87 Matching Annotations
  1. Aug 2020
    1. Roles for participants in real-time meetings

      We tend to refer to these as "Rheingoldian roles" since Howard Rheingold introduced them in his HRU courses (and maybe in earlier courses as well).

    1. based on its expected utility

      ... Now, don't we also have considerable uncertainty about the actual utilities of actions?

    2. calibrate

      Is this ever defined?

    3. how to interact with the latent phenomenon encompassed within the true data generating process

      This looks a lot like the set-up in scattering theory.

    4. Regardless of its interpretation we presume that this variation is sufficiently regular that, while an observational process cannot be quantified by any single observation, it can be quantified with a distribution of observations.

      A key assumption, but this does constrain the setting quite a bit. For example, imagine a delicate ancient manuscript that could be read 3 times only before it crumbles to dust.

    5. aleatoric randomness

      Just for the record: aleatory processes are related to games (like dice games). That's different from 'stochastic' processes.

    6. probe

      Cameron suggests to think about this in relation to "projection"

      In category theory, the above notion of cartesian product of sets can be generalized to arbitrary categories. The product of some objects has a canonical projection morphism to each factor. This projection will take many forms in different categories. The projection from the Cartesian product of sets, the product topology of topological spaces (which is always surjective and open), or from the direct product of groups, etc. Although these morphisms are often epimorphisms and even surjective, they do not have to be.

    7. formalize learning and decision making

      This is the sort of thing that we're interested in studying, both in research on collective intelligence and artificial intelligence.

    8. a familiarity of probability theory at the level introduced in my probability theory and conditional probability theory case studies

      Foundational topics.

    9. presumes the existence of a true data generating process

      I guess this relates to philosophical realism?

    10. however, even the most rigorous utility assignments will depend on circumstances we do not know with perfect certainty

      Interesting to wonder why this is! I am reminded of the idea (which I think is incorrect) that generating the maximum number of possible answers will lead to more creative outcomes.

    11. utility

      Related to reinforcement learning, this can create ordering on the actions.

  2. May 2020
    1. To double down on this agenda our aim will be to build the company around open source software.

      From the RM Unger whitepaper:

      "The more one knows and discovers, the easier it is to make the next discovery. If the process of production can be organised on a model of scientific inquiry and experimentalism, innovation can stop being episodic and become permanent. Continuous innovation undermines the basis for the constraint of diminishing marginal returns."

    1. knowledge economy

      Worth having a look at the whitepaper produced by R.M. Unger for Nesta, "Imagination unleashed: Democratising the knowledge economy"

  3. Apr 2020
    1. Dame Wendy Hall and Jérôme Pesenti conclude that “AI could positively affect every area of STEM education”

      I worked briefly in the SOCIAM consortium with Dame Wendy Hall. I wonder if some of the stakeholders in the AI report mentioned here could be approached to ask how they are sourcing technical talent. Benevolent AI would be one interesting possibility.

      A first step could be to follow up with the Southampton folk about the Innovate UK proposal.

    2. [33] “Uncovering the Dynamics of Crowdlearning and the Value of Knowledge”. Proc. Tenth ACM International Conference on Web Search and Data Mining. 2017 [34] “Emergent Complexity via Multi-Agent Competition”. arXiv preprint arXiv:1710.03748, 2017

      These look like particularly worthwhile references.

    3. Universities UK

      Universities are a primary incumbent for any kind of skill sourcing! https://www.universitiesuk.ac.uk/

    4. Wolfram Research

      Another possible speculative angle. They will have a broad interest in sourcing technical talent, not just programmers but also mathematicians.

    5. developing new business models for education using open source software

      London-based experts in this aspect of things include Canonical.

    6. Elsevier

      It's a bit of a strange angle but at the level of a brainstorm we could look at how publishers source technical talent. They are probably not the biggest employer of programmers out there, but it would be a non-trivial number.

    7. Building our Industrial Strategy

      "The aim of the Industrial Strategy is to boost productivity by backing businesses to create good jobs and increase the earning power of people throughout the UK with investment in skills, industries and infrastructure."

