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Members: Football analysis for December 10-11, 2022
By Dr. Ed Feng Leave a Comment
This content is for members only
Predictions for the Masters, 2022
You want to bet a Masters outright. You check out a site like Data Golf and get their win probability for each golfer. Compare it to the markets and make a bet.
Unfortunately, most of these predictions won't show any value. For example, Xander Schauffele has a 3.0% chance to win, which doesn't suggest value at +2400 (4% break even win probability).
To find value, you have to go beyond the predictions. Data Golf uses data on each and every shot to make predictions. Perhaps some of these shots have more randomness than others, and this presents an advantage.
To make a comparison to a different sport, consider college basketball. As I discussed in March, three point shooting has a large component of randomness. Teams that have made a high rate of threes should expect regression to the mean.
Brandon Gdula of numberFire found a similar result for putting. To understand his results, consider strokes gained, a metric for how well a golfer performs compared to the tour average. For example, consider a putt within five feet, a shot made 97% of the time. If a golfer sinks this putt, then he gains 0.03 strokes (one minus the tour average of 0.97). Missing this putt results in -0.97 strokes gained.
Brandon found that strokes gained for short putts explains most of the variance for strokes gained on all putts. To be specific, let's look at the R-squared value. Strokes gained for putts of 15 feet or less explained 80.5% of the strokes gained overall for putting.
This implies a huge random component for long putts. Brandon suggests looking at the 73% of putts from 15 feet or less in getting a more accurate assessment of putting.
To apply this idea to the Masters, consider Xander Schauffele. Through March 18th, Brandon pulled data for players with at least 100 rounds of strokes gained data. Overall, Schauffele was 15th in strokes gained putting.
However, when only using putts from within 15 feet, Schauffele ranks first overall. He is great on putts that are predictive, and he has had some bad luck on longer putts that pulls down his overall putting strokes gained.
This analysis will be far from perfect. In Brandon's article, he mentioned that he didn't find putting at any distance to be predictive over half year intervals. There is a ton of randomness in putting.
However, Schauffele is a great all around golfer who finished 3rd in last year's Masters. The putting data suggests that the numbers might be low on him, and there is value in betting Schauffele to win at +2400.
Here are golf and Masters resources to check out:
The putting study by Brandon Gdula
Masters predictions by Brandon Gdula
Data Golf. They put most of their predictions behind a pay wall but they also have many free resources.
Sports betting with a PhD edge
This article was sent to The Power Rank's email newsletter, a free service that strives to be:
While the primary focus is NFL and college football, the content covers golf, the NFL draft and the NBA during the off season.
7-Nugget Saturday, March 12, 2022
Your weekly dose of sports betting tips and news, every Saturday morning at 10am Eastern.
College basketball predictions – These predictions come from The Power Rank's member numbers that combine a number of powerful predictors into an ensemble. These conference tournament games are all on neutral sites.
Duke will beat Virginia Tech by 7.0 points – The markets have favored Duke more aggressively than my numbers. However, as of Saturday morning, they have Duke -5.5. Either the markets move strongly in Duke's favor or they have lost some faith in this team after not looking sharp in their two ACC tournament games.
Iowa will beat Indiana by 3.7 points – The Hoosiers have won both of their Big Ten tournament games by five or fewer points. They had a regular season Big Ten record of 2-5 in these type of close games. The markets have Iowa -6.
Arizona will beat UCLA by 1.5 points – UCLA thumped Arizona by 16 at home, and then Arizona won by 10 over UCLA at home.
NFL futures after QB trades – One of the more foolhardy segments in sports talk is arguing which side of a major transaction won the trade. Often times, it is a stalemate in which no team will end up in a better place. Even if a team did win a trade, we will not know for years.
However, in the short term, Denver became drastically better by acquiring Seattle QB Russell Wilson. Per Next Gen Stats, Wilson finished 15th among qualifying quarterbacks in Completion Percentage Over Expected last season.
By adding Wilson, Denver now has the 6th lowest odds to win the Super Bowl (+1300 per FanDuel Sportsbook). It is worth noting they are in the same division as Kansas City at +850, and only one team in the AFC gets homefield advantage throughout the playoffs.
In addition, Green Bay kept Aaron Rodgers, and they have the second best Super Bowl odds (+750) behind Buffalo.
Model vs subjective analysis – On the Circles Off podcast, The Power Rank founder Ed Feng talked with Rob and Johnny about the balance between predictive analytics and subjective adjustments.
Ed talked about how his NFL model has very little contribution from rushing statistics. As a consequence, he made some bets against the Colts and Eagles this past season that didn't get closing line value.
In addition to football betting, Ed also discussed content creation and March Madness bracket strategies. Circles Off has a ton of great episodes worth checking out.
Three point shooting in college basketball – As an analytics fella, I want to look at three point shooting offense and defense when projecting the NCAA Tournament. However, in an episode of Bracket Wisdom, Ed Feng explained the randomness in these statistics.
Among projected tournament teams, you might consider fading South Dakota State, Purdue and Michigan State because of a high three point field goal percentage. In contrast, LSU, San Francisco and Iowa State have unsustainable rates of three point shooting defense.
These projected teams were obtained from Bracketmatrix, a wisdom of crowds estimator of the teams that will make the tournament.
Baylor – Scott Drew's team got bumped from the Big 12 tournament in the quarterfinals against Oklahoma. However, don't make too much of one game. Oklahoma shot a blistering 52.4% from 3 while Baylor went cold at 13.6%.
As discussed on a Bracket Wisdom episode, Baylor thrives on shots at the rim and offensive rebounding. On defense, they rank a very respectable 12th in The Power Rank's adjusted points per possession.
In addition, athletic freshman Kendall Brown and Jeremy Sochan are potential 1st round picks in the next NBA draft. This gives Baylor an upside that few other tournament contenders can match.
You can get all of the daily Bracket Wisdom episodes on Apple Podcasts and Spotify.
Baseball is Back – If fireworks can be legally popped when a home team wins World Series games, why can't we do the same across the country knowing we are getting a full 162-game season? Fangraphs went over what the new Collective Bargaining Agreement will look like and how it will affect our enjoyment of the game.
This weekend could mark a free agent frenzy, given how soon Spring Training will begin. The Dodgers are clear favorites to win the World Series, but for value plays, it may be worth forecasting which free agents will go where, or pouncing the moment news is released on a new signing. Spotrac.com may be worth hitting the refresh button to keep track of free agency.
Contrarian strategies – In 2019, Duke came into the NCAA tournament as a big favorite. Zion Williamson came back from an injury, and RJ Barrett was one of college basketball's most dominant players on the drive in the last decade.
The Power Rank gave Duke a 34% chance to win this tournament, and picking Duke as champion gave you the best chance to win a small pool. However, 36% of the public brackets on ESPN had Duke as champion. This suggests a better strategy for intermediate sized pool.
In The Power Rank 2022 Bracket Advice and Course, there is a 22 minute audio course that explains this strategy.
You also get The Power Rank's March Madness cheat sheet that makes it drop dead easy to fill out your bracket.
Members: Conference tournament futures
Podcast: Colin Davy on finding sport betting value through Betscope
On this episode of The Football Analytics Show, I'm joined by Colin Davy, former director of data science at The Action Network and Jeopardy champion through analytics. In talking about how to find sports betting value, we discuss:
The foundational idea behind Betscope (5:29)
How to use correlations to find sports betting value (14:41)
The analytics (underlying distributions) behind player props (17:16)
The underlying distributions for 100 yard rushers (24:10)
Attracting smart sports bettors (38:00)
To listen to here, click on the right pointing triangle:
This episode of The Football Analytics Show is also available on Apple Podcasts and Spotify.


Time outs, grounding, and spanking: Do they work?
As a parent, one of your jobs is to teach your child to behave. While this can take time, try not to get frustrated and learn effective ways to discipline your child.
Click here for strategies you can use from the American Academy of Pediatrics (AAP) when your child does not listen.
The information contained in this newsletter and on HealthyChildren.org should not be used as a substitute for the medical care and advice of your pediatrician. There may be variations in treatment that your pediatrician may recommend based on individual facts and circumstances.


