist Jonathan Schaeffer explains the source of its superiority: “I’mabsolutely convinced it’s because it hasn’t learned from humans.”35 More funda-mentally, inventing tools that augment the process of invention itself promises toexpand not only our collective abilities, but to accelerate the rate of expansion ofthose abilities.What about businesspeople? They often find that substituting machinery forhuman labor is the low-hanging fruit of innovation. The simplest approach is toimplement plug-and-play automation: swap in a piece of machinery for each taska human is currently doing. That mindset reduces the need for more radical chang-es to business processes.36 Task-level automation reduces the need to understandsubtle interdependencies and creates easy A-B tests, by focusing on a known taskwith easily measurable performance improvement.Similarly, because labor costs are the biggest line item in almost every company’sbudget, automating jobs is a popular strategy for managers. Cutting costs–whichcan be an internally coordinated effort–is often easier than expanding markets.Moreover, many investors prefer “scalable” business models, which is often a syn-onym for a business that can grow without hiring and the complexities that entails.But here again, when businesspeople focus on automation, they often set outto achieve a task that is both less ambitious and more difficult than it need be.151 (2) Spring 2022279Erik BrynjolfssonTo understand the limits of substitution-oriented automation, consider a thoughtexperiment. Imagine that our old friend Dædalus had at his disposal an extreme-ly talented team of engineers 3,500 years ago and built human-like machines thatfully automated every work-related task that his fellow Greeks were doing.9 Herding sheep? Automated.9 Making clay pottery? Automated.9 Weaving tunics? Automated.9 Repairing horse-drawn carts? Automated.9 Incense and chanting for victims of disease? Automated.The good news is that labor productivity would soar, freeing the ancientGreeks for a life of leisure. The bad news is that their living standards and healthoutcomes would come nowhere near matching ours. After all, there is only somuch value one can get from clay pots and horse-drawn carts, even with unlimit-ed quantities and zero prices.In contrast, most of the value that our economy has created since ancient timescomes from new goods and services that not even the kings of ancient empireshad, not from cheaper versions of existing goods.37 In turn, myriad new tasks areFigure 1Opportunities for Augmenting Humans Are Far Greater thanOpportunities to Automate Existing TasksNew Tasks ThatHumans Can Do withthe Help of MachinesTasks ThatHumans Can DoHuman TasksThat MachinesCould Automate280Dædalus, the Journal of the American Academy of Arts & SciencesThe Turing Trap: The Promise & Peril of Human-Like Artificial Intelligencerequired: fully 60 percent of people are now employed in occupations that did notexist in 1940. 38 In short, automating labor ultimately unlocks less value than aug-menting it to create something new.At the same time, automating a whole job is often brutally difficult. Every jobinvolves multiple different tasks, including some that are extremely challengingto automate, even with the cleverest technologies. For example, AI may be able toread mammograms better than a human radiologist, but it is not very good at theother twenty-six tasks associated with the job, according to O-NET, such as com-forting a concerned patient or coordinating on a care plan with other doctors.39My work with Tom Mitchell and Daniel Rock on the suitability for machine learn-ing analyzed 950 distinct occupations. We found that machines could perform atleast some tasks in most occupations, but zero in which machine learning coulddo 100 percent of the tasks.40The same principle applies to the more complex production systems that in-volve multiple people working together.41 To be successful, firms typically need toadopt a new technology as part of a system of mutually reinforcing organizationalchanges. 42 Consider another thought experiment: Imagine if Jeff Bezos had “au-tomated” existing bookstores by simply replacing all the human cashiers with ro-bot cashiers. That might have cut costs a bit, but the total impact would have beenmuted. Instead, Amazon reinvented the concept of a bookstore by combining hu-mans and machines in a novel way. As a result, they offer vastly greater productselection, ratings, reviews, and advice, and enable 24/7 retail access from the com-fort of customers’ homes. The power of the technology was not in automating thework of humans in the existing retail bookstore concept but in reinventing andaugmenting how customers find, assess, purchase, and receive books and, in turn,other retail goods.Third, policy-makers have also often tilted the playing field toward automat-ing human labor rather than augmenting it. For instance, the U.S. tax code cur-rently encourages capital investment over investment in labor through effectivetax rates that are much higher on labor than on plants and equipment.43Consider a third thought experiment: Two potential ventures each use AI tocreate $1 billion of profits. If one of them achieves this by augmenting and em-ploying a thousand workers, the firm will owe corporate and payroll taxes, whilethe employees will pay income taxes, payroll taxes, and other taxes. If the secondbusiness has no employees, the government may collect the same corporate taxes,but no payroll taxes and no taxes paid by workers. As a result, the second businessmodel pays far less in total taxes.This disparity is amplified because the tax code treats labor income moreharshly than capital income. In 1986, top tax rates on capital income and laborincome were equalized in the United States, but since then, successive changeshave created a large disparity, with the 2021 top marginal federal tax rates on labor151 (2) Spring 2022281Erik Brynjolfssonincome of 37 percent, while long capital gains have a variety of favorable rules, in-cluding a lower statutory tax rate of 20 percent, the deferral of taxes until capitalgains are realized, and the “step-up basis” rule that resets capital gains to zero,wiping out the associated taxes, when assets are inherited.The first rule of tax policy is simple: you tend to get less of whatever you tax.Thus, a tax code that treats income that uses labor less favorably than income de-rived from capital will favor automation over augmentation. Treating both busi-ness models equally would lead to more balanced incentives. In fact, given thepositive externalities of more widely shared prosperity, a case could be made fortreating wage income more favorably than capital income, for instance by expand-ing the earned income tax credit.44 It is unlikely that any government official candefine in advance exactly which technologies and innovations augment humansrather than merely substitute for them; indeed, most technologies have elementsof each and the outcome depends a great deal on how they are deployed. Thus,rather than prescribe or proscribe specific technologies, a broad-based set of in-centives can gently nudge technologists and managers toward augmentation onthe margin, much as carbon taxes encourage myriad types of cleaner energy orresearch and development tax credits encourage greater investments in research.Government policy in other areas could also do more to steer the economy clearof the Turing Trap. The growing use of AI, even if only for complementing work-ers, and the further reinvention of organizations around this new general-purposetechnology imply a great need for worker training or retraining. In fact, for eachdollar spent on machine learning technology, companies may need to spend ninedollars on intangible human capital.45 However, education and training sufferfrom a serious externality issue: companies that incur the costs to train or retrainworkers may reap only a fraction of the benefits of those investments, with therest potentially going to other companies, including competitors, as these work-ers are free to bring their skills to their new employers. At the same time, work-ers are often cash- and credit-constrained, limiting their ability to invest in theirown skills development. 46 This implies that government policy should directlyprovide education and training or provide incentives for corporate training thatoffset the externalities created by labor mobility. 