    8. IBM

      I have a couple of rather remote links to people who work at IBM, I wonder how they go about sourcing talent there.

    1. Simulating Developer Communities

      I found some earlier work, though it's not very fine grained.

      • Modeling the Free/Open Source Software Community: A Quantitative Investigation


      • Agent-based Simulation of Open Source Software Evolution
    1. A short bio and link to LinkedIn would be perfect.

      A link to Github would perhaps be more relevant for many developers. Indeed, wouldn't a good starting place be to crawl Github and try to recruit people whose profiles look suitable?

    1. Practice meditation. It occupies only ten minutes of my day

      Some text relating that back to the kinds of reflection that you do when you process your task list could be thought-provoking. I'd say that each of the little actions with your task list is a kind of mini-meditation.

      Since you're interested in meditation I will take a moment to advertise a book I absolutely love, called After Buddhism. It was probably the most clarifying book I read on the topic after nibbling around the periphery for 10 years or more.

    2. 5. Matthew Walker. 2018. Why we sleep. Scribner.

      An excellent book!

    3. try squeeze

      try to squeeze

    4. coffee

      Well, if I maximized my intake of coffee beyond a couple of cups a day, I might not get any sleep!

    5. It is important to understand that your seemingly perfect colleagues are anything but, and often struggle with the very same issues.

      I think this is a good insight, and that attention to how people think about things, how they get things done, can further bring home the notion that we're all just human. Some people may have more effective "tools" of one kind or another but mostly these different toolsets are learnable.

    6. I take notes in the simple, yet expressive markdown format, which is both expressive and very simple.

      The text here is redundant and yet also repetitive.

    7. Take notes of meetings

      Completely technical point here: if you have a look in the sources of sub-pages on hyperreal.enterprises you'll see the Javascript plugin that I use to create anchors for linking to sections. Maybe useful.

    8. polices

      Just etymologically, the notion of a "policing" function is linked to the notion of a 'polis' or communal inhabitation. It seems like with these tools you are in a way multiplexing your mindset so that you can explicitly look at things from different perspectives. Again, the notion of a shared language is important: there is a difference between the 'polis' and a simple conurbation.

    9. Taking a look at your work log makes it easier to realise when you’re off track

      I've been thinking about the degree to which this sort of feedback could be automated -- but reflecting on some of the earlier comments, I think it's also (and maybe even more) beneficial to keep track of the things that are going well, and understand those better so that you can play to your strengths.

      For example, the time spent exploring infeasible ideas might not be "wasted", e.g., maybe they are only infeasible now but could become feasible later. Thinking of this as "wasted" time ignores the long-term learning and the possibility of recontextualisation later on. By the same token, if you could detect early on when you were potentially about to go down a rabbit hole, maybe there is some information that you could bring in to the current context that could afford a speedy resolution (if that is what was truly needed). This seems to be less about time management and more about understanding the problem spaces you are exploring and the "niches" that you are creating.

    10. If I see one or two low-progress days in a row, I realise it’s time to make a conscious effort to improve my productivity.

      For me I think this could be a sign that I was getting sick and needed to rest!

    11. Right after I complete a task worth writing down, I spend approximately five seconds adding it to my log and then move on.

      The benefits of this way of working could be partly due to positive psychology: you acknowledge things you have been successful at, and this gives you a boost.

    12. I am a big advocate of keeping a log of what I have accomplished throughout the day.

      Given how much data we produce, there already is a log. E.g., consider git commits as a source of data as well as text messages or emails. Pulling these things into a unified tracker would be a nice thing to automate.

    13. Over time, my estimates became closer and closer to how much time I really needed–minus the occasional outlier, obviously.

      I ran into huge conflicts with my boss when, in my second postdoc, I went over my initial planned timeline, and didn't deliver quite what she had in mind. The problem there wasn't necessarily my time management (although she claimed it was), but also the degree to which the project was well specified (something that she had some responsibility for). I imagine part of making good effort estimates is a good understanding of the "domain" you are working in and a reasonable way to break tasks down into subtasks. If there are multiple stakeholders (as in most workplace situations) it seems important for all of these stakeholders to have at least some grasp of the common "language" describing the domain. Without these kinds of resources, I think there's no such thing as good time management (unless time is spent producing them!).