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Lurie writes: "Donald Trump has been mocked for threatening to sue Nancy Pelosi and Adam Schiff to prevent his impeachment, but don't laugh too soon."
Judge Neomi Rao. (photo: Zach Gibson/Getty)
Did Kavanaugh's Replacement, Neomi Rao, Show the Supreme Court a Path to Justify Trump's Defiance of Congress?
By David R. Lurie, The Daily Beast
Rao, whom Trump appointed, sided with his dubious contention that the Constitution provides the president with "enhanced protections" from impeachment.
onald Trump has been mocked for threatening to sue Nancy Pelosi and Adam Schiff to prevent his impeachment, but don't laugh too soon.
The Supreme Court may be poised to legitimize Trump's desperate effort to stymie Congress' impeachment investigation. The judge Donald Trump appointed to take Brett Kavanaugh's place on a D.C. federal appeals court may have just blazed a trail toward a high court decision that could cement the court's role as Trump's protector, and gravely tarnish the Supreme Court's reputation in the process.
Last week, Judge Neomi Rao—a prominent conservative legal scholar, former Trump administration official, and long-rumored future Supreme Court nominee herself—dissented from a decision upholding a congressional subpoena to Trump's accounting firm for tax returns and other financial information he has assiduously sought to hide since the 2016 campaign.
Congress issued the subpoena before commencing its impeachment investigation into the president. Accordingly, the legal issue before Rao and her appellate court colleagues was whether Congress' authority to engage in legislative oversight was sufficient to justify the subpoena. Trump's lawyers argued to the court that such a request could only be justified as part of an inquiry into whether Trump engaged in potentially impeachable high crimes or misdemeanors.
As the well-reasoned majority decision demonstrated, however, Supreme Court precedents provide that Congress can conduct investigations that directly implicate and concern illegal conduct by the president and other Executive Branch officials in order to consider potential legislative options available to prevent misconduct in the future. Yet Judge Rao disagreed, in an opinion that many constitutional scholars observed was squarely at odds with settled law.
It may seem initially puzzling why Rao devoted the effort to providing an unconvincing argument that Congress is without the ability to conduct an investigation concerning misconduct by a government official in its legislative oversight role. After all, Congress has now begun an impeachment investigation that should ultimately allow the House to obtain the materials at issue, even under the argument Trump initially proffered to the appeals court.
But Rao's agenda clearly extends beyond the subject at hand. Her dissent appears calculated to provide judicial credence to the contention of Trump's White House Counsel Pat Cipollone that it is "constitutionally invalid" for Trump to be impeached.
Article I of the Constitution grants the House exclusive jurisdiction over presidential impeachment proceedings. Accordingly, Trump's threat to "sue" to prevent his impeachment is as ridiculous as it appears. Indeed, in her dissent, Rao concedes that disputes regarding impeachment proceedings may not be "justiciable." Yet Rao's dissent nonetheless implies that Trump may be able to turn to the courts to frustrate, and challenge the legitimacy of, Congress' impeachment investigation nonetheless.
Like Trump, Rao asserts that the Constitution provides the president with a number of "enhanced protections" and procedural "safeguards" in connection with a House impeachment inquiry. As impeachment scholar Frank Bowman has explained, however, this claim is "specious." While the Supreme Court has indicated that there may be some minimal procedural requirements for the Senate trial of an impeached government official (which amounts to a type of adjudication), there are no constitutionally mandated procedural standards or requirements for an impeachment by the House (which is the rough equivalent of a pre-trial indictment), let alone "enhanced protections" in connection with a House investigation preceding an impeachment vote. Furthermore, as Bowman explains, even if the Constitution imposed such standards, courts would not have any proper role in enforcing them.
Yet embedded in Rao's opinion is a hint of how the Supreme Court might nonetheless ride to Trump's rescue, should it choose to adopt her (and Cipollone's) extraordinary contention that Trump has "due process" rights in connection with an impeachment investigation. Just as Rao argues that the courts should police "illegitimate" legislative oversight investigations by refusing to enforce congressional subpoenas, her opinion likewise can be read to suggest that federal judges could stymie a "constitutionally invalid" impeachment inquiry by backing up Trump's efforts to prevent Congress from obtaining access to witnesses and evidence.
Trump's avowed attempt to stonewall the Ukraine investigation has faced early reverses, as key witnesses—such as former Ambassador to Ukraine Marie Yovanovitch and presidential adviser Fiona Hill—have complied with congressional subpoenas, despite White House efforts to limit their testimony.
Nonetheless, Trump remains committed to preventing Congress from questioning key witnesses and obtaining critical evidence. For example, according to Adam Schiff, the State Department is withholding potentially inculpatory documents, while Defense Secretary Mark Esper has reneged on a previous commitment to comply with a congressional subpoena at the instruction of the White House. Furthermore, Rudy Giuliani's attorney recently responded to a congressional subpoena by "adopt[ing] all the positions set forth in" Cipollone's letter, and flatly refusing to comply.
Accordingly, it is highly likely that the Trump's administration's defiance of Congress' impeachment subpoena power will reach the Supreme Court, possibly very soon.
If the high court is asked to rule upon Trump's stonewalling, a majority of conservative justices may be tempted to endorse the Cipollone/Rao claim that Trump is entitled to procedural "safeguards" from impeachment, and to employ that claim as a rationale for excusing Trump's defiance of Congress' subpoenas.
One possibility is that the court could allow Trump to withhold witnesses and evidence unless Congress accedes to his vague demands for "procedural" protections against impeachment. Although such a ruling would not prevent Congress from impeaching the president, it could provide a stamp of legitimacy to Trump's defiance that would be of great political value to the president.
If, however, a conservative Supreme Court majority chooses to legitimize Trump's effort to prevent the Congress from holding the president to account for his abuses of power, then the high court would be openly serving as political ally and protector of the president, and could sacrifice its own legitimacy in the process.
THE NEW STREAMLINED RSN LOGIN PROCESS: Register once, then login and you are ready to comment. All you need is a Username and a Password of your choosing and you are free to comment whenever you like! Welcome to the Reader Supported News community.
CNN's Debate Performance Was Villainous and Shameful
Matt Taibbi, Rolling Stone
RSN: Not Bernie, Us. Not Warren, Us. Their Clash Underscores the Need for Grassroots Wisdom.
Norman Solomon, Reader Supported News
FOCUS: I Don't Think the Lev Parnas Texts Are the Last Hound to Be Unleashed
Charles Pierce, Esquire
Exclusive Poll: Just as Many African-Americans Say They'd Consider Voting for Bernie Sanders as Joe Biden
Cameron Joseph, VICE
At Iowa Debate, Bernie Sanders's Biggest Opponent Was CNN
Ryan Grim, Aída Chávez and Akela Lacy, The Intercept
FOCUS | Surprise: Trump Himself Is the Deep State
Rebecca Gordon, TomDispatch
Wealthy Donors Now Allowed to Give Over Half a Million Dollars Each to Support Trump's Reelection
Michelle Ye Hee Lee, The Washington Post
While Bernie Sanders Has Always Stood Up for African Americans, Joe Biden Has Repeatedly Let Us Down
Nina Turner, The State
Rudy Giuliani's Fixer, Lev Parnas, Turned Over Documents. They're Very Ugly.
Andrew Prokop, Vox

redpajama_set_name: RedPajamaCommonCrawl


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Showing every road so far featured
(N.B. So as not to break the map, this will only show the first 5000).
Road · Shenley · AL2 ·
Bell Lane nowadays runs parallel to the M25, slightly south of it.
Bell Lane (1937)
It is an ancient lane connecting London Colney and Colney Street. The modern site of the McDonald's restaurant is the former site of the Bell Inn.
Arsenal FC has its training ground near Bell Lane.
Thomas Telford's London Road (1795) was part of his overall plan for the London to Holyhead road. It was later the A6 trunk road but when the M25 arrived, the eastern end of Bell Lane was diverted near to the Bell to accommodate the motorway.
Main source: https://www.hertsmemories.org.uk/content/herts-history/towns-and-villages/st-albans/the-road-that-moved
Further citations and sources
User unknown/public domain
Shenley
Shenley is a village in Hertfordshire, England, between Barnet and St Albans.
sciene + leah (Old English: 'bright clearing')
The history of Shenley stretches back a thousand years or more - it is mentioned in the Domesday Book. The name Shenley is based on the Anglo-Saxon Scenlai, Scenlei or Senlai, which means fair or bright clearing or wood. In the early Middle Ages, south-west Hertfordshire was heavily wooded, with isolated farmsteads or hamlets in forest clearings. Shenley would have been one of these settlements.
By the 1300s, Shenley was considered to be a convenient parish for a country estate, being within reasonable reach of London. Its pure air, after the smoke and fog of the city made it a healthy place to live. The present village of Shenley apparently grew to accommodate the families of those providing a variety of services for the country estates of the gentry. Parish Registers, dating back to 1657, include service occupations such as coachmen, bailiffs, bakers and labourers. Others worked in agriculture, as cattle drovers, shepherds and millers. Craftsmen in Shenley included tailors, weavers, shoemakers, cordwainers, brick makers, blacksmiths and carpenters. Tiles and bricks were made in the area, due to the abundance of suitable clay.
Although many of Shenley's population were involved in humble occupations, the village was considered quite prosperous. In 1754 the village was assessed to be the sixteenth highest parish in the county (excluding the areas around St Albans) and by 1823, the rateable value of the parish was �£9,796.00, with only nine other parishes in the county rating higher.
During the First World War, part of the land at Porters was requisitioned and used as an aerodrome. Later Mr Raphael sold the land to Middlesex County Council in 1924 and, several years later, two psychiatric hospitals were built on the land. The design was such that as many of the existing buildings as possible were incorporated, including the mansion, the walled garden, stables and coach houses. King George V and Queen Mary officially opened the hospital in 1934. During the Second World War, part of the hospital was used as a military hospital, with three thousand wounded soldiers being treated there.
Shenley Hospital remained in service for over 60 years. It was then sold off to property developers for housing. It was not without some trepidation that some of the old-time residents viewed what had been described as an annex to Shenley but what, in reality, would more than double the number of residences in the village. However, the development took place, but as well as houses, Shenley Park was developed and maintained for the enjoyment of the whole village. These included preserving the orchard and spinney for pleasant walks and recreation, landscaping the walled garden, which are often open to the public and host a number of events throughout the year, redeveloping the tennis courts to a high standard, and, more recently, the introduction of a teashop and play area.
Shenley is also home to the training ground of Arsenal Football Club, one of England's top football teams. It boasts state of the art facilities, and was opened in 2000.
Shenley also is home to the prestigious Shenley Cricket Centre which plays host to many womens and U19 international matches throughout the summer. At the heart of the Centre is the beautiful 19th Century Pavilion, originally designed by the legendary cricketer W.G Grace. The cricketing theme runs through many of the road names on the Porters Park housing estate.