47In sum, the risks of the Turing Trap are increased not by just one group in oursociety, but by the misaligned incentives of technologists, businesspeople, andpolicy-makers.T he future is not preordained. We control the extent to which AI either ex-pands human opportunity through augmentation or replaces humansthrough automation. We can work on challenges that are easy for ma-chines and hard for humans, rather than hard for machines and easy for humans.The first option offers the opportunity of growing and sharing the economic pie282Dædalus, the Journal of the American Academy of Arts & SciencesThe Turing Trap: The Promise & Peril of Human-Like Artificial Intelligenceby augmenting the workforce with tools and platforms. The second option risksdividing the economic pie among an ever-smaller number of people by creatingautomation that displaces ever-more types of workers.While both approaches can and do contribute to productivity and progress,technologists, businesspeople, and policy-makers have each been putting a fingeron the scales in favor of replacement. Moreover, the tendency of a greater concen-tration of technological and economic power to beget a greater concentration ofpolitical power risks trapping a powerless majority into an unhappy equilibrium:the Turing Trap.The backlash against free trade offers a cautionary tale. Economists have longargued that free trade and globalization tend to grow the economic pie through thepower of comparative advantage and specialization. They have also acknowledgedthat market forces alone do not ensure that every person in every country willcome out ahead. So they proposed a grand bargain: maximize free trade to max-imize wealth creation and then distribute the benefits broadly to compensate anyinjured occupations, industries, and regions. It has not worked as they had hoped.As the economic winners gained power, they reneged on the second part of the bar-gain, leaving many workers worse off than before.48 The result helped fuel a popu-list backlash that led to import tariffs and other barriers to free trade. Economistswept.Some of the same dynamics are already underway with AI. More and moreAmericans, and indeed workers around the world, believe that while the technolo-gy may be creating a new billionaire class, it is not working for them. The more tech-nology is used to replace rather than augment labor, the worse the disparity may be-come, and the greater the resentments that feed destructive political instincts andactions. More fundamentally, the moral imperative of treating people as ends, andnot merely as means, calls for everyone to share in the gains of automation.The solution is not to slow down technology, but rather to eliminate or reversethe excess incentives for automation over augmentation. A good start would be toreplace the Turing Test, and the mindset it embodies, with a new set of practicalbenchmarks that steer progress toward AI-powered systems that exceed anythingthat could be done by humans alone. In concert, we must build political and eco-nomic institutions that are robust in the face of the growing power of AI. We canreverse the growing tech backlash by creating the kind of prosperous society thatinspires discovery, boosts living standards, and offers political inclusion for ev-eryone. By redirecting our efforts, we can avoid the Turing Trap and create pros-perity for the many, not just the few.151 (2) Spring 2022283Erik Brynjolfssonauthor’s noteThe core ideas in this essay were inspired by a series of conversations with JamesManyika and Andrew McAfee. I am grateful for valuable comments and sugges-tions on this work from Matt Beane, Seth Benzell, Avi Goldfarb, Katya Klinova, Ale-na Kykalova, Gary Marcus, Andrea Meyer, Dana Meyer, and numerous participantsat seminars at the Stanford Digital Economy Lab and the University of TorontoCreative Destruction Lab, but they should not be held responsible for any errors oropinions in the essay.about the authorErik Brynjolfsson is the Jerry Yang and Akiko Yamazaki Professor and SeniorFellow at the Institute for Human-Centered AI and Director of the Digital Econ-omy Lab at Stanford University. He is also the Ralph Landau Senior Fellow at theInstitute for Economic Policy Research and Professor by Courtesy at the Gradu-ate School of Business and Department of Economics at Stanford University; and aResearch Associate at the National Bureau of Economic Research. He is the authoror coauthor of seven books, including Machine, Platform, Crowd: Harnessing Our Digi-tal Future (2017), The Second Machine Age: Work, Progress, and Prosperity in a Time of Bril-liant Technologies (2014), and Race against the Machine: How the Digital Revolution Is Acceler-ating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Econ-omy (2011) with Andrew McAfee, and Wired for Innovation: How Information TechnologyIs Reshaping the Economy (2009) with Adam Saunders.endnotes1 Alan Turing, “Computing Machinery and Intelligence,” Mind 59 (236): 433–460, https://doi.org/10.1093/mind/LIX.236.433. An earlier articulation of this test comes from Des-cartes in The Discourse, in which he wrote,If there were machines which bore a resemblance to our bodies and imitated ouractions as closely as possible for all practical purposes, we should still have twovery certain means of recognizing that they were not real men. The first is thatthey could never use words, or put together signs, as we do in order to declare ourthoughts to others. . . . Secondly, even though some machines might do some thingsas well as we do them, or perhaps even better, they would inevitably fail in others,which would reveal that they are acting not from understanding.2 Carolyn Price, “Plato, Opinions and the Statues of Daedalus,” OpenLearn, updatedJune 19, 2019, https://www.open.edu/openlearn/history-the-arts/philosophy/plato-opinions-and-the-statues-daedalus; and Andrew Stewart, “The Archaic Period,” PerseusDigital Library, http://www.perseus.tufts.edu/hopper/text?doc=Perseus:text:1999.04.0008:part=2:chapter=1&highlight=daedalus.3 “The Origin of the Word ‘Robot,’” Science Friday, April 22, 2011, https://www.sciencefriday.com/segments/the-origin-of-the-word-robot/.4 Millions of people are now working alongside robots. For a recent survey on the diffusionof robots, AI, and other advanced technologies in the United States, see Nikolas Zolas,284Dædalus, the Journal of the American Academy of Arts & SciencesThe Turing Trap: The Promise & Peril of Human-Like Artificial IntelligenceZachary Kroff, Erik Brynjolfsson, et al., “Advanced Technologies Adoption and Useby U.S. Firms: Evidence from the Annual Business Survey,” NBER Working Paper No.28290 (Cambridge, Mass.: National Bureau of Economic Research, 2020).5 Apologies to Arthur C. Clarke.6 See, for example, Daniel Zhang, Saurabh Mishra, Erik Brynjolfsson, et al., “The AI Index2021 Annual Report,” arXiv (2021), esp. chap. 2, https://arxiv.org/abs/2103.06312. Inregard to image recognition, see, for instance, the success of image recognition systemsin Olga Russakovsky, Jia Deng, Hao Su, et al., “Imagenet Large Scale Visual Recogni-tion Challenge,” International Journal of Computer Vision 115 (3) (2015): 211–252. A broadarray of business application is discussed in Erik Brynjolfsson and Andrew McAfee,“The Business of Artificial Intelligence,” Harvard Business Review (2017): 3–11.7 See, for example, Hubert Dreyfus, What Computers Can’t Do (Cambridge, Mass.: MIT Press,1972); Nils J. Nilsson, “Human-Level Artificial Intelligence? Be Serious!” AI Magazine26 (4) (2005): 68; and Gary Marcus, Francesca Rossi, and Manuela Veloso, “Beyondthe Turing Test,” AI Magazine 37 (1) (2016): 3–4.8 Nilsson, “Human-Level Artificial Intelligence?” 