    14. I actually am productive when I finish a handful of well-defined tasks throughout the day.

      This sounds like the epitome of self-management thinking.

      I'm also interested in productivity, but I have some doubts about how that relates to self-management. This is complex and I don't know if there are any "right answers" but, coming back to Banathy for example, it quite depends on what you're aiming to produce, doesn't it?

      At the top of this page of notes, I included a scan of a "spiral" process from Banathy, where he talks about all the different levels of a system that need to be produced to bring about major change. Self-management might be the answer at some but not all of these stages.

    15. Tracking my time helps me stay on track.

      Do you think that this is relevant at a certain level of granularity? For example, if you put "scratch nose" or "scratch head" every time you scratched an itch, that would be time consuming and probably a non-useful overhead because the information you logged would not be actionable.

    16. I open the Time Tracker tool and jot down what I’m going to work on next.

      At one point I tried to set up a stock tool that would automatically record how I was spending time, but I didn't use it or its reporting functions very much. It would be interesting to see how the output of Time Tracker corresponds to your plan for the day.

    17. watching obscure YouTube video

      There's a book called Wasting Time on the Internet that might be relevant here.

    18. Having a daily plan in front of my nose serves as a reminder that the perfect is the enemy of the good

      The "daily plan" might also include (or imply) success criteria, so, giving some pointers about when something is good enough to ship.

      Yes, I suppose I do wonder how much the plan would impede creativity, even while it frees cognitive load. I saw an interview with a Shaolin guy where he said that freedom only comes from discipline. But what about serendipitous unplanned encounters? That's another category?

    19. By spending a few minutes planning your day, you reduce your cognitive load throughout the day.

      This seems like good advice and could potentially be set in bold face.

    20. you notice that the function that contains your bug has poor documentation. So you spend a moment updating the documentation.

      Funny! Yes this sort of thing has happened to me in the past, especially when I was focusing on self-directed projects. I think this is one reason why collaborative projects can sometimse go better, and why in collaborations we have things like standups. It's also true that teams can waste time in much the same way, but perhaps it's slightly less likely?

      At a higher level of abstraction, I think it is a shame that PhD researchers (your target audience) are so often stuck doing "individual" research, when "collaborative" research can be much more powerful and effective. This doesn't invalidate the need/use for individually tailored methods of organisation, but sometimes the main limiting factor is not having people to talk to. Vide, you asked for comments on Twitter presumably because other people would have ideas on this material that you didn't have.

    21. When I finish a task, I move it from my todo list to my work log, which is in the same file, so it’s a matter of literal seconds

      This seems to replicate Org Mode's mode change and archiving actions.

    22. freeing you of the cognitive load of having to remember the task.

      For me I have made many attempts to use Org Mode as intended (as a task tracker) and it never quite clicks. I'm not sure where it breaks down. The system has a bunch of complex options that need to be configured. At present the only task tracking tool that kind of works for me is Google Calendar, since it is linked to events that will happen whether or not I show up (and it is much better if I do remember to look at it and show up). Org Mode's agenda could be used similarly but since my colleagues use Google Calendar, that's preferable. I don't think Org Mode's google calendar integration is that robust at the moment, but I could be wrong.

    23. For example, configure a keyboard shortcut that opens your todo file.

      Here a sidebar or endnote that shows what this might mean in different organisational systems could be helpful. For example, in C-c a a opens the agenda in Org Mode, C-c n f gives a list of files to open in Org Roam... I'm sure there are ways to do it within a windowing system too (e.g., a key command that will run inside Ubuntu, hit emacsclient and open a new file in Org Roam sounds nice, maybe a good exercise for me for later today!)

    24. tools

      "Task tracking tools" ?

    25. Once I transitioned from my postdoc into the “real world”, I quickly realised that this had to change.

      The book has begun kind of in media res so by this point the reader does not know who you are or why they should take your word for it that the ideas you are developing here are bona fide best practices. It might be nice to have a paragraph earlier on that says who you are and why your views should be given consideration!

