open innovation

Yesterday, Allison Randal gave a great lecture on open innovation and open source and collaboration for the Turing Institute - the audience asked some really interesting questions (e.g. on open data; and on applying the model of open source to medicine - e.g. drugs - and on how much open source works across north/south divide in the world)....

I didn't want to take time, so i'll add my questions here:

1/ as well as open source software, we're seeing open hardware - not just processors (risc V) but peripherals, but also affordable 3D printing means even things like electric guitars - so the maker community that does a lot of this stuff (c.f. Cory Doctorow's books:) maybe exemplify the open collaborative ecosystems even more than coders, no? and they get to have a really good story about sustainability (repairing stuff is so much better than replacement.

2/ Sustainability - so machine learning (particularly deep learning) appears to be badly unsustainable in terms of compute resource training takes - this argues strongly for sharing trained classifiers - perhaps a carbon tax on neural networks could be turned into an incentive (carbon trading for AIs)

3/ some open ideas have horrible consequences - simple things like pagerank (which made google's search very hard to game compared to predecessors like Altavista) led to clickthrough which led to two-sided markets which led to surveillance capitalism. H-Index, which is supposed to replace publish-or-perish with citation count weight as a measure of quality, just leads to citation gaming. And so on - can we encourage replacements from the open source community, please, asap.

4/ Open source also depends somewhat on freedom of movement of people between different organisations - indeed, California mandated this right in law, stopping "golden handcuff" employment contracts.  In the Cambridge ecosystem, i know people that have moved from microsoft to oracle to amazon (and even back) to work on the next thing. In the US, famously, people went from Cisco to Juniper to Cisco, as innovation moved around - this is clearly a Good Thing - perhaps folks who are working on Brexit could learn something from this (although they seem impervious to learning anything based on evidence).

5/ Most of the talk was on details of uptake of the culture and forms by industry - of course, the Turing Institute (and its member universities) are not-for-profit - so the culture is probably adopted in a slightly different light - what are the appropriate incentive forms for academia to adopt openness (aside from just being told to by our funding agencies:-) ?

rumours of his death are accurately predictions...

Back in the day, legend has it, a newspaper published an obituary of Mark Twain, while he was travelling in England, and he famously quipped "The rumours of my death have been greatly exaggerated".

What if someone built an AI (ok, ok, machine learning algorithm), that could precisely predict the day of your death; for everyone; to the day. with only the occasional false positive or false negative (for example, due to sudden accident, or sudden unexpected advance in treatment techniques)?

How fanciful is this? 

if you look at actuarial tables, and the error margins, you'd be surprised how accurately they describe expected longevity already, and note that these are typically compiled for purposes like life insurance (i.e. to give risk&therefore  premium rates), and are not using all the detail that they might have (since the risk can be spread over broad groups, even if more precise predictions could be made). When looking after elderly relatives in recent years, these tables have been very useful for planning care costs and have proved (somewhat alarmingly) accurate. 

It is also well known that as you get older, especially in middle age, details of life style+health conditions start to provide ever more precise predictors of how long you will last. However, to date, these systems only make use of a relatively small fraction of personal health data about you. What if we use it all?

Recent work in the Turing looked at predicting when someone would have a subsequent hospital appointment after a visit to A&E (or respectively for elective). Other work looked at morality in certain wards and (more happily) at the predictors of who to release to go home and when with best chances of recovery. These systems have impressive performance (e.g. 98% to the day in some cases).

So imagine at some point (for the sake of argument, lets say if you make it to "majority"/adulthood), it is revealed what date you will live til? What would that do to society? Economics? What about ethics?

I can imagine people "cheating death" the wrong way.
No more health insurance (since there's certainty).
How might people plan funerals?
Many, many perverse incentives, unintended consequences and downright weird stuff.

Much harder than just having slightly better automatic language tools that might make better fake news, but also, much more likely to appear soon.

The Center for Mathematical Seances

The Center for Mathematical Seances (CMS), was not designed along the lines of Teletubby land, contrary to popular myth. In fact, it was flown here on Mistletoes by the Master of Duality College from the Miskatonic University in Arkham as a gift, when she realized that Cambridge could no longer afford architects, let alone builders. Of course, due to its unique Nomenklature, the Center (or Centre, which is of course near the edge of Cambridge) is able to operate at very reduced academic salaries, since many of its faculty have been, not to mince words, dead for some time. This hs caused no end of problems with the REF, since outputs cannot be returned through research fish or ORCID, for deceased, and much of the original work was done too many centuries earlier to be allowed for impact case studies, Fermat's first posthumous theorem being a standout example, and Turing's work on quantum ghosting with Paul Dirac and Paul Wittgenstein, which will haunt the UKRI policy makers for decades, since it has proved to have so many applications and saved the British economy from collapse after brexit, for example allowing true precognitive behavioural economic models of trade to be built with genuine precision.

clock synchronisation in data centers - why not just use GPS?

in a recent discussion about accurate one-way latency measurements in data centers, it was asked "why not use GPS?" (instead of PTP for example) - the rationale being every smart phone has GPS in so it must be cheap...

at first blush, this sounds plausible, given the pervasiveness of GPS (G=Global) and decent accuracy, so I started to come up with a (long) list of reasons why it isn't (plausible) - starting from

1. you're indoors.
no reception -
ok, so a) run an antennae from the roof of the building down to each rack, and re-dist across the systems in the rack
or b) have one receiver and re-broadcast the radio signal in the server rooms and have an antennae on every rack or system

2. distributed antennae
a) need to calibrate the latency of the signal over the roof to each system + significant wiring cost
b) re-broadcast could cause significant interference, plus the racks themselves would cause massive multi-path problems - since they're stationary could obviously calibrate for that....

note you need to have sight of enough satellites at any given time to get reliable signal, plus they are not actually 100% reliable anyhow....

3. What about re-distributing the GPS received data in packets (ideally as part of ethernet pre-amble)
So you still now have all the packet delay variance/jitter you had to solve with PTP (or NTP in the old days) and estimating that was the whole point of PTP - GPS is just one source - just have a local accurate master clock on some systems in the data center is fine and dandy

4. cost
phone GPS is actually Assisted GPS usually and not very accurate - indeed, even outdoors, mult-path (reflections off buildings) disrupts things sufficiently that most navigation systems resort to accelerometers, gyros and maps to validate (or rule out) received clock/location data. Also the signals need to be cross checked against Ephemeris data, which is 50k of info about where the satellites orbits take them. real precision GPS (satnav in planes/boats) is not cheap in fact.

that'll do for now