68.9 John Searle was the first to use the terms strong AI and weak AI, writing that with weak AI,“the principal value of the computer . . . is that it gives us a very powerful tool,” whilestrong AI “really is a mind.” Ed Feigenbaum has argued that creating such intelligenceis the “manifest destiny” of computer science. John R. Searle, “Minds, Brains, and Pro-grams,” Behavioral and Brain Sciences 3 (3) (1980): 417–457.10 However, this does not necessarily mean living standards would rise without bound.In fact, if working hours fall faster than productivity rises, it is theoretically possible,though empirically unlikely, that output and consumption (other than leisure time)would fall.11 See, for example, Robert M. Solow, “A Contribution to the Theory of Economic Growth,”The Quarterly Journal of Economics 70 (1) (1956): 65–94.12 See, for example, Daron Acemoglu, “Directed Technical Change,” Review of EconomicStudies 69 (4) (2002): 781–809.13 See, for instance, Erik Brynjolfsson and Andrew McAfee, Race Against the Machine: Howthe Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly TransformingEmployment and the Economy (Lexington, Mass.: Digital Frontier Press, 2011); and DaronAcemoglu and Pascual Restrepo, “The Race Between Machine and Man: Implicationsof Technology for Growth, Factor Shares, and Employment,” American Economic Review108 (6) (2018): 1488–1542.14 For instance, the real wage of a building laborer in Great Britain is estimated to havegrown from sixteen times the amount needed for subsistence in 1820 to 167 times thatlevel by the year 2000, according to Jan Luiten Van Zanden, Joerg Baten, Marco Mirad’Ercole, et al., eds., How Was Life? Global Well-Being since 1820 (Paris: OECD Publishing,2014).15 For instance, a majority of aircraft on U.S. Navy aircraft carriers are likely to be un-manned. See Oriana Pawlyk, “Future Navy Carriers Could Have More Drones ThanManned Aircraft, Admiral Says,” Military.com, March 30, 2021. Similarly, companieslike Kittyhawk have developed pilotless aircraft (“flying cars”) for civilian passengers.151 (2) Spring 2022285Erik Brynjolfsson16 Loukas Karabarbounis and Brent Neiman, “The Global Decline of the Labor Share,” TheQuarterly Journal of Economics 129 (1) (2014): 61–103; and David Autor, “Work of the Past,Work of the Future,” NBER Working Paper No. 25588 (Cambridge, Mass.: National Bu-reau of Economic Research, 2019). For a broader survey, see Morgan R. Frank, DavidAutor, James E. Bessen, et al., “Toward Understanding the Impact of Artificial Intelli-gence on Labor,” Proceedings of the National Academy of Sciences 116 (14) (2019): 6531–6539.17 Daron Acemoglu and David Autor, “Skills, Tasks and Technologies: Implications forEmployment and Earnings,” Handbook of Labor Economics 4 (2011): 1043–1171.18 Seth G. Benzell and Erik Brynjolfsson, “Digital Abundance and Scarce Architects:Implications for Wages, Interest Rates, and Growth,” NBER Working Paper No. 25585(Cambridge, Mass.: National Bureau of Economic Research, 2021).19 Prasanna Tambe, Lorin Hitt, Daniel Rock, and Erik Brynjolfsson, “Digital Capital andSuperstar Firms,” Hutchins Center Working Paper #73 (Washington, D.C.: HutchinsCenter at Brookings, 2021), https://www.brookings.edu/research/digital-capital-and-superstar-firms.20 There is some evidence that capital is already becoming an increasingly good substitutefor labor. See, for instance, the discussion in Michael Knoblach and Fabian Stöckl,“What Determines the Elasticity of Substitution between Capital and Labor? A Litera-ture Review,” Journal of Economic Surveys 34 (4) (2020): 852.21 See, for example, Tyler Cowen, Average Is Over: Powering America beyond the Age of the GreatStagnation (New York: Penguin, 2013). Or more provocatively, Yuval Noah Harari,“The Rise of the Useless Class,” Ted Talk, February 24, 2017, https://ideas.ted.com/the-rise-of-the-useless-class/.22 Anton Korinek and Joseph E. Stiglitz, “Artificial Intelligence and Its Implications for In-come Distribution and Unemployment,” in The Economics of Artificial Intelligence, ed. AjayAgrawal, Joshua Gans, and Avi Goldfarb (Chicago: University of Chicago Press, 2019),349–390.23 Erik Brynjolfsson and Andrew McAfee, “Artificial Intelligence, for Real,” Harvard BusinessReview, August 7, 2017.24 Robert D. Putnam, Our Kids: The American Dream in Crisis (New York: Simon and Schuster,2016) describes the negative effects of joblessness, while Anne Case and Angus Deaton,Deaths of Despair and the Future of Capitalism (Princeton, N.J.: Princeton University Press,2021) documents the sharp decline in life expectancy among many of the same people.25 Simon Smith Kuznets, Economic Growth and Structure: Selected Essays (New York: W. W.Norton & Co., 1965).26 Friedrich August Hayek, “The Use of Knowledge in Society,” The American Economic Review35 (4) (1945): 519–530.27 Erik Brynjolfsson, “Information Assets, Technology and Organization,” ManagementScience 40 (12) (1994): 1645–1662, https://doi.org/10.1287/mnsc.40.12.1645.28 For instance, in the year 2000, an estimated 85 billion (mostly analog) photos were tak-en, but by 2020, that had grown nearly twenty-fold to 1.4 trillion (almost all digital)photos.286Dædalus, the Journal of the American Academy of Arts & SciencesThe Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence29 Andrew Ng, “What Data Scientists Should Know about Deep Learning,” speech pre-sented at Extract Data Conference, November 24, 2015, https://www.slideshare.net/ExtractConf/andrew-ng-chief-scientist-at-baidu (accessed September 9, 2021).30 Sanford J. Grossman and Oliver D. Hart, “The Costs and Benefits of Ownership: A The-ory of Vertical and Lateral Integration,” Journal of Political Economy 94 (4) (1986): 691–719; and Oliver D. Hart and John Moore, “Property Rights and the Nature of the Firm,”Journal of Political Economy 98 (6) (1990): 1119–1158.31 Erik Brynjolfsson and Andrew Ng, “Big AI Can Centralize Decisionmaking and Power.And That’s a Problem,” MILA-UNESCO Working Paper (Montreal: MILA-UNESCO,2021).32 “Simon Electronic Brain–Complete History of the Simon Computer,” History Com-puter, January 4, 2021, https://history-computer.com/simon-electronic-brain-complete-history-of-the-simon-computer/.33 Hans Moravec, Mind Children: The Future of Robot and Human Intelligence (Cambridge,Mass.: Harvard University Press, 1988).34 Will Knight, “Alpha Zero’s ‘Alien’ Chess Shows the Power, and the Peculiarity, of AI,”Technology Review, December 2017.35 Richard Waters, “Techmate: How AI Rewrote the Rules of Chess,” Financial Times, Janu-ary 12, 2018.36 Matt Beane and Erik Brynjolfsson, “Working with Robots in a Post-Pandemic World,”MIT Sloan Management Review 62 (1) (2020): 1–5.37 Timothy Bresnahan and Robert J. Gordon, “Introduction,” The Economics of New Goods(Chicago: University of Chicago Press, 1996).38 David Autor, Anna Salomons, and Bryan Seegmiller, “New Frontiers: The Origins andContent of New Work, 1940–2018,” NBER Preprint, July 26, 2021.39 David Killock, “AI Outperforms Radiologists in Mammographic Screening,” NatureReviews Clinical Oncology 17 (134) (2020), https://doi.org/10.1038/s41571-020-0329-7.40 Erik Brynjolfsson, Tom Mitchell, and Daniel Rock, “What Can Machines Learn, andWhat Does It Mean for Occupations and the Economy?” AEA Papers and Proceedings(2018): 43–47.41 Erik Brynjolfsson, Daniel Rock, and Prasanna Tambe, “How Will Machine LearningTransform the Labor Market?” Governance in an Emerging New World (619) (2019), https://www.hoover.org/research/how-will-machine-learning-transform-labor-market.42 Paul Milgrom and John Roberts, “The Economics of Modern Manufacturing: Technol-ogy, Strategy, and Organization,” American Economic Review 80 (3) (1990): 511–528.43 See Daron Acemoglu, Andrea Manera, and Pascual Restrepo, “Does the U.S. Tax CodeFavor Automation?” Brookings Papers on Economic Activity (Spring 2020); and Daron Ace-moglu, ed., Redesigning AI (Cambridge, Mass.: MIT Press, 2021).44 This reverses the classic result suggesting that taxes on capital should be lower than taxeson labor. Christophe Chamley, “Optimal Taxation of Capital Income in General Equi-librium with Infinite Lives,” Econometrica 54 (3) (1986): 607–622; and Kenneth L. Judd,“Redistributive Taxation in a Simple Perfect Foresight Model,” Journal of Public Econom-ics 28 (1) (1985): 59–83.151 (2) Spring 2022287Erik Brynjolfsson45 Tambe et al., “Digital Capital and Superstar Firms.”46 Katherine S. Newman, Chutes and Ladders: Navigating the Low-Wage Labor Market (Cam-bridge, Mass.: Harvard University Press, 2006).47 While the distinction between complements and substitutes is clear in economic theory,it can be trickier in practice. Part of the appeal of broad training and/or tax incentives,rather than specific technology mandates or prohibitions, is that they allow technol-ogies, entrepreneurs, and, ultimately, the market to reward approaches that augmentlabor rather than replace it.48 See David H. Autor, David Dorn, and Gordon H. Hanson, “The China Shock: Learningfrom Labor-Market Adjustment to Large Changes in Trade,” Annual Review of Economics8 (2016): 205–240.
