Robert Mercer, Renaissance Tech, Supercomputers, DoE, Data Warehouses, Project Looking Glass, etc.
>>2767526 >>2767604 >>2767660 >>2767663 >>2767730 >>2766759
Thank you co-diggers >>2767295 , >>2767107 , >>2766812
Reposting search terms received from informant in pb night of August 27, 2018.
I presume the "non-text" strings may be cryptographic authentications. They don't resolve in a search engine (not that I expected they would).
—–0 0 0 0 0 0 0 0 0 0—–
Anonymous 08/27/18 (Mon) 21:37:32 099e68 (1) No.2761603 >>2761805 (You)
ROBERT MERCER.
FOLLOW.
3S<r5_=;.U[06|P<xCSgf.^$.nw5wt<E27L:/ugL+LMg[DUbZbS$4"p+s?:RENAISSANCE TECH. MERCER. BANNON. THEIL. BTC. COINBASE. FOLLOW. DoE TIE IN. FIND. [7] ^]I%/<NS?jK:gQ'1:1]IJ-u$x^~a-1,1/k2h7saj!72xSp:Q1gGxyx;tTvI+r!'
https:// en.wikipedia.org/wiki/Renaissance_Technologies
RENAISSANCE TECH.
MERCER.
BANNON.
THEIL.
BTC.
COINBASE.
FOLLOW.
DoE TIE IN.
FIND.
[7]
^]I%/<NS?jK:gQ'1:1]IJ-u$x^~a-1,1/k2h7saj!72xSp:Q1gGxyx;tTvI+r!'
https:// en.wikipedia.org/wiki/Renaissance_Technologies
MEDALLION FUND.
FOLLOW.
BRADLEY BIRKENFELD.
UBS.
KEY.
ISIS.
PROJECT CASSANDRA
fall of cassandra 2B6DAE482AEDE5BAC99B7D47ABDB3
xX!dx^[FSomOsAQ5sR(+c1-.^g#X9iW!|w'kZP;:^pk$sH?34f5V%]j,@ngsq;Z
SCOTT BENNETT.
YOSSI COHEN.
FOLLOW.
WEINSTEIN.
COINCIDENCE?
m>f*[z^/}lE`|W?@Xi8F{_ayJ=_XNjebQK?yRJ]jqG6FK)C7QPJ=wo'%Vf+y|dB
https:// github.com/ytisf/theZoo
SPECTRE, MELTDOWN AND ZUES ADDED…..
SHOVEL WILL GET HEAVY.
CARRY IT.
GODBLESS.
Manifold Learning
One of the perennial quant guessing games is speculating on RenTech (e.g. see amusing 5-year NP thread), particularly given the fascinating background of Jim Simons (see his arXiv for recent work on differential cohomology). Ignoring public commentary, whose veracity is obviously questionable, careful consideration of historical hiring trends and corresponding employee backgrounds are suggestive. While such speculation is amusing, potential relevance arises in assisting in filtering the exploration of research.
Specifically, several themes are consistent:
Infrastructure / execution: computer scientists speaks to the mundane realities of large-scale offline and online data management, risk management, multi-venue execution, and the usual collection of optimal execution concerns (particularly relevant for liquidity providing and statarb)
Applied mathematics: “natural scientists”, with an emphasis on modern physics (much of which is built upon differential geometry and statistical mechanics), seems reasonable given heavy mathematical and statistical modeling
High dimensionality: analysis and signal generation from high-dimensional spaces, which seems reasonable given many trading problems can elegantly be formulated in such a context; plus a deep well exists of both pure and applied math built by academia over the past 20 years; further, this makes obvious sense given Jim’s academic background (e.g. see Chern-Simons)
Mixing models: RenTech grew through a combination of small acquisitions and internal development, suggesting “the predictive model” (historically referred to as “Basic System”) is not one but rather a collection of heterogeneous models which are dynamically overlaid and mixed; seems reasonable, given market regimes and consistent Medallion performance over the past 20 years
Computational linguistics / NLP: numerous high-profile folks originated from speech recognition, of which numerous advancements over the past 30 years are based upon applied signal processingand statistical information theory (e.g.Mathematics of Statistical Machine Translation, by Brown, Pietra, and Mercer); a particularly consistent theme is HMM (going back to the Dragon system by Baker in 1975), which naturally support mixing via HHMM, and causal filtering(see also Berlekamp, who worked with Kelly)
TY SIR.
JOINING THIS SHIT SHOW IS LIKE KNOWING WHO ONE THE BIGGEST PIECE OF SHIT TO MAKE MONEY CONTEST.
GUESS WHAT? i HELPRED.
FUCK IT ALL.
RESTORE THE NORMAL SHIT.
OK FOR REAL. OUT.
jw5^3jK1:FXdyr}sUR2!IsMnRj"4!R>i8u$+_!|A0+6(ED5s]Q<;0KS)ie[qHHs
_________
Sorry for the lousy formatting, but I don't want to risk deleting a meaningful character to go through and delete his newlines.
repost from >>2761603 (pb)
Part 1 of my further dig into Robert Mercer and Renaissance Technologies (originally begun in the DoE Supercomputers Deep Dig, months ago). Other names will become involved as the dig progresses.
Not sure where we're going with this… I suspect it will get into how petabyte-size data warehouses and advanced computational algorithms are able to successfully predict not only financial markets, but trends and turning points in human history. It will link to the U.S. Department of Energy (DoE). I suspect the reason this was dropped is to reveal to us something about the DoE's predictive capacity (undoubtedly classified), by revealing something about a civilian-developed version of such technology.
Here's the first little bit of the dig.
We're not looking at specific hardware vendors and their (publicly-known) products, except to characterize their capabilities versus our estimate of the requirements, and develop a projection of what may be feasible. If we can accomplish that, from there we may want to extrapolate beyond, to not-publicly-known technologies and capabilities… That's a few steps ahead of where we are.
We are looking at multiple factors (technologies), all of which are required to pull off predictive analytics at the scale we think we're talking about.
-
hardware technologies (storage, SAN, fast CPUs, CPU clustering/supercomputers, RAM, data transfer technologies like fiber channel, high-end packet switches, other I/O technologies, quantum computers, …)
-
software technologies, algorithms, implementations that can run on very large clusters and/or supercomputers, data mining, data visualization, data analytics…
-
access to the actual data sources, data converters and transcoders, categorization of the data, storage formats…
…
That's just a rough list and undoubtedly incomplete.
Attached: Feb 2018 (incomplete) dig on Exascale Computing Project
I suggest working down the list of keywords provided by the 8/27 informant first.