Goodale is experienced in supporting major cultural change initiatives and in aligning organizational development with strategic plans. Her particular areas of interest are identifying cultural facilitators in communities of practice, helping to promote internal transfer of best practices, and developing leadership skills in management and staff. She serves as director of training for CIGNA Health Care of California and teaches adult learning theory/lifespan learning, and computer interaction as an adjunct professor for Pepperdine University. Her dissertation, "Assessing Cultural Impact: A Case Study in Supporting a Knowledge Management Practice," examines the interaction of culture relative to management practice.


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New Boles Book for Becoming Job Ready!
Today, I am pleased to share with you my new book — a Boles Book for Becoming Job Ready — and I wrote the book to help young people learn how to wend their way into a new job marketplace, an area that is getting tougher, and more crowded, to survive in, and conquer, every day.
Continue reading → New Boles Book for Becoming Job Ready!
Writing a Journal of Memories: The Education of a Teacher
[Publisher's Note: What you see on this page is the beginning of a publication project Dr. Howard Stein was preparing for David Boles Blogs in the year 2000 upon the celebration of the occasion of his birth — July 4 — when he was 78-years-old. We have unearthed this early draft of — The Howard Stern Journal of Memories — and we share it with you today so you may not only enjoy Dr. Stein's wisdom, but also revel in the revision process you can see below in an image of his typewritten submission. You may view a larger size of the image on the Boles.com Howard Stein Archive Page.
Howard's health began to nag him as the days aged, and he never returned to this project, but you may still read a lot of Dr. Stein's work here, there and elsewhere. Howard Stein died on October 12, 2012 of heart failure. He was 90. We miss him every moment of every notion and it is amazing that 15 years after he wrote this for us, Howard is still publishing with us from the grave. Howard Stein always said he was "born lucky" — and so, too, are we lucky to have this article! — but this is his story.]
Continue reading → Writing a Journal of Memories: The Education of a Teacher
Philip Seymour Hoffman, Dylan Farrow and the Consequence of Fame
There were two remarkable, maddening, things that happened over the weekend. Both events were related to fame and the failure of human consequence against the living, but the terms of the punishments were different: Both eternal, but one forever ended.
On Saturday, we read in the New York Times about the harrowing child abuse Dylan Farrow suffered at the hands of her infamous father, writer, director, actor and movie producer, Woody Allen.
On Sunday, we learned of the early death of actor Philip Seymour Hoffman who, at age 46, lived up to his earlier prescience about fame and fortune leading to a quick Hollywood death. He made his point real in New York City with a needle jabbed in the arm of his corpse.
Continue reading → Philip Seymour Hoffman, Dylan Farrow and the Consequence of Fame
The Sexualization of Platonic Business Relationships: How Many Families Do You Need?
I've always found it odd when people you work with, or collaborate with, or may work with in the future, use the phrase "getting into bed together" as a business condiment as if to somehow oddly sexualize what is, in fact and deed, a working relationship that is, if anything, asexually platonic by necessity of average function.
I wonder why there is a need to make a business contract a personal and intimate formality in such a dramatic manner. Private relationships are bound by blood and emotion and decrees of love and passion. No public business should operate under any of those terms. I always wonder why that "in bed" phrase is so important for some people to utter during a negotiation or in a team spirit meeting.
Continue reading → The Sexualization of Platonic Business Relationships: How Many Families Do You Need?
Kitten Explosion!
I have had to move away from my old house, I have children of my own to protect from the unfriendly dogs and the foxes.
I do sneak back from time to time — and thought I would update you on some of the changes in the growing family of Alentejo cats .
I had heard rumours about new kittens and thought I would go and investigate. My first couple of return visits I saw nothing but the usual crowd I knew all growing up well. Little Squeak is no longer frail and tiny. He is growing up into a fine specimen of a cat and his sister Bubbles is blossoming too as is the aloof Nimbus.
Here is Mr B. One of the naughtiest cat I have ever met!
Continue reading → Kitten Explosion!
The Eggshell Generation: No Freedom for Danger Children
Life has changed for modern children. When I was growing up in the Midwest, you sought freedom — and if it wasn't granted with a bicycle, then you found other, more nefarious ways, to run away and play far away from your doorstep.
It isn't that way any longer. Today, kids are protected and driven and supervised in organized sports and cultural events. There's no spontaneity now because there's fear of the unknown and danger in the creative. No sandlot baseball. No football games with self-set boundaries and special scoring. Everything is regulation. There can be no divergence from the norm.
We're creating a society of young people who are risk-averse and too frightened to set their own agendas and follow their own, unblazed, pathway. Fun is the new mysterious stranger. "Do what you want" is the new monster under the bed.
Continue reading → The Eggshell Generation: No Freedom for Danger Children
Keep a Song in Your Heart: Remembering Lawrence Welk
Every time I visited my grandfather in North Loup, Nebraska — there was one unspoken, but wholly enforced rule — on Sunday nights at 7:00pm, you sat down with him and watched the Lawrence Welk Show on ABC television.
It was an hour of a painful persuasion for a young lad to bear — second only to the never-ending reruns of Hee Haw that aired every single weeknight that I was also forced to watch during each visit.
I never learned to like, or even tolerate, the Welk show. The show was a matter of saccharine moments topped with thick frosting of faux frivolity and façade. All show and no substance. Complete spectacle and no plot.
Continue reading → Keep a Song in Your Heart: Remembering Lawrence Welk


The Makeup Box: Lime Crime Countessa Fluorescent Dupe: Barry M Vibrant Pink Review and Swatches!
Lime Crime Countessa Fluorescent Dupe: Barry M Vibrant Pink Review and Swatches!
I've always considered Lime Crime's Countessa Fluorescent the Queen of Barbie Pinks. It's different from hot electric pinks and fuchsias like MAC's Candy Yum Yum in that it is a truer pink (as opposed to blue-based), not as deep, and almost highlighter-bright on the lips.
Imagine my delight when my Barry M package included one that was extremely similar in shade.
Meet Barry M Vibrant Pink (left) and Lime Crime Countessa Fluorescent (right).
Barry M Vibrant Pink is something of a satin finish (similar to MAC Pink Nouveau), which means it is opaque and tacky, with a muted sheen - which I love. This is my favorite texture of all MAC lipsticks because it imparts great color, lasts really long, but doesn't feel as dry as a full matte lipstick.
The right side of my hand is a little more shaded, or the two swatches would look even more similar. I was quite surprised to realize the Barry M was actually more opaque and intense than the Lime Crime, which is more of a creamy Amplified finish. If you like demi-matte finishes that last a long while, get Barry M Vibrant Pink. If you want a bit more moisture, get Lime Crime Countessa Fluorescent.
The other difference is also that if you want to be really picky about it, the Barry M is just a hint deeper and more cool-toned. But just worn on the lips individually, the difference is not visible at all.
Barbie Pink vs Hot Pink: Barry M Lip Paints in 62 Vibrant Pink (left) and 52 Shocking Pink (right).
Just for purposes of comparison, here is Barry M's Vibrant Pink swatched against Barry M Shocking Pink, the widely-acknowledged Candy Yum Yum dupe. As you can see, Vibrant Pink is more lustrous and reflective, whereas Shocking Pink is a deeper, cooler-based, more intense matte-pink.
Do note that all the neon pinks do stain the lips, without exception. (If you've found any of these neon pinks that don't stain, let me know!) I believe it's the nature of the liquid dyes needed to get that intense highlighter-pink effect, as more subdued pinks I own, like MAC Pink Nouveau, do not do this.
The main drawback for this lip shade? It can make teeth look dull and yellow, so watch out there!
Barry M Vibrant Pink can be purchased internationally on Barrym.com for £4.49 each.