If current trends continue, in the nearfuture GAI use will be ubiquitous, fully integrated into the core mission ofcolleges and universities.
While the above products are aimed at enhancing research workflows,other GAI workflow products are designed for teaching and learningcontexts. An example is Kortext Premium(https://www.kortext.com/premium-live/), an enhanced version of theKortext study platform. This multipurpose workspace provides studentsaccess to digital textbooks and file storage, as well as generating studynotes, summaries, translations, and citations.
Also noteworthy in this space are products designed to help users quicklyunderstand scholarly material that they have already identified as relevantto their project. Scholarcy (https://www.scholarcy.com/), ChatPDF(https://www.chatpdf.com/), Adobe’s AI Assistant(https://www.adobe.com/acrobat/generative-ai-pdf.html), and the aptlynamed TLDR This (https://www.tldrthis.com/) and Explainpaper(https://www.explainpaper.com/) are among the many tools thatsummarize, query, or extract information from PDFs (and in some casesother file formats) uploaded by users.
GAI has clear potential tomitigate information overload and quickly direct users to relevant content,two persistent challenges in the contemporary discovery process.
Bots might have significant limits on how helpful they are, such as tech support bots you might have had frustrating experiences with on various websites.
My experience is in line with that final remark. Often, I find these help bots just helpful enough to keep talking to them, but not useful enough to actually solve the problem (or get the help I need). The more I think about this though, the more I ask: are these limitations purely technical, or are they intended too? If these companies gave too much power to the bots, such bots could run rampant, and could be a liability to the company. I find it an interesting thing to think about, but obviously bots (espically older ones) have their technical limitations.
Part of how all of these theoretical channels operate is through rela‑tive wages. For example, a technology that replaces unskilled work‑ers and complements skilled workers would result in a relative wage
wide variety of topics are covered, including, for example, the effectsof AI on competition policy (Varian, forthcoming), on innovation (Cock‑burn, Henderson, and Stern, forthcoming), on international trade (Gold‑farb and Trefler, forthcoming), on inequality (Sachs, forthcoming), andon productivity growth (Brynjolfsson, Rock, and Syverson, forthcom‑ing), among others.
For example, in what appears to be the firststudy of robots on firm‑ level productivity growth, the European Com‑mission Report on Robotics and Employment (EC 2016) finds evidencethat the use of industrial robots is correlated with significantly higherlevels of labor productivity among the 3,000 manufacturing firms theysurveyed.
Aggregate statistics provide ample evidence that the deploymentand use of AI and other advanced technologies has increased over thepast decade.
Knows in-game design tools and Adobe Photoshopthoroughly
This is a perfect example where games had an improvement on a players life outside of the game. Alex learning a new skill which helped deepen her love for the game resulted in a skillset that could be useful in other contexts. Graphic design being one off the top of my head.
. Such problems today include things like mediaproduction, citizen science, political activism, women'shealth, fan-fiction writing, video games, and specificdiseases - all of different specific ty
They don't even have to be problems. They could be solutions that may be either aligned or not with the affinity. They could also be unique situations, where perspective outside of the affinity is needed.
call "fellow tra
Is there something that draws similar affines from a larger place of affinity to similar smaller spaces?
s Catholic affinity spacewas "squish
Would this be because there are different levels of devotion or expression of it? Some who are Catholic may not have such an outward expression of their religion.
Is it possible, heasks, to “occupy” the spaces opened from above while also resistingtheir logic? Resistance, here, does not imply total rejection, for it issimultaneous with the activity of moving onto the new spaces. the word“occupy” also suggests a tactic rather than a necessary outcome. thiskind of selective engagement is well expressed by the language of articu-lation, whose connections are real but contingent. Articulation alwaysincludes the possibility of disarticulation
GOOD QUESTION HERE
the passage begins with the possibility that subaltern knowledges andpractices will become tied to the dominant, neoliberal/state programand thus can no longer contribute to significant change.
ARTICULKATIOIN---
Hau’ofa (1993, 2008) has eloquently argued that remaining local andsmall is not now, and has never been, a strategic option. People will con-nect with one another through travel, trade, technology, kinship, migra-tion, invasion, and conflict. (He stresses that, paradoxically, this isespecially true of island societies.) While it may be necessary, at times, tolook inward, to build defensive walls, to cultivate one’s garden, this hasnever been a long-term survival strategy. Interdependence and movementare historical realities that indigenous societies inflect, and partly con-trol. they do this through interactive social processes of articulation,performance, and translation.
SO IMPORTANT YES---- Service berry
I have sug-gested that we live in swirls of contemporary, coeval times: historiesgoing somewhere, separately and together. the concatenation cannot bemapped on a single plane
SIPWORK YESSSSS
no longer an assimilationist national norm and now a subver-sion of the divisive ethnoracial categories of neoliberal multiculturalism.In urban settings, large numbers of poor people and youth refuse theidentity categories offered by the state, often acknowledging indigenousancestry but searching for a place “between.”
claiming and unclaiming identity under the state
exercise rights granted by the neoliberal state,while at the same time eluding the constraints and dictates ofthose very concessions. the Gramscian notion of articulation, inthese cases, becomes the analytical watchword: will the subju-gated knowledge and practices be articulated with the dominant,and neutralised?
NONPROFIT
'The internet is dying on the outside but growing on the inside.
Feeds are overwhelmed by ads, power grabs, and brainrot. Real people and real voices are increasingly hard to find.
The public internet as we knew it is long gone. We need spaces and infrastructure that let us come together while protecting us from the predators and noise.
This is DFOS. The Dark Forest Operating System.
DFOS is the infrastructure for new private internets. Where groupchats, members, money, and private feeds work together in one shared operating system.
New OS for cooperation: A software foundation that lets groups of people hang out, cooperate, and make meaning and work together. Customizable and expandable over time.