    26. Atomic Habits [1], James Clear

      Might be nice to make full use of the Tufte style here and put the ref in the margin!

    27. After all, research is a marathon and not a sprint.

      So far it is implicit, but many people don't go on to academic careers in research. Nevertheless, things like "working in a startup" are also described as marathons! You could potentially widen out your "net" a little bit and point out that research skills are relevant even for people who don't have an academic career. Hopefully that's obvious but it may not be!

    28. I spell out aspects of research that don’t see much elaboration elsewhere

      It might be good to have a set of pointers to books on other aspects of the "new graduate student" journey, of which there are many.

    29. the reputation of conferences

      And even the relative importance of journal papers! During my first postdoc I just did what my line manager asked us to do, and wrote a bunch of conference papers (which was his preference). I didn't realise that these papers had effectively no relevance for the REF.

    30. reading hundreds of papers

      Earlier this week, someone pointed me to org-roam, which is a clone of Roam Research, which itself looks like a clone of Notion. I started using org-roam and it seems pretty natural. There is an org-roam-bibtex package as well, but I haven't got that set up yet.

      Of course, Org mode comes with the learning curve for Emacs too, so it's not clear this solves the problem you were talking about in this paragraph.

    31. new graduate students in computer systems.

      Oh, when I clicked through from Twitter I thought you were talking about "systems" studies in general, not just with computers (e.g., in the school of Banathy). Well, computer systems are good too! But of course they bring a whole set of further problems -- writing and maintaining code. Golly!

    32. research


    33. The resulting research paper is originally called paper.doc, then paper-new.doc, paper-new-2.doc, paper-final.doc, and eventually paper-final-FINAL.doc

      Well, I tend to write academic papers in LaTeX, and often do the collaborative ones on Overleaf, so versioning is taken care of by Git.

      But not all of my collaborators are academics, and we've used Google Docs, Github Pages, hypothes.is, Etherpad, HackMD, Floobits, wikis both classic and modern... there is a real chance of exhaustion due to switching between all of these different formats, but none of them is 100% satisfactory.

    1. The real test of meaningfulness will come in the use of the extracted information, via evaluation of agent performance on both synthetic tasks and human-in-the-loop applications.

      This sentence kicks off a paragraph with a grab-bag of different methods: all interesting, but from different domains. As such they seem likely to confuse the reader. Don't get me wrong, TPGs, PP/AI, and IAD are all really cool, but their application here remains speculative! The actual problem being addressed exists at a higher level of abstraction.

    2. “complex feed-backs present between individuals and their environments”

      Clearly this wasn't a watertight case for getting the job. Nevertheless I think there are interesting connections between this way of thinking and the Andy Clark way of thinking about niche construction.

    3. Helena Miton’s work on “the role of institutions in generating and transmitting technical knowledge and practices” would find concrete analogues within the work I have proposed.

      I wonder if we could set up an interview to talk about this!

    4. koans

      As people learn programming, what else do they need besides koans?

    5. In order for agents to explore this domain, they will need stepping stones, starting from the simplest possible tasks and growing in complexity.

      This is a worthwhile principle to keep in mind.

    1. We're beginning by marking up these old proposals with new commentary.

      Annotations are via the Hypothes.is sidebar. Anyone is welcome to add them!

    1. rationale

      Instead of a Problem, Solution, Rationale triple, the Y Combinator folks talk about a Problem, Solution, Insight triple. The insight concerns unfair advantages related to growth. It could come from across several "suits": Founders, Market, Product, Acquisition, and Monopoly.

      Whereas the rationale concerns repeatable patterns, startup ideas concern more time-, location- and context-specific opportunities. So, OK, there are some differences: but it seems to me that the common features between these two design languages is worth keeping in mind!

      The breakdown across different "suits" reminds me also of the multiple capitals theory used by XinX.

    2. We can build computational models of social processes and research heuristics using a formal variant of the design pattern methodology

      What I think I have only just realised today is that the process based material could be combined with Monocl and properly formalised inside of category theory.