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This is going to be the most epic bout of movie watching I've done since the back to back showings of Star Wars and The Empire Strikes Back before the premiere of Return of the Jedi.
I already purchased my ticket. Who's going to join me for this massive gorging?
I may be comatose by the time Avengers plays.


text:
Architectural Digest Magazine Archive (EBSCO)
International design magazine from 1920 to 2011. For architects, interior designers and design enthusiasts. With a lot of photographs of architecture, interior design, art and antiques.
Art & Architecture Source (EBSCO)
Includes scientific articles about art from all countries, eras and important artists. From interior and graphic design to architecture and art. The database also includes videos. It is a valuable resource for anyone interested in architecture and visual arts.
Art and Architecture Archive (ProQuest)
Browse the most important art and architectural magazines of the 20th century. Find articles on visual and applied arts, interior and industrial design and landscape architecture. With high-quality images and fully searchable text. Includes a lot of information about the life and work of artists and architects, and about art movements and social trends. For art historians, sociologists and historians.
Art Magazine Collection Archive (EBSCO)
Book & library science
Music and film/tv
Psychology / health
Extensive database of millions of articles from more than 17,000 scientific journals and other leading sources. From CNN podcasts to BBC Worldwide Learning videos. Also includes important reference sets such as Gale Encyclopaedia of Science and Encyclopaedia of World Biography. Interesting for researchers and students.
Gale General OneFile
Database of over 9,000 titles. Find information about art, economics, language, mathematics, politics and more. From 1980 to the present day and updated daily. Includes a tool that translates articles into more than 12 languages. Interesting for researchers and students.
(-) Architecture (6)
Book & library science (4)
Psychology / health (2)
(-) E-journals / Magazines (6)
Catalogues (1)
Toegang voor KB-leden (6)


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Straight off Batman's Utility Belt
A Dark Knight-like detention device that fires an 8' Kevlar cord is ready for real-life law enforcement.
Jeff ReinkeEric Sorensen
Since his first appearance in 1939, Batman has undergone a number of changes in his quest to both stay ahead of his enemies and relevant to comic book fans. However, one thing that has remained a constant is his continued use of unique tools and devices for vanquishing his foes.
And now, one of those devices is set to make its way into real-life law enforcement. I'm not sure what the Dark Knight called it, but the folks at Wrap Technologies are calling their Kevlar rope shooting device the BolaWrap 100. Just like in the comics, video games, animated series and movies featuring the Caped Crusader, the BolaWrap 100 fires like a 9 mm handgun in propelling an eight-foot long cord at 640 feet-per-second.
The Kevlar cord has two metal barbs on each end that attach to the targeted individual and allow the cord to wrap around the torso or legs. The cord is fired from a cartridge, so loading and unloading is similar to a firearm's magazine or clip. It also features a laser aiming function and is effective from up to 25'. The general idea is for the BolaWrap to detain or restrain a person of interest without the use of firearms, tasers, rubber bullets or physical force.
The inventor of the device, who has no known connections to Wayne Enterprises, is Woody Norris – who also developed the LRAD acoustic cannon known for blasting out painful soundwaves over long distances. He got his inspiration from the bolas, which is Spanish for ball, that were used by South American ranchers to help capture straying cattle.
A number of law enforcement agencies around the country are testing the devices, with perhaps the most notable being the Los Angeles Police Department. The LAPD is slated to begin a 90-day trial in January.
Dad Makes Re-Engineered Controller
Apple Accused of Reading Texts
General Dynamics Gets $22.2B to Make Navy Subs
The Bullets that Killed JFK