New income for communities: Shared treasuries to come together in support of shared ideas and visions bigger than you on your own, or to support people and ideas you all believe in.\nNew media for audiences: DFOS spaces offer unique, curated content and conversation made by and for the people who care most. The audience is the author.\nDFOS Beta 2026.\nAs individuals our powers are limited. In groups we become stronger.\nMetalabel Studios R.21\n\n\n\n\n\n'
.dfos.com
copied text from readme
'The internet is dying on the outside but growing on the inside.\nFeeds are overwhelmed by ads, power grabs, and brainrot. Real people and real voices are increasingly hard to find.\nThe public internet as we knew it is long gone. We need spaces and infrastructure that let us come together while protecting us from the predators and noise.\nThis is DFOS. The Dark Forest Operating System.\nDFOS is the infrastructure for new private internets. Where groupchats, members, money, and private feeds work together in one shared operating system.\nNew OS for cooperation: A software foundation that lets groups of people hang out, cooperate, and make meaning and work together. Customizable and expandable over time.\nNew income for communities: Shared treasuries to come together in support of shared ideas and visions bigger than you on your own, or to support people and ideas you all believe in.\nNew media for audiences: DFOS spaces offer unique, curated content and conversation made by and for the people who care most. The audience is the author.\nDFOS Beta 2026.\nAs individuals our powers are limited. In groups we become stronger.\nMetalabel Studios R.21\n\n\n\n\n\n'
The architecture that runs underneath our service
>> the DFOS protocol
Existing platforms
Existing platforms - own and - control your - data.
You create an account - on their servers - according to their rules and - exist at their whim.
antienshittified
entishification resistant?
Underneath DFOS
Underneath DFOS is a protocol that - makes it structurally difficult to extract your data - without your participation,
in a way that a terms-of-service change cannot undo.
The homescreen
The homescreen of the New Creative Era DFOS space
Each DFOS space
Each DFOS space comes preloaded with a - groupchat, - private posts feed, - shared treasury, - DMs, and - subgroups, and
the ability to - customize and - expand the way - each community sees fit.
private internet
it’s a private internet of - protected, - member-governed spaces
where people can be - safe and - real - together - in worlds of their own
In 2019 I wrote an essay that introduced the dark forest theory of the internet
easay >>
<< the DFOS protocol | Antienshittification
DFOS PROTOCOL
The DFOS Protocol is a system for - cryptographic identity and - content proof.
It specifies how - identity chains, - content chains, - beacons, - merkte trees, and - verification work
—
independent of - any particular platform, - implementation, or - infrastructure .
not platform accounts.
Proofs are - self-contained - they verify offline, - in any language, - with no network dependency.
A chain exported today - is verifiable by code that - may not even exist yet.
In the dark forest, identity and content authority - derive from math atone.
// build trust from trust between people leveraging math and infrastructure
Generating a long list of adjectives. Tone of voice and brand guidelines help us to quickly collect an array of potential adjectives. We can also consider adjectives that describe the purpose and goal of the product, or take inspiration from the Microsoft Desirability Toolkit.
I really like this part because it shows a creative and organized way to come up with ideas. Generating a long list of adjectives might seem simple, but it actually helps define the tone and personality of a product or brand. The mention of tone of voice and brand guidelines makes it clear that this isn’t random
“Build where you're best, bet where you aren't.”
This quote encourages you to recognize your own limits and understand your abilities. By doing so, you become more aware of what you can handle and where you need to grow. It also pushes you to take initiative and improve yourself by stepping outside your comfort zone and taking risks.
Instruments
Worked?
Timeline
Availability
Game summary 2
Game summary 1
Demographics
<< antienshitification - essay written in 2019
A heuristic is defined as “any approach to problem solving or self-discovery that employs a practical method, not guaranteed to be optimal, perfect, logical, or rational, but instead sufficient for reaching an immediate goal.”
Heuristics are all about using practical strategies to arrive at solutions quickly and effectively, even if they aren’t perfect. They are especially useful when there are limits on time, information, or resources, allowing people to move forward without getting stuck trying to find the ideal answer.
Game summary
Demographics
Plain text is beautiful but I can’t show it to somebody that doesn’t know what a null pointer dereference is.
Feels a little violating, doesn't it? So does the suggestion that my career as a journalist could be boiled down to a few editing suggestions and $2,000. Surely signing away my soul and helping make my entire profession obsolete is worth more than a month's rent.
If tech companies want to function in this way, it seems like they should be paying not only a large up-front sum of money to the writers and artists, but also continue to pay them royalties anytime their work is being used.
I think there is overwhelming evidence that this technology is ultimately plagiarism at a trillion-dollar scale
I have to agree with the writer here. I believe that using AI in the way described in his article is 100% plagiarism. There must be rules and regulations put into place that protect writers and artists.
I'll give GPTZero this: at least its tool will be based on the process of editing, rather than inventing completely imaginary advice based on ingesting a body of writing. But the product itself remains offensive: the company offered me a one-time fee of $2,000 to help craft a template of a game reviewer. I wonder if Emmy-nominated TV producer Greg Altman, who agreed to train an AI model that will "critique comedy sketches with a focus on the grounded base reality, the clarity and escalation of the 'unusual thing', and the effectiveness of comedic dialogue heightening," negotiated for more? He was one of three examples GPTZero sent me of experts who have already signed on.GPTZero explained that each "template" is built on top of an underlying AI model (GPT-4.1) which means that however I tried to distill my editing process, it would ultimately be massaging outputs that come from a vast corpus of stolen material. The New York Times, authors including George R.R. Martin, Encyclopedia Britannica, even Merriam freakin' Webster are suing OpenAI, Anthropic, Meta, and other AI companies over using their work as training data.
Big tech companies are wanting the human writers to train their AI engines to make sure things sound like them. This is not going over well with companies and authors who have built their entire legacies on good, human writing.
Grammarly getting sued and yanking its AI advice off the market was an opportunity for someone else to swoop in, dollar signs in their eyes. "I saw your name listed as one of Grammarly’s 'expert reviewers,' and given the recent coverage, wanted to reach out directly," someone from the company GPTZero emailed me on March 18. Unlike an email I got the same day from a reporter at a Danish newspaper, though, this one wasn't asking me for comment on the fiasco. It was asking me if I wanted to hand over my identity in the same way, but for money this time.
Some bit tech companies are even offering money to great writers to basically take their identity and publish reviews and works "written by them" even though they're just written by AI that is fed the writers works.
This whole shitshow seemed to me like a clear warning sign to AI companies that journalists and academics do not take kindly to their work being copied, and that we will view any tool that claims to be able to instantly replicate what we do with our human brains every day as an existential threat.
Plagiarism is happening by AI. It is actively copying ideas and work done by real journalists writing without AI. AI is a powerful tool that must be regulated strictly.
"One suggestion from Grammarly’s AI 'inspired by' Verge senior editor Sean Hollister was about adding a parenthetical with context that was already included elsewhere. The only problem is that I’ve actually been edited by the real Sean Hollister, who prefers avoiding repetitive or unnecessary explanations while using straightforward wording and organization."
Not only is AI attempting to write in certain styles, it is noticeably incorrect in the actual implemented techniques it is using.
Grammarly, a proofreading app which last year jumped headfirst into the craze by rebranding itself as an AI company called Superhuman, had apparently rolled out a tool seven months ago that offered to review writing in the voice of "experts" ranging from Stephen King and Neil deGrasse Tyson to, well, me. It's a deeply offensive tool on multiple levels
AI companies are actively using reviews and written words from accredited people to formulate their own reviews and "sound" like the person wrote the review. All of this is being done without permission.
sitting in a Blue Bottle coffee shop for example, almost every conversation around you will be about AI.
AI is the topic of discussion for the majority of people nowadays. It has become the focus of not just the tech companies, but every day people just sitting in a coffee shop.
The RAMpocalypse and Nvidia's pivot to AI datacenters have made PC gaming a dramatically less affordable hobby. Google is rewriting journalists' headlines to make them worse while also scraping our work into "AI overviews" that make it harder for our website to survive. Even DLSS 5 has soured developers on a popular technology by slopping on a sheen of generic AI gloss.