    3. The latter will draw on direct observation, interviews, “instrumentation” of the social media accounts of researchers who agree to participate in the study, and software integration work as relevant.

      This epistemic aspect is preserved in many of the proposals and seems to be a key aspect of the offering.

    4. enrich the inquiry with both technical and “common sense” features

      I think the "impact" again falls flat in this paragraph.

      The last bit here harkens back to a disagreement that I had with Bob Boyer at UT Austin circa 2003. I felt it would be worthwhile to model mathematics in more common sense terms, but he did not see the value of that pursuit and wanted me to work on a project more oriented towards theorem proving. But all of the interest (and difficulty) of that proposal is implicit here.

      Naturally people will be interested in the adventure but once people begin to grasp the technical ideas they ask "Is it possible? What's really required? What are the stepping stones or proof points?"

    5. a content-oriented model of technical domains, which will be directly useful for education and research

      It's as if the big ideas here are buried (perhaps because I didn't want to be too bold, but in that case it's strange to write a paragraph about 'importance')! To be clear, if it actually worked this idea would transform the way we do knowledge work. That's a bit more bold! The 2019 whitepaper "Imagination Unleashed: Democratising the Knowledge Economy" might say some of this better than I can, even now! (I have only had a look so far.)

    6. The next step in understanding the relationship between content and process could be made using simulation studies

      This should probably have been pulled to the top of the document, since it is an overall thesis for the proposal.

    7. One example application is a recommender system that shows questions and answers from Stack Exchange to a programmer at work.

      I think this is referring "Seahawk: Stack Overflow in the IDE" by Luca Ponzanelli et al. (https://lucaponzanelli.gitlab.io/).

    8. The people who visit the library can teach you where the data that surrounds you comes from.

      This is basically the thesis statement of this paragraph, embedded here in the middle.

    9. ContentMine

      http://contentmine.org/ "We offer a broad range of text mining services for small, medium size and large projects. Our mission is to give researchers an easy-to-use open source text mining code allowing them to find, download, analyse and extract knowledge from academic papers."

    1. Admas Kanyagia

      It would be great to talk with her about the project of building a 'talent incubator' for engineers!

  4. Aug 2018
    1. # pdfnup-2x4 slides.pdf '1-8' | only pages 1 to 8

      This is a way to add comments on a line.

    2. This is a way to add comments on a file

  5. Mar 2017
    1. What the statement should say is that if HHH is a proper finite index subset of GGG then G≠⋃g∈GgHg−1G≠⋃g∈GgHg−1G\ne\bigcup_{g\in G}gHg^{-1}


    2. Does this remain true for the infinite case also?

      The main Question.

  6. Jan 2016
  7. Dec 2015

      This underlining should be longer!

    1. Simulation comes into its own when the phenomena to be studied is either not directly accessible or difficult to observe directly.

      But it also seems to be a useful method when the phenomena is observable, but its workings are not understood. The point is that simulation gives hypotheses about what's going on inside a black box, I suppose.

  8. Nov 2015
    1. Their trust in writing, produced by external characters which are no part of themselves, will discourage the use of their own memory within them.

      How should we respond to this criticism, considering the ubiquity of writing these days?

    1. Motivation

      Maybe this needs a short section intro, since, actually, the topic under discussion here is Chapter Summaries, not Motivation.

    1. Technology Features/Functions

      This could be a good place to add links to interesting websites @daytripper

  9. Aug 2015
    1. We want to kick things off with a candid confession: we’re not going to pretend that this book is perfect.

      I'm interested in understanding how hypothes.is handles changing content. I made a comment on an earlier version of this page, and the text I highlighted no longer exists. But what happens if the text only moves around? ... OK, here's the technical description: https://hypothes.is/blog/fuzzy-anchoring/

      Interesting. I might like to be able to see a pool of "orphaned" annotations, like the one I made before, which don't reattach anywhere. But current behavior is certainly OK for now!

  10. Jul 2015
    1. we think will be helpful as you get started.

      It's worth pointing out the ways in which the handbook is not perfect. I've added some discussion about that in https://github.com/Peeragogy/Peeragogy.github.io/issues/1