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Ω125347360
Iterated Amplification
72Hiring engineers and researchers to help align GPT-34mo
29"Unsupervised" translation as an (intent) alignment problem4mo
32Better priors as a safety problem7mo
35Learning the prior7mo
43Inaccessible information8mo
47Writeup: Progress on AI Safety via Debate10mo
23Of arguments and wagers1y
18AI alignment landscape1y
29The strategy-stealing assumption1y
24Ought: why it matters and ways to help1y
Some thoughts on risks from narrow, non-agentic AI
Paul Christiano18h
I agree that the core question is about how generalization occurs. My two stories involve kinds of generalization, and I think there are also ways generalization could work that could lead to good behavior.
It is important to my intuition that not only can we never train for the "good" generalization, we can't even evaluate techniques to figure out which generalization "well" (since both of the bad generalizations would lead to behavior that looks good over long horizons).
If there is a disagreement it is probably that I have a much higher probability of the kind of generalization in story 1. I'm not sure if there's actually a big quantitative disagreement though rather than a communication problem.
I also think it's quite likely that the story in my post is unrealistic in a bunch of ways and I'm currently thinking more about what I think would actually happen.
Some more detailed responses that feel more in-the-weeds:
you think long-horizon real-world data will play a significant role in training, because we'll need it to teach agents to do the most valuable tasks. This seems plausible to me; but I think that in order for this type of training to be useful, the agents will need to already have robust motivations (else they won't be able to find rewards that are given over long time horizons
I might not understand this point. For example, suppose I'm training a 1-day predictor to make good predictions over 10 or 100 days. I expect such predictors to initially fail over long horizons, but to potentially be greatly improved with moderate amounts of fine-tuning. It seems to me that if this model has "robust motivations" then they would most likely be to predict accurately, but I'm not sure about why the model necessarily has robust motivations.
I feel similarly about goals like "plan to get high reward (defined as signals on channel X, you can learn how the channel works)." But even if prediction was a special case, if you learn a model then you can use it for planning/RL in simulation.
But it seems to me by default, during early training periods the AI won't have much information about either the overseer's knowledge (or the overseer's existence), and may not even have the concept of rewards, making alignment with instructions much more natural.
It feels to me like our models are already getting to the point where they respond to quirks of the labeling or evaluation process, and are basically able to build simple models of the oversight process.
my concern is that this underlying concept of "natural generalisation" is doing a lot of work, despite not having been explored in your original post
Definitely, I think it's critical to what happens and not really explored in the post (which is mostly intended to provide some color for what failure might look like).
That said, a major part of my view is that it's pretty likely that we get either arbitrary motivations or reward-maximization (or something in between), and it's not a big deal which since they both seem bad and seem averted in the same way.
I think the really key question is how likely it is that we get some kind of "intended" generalization like friendliness. I'm frequently on the opposite side of this disagreement, arguing that the probability that people will get some nice generalization if they really try is at least 25% or 50%, but I'm also happy being on the pessimistic side and saying that the probability we can get nice generalizations is at most 50% or 75%.
(or anywhere else, to my knowledge)
Two kinds of generalization is an old post on this question (though I wish it had used more tasteful examples).
Turning reflection up to 11 touches on the issue as well, though coming from a very different place than you.
I think there are a bunch of Arbital posts where Eliezer tries to articulate some of his opinions on this but I don't know pointers offhand. I think most of my sense is
I haven't written that much about why I think generalizations like "just be helpful" aren't that likely. I agree with the point that these issues are underexplored by people working on alignment, and even more underdiscussed, given how important they are.
There are some google doc comment threads with MIRI where I've written about why I think those are plausible (namely that it plausible-but-challenging for breeding of animals, and that seems like one of our best anchors overall, suggesting that plausible-but-challenging is a good anchor). I think in those cases the key argument was about whether you need this to generalize far, since both me and MIRI think it's a kind of implausible generalization to go out to infinity rather than becoming distorted at some point along the way, but I am more optimistic about making a series of "short hops" where models generalize helpfully to being moderately smarter and then they can carry out the next step of training for you.
Paul Christiano2d
I agree that this is probably the key point; my other comment ("I think this is the key point and it's glossed over...") feels very relevant to me.
I feel like a very natural version of "follow instructions" is "Do things that would the instruction-giver would rate highly." (Which is the generalization I'm talking about.) I don't think any of the arguments about "long horizon versions of tasks are different from short versions" tell us anything about which of these generalizations would be learnt (since they are both equally alien over long horizons).
Other versions like "Follow instructions (without regards to what the training process cares about)" seem quite likely to perform significantly worse on the training set. It's also not clear to me that "follow the spirit of the instructions" is better-specified than "do things the instruction-giver would rate highly if we asked them"---informally I would say the latter is better-specified, and it seems like the argument here is resting crucially on some other sense of well-specification.
On meta-learning: it doesn't seem realistic to think about an AI "trying to get high rewards" on tasks where the time horizon is measured in months or years.
I've trained in simulation on tasks where I face a wide variety of environment, each with a reward signal, and I am taught to learn the dynamics of the environment and the reward and then take actions that lead to a lot of reward. In simulation my tasks can have reasonably long time horizons (as measured by how long I think), though that depends on open questions about scaling behavior. I don't agree with the claim that it's unrealistic to imagine such models generalizing to reality by wanting something-like-reward.
In most of the cases you've discussed, trying to do tasks over much longer time horizons involves doing a very different task [...]
Trying to maximize wealth over 100 minutes is indeed very different from maximizing wealth over 1 year, and is also almost completely useless for basically the same reason (except in domains like day trading where mark to market acts as a strong value function).
My take is that people will be pushed to optimizing over longer horizons because these qualitatively different tasks over short horizons aren't useful. The useful tasks in fact do involve preparing for the future and acquiring flexible influence, and so time horizons long enough to be useful will also be long enough to be relevantly similar to yet longer horizons.
Developers will be incentivized to find any way to get good behavior over long horizons, and it seems like we have many candidates that I regard as plausible and which all seem reasonably likely to lead to the kind of behavior I discuss. To me it feels like you are quite opinionated about how that generalization will work.
It seems like your take is "consequences over long enough horizons to be useful will be way too expensive to use for training," which seems close to 50/50 to me.
I think that throughout your post there's an ambiguity between two types of measurement. Type one measurements are those which we can make easily enough to use as a feedback signal for training AIs. Type two measurements are those which we can make easily enough to tell us whether an AI we've deployed is doing a good job. In general many more things are type-two-measurable than type-one-measurable, because training feedback needs to be very cheap.
I agree that this is a useful distinction and there will be some gap. I think that quantitatively I expect the gap to be much smaller than you do (e.g. getting 10k historical examples of 1-year plans seems quite realistic), and I expect people to work to design training procedures that get good performance on type two measures (roughly by definition), and I guess I'm significantly more agnostic about the likelihood of generalization from the longest type one measures to type two measures.
In other words, we should expect generalisation to long-term tasks to occur via a general motivation to follow our instructions, rather than on a task-specific basis, because the latter is so underspecified. But generalisation via following instructions doesn't have a strong bias towards easily-measurable goals.
I'm imagining systems generalizing much more narrowly to the evaluation process used during training. This is still underspecified in some sense (are you trying to optimize the data that goes into SGD, or the data that goes into the dataset, or the data that goes into the sensors?) and in the limit that basically leads to influence-maximization and continuously fades into scenario 2. It's also true that e.g. I may be able to confirm at test-time that there is no training process holding me accountable, and for some of these generalizations that would lead to a kind of existential crisis (where I've never encountered anything like this during training and it's no longer clear what I'm even aiming at). It doesn't feel like these are the kinds of underspecification you are referring to.
We do need to train them by trial and error, but it's very difficult to do so on real-world tasks which have long feedback loops, like most of the ones you discuss. Instead, we'll likely train them to have good reasoning skills on tasks which have short feedback loops, and then transfer them to real-world with long feedback loops. But in that case, I don't see much reason why systems that have a detailed understanding of the world will have a strong bias towards easily-measurable goals on real-world tasks with long feedback loops.
I think this is the key point and it's glossed over in my original post, so it seems worth digging in a bit more.
I think there are many plausible models that generalize successfully to longer horizons, e.g. from 100 days to 10,000 days:
Acquire money and other forms of flexible influence, and then tomorrow switch to using a 99-day (or 9999-day) horizon policy.
Have a short-term predictor, and apply it over more and more steps to predict longer horizons (if your predictor generalizes then there are tons of approaches to acting that would generalize).
Deductively reason about what actions are good over 100 days (vs 10,000 days), since deduction appears to generalize well from a big messy set of facts to new very different facts.
If I've learned to abstract seconds into minutes, minutes into hours, hours into days, days into weeks, and then plan over weeks, its pretty plausible that the same procedure can abstract weeks into months and months into years. (It's kind of like I'm now I'm working on a log scale and asking the model to generalize from 1, 2, ..., 10 to 11, 12, 13.)
Most possible ways of reasoning are hard to write down in a really simple list, but I expect that many hard-to-describe models also generalize. If some generalize and some do not, then training my model over longer and longer horizons (3 seconds, 30 seconds, 5 minutes...) will gradually knock out the non-generalizing modes of reasoning and leave me with the modes that do generalize to longer horizons.
This is roughly why I'm afraid that models we train will ultimately be able to plan over long horizons than those that appear in training.
But many of these would end up pursuing goals that are closely related to the goals they pursue over short horizons (and in particular the first 4 above seem like they'd all be undesirable if generalizing from easily-measured goals, and would lead to the kinds of failures I describe in part I of WFLL).
I think one reason that my posts about this are confusing is that I often insist that we don't rely on generalization because I don't expect it to work reliably in the way we hope. But that's about what assumptions we want to make when designing our algorithms---I still think that the "generalizes in the natural way" model is important for getting a sense of what AI systems are going to do, even if I think there is a good chance that it's not a good enough approximation to make the systems do exactly what we want. (And of course I think if you are relying on generalization in this way you have very little ability to avoid the out-with-a-bang failure mode, so I have further reasons to be unhappy about relying on generalization.)
In the second half of WFLL, you talk about "systems that have a detailed understanding of the world, which are able to adapt their behavior in order to achieve specific goals". Does the first half of WFLL also primarily refer to systems with these properties? And if so, does "reasoning honed by trial-and-error" refer to the reasoning that those systems do?
If yes, then this undermines your core argument that "[some things] can't be done by trial and error. To solve such tasks we need to understand what we are doing and why it will yield good outcomes", because "systems that have a detailed understanding of the world" don't need to operate by trial and error; they understand what they're doing.
I agree that it's only us who are operating by trial and error---the system understands what it's doing. I don't think that undermines my argument. The point is that we pick the system, and so determine what it's doing, by trial and error, because we have no understanding of what it's doing (under the current paradigm). For some kinds of goals we may be able to pick systems that achieve those goals by trial and error (modulo empirical uncertainty about generalization, as discussed in the second part). For other goals there isn't a plausible way to do that.
To clarify your position: if I train a system that makes good predictions over 1 minute and 10 minutes and 100 minutes, is your position that there's not much reason that this system would make a good prediction over 1000 minutes? Analogously, if I train a system by meta-learning to get high rewards over a wide range of simulated environments, is your position that there's not much reason to think it will try to get high rewards when deployed in the real world?
I consider those pretty wide open empirical questions. The view that we can get good generalization of this kind is fairly common within ML.
I do agree once you generalize motivations from easily measurable tasks with short feedback loops to tasks with long feedback loops then you may also be able to get "good" generalizations, and this is a way that you can solve the alignment problem. It seems to me that there are lots of plausible ways to generalize to longer horizons without also generalizing to "better" answers (according to humans' idealized reasoning).
(Another salient way in which you get long horizons is by doing something like TD learning, i.e. train a model that predicts its own judgment in 1 minute. I don't know if it's important to get into the details of all the ways people can try to get things to generalize over longer time horizons, it seems like there are many candidates. I agree that there are analogously candidates for getting models to optimize the things we want even if we can't measure them easily, and as I've said I think it's most likely those techniques will be successful, but this is a post about what happens if we fail, and I think it's completely unclear that "we can generalize to longer horizons" implies "we can generalize from the measurable to the unmeasurable.".)
(Analogously: when you put humans in a new domain, and give them tasks and feedback via verbal instructions, then we can quickly learn sophisticated concepts in that new domain, and optimise for those, not just the easily-measured concepts in that new domain.)
When we deploy humans in the real world they do seem to have many desires resembling various plausible generalizations of evolutionary fitness (e.g. to intrinsically want kids even in unfamiliar situations, to care about very long-term legacies, etc.). I totally agree that humans also want a bunch of kind of random spandrels. This is related to the basic uncertainty discussed in the previous paragraphs. I think the situation with ML may well differ because, if we wanted to, we can use training procedures that are much more likely to generalize than evolution.
I don't think it's relevant to my argument that humans can learn sophisticated concepts in a new domain, the question is about the motivations of humans.
Why is your scenario called "You get what you measure" if you're agnostic about whether we actually get what we measure, even on the level of individual AIs?
Or do you mean part 1 to be the case where we do get what we measure, and part 2 to be the case where we don't?
Yes, I'm saying that part 1 is where you are able to get what you measure and part 2 is where you aren't.
Also, as I say, I expect the real world to be some complicated mish-mash of these kinds of failures (and for real motivations to be potentially influenced both by natural generalizations of what happens at training time and also by randomness / architecture / etc., as seems to be the case with humans).
The case in which this is more worrying is when an organisation's success is determined by (for example) whether politicians like it, and politicians only pay attention to easily-measurable metrics. In this case, organisations which pursue easily-measured goals will be more successful than ones which pursue the goals the politicians actually want to achieve. This is why I make the argument that actually the pressure on politicians to pursue easily-measurable metrics is pretty weak (hence why they're ignoring most economists' recommendations on how to increase GDP).
Wanting to earn more money or grow users or survive over the long term is also an easily measured goal, and in practice firms crucially exploit the fact that these goals are contiguous with their shorter easily measured proxies. Non-profits that act in the world often have bottom-line metrics that they use to guide their action and seem better at optimizing goals that can be captured by such metrics (or metrics like donor acquisition).
The mechanism by which you are better at pursuing easily-measureable goals is primarily via internal coherence / stability.
I agree that you've described some potential harms; but in order to make this a plausible long-term concern, you need to give reasons to think that the harms outweigh the benefits of AI enhancing (the effective capabilities of) human reasoning.
I've said that previously human world-steering is the only game in town but soon it won't be, so the future is more likely to be steered in ways that a human wouldn't steer it, and that in turn is more likely to be a direction humans don't like. This doesn't speak to whether the harms on balance outweigh the benefits, which would require an analysis of the benefits but is also pretty irrelevant to my claim (especially so given that all of the world-steerers enjoy these benefits at all and we are primarily concerned with relative influence over the very long term). I'm trying to talk about how the future could get steered in a direction that we don't like if AI development goes in a bad direction, I'm not trying to argue something like "Shorter AI timelines are worse" (which I also think is probably true but about which I'm more ambivalent).
If you'd written a comparable post a few centuries ago talking about how human physical power will lose out to inhuman physical power, I would have had the same complaint.
I don't see a plausible way that humans can use physical power for some long-term goals and not other long-term goals, whereas I've suggested two ways in which automated reasoning may be more easily applied to certain long-term goals (namely the goals that are natural generalizations of training objectives, or goals that are most easily discovered in neural networks).
I classify Facebook's newsfeed as future-steering in a weak sense (it steers the future towards political polarisation), but non-agentic. Do you agree with this?
If Facebook's news feed would generate actions chosen to have the long-term consequence of increasing political polarization then I'd say it was steering the future towards political polarization. (And I assume you'd say it was an agent.)
As is, I don't think Facebook's newsfeed steers the future towards political polarization in a meaningful sense (it's roughly the same as a toaster steering the world towards more toast).
Maybe that's quantitatively just the same kind of thing but weak, since after all everything is about generalization anyway. In that case the concern seems like it's about world-steering that scales up as we scale up our technology/models improve (such that they will eventually become competitive with human world-steering), whereas the news feed doesn't scale up since it's just relying on some random association about how short-term events X happen to lead to polarization (and nor will a toaster if you make it better and better at toasting). I don't really have views on this kind of definitional question, and my post isn't really relying on any of these distinctions.
Something like A/B testing is much closer to future-steering, since scaling it up in the obvious way (and scaling to effects across more users and longer horizons rather than independently randomizing) would in fact steer the future towards whatever selection criteria you were using. But I agree with your point that such systems can only steer the very long-term future once there is some kind of generalization.
If it's via a deliberate plan to suppress them while also overcoming human objections to doing so, then that seems less like a narrow system "optimising for an easily measured objective" and more like an agentic and misaligned AGI
I didn't mean to make any distinction of this kind. I don't think I said anything about narrowness or agency. The systems I describe do seem to be optimizing for easily measurable objectives, but that seems mostly orthogonal to these other axes.
I'm pretty agnostic on whether AI will in fact be optimizing for the easily measured objectives used in training or for unrelated values that arise naturally in the learning process (or more likely some complicated mix), and part of my point is that it doesn't seem to much mater.
Secondly, let's talk about existing pressures towards easily-measured goals. I read this as primarily referring to competitive political and economic activity - because competition is a key force pushing people towards tradeoffs which are undesirable in the long term.
I'm saying: it's easier to pursue easily-measured goals, and so successful organizations and individuals tend to do that and to outcompete those whose goals are harder to measure (and to get better at / focus on the parts of their goals that are easy to measure, etc.). I'm not positing any change in the strength of competition, I'm positing a change in the extent to which goals that are easier to measure are in fact easier to pursue.
Regarding the extent and nature of competition I do think I disagree with you fairly strongly but it doesn't seem like a central point.
the US, for example, doesn't seem very concerned right now about falling behind China.
I think this is in fact quite high on the list of concerns for US policy-makers and especially the US defense establishment.
Further, I don't see where the meta-level optimisation for easily measured objectives comes from.
Firms and governments and people pursue a whole mix of objectives, some of which are easily measured. The ones pursuing easily-measured objectives are more successful, and so control an increasing fraction of resources.
So if narrow AI becomes very powerful, we should expect it to improve humanity's ability to steer our trajectory in many ways.
I don't disagree with this at all. The point is that right now human future-steering is basically the only game in town. We are going to introduce inhuman reasoning that can also steer the future, and over time human reasoning will lose out in relative terms. (If you classify all future-steering machinery as "agentic" then evidently I'm talking about agents and I agree with the informal claim that "non-agentic" reasoning isn't concerning.) That's compatible with us benefiting enormously, if all of those benefits also accrue to automated reasoners---as your examples seem to. We will try to ensure that all this new reasoning will benefit humanity, but I describe two reasons that might be difficult and say a little bit about how that difficulty might materialize.
I don't really know if or how this is distinct from what you call the second species argument. It feels like you are objecting to a distinction I'm not intending to make.
Thoughts on Iason Gabriel's Artificial Intelligence, Values, and Alignment
If it turns out not to be possible then the AI should never fade away.
If the humans in the container succeed in becoming wiser, then hopefully it is wise for us to leave this decision up to them than to preemptively make it now (and so I think the situation is even better than it sounds superficially).
But it seems to me that there are a small number of humans on this planet who have moved some way in the direction of being fit to run the world, and in time, more humans could move in this direction, and could move further.
It seems like the real thing up for debate will be about power struggles amongst humans---if we had just one human, then it seems to me like the grandparent's position would be straightforwardly incoherent. This includes, in particular, competing views about what kind of structure we should use to govern ourselves in the future.
I buy into the delegation framing, but I think that the best targets for delegation look more like "slightly older and wiser versions of ourselves with slightly more space" (who can themselves make decisions about whether to delegate to something more alien). In the sand-pit example, if the child opted into that arrangement then I would say they have effectively delegated to a version of themselves who is slightly constrained and shaped by the supervision of the adult. (But in the present situation, the most important thing is that the parent protects them from the outside the world while they have time to grow.)
I basically agree that humans ought to use AI to get space, safety and time to figure out what we want and grow into the people we want to be before making important decisions. This is (roughly) why I'm not concerned with some of the distinctions Gabriel raises, or that naturally come to mind when many people think of alignment.
That said, I feel your analogy misses a key point: while the child is playing in their sandbox, other stuff is happening in the world---people are building factories and armies, fighting wars and grabbing resources in space, and so on---and the child will inherit nothing at all unless their parent fights for it.
So without (fairly extreme) coordination, we need to figure out how to have the parent acquire resources and then ultimately "give" those resources to the child. It feels like that problem shouldn't be much harder than the parent acquiring resources for themselves (I explore this intuition some in this post on the "strategy stealing" assumption), so that this just comes down to whether we can create a parent who is competent while being motivated to even try to help the child. That's what I have in mind while working on the alignment problem.
On the other hand, given strong enough coordination that the parent doesn't have to fight for their child, I think that the whole shape of the alignment problem changes in more profound ways.
I think that much existing research on alignment, and my research in particular, is embedded in the "agency hand-off paradigm" only to the extent that is necessitated by that situation.
I do agree that my post on indirect normativity is embedded in a stronger version of the agency hand-off paradigm. I think the main reason for taking an approach like that is that a human embedded in the physical world is a soft target for would-be attackers and creates a. If we are happy handing off control to a hypothetical version of ourselves in the imagination of our AI, then we can achieve additional security by doing so, and this may be more appealing than other mechanisms to achieve a similar level of security (like uploading or retreating to a secure physical sanctuary). In some sense all of this is just about saying what it means to ultimately "give" the resources to the child, and it does so by trying to construct an ideal environment for them to become wiser after which they will be mature enough to provide more direct instructions. (But in practice I think that these proposals may involve a jarring transition that could be avoided by using a physical sanctuary instead or just ensuring that our local environments remain hospitable.)
Overall it feels to me like you are coming from a similar place to where I was when I wrote this post on corrigibility, and I'm curious if there are places where you would part ways with that perspective (given the consideration I raised in this comment).
(I do think "aligned with who?" is a real question since the parent needs to decide which child will ultimately get the resources, or else if there are multiple children playing together then it matters a lot how the parent's decisions shape the environment that will ultimately aggregate their preferences.)
What technologies could cause world GDP doubling times to be <8 years?
Paul Christiano1mo
France is the other country for which Our World in Data has figures going back to 1400 (I think from Maddison), here's the same graph for France:
There is more crazy stuff going on, but broadly the picture looks the same and there is quite a lot of acceleration between 1800 and the 1950s. The growth numbers are 0.7% for 1800-1850, 1.2% for 1850-1900, 1.2% for 1900-1950, 2.8% for 1950-2000.
And for the even messier case of China:
Growth averages 0 from 1800 to 1950, and then 3.8% from 1950-2000 and 6.9% from 2000-2016.


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Raško (cyr. Рашко) – wieś w Czarnogórze, w gminie Kolašin. W 2011 roku liczyła 13 mieszkańców.

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Mon, Apr. 24, 2017: Trump meets with conservative media at White House
Dozens of members of the conservative media attended a reception at the White House on Monday, where President Trump spoke to reporters and personalities whom he's said have, at times, covered him more fairly than the mainstream press.
Among those present was Charlie Spiering, White House correspondent for Breitbart News, who tweeted that Trump spoke for more than a half an hour. The White House later allowed Trump's remarks to be on the record.
According to Spiering. Trump spoke about Syria, North Korea, immigration, and infrastructure spending.
When asked about Assad's existing stockpile of chemical weapons, Trump responded, "Wait and see if he uses them again, OK?" Spiering tweeted. He also said Assad's regime "duped" the Obama administration into thinking they got rid of chemical weapons.
Click here to read more from Variety.
Mon, Apr. 24, 2017: Trump signs Holocaust Remembrance proclamation
President Donald Trump described how "six million Jews had been brutally slaughtered," in a proclamation marking the week-long Days of Remembrance of Victims of the Holocaust.
The White House released the declaration Monday, Holocaust Remembrance Day, ahead of Trump's planned speech at the U.S. Holocaust Memorial Museum.
Trump's statement condemned the Nazi murder of 6 million Jews as well as other minorities.
"The Holocaust was the state-sponsored, systematic persecution and attempted annihilation of European Jewry by the Nazi regime and its collaborators. By the end of World War II, six million Jews had been brutally slaughtered," read the statement, adding that other targeted groups included "Roma (Gypsies), persons with mental and physical disabilities, Soviet prisoners of war, Jehovah's Witnesses, Slavs and other peoples of Europe, gays, and political opponents."
Click here to read more from JTA.
Mon, Apr. 24, 2017: Trump meets with UN Security Council representatives at White House
President Trump told ambassadors from countries on the United Nations Security Council Monday that they were going to be busy tackling problems that the U.N. typically avoids addressing.
"You're going to be very busy people over the coming months and years," Mr. Trump said at the opening of a working lunch with the ambassadors at the White House.
"The United Nations doesn't like taking on certain problems," he continued, citing the Syrian regimes use of chemical weapons against its people. "I encourage the Security Council to come together to take action on all of these many threats."
The president also spoke of the rising tensions with North Korea, calling the reclusive communist country "a real threat to the world."
Click here to read more to The Washington Times.
Mon, Apr. 24, 2017: Trump, Merkel discuss North Korean security challenge in phone call
U.S. President Donald Trump and German Chancellor Angela Merkel discussed the "urgent security challenge" posed by North Korea in a phone call on Monday, the White House said.
A White House statement said the two leaders also discussed Syria and Yemen and the need for a peaceful settlement to the conflict in Ukraine.
–Reuters, Steve Holland
Mon, Apr. 24, 2017: Trump calls NASA astronaut Peggy Whitson, congratulates her on record number of days in space
President Trump on Monday spoke with NASA astronaut Peggy Whitson to congratulate her after she set the U.S. record for the most cumulative days in space.
The president called Whitson from the Oval Office, sitting alongside his daughter Ivanka Trump and NASA astronaut Kate Rubins.
"I want to say that this is a very special day in the glorious history of American space flight," the president said at the start of the call. Continue reading "Mon, Apr. 24, 2017: Trump calls NASA astronaut Peggy Whitson, congratulates her on record number of days in space"
Mon, Apr. 24, 2017: Trump meets with UN ambassadors, signs Holocaust proclamation
9:30 am: Speaks with German Chancellor Merkel
10:00 am: Has a video conference with NASA astronauts aboard the International Space Station
11:30 am: Has a working lunch with ambassadors of countries on the United Nations Security Council; State Dining Room
2:30 pm: Signs a proclamation on Holocaust Remembrance
3:00 pm: Hosts a credential ceremony for newly appointed ambassadors to Washington, D.C.
4:30 pm || Meets with Secretary of Defense James Mattis and Chairman of the Joint Chiefs of Staff Joseph Dunford
5:30 pm || Participates in a reception with conservative media; Chief of Staff Patio
6:30 pm || Has dinner with Senator and Mrs. John McCain and Senator Lindsey Graham; Residence


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The grid is emerging as a great computational resource but its dynamic behavior makes the Grid environment unpredictable. Systems and networks can fail, and the introduction of more users can result in resource starvation. Once a job has been submitted for execution on the grid, monitoring becomes essential for a user to see that the job is completed in an efficient way, and to detect any problems that occur while the job is running. In current environments once a user submits a job he loses direct control over the job and the system behaves like a batch system: the user submits the job and later gets a result back. The only information a user can obtain about a job is whether it is scheduled, running, cancelled or finished. Today users are becoming increasingly interested in such analysis grid environments in which they can check the progress of the job, obtain intermediate results, terminate the job based on the progress of job or intermediate results, steer the job to other nodes to achieve better performance and check the resources consumed by the job. In order to fulfill their requirements of interactivity a mechanism is needed that can provide the user with real time access to information about different attributes of a job. In this paper we present the design of a Job Monitoring Service, a web service that will provide interactive remote job monitoring by allowing users to access different attributes of a job once it has been submitted to the interactive Grid Analysis Environment.


Last week, we attended the Microsoft Exchange Conference (MEC) in Austin, Texas with partners from 41 countries and six continents to discuss current Microsoft Exchange trends.
Not surprisingly, the impact of the cloud, mobility and BYOD, social media and collaboration, and big data were the major topics driving the discussion. The keynote, moderated by Julia White, General Manager of the Office Division of technical marketing, was really interesting.
We had the opportunity to listen to three great speakers from Microsoft: Jeff Teper, CVP, Office Servers & Services Program Management, Applications & Services; Kristian Andaker, PM Director for the Information Protection team; and Harv Bhela, Director, Program Management, Exchange.
Jeff Teper kicked it off the first one with a great talk about the transformation of the workplace in increasingly mobile, cloud-based environments. Teper discussed how Microsoft is reimagining Office to bring more value to IT folks with the recent release of Office for the iPad, and new policy management and reporting features that ensure that productivity does not suffer in Exchange environments. Teper elaborated on how the cloud is affecting how organizations need to manage messaging environments which are more social and driven by the end-user, as well as the increased security concerns IT messaging administrators are faced with today. He acknowledged that productivity platforms need to be integrated with open, social communications tools like Yammer to facilitate open communication.
He also touched on the importance of supporting the BYOD trend, and how Microsoft is making significant investments in developing a trusted, secure and scalable platform to do this. Most importantly for IT administrators that worry about job security when moving to the cloud, Teper pointed out that the jobs are still there, and that the cloud only enables messaging administrators to work on more strategic projects.
The Information Protection and Compliance is a key topic when we talk about Unified Communications with the importance of keeping the corporate data safe, which pushes business lines to use the tools available in their companies. Very often user adoption is not at easy as IT folks expect because sometimes, available tools are difficult to access with SSO barriers. The result is a lack of productivity or people who use external solutions that are not within the corporate company policy. The main Mojo was "Do not sacrifice user productivity" at all.
Mobile: Proliferation of devices and half of the email are seen on the phone first.
Social: How a company is working like a network as communication is becoming more open and more expressive.
Big Data email: Machine learning has a lot of potential allowing the overall email experience to be tailored, personalized.
With the BYOD trend, market research highlights that the phone is becoming the only screen that matters for communication and email. With the proliferation of devices, it appears that smartphones will soon be more important than PCs in personal and professional workplaces.
An interesting notion has been mentioned by Harvinder Bhela: what he calls the "intelligence triage," which is how we take all power of social and machine learning to bring it right into email to provide a riche tailored experience on all screens to help business lines to stay on top of things.
In addition, Bhela touched on the importance of more open social communications, how big data and machine learning are enabling IT administrators to deliver more personalized experiences to the end users and the importance of smart collaboration.
Overall, the Microsoft speakers gave helpful insight into the company's Exchange strategy, and the cloud is where Microsoft believes it can deliver the most value to partners and customers alike. The company aims to lead the market with faster, easier and more innovative offerings, and is committed to ensure 99.9% availability of its critical messaging and collaboration platform through intelligent, proactive management.
We're excited to continue on this path with our valued partner!


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AdultFriendFinder Review - Find a Third or Couple for Threesome
Star Ratings of Reviewer
Chance of Getting a Date
Overall Editor's Rating
» Visit AdultFriendFinder.com
The AdultFriendFinder.com (AFF) is one of the most popular swinger dating sites out there catering to the needs of swingers, cougars, cubs, cuckolds, groups, couples, bisexuals, threesome, etc. This is one of the top threesome dating sites available today with a member base exceeding well over 25 million. Joining this site is rather simple as well.
Sign Up Process
Users can sign-up in moments. In order to sign-up, users are required to input their basic details along with a valid email ID that will be used to verify the account. Once the verification is complete, the user can access the account and look for probable partners. When signing up, the following details are collected from users for the profile:
Location of profile
Personal details i.e username, email address, gender, desired gender, introduction title, etc
Physical information
Once these details have been filled up, the profile is complete and ready to be matched.
1 Month Fees for $40
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Being one of the leading dating sites on the web, AdultFriendFinder.com (AFF) has some of the best features available that work to aid the users in finding the perfect match. While some of these features are free, many of the premium features require the user to buy a monthly subscription. The key features of AdultFriendFinder.com are:
The versatile smartphone app is one of the key features of AdultFriendFinder.com (AFF). This makes it easier for users to manage their accounts and interact with fellow members of the dating site. It allows users to enjoy the features of AFF all from the comfort of their smartphone.
Instant Messaging Service or IM
Though this service is available to the premium users only, it is nonetheless one of the key features of this site. It allows users to communicate with each other in real time and makes interaction a lot easier. Using this, users can talk to the matches and get to know them better. IMs truly help users find their perfect partner and thus is one of the most important features of AdultFriendFinder.com (AFF).
Though this is a premium feature as well, this allows the users to video chat online, letting them interact at a personal level. This feature helps users know the person who they are talking to better and also make sure that the people are who they say they are. This feature helps bridge the distance between people and further helps them hook up.
Profile Boost
It's hard to stand out in a search engine. These searches made in search engines of the site can help people hook up better. So, in order to increase a user's chances for getting hooked up or find a good partner, users are allowed to purchase profile boosts which helps place the users in better position in search. This can greatly increase someone's chances of getting hooked up.
Forums and Blogs
The forums and blogs present in AFF can act as a guide for the users. It also creates opportunities for the users to interact with each other and form groups and friendships with new users.
Search System
AdultFriendFinder.com provides users with search capabilities that let's them find users based on their specific demands. The search systems available on AFF are:
Basic Search:
Location proximity
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AdultFriendFinder.com works with third party network security members to ensure complete data encryption and protection. This provides the users with ultimate privacy and security. Similarly, users are protected from scammers and frauds using the ID verification and other security steps taken by the third party network personnel. Furthermore, the Web Server Certificate which this site uses, acknowledges that transactions on the site are protected with up to 256-bit Secure Sockets Layer encryption. Thus, making AFF safe and secure.
AdultFriendFinder.com (AFF) comes with both a smartphone app and a mobile version of the site. The mobile app ensures maximum connectivity even when the user is travelling. IM, video chats, forums, etc further help the user connect with each other and explore their options.
Overall, AdultFriendFinder.com ( AFF ) is one of the best swinger websites out there catering to the needs of people with diverse demands. When looking for the best dating experience, AFF is one of the threesome dating sites that must be visited. It's large member base and diversity of the member base allows the users a large member base to choose their perfect partner from and have a good time.
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Q: "come to look for" VS "come looking for" Is there any difference in between those below?

He's waiting for us to come to look for him.
He's waiting for us to come looking for him.

If not, is there any in another contexts other than "He's waiting..."?

A: Either way is fine, although it's important to note that I would say come look for rather than come to look for. Come to look for just sounds unnatural.

He's waiting for us to come look for him.
He's waiting for us to come looking for him.

I don't have any grammar rule or research to back that up, though, I'm too tired at the moment.
I also can't think of any specific circumstance where one would be grammatically correct and the other not, although you shouldn't quote me on that.

redpajama_set_name: RedPajamaStackExchange


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Open/Close Menu The leader in family fun within the Long Island community!
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Sign up today to receive the latest Helping Hands Foundation news.
The Helping Hands Foundation was founded in 2013 with the goal of helping Long Island reach its potential. Tony Gentile, one of the founding fathers of Adventureland, always wanted to give back to the Long Island community, and this foundation was created in his memory to do just that.
Thanks to the tireless efforts of our supporters, by the end of this year we will have donated over $80,000 in scholarships to Long Island students. Applications for the Tony Gentile Memorial Scholarship Fund are accepted annually, and award recipients are announced every June. Eligible participants must be a High School Senior on Long Island attending a college or university on Long Island the upcoming semester and must have a passion for the Long Island Community.
Applications are available here.
We also help support local charities and organizations by hosting collection drives each year. Our Toy Drive supports the Ronald McDonald House of Long Island and Stony Brook Children's Hospital—each year, our goal is to donate 2,000 toys to these wonderful organizations! Our School Supply Drive is held each August, and each year we select 2 school districts to support. Items like backpacks, pencils, and crayons help students start the school year off right! Our Fall Food Drive benefits Island Harvest and the Town of Babylon Food Pantry—our goal is to donate 250 turkeys and 3,000 pounds of nonperishable food for the holiday season!
We also help support local nonprofits through our grant program. We continue to support Stony Brook Children's Child Life Program alongside Adventureland with a $20,000 pledge. The grants we award to organizations like JDRF, Uplift Our Towns, and Walk on Water help ensure they can provide services to better the lives of Long Islanders.
You can help support our mission by donating goods to our drives, contributing to our scholarship fund, or just by talking about us! Help spread the word about our foundation, so we can help more and more Long Islanders in need each year!
The Tony Gentile Memorial Scholarship will award sixteen $2,500 scholarships this year. Scholarship application deadline is May 10th.
Helping Hands is the non-profit branch of L.I. Adventureland that supports the Long Island community in increasing awareness about local issues, supporting local initiatives, and providing educational resources for community residents.
LI Adventureland's Helping Hands Foundation is a 501 (c)(3) not-for-profit, tax exempt organization and contributions are tax deductible to the extent permissible by law.
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Traditionally designed with their rounded bodies, the Winsome Wood 24-Inch Wooden Counter Stools are classic, familiar-looking stools that can complete any traditional kitchen. These stools are made out of solid wood and have been given a natural finish. There is a beveled seat for your comfort.
The Linon 29-Inch Wooden Stool is a gracefully tall and slim wooden stool that has been given a lovely natural finish. This stool stands upon solid wood legs and reaches heights of 29 inches. It features footrests running up and down the stool so anyone of any height can get comfortable.
Short and stocky, the International Concepts Round Wooden Stool is a traditional wooden stool that is made out of solid, heavy-duty parawood. It is left unfinished so that you can finish it in a way that best suits you. This stool measures 18 inches high and weighs eight pounds.
The Winsome Saddle Seat 24-Inch Counter Stool is a saddle-style stool with a contoured seat to ensure your comfort. This stool is crafted out of solid beechwood and comes in a rich finish. The legs are squared off for stability and support with foot rests on either side.
Get the convenience and storability of a folding stool with the sophistication of a wooden one with the Wee's Beyond Folding Wooden Stool. This stool sits at 18 inches in height and features a spring secure lock that keeps the stool in place. It weighs only a total of three pounds.
Traditional by design, the Winsome Wood 30-Inch Wooden Bar Stools are heavy duty stools that are made out of solid wood that has been given a natural finish. These stools come with beveled seats that provide total comfort. Their shapes have been designed to be seated at bars and tall countertops.


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2020 NLRA Schedule Release
Speedway Shots photo.
The schedule for the 23rd season of NLRA racing has been released, and it currently features 16 events at eight area tracks. The season is set to begin on Friday night, June the 5th, at the River Cities Speedway in Grand Forks with the World of Outlaws Sprint Car