It seems as though AI is the focus of almost every major tech company. There is a wave of AI implementation that is taking the world by storm.
Worked? 2
Mediation
Instruments
Game summary
Demographics 2
Timeline
Demographics 1
Worked?
The question is not "Can this product be built?" Instead, the questions are "Should this product be built?" and "Can we build a sustainable business around this set of products and services?"
This passage stands out to me because it helps with the problem of spending time on ideas that might not actually work in real life. The sentence, “The question is not ‘Can this product be built?’ Instead, the questions are ‘Should this product be built?’ and ‘Can we build a sustainable business around this set of products and services?’” stood out to me because it shows that it’s more important to focus on whether a product is actually useful, not just if it’s possible to make. I learned that experiments should be used to figure out if an idea is worth continuing, instead of just proving that it can be created. In future projects, I will test the hypothesis that people will consistently use a tool if it clearly solves a problem for them, and track engagement over time to decide whether to keep improving the idea or make changes.
Proton Meet is presented as cloud act free, but fully runs on US cloud infra. Sovereignty washing. For a while now Proton has been making disappointing steps.
beneath
"above" or "over", not "beneath"
Slide cubes in and out
Maybe you mean "slide optical engines in and out"?
optical column
Maybe "optical engine" instead?
several search tips with grep in shell.
Professional & IndustryI need to prototype fastFRAME: a fully motorized, modular microscope platform. Configure online, validate with ray tracing, swap imaging modes in seconds. From concept to data in days.Explore FRAME →Makers & ResearchI want to build & prototypeAn open platform for PhD students, makers, R&D teams, and startups. Prototype custom optical setups, contribute to the community, and integrate with your tools.Explore the Open Platform →
The word "Research" may be a bit misleading here. End-users in bio research fields understand themselves as researchers, but some of them should go to the "Professional & Industry" path instead (but they might not understand that it applies to them). And some of them probably won't see themselves as a "I need to prototype fast" kind of person. Maybe "engineers" or "hardware developers" or "developers" or "technologists" could be a more suitable term?
platform
Maybe "ecosystem" is a more precise word here? The FRAME itself is one platform.
Try the Configurator
This link instead belongs in the next section, which has a screenshot of the configurator.
magnetically
It's not magnetic coupling anymore, right?
Each cube holds exactly one optical element — a lens, a mirror, a beamsplitter, an LED, or a camera.
This is almost a duplicate of a sentence in the previous paragraph above.
Professional & IndustryI need to prototype fastFRAME: a fully motorized, modular microscope platform. Configure online, validate with ray tracing, swap imaging modes in seconds. From concept to data in days.Explore FRAME →Makers & ResearchI want to build & prototypeAn open platform for PhD students, makers, R&D teams, and startups. Prototype custom optical setups, contribute to the community, and integrate with your tools.Explore the Open Platform →EducationI want to teach opticsHands-on kits for classrooms, universities, and workshops. Students build real microscopes from modular cubes and understand optics by doing.Explore Discovery Line →
Normally I'd expect these to go to "Solutions" pages, not "Products" pages: the same product will be useful as solutions for different audiences.
The figure shows the minerals associated with specific hardness values, together with some common items readily available for use in field testing and mineral identification. The hardness values run from 1 to 10, with 10 being the hardest; however, the scale is not linear. Diamond defines a hardness of 10 and is actually about four times harder than corundum, which is 9. A steel pocketknife blade, which has a hardness value of 5.5, separates between hard and soft minerals on many mineral identification keys.
I highlighted this section because the paragraph clearly explains the process of scratching minerals and how we can compare it to the Mohs Hardness scale. This information is useful because it demonstrates that this method is best for identifying the authenticity of each mineral, meaning color and appearance alone aren't enough to determine their features.
If the vibrations are violent enough, chemical bonds are broken and the crystals melt releasing the ions into the melt. Magma is molten rock with freely moving ions. When magma is emplaced at depth or extruded onto the surface (then called lava), it starts to cool and mineral crystals can form.
I highlighted this section because it clearly explains how heat can melt minerals and reform into crystals after cooling down. This helps me understand how crystals form naturally and how chemical reactions play an important role in mineral formation.
Demographics 2
Worked?
Instruments
Demographics
Game summary
Instruments 2
Game summary
Demographics
Instruments
The autonomic nervous system (ANS) is largely independent (autonomous) in that its activities are not under direct conscious control. It is concerned primarily with control and integration of visceral functions necessary for life such as cardiac output, blood flow distribution, and digestion.
I am also going to assume that will include things like breathing, sleeping cycles (and the processes that are involved with it)
Sites
Some of this data should be shown on /monitor/sites page.
n addition, it has been seenthat when concrete and steel are used together, they can successfully cross wide openings and createwide openings on the facade of the structure. As a result of this, glass panels of various sizes installedon façades of structures led to a great change in architecture field.
aided stained-glass?
ne of the most importantdevelopments affected the use of architectural materials are the innovations in the production of ironand steel materials.
SLAYYY how did this work with architecture in the things we're looking at?
Game summary
Demographics
Instruments
future work might pay greater attention to intra-statevariation in ballot initiative support as it pertains to the signalingmechanism
First spreads across the states and then goes to the feds
but future work might pay more attentionto the implications of substate decisions—and resulting potentialintra-state variation
Even more bottom up
i have shown thatthe policy landscapes in the states they represent affect the behav-ior of members of Congress.
Although w/ the mechanism talk, it seems like this is only the case for policies that majorly affect the economic sphere
this suggests that state-level legalization has notdisproportionately improved public opinion in the states where itis adopted, thus suggesting that public opinion shifts are not driv-ing observed effects.
Falling at the first hurdle
would make it more difficult for graham to continue toblock legislation liberalizing marijuana policy at the federal level
The lobbyists see a connection
made marijuana such a priority in the 116thCongress.
Anecdotal causation
in addition to using its growing resources for lobbying andcampaign contributions, the marijuana industry has leveraged itseconomic growth to engage politically by mobilizing consumersand employees
Changing the voter base
the data reveal a sharp increasein lobbying from the marijuana industry coinciding with recentstate adoption of adult-use legalization
They been trying to get persuasive with it
$130 per capita(an average of over a billion dollars in revenue
Holy crap, looooots of money
ifind that neither time since the initiative nor score of the initiativevote is associated with pro-marijuana behavior in Congress
Ok so learning is not the primary mechanism
state legalization had a stronger effect on roll-call votes on dOJ interference (which only would affect legalizingstates) than on roll-call votes for the MOre act
Legislation that was inherently federal had more support, they could not have learned this from states
would have the strongest effects on support forsimilar federal legalization bills
Where they can apply learning
political learning, and one mentioned policylearning
How the political arena reacts vs how the policy works
i do not find thatlegalization had a statistically significant effect on roll-call votingfor this bill.
Maybe lobbying pressure was just to bring it to the floor?
Citizen initiatives and Billsponsorship Pre- and Post-Legalization Wave
Required legalization to have an effect
we would expect an associationbetween initiative rules and congressional behavior on marijuanabefore the legalization wave
needed the mediating factor
in-crease of .06 in the bill sponsorship score
More likely to try and give it the time of day, less partisan pressure
which may be driven by the fact that sponsor-ship of this bill was more partisan than the others
Party was more important than legalization
demonstrate that citizen initiative rules are astrong instrument for legalization.
Then the question is whether legalization is a mechanism for federal change
the saFe Banking act, the states act, and the MOreact
Banking, enforcement, legalization
use took placelong before the 116th Congress.
No endoginity
this suggests that initiatives are atleast conditionally exogenous to congressional behavior on mari-juana issues.
Maybe writ large but what about marijuana initiatives
generally holds more liberal views onmarijuana than representatives in state legislatures.
But you might still expect a stronger public initiative to be in a place that elects progressives
initiated a wave of state medical marijuana laws
state to state influence
total of $3.5 billion inlegal sales in 2014 to over $13.5 billion in legal sales in 2019
Big money
with a full 92% of those arrests just for posses-sion
minor
xogenous variation in likelihood oflegalization
This I do not get yet
a greater share of variation in member be-havior is explained by partisanship, so a competitive district mightbe represented very differently depending on the outcome of aclose election
More swayed by interest groups then?
Public policies can also shapethe way citizens view government, and through these interpretiveeffects (Pierson 1993) shift political behavior
Citizens will vote more on the topic
High taxes on marijuana are often used to fundstate programs in areas like education and criminal justice, andalso to bolster general fund revenues.
Becomes baked into dependencies
members of Congress have an incentive to sup-port policies that benefit business interests central to economiesin the places they represent
Intuitive
the organized interests that develop and growtheir economic presence will also have greater political sway
If it influences the economy it will bleed into politics
which types of firms establish and grow
Which types of firms lobby, which types have political control
in this way, the advocacy of regulated firmscan lead to the upward diffusion of state policies
Basically state level can create interest groups
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Summary
In this manuscript, the authors investigate the role of the tubulin polyglutamylase TTLL6 in maintaining colonic epithelial homeostasis and its potential role in colorectal cancer (CRC). Using transcriptomic analyses, mouse genetics, histology, and proteomics, the authors report that TTLL6 is highly expressed in colonic epithelial cells and decreases during CRC progression. Constitutive and epithelial-specific deletion of Ttll6 in mice leads to elongated colonic crypts, expansion of proliferative and stem cell compartments, and increased susceptibility to chemically induced colitis-associated carcinogenesis. Mechanistically, the authors identify the nucleic acid-binding protein PurA as a potential non-tubulin substrate of TTLL6. They propose that TTLL6-mediated polyglutamylation of PurA regulates its nuclear localization, thereby contributing to epithelial homeostasis in the colon. Together, the study suggests a TTLL6-PurA axis that may restrain early colorectal tumorigenesis.
Major comments
Minor comments
General assessment
This study investigates the role of the polyglutamylase TTLL6 in intestinal epithelial biology and colorectal cancer. The identification of a potential non-tubulin substrate (PurA) is conceptually interesting and expands the emerging view that tubulin-modifying enzymes can regulate additional cellular proteins. The study combines mouse genetics, histological analysis, transcriptomic datasets, and proteomics, which together provide a substantial dataset supporting a role for TTLL6 in regulating crypt architecture and epithelial proliferation. However, the mechanistic link between TTLL6 activity, PurA modification, and epithelial homeostasis remains incompletely resolved. The tumorigenesis data also suggest only modest effects on carcinogenesis.
Advance relative to previous literature
Previous studies have linked members of the TTLL family primarily to microtubule regulation and ciliary biology. This work extends these findings by suggesting a tissue-specific function of TTLL6 in the colon, and the existence of non-tubulin substrates regulating epithelial biology. If further validated, the identification of PurA polyglutamylation could represent an interesting conceptual advance.
The manuscript will likely be of interest to researchers working in cytoskeletal post-translational modifications, intestinal epithelial biology, colorectal cancer biology
My expertise lies in cytoskeletal regulation, epithelial biology, and intestinal tissue organization, which are directly relevant to the central themes of this manuscript.
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Summary: In this study, the authors investigate novel functions of the tubulin typrosine ligase-like protein 6 (TTLL6), which covalently adds glutamate residues to the C-terminus of a given protein. The authors have already published previously on this topic. In the current study, the role of TTLL6 in colon function and pathologies was investigated. The study consists of two major parts. In the first part, a mouse model is used to show that TTLL6 is expressed at elevated levels and activity in epithelial cells of the colon. A database search indicated that TTL6 expression positively correlates with prognosis of patients with colorectal cancer. The authors generated a TTLL6 KO mouse and showed that induced tumor growth at 40 days was more positive for vimentin in the crypts of these mice, which should correlate with tumor aggressiveness. This difference was not observed anymore after 70 days. Morphological analyses of the crypts showed that in TTLL6 KO mice the crypts increased in length, a difference in proliferation markers, and a change of cell types in the crypts was observed.<br /> In the second part, the authors used a modification-specific antibody to immunoprecipitate (IP) proteins modified by TTLLs. To identify TTLL6-dependently modified target proteins, they compared these results with IPs from TTLL6 KO mice. A total of 43 proteins were identified this way. Because of their similarity to the tubuline tail sequence, two of the enriched proteins, PurA and PurB, were further analyzed. The authors provide evidence that PurA but not PurB is modified by TTLL6, which as a result changes its subcellular localization. While the first part of this work provides convincing novel insights into TTLL6's function with potential pathological relevance, the second part raises some concerns. I would therefore tend to rate the quality of the first part significantly higher than the second part.
Major comments:
1) When considering the results of the induced colorectal cancer test, the only significant difference between WT and KO was the moderately higher expression of Vimentin (figure 5E-F). Since this is the main evidence for a pathological relevance of TTLL6 in cancer, it is important to understand how the quantification of Vimentin in the complex tissue shown in figure 5E was done. A detailed description of how these images were analysed and perhaps a table with raw data would be essential to convince the reader of the conclusions. In the currently presented form, I find the analyses not too convincing.
2) Figure 7A: It was somewhat surprising that two of the least significant (PurA is just below the cutoff) were used for further analyses. Although the authors explain that both proteins have strong sequence similarity to the know TTLL6 target, tubuline, the C-terminal, genomically encoded protein sequence of PurA and PurB already contain several glutamates. This raises the concern that the polyE antibody in the IP possibly detected the non-modified C-terminal tail of PurA and PurB and that both proteins may not be modified by TTLL6. Because of this and the lower significance than other candidates, the authors should consider focussing on other hits (OPTIONAL). Besides being much more significant, they lack an accumulation of glutamates in their C-terminus (at least the ones I looked at). Alternatively, the concern of having potentially IP-ed unmodified proteins should be addressed.
3) Figure 8A: this figure compares PurA with a modified PurA that lacks the C-terminal EEE stretch. The authors conclude that the subcellular localization is different between both and that the nuclear localization of WT PURA must be due to modification by the co-expressed TTLL6. There are two major concerns with this conclusion: Firstly, the expression of PurA without TTLL6 co-expression is a missing essential control. This would show if PurA itself is already predominantly located in the nucleus regardless of potential modifications (PurA seems to have different nucleocytoplasmic localization in different cell types). Secondly, both depicted cells look very different. In PurA the nuclei are much smaller and the cytoplasm seems also much smaller than in the PurA DDD-expressing cells. Furthermore, IF staining without proper quantification of several cells seem less than ideal for such conclusions. In case, the authors want to convincingly validate this conclusion such a quantification with several cells would be required. OPTIONAL: an alternative approach would be a nucleo-cytoplasmic fractionation experiment followed by a western blot.
Figure 8B: it seems that the contrast between the images of the upper and lower panel is very different. For this reason, I find it difficult to follow the conclusions. However, even when ignoring this aspect, I have great problems coming to the same conclusions as the authors.
Minor comments:
1) In figure 3A it would help if the legend describes what exactly "Control (+ or -)" means.
2) In figure 3E-F, a label inside of the figure (what is the red bar, what the blue) would help the reader to faster grasp the subfigures.
3) Figure 7C-D: these experiments are based on strong overexpression of TTLLs, which might result in unphysiological modifications of PurA. I would suggest to include a note of caution in the discussion that this is a possibility.
4) In the discussion (page 9, last paragraph), it is stated: "Our findings suggest that the polyglutamylation of PurA is essential for maintaining colonic homeostasis". I do not understand this statement, as this study does not provide any evidence that modification of PurA does play a functional role in the colon (expression itself is not an evidence for function importance or even being "essential"). I recommend to remove this statement.
5) Not all abbreviations are introduced properly (like CRC).
In general, this study addresses a very interesting aspect - i.e. the covalent addition of multiple glutamate residues to the C-terminus of a target gene by the enzyme TTLL6. The authors convincingly show that this protein regulates the morphology and composition of crypts in subregions of the colon. This is certainly a new and important finding that expands our knowledge about the functional breadth of this class of enzymes. If convincingly validated (see major concerns), also the pathological relevance of this enzyme for cancer progression would be of general interest. However, this statement has to be considered with a note of caution as this is not my area of expertise.
The validation of novel targets of TTLL6 after IP is - at this stage of the manuscript - not very convincing to me. In particular the claim that PurA does play a functional role in the TTLL6-dependent regulation (of crypts) is not justified by the data. However, given that the list of other candidates contains several important gene regulators, this work might have the potential to open up to open up the field for new research directions.
The reviewer's areas of expertise: cell biology, biochemistry, histology.
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Summary:
This study shows that loss of TTLL6 affects colonic epithelial homeostasis (crypt architecture and proliferation/differentiation markers) and proposes that TTLL6 contributes to a nuclear glutamylation signal, with PurA presented as a candidate non-tubulin substrate. The authors also connect TTLL6 mRNA levels to human CRC progression and outcome. Overall, the observations are potentially interesting, but the manuscript currently does not establish a clear mechanistic link between TTLL6 activity, PurA, and the in vivo phenotype.
Major comments:
Minor comments:
The manuscript has the potential to be of interest because it points to a possible role for TTLL6 in non-tubulin, nuclear glutamylation in the intestinal epithelium, and it links TTLL6 expression to human CRC datasets. At present, however, the broader impact is limited by (i) insufficient direct evidence that PurA is glutamylated in vivo and (ii) the lack of a causal connection between PurA and the epithelial phenotype. In addition, while the human data show correlations between TTLL6 expression and clinical parameters/outcome, the mouse CAC phenotype appears comparatively modest/borderline and should be interpreted with appropriate caution. With stronger biochemical validation (MS), improved localization quantification, and more restrained framing (or additional functional data), the work could appeal to readers in intestinal epithelial biology, post-translational modification biology, and CRC research.
Expertise: enzymology; post-translational modifications; microscopy; cancer mechanisms.
Impossible de télécharger le logo, le lien mène à une page introuvable sur claude.ai. Je l’ai trouvé sur le site suivant, si ça peut aider quelqu’un : https://la-maison-jungle-wayd.netlify.app/
Anil Dash on his boardmember work.
Vouwtent 3x3 Octa Go met eenzijdige bedrukking: Polyester - SET
t
In 1865, at Cardiff Castle in Wales, he began to interpret medieval architecture with merry and decorative freedom. The interiors of this building and of Castell Coch, built 10 years later, are a riot of decoration.
slayyyy - Castell Coch is perhaps the most riotous in its design
But Gothic was to be most widely used—and even exploited—for church architecture, not because it was thought more appropriate than Classical architecture but rather because it was cheaper
SLAYYYY - this could be one reason why we see a gothic revival in church buildinggs?? and we see the church building act providing moneys for it
La transgression apparaît quand ce code est dépassé.
On peut se demander si la transgression est un problème ou si c'est normale de la culture gamer ?
les “vannes” et certaines insultes peuvent être interprétées comme des marqueurs de proximité, à condition de respecter le degré de familiarité.
Je trouve aussi que l’humour agressif peut renforcer la cohésion quand il existe déjà une familiarité entre les membres.
Open Dataspace Lab, confusing term for max EU subsidies? By RWS / IenW this annotated opendataspacelab.eu but it falls back to pontus-x.eu
The region’s dense network of short-haul routes, typically under 100 miles, aligns closely with the operational range and efficiency profile of today’s electric aircraft, making Scotland a natural first market for commercial electric flight at scale.
not sure then what 'scale' means, other than perhaps regular operational usage. 160km short haul flights mentioned as current range of e-planes, and that Scotland fits that well.
Scotland’s geography makes it one of the most compelling proving grounds for electric aviation anywhere in the world. With more than 90 inhabited islands and communities in the Highlands separated by hundreds of miles of terrain that road and rail cannot bridge, air connectivity is not a convenience- it is critical infrastructure.
In Europe yes, but there must be many other places where the same is true.
Electric aviation pilot in Scotland successful. Royal Mail used electric planes for mail delivery to the many Scottish islands.
八成是错的。粘贴全文，要求总结，拿到一段流畅的摘要，合上标签页，以为搞定了。
沈向洋论文10问
Richard hamming you and your research
bibliographie
majuscule
untitled
il manque la description, les mots clés...
règles juridiques et éthiques
structure : à l'oral c'est mieux de lire d'abord éthique et ensuite juridique, sinon deux "é" se suivent ("et éthiques"
pour expliquer et guider le patient
structure : "pour lui expliquer et le guider" répétition "patient" en fin de phrase deux fois d'affilée
“le numérique en santé et le rôle du patient” de Lina Williatte,
media : j'aurai mis un lien vers l'article au lieu de l'écrire
Comme le souligne l’article de Dominique Dupagne consacré à la e-santé,
media : j'aurai mis le lien de l'article
des décisions mauvaises
structure : "de mauvaises décisions"
«la «
" en trop
il est également selon l’article de Lina Williatte
structure : "selon l'article de...il est..."
Le développement de la e-santé, qui correspond à l’utilisation des technologies numériques dans le domaine médical, transforme ainsi la manière dont les patients accèdent aux soins et gèrent leur santé
structure : commencer la phrase pas "Selon..., le développement de le e-santé correspond à..."
Ces informations, collectées par des applications et des objets connectés, transforme la manière dont les individus suivent leur santé et interagissent avec le système médical et constituent peu à peu une identité numérique de santé, c’est-à-dire un ensemble d’information numérique lié à la santé et au suivi médical d’une personne.
structure : couper la phrase en 2. "Ces informations...". "Elles constituent..." orthographe : transforme > tranforment
Chaque jour
test
identité numérique
test
Car écrire reste l’essentiel. Le reste est une mise en scène.
Conclusion très efficace et cohérente avec l’ensemble de l’article
Ces acteurs jouent en réalité un rôle que les plateformes ne peuvent pas remplir c’est à dire celui de la légitimité symbolique.
Point très pertinent : distinction claire entre visibilité et légitimité
Les réseaux sociaux fonctionnent davantage comme un amplificateur que comme un véritable tremplin.
Certains auteurs peuvent émerger grâce aux réseaux sociaux (même si ça arriver rarement)
les frontières entre l’auteur et son public se sont considérablement réduites.
Analyse pertinente et bien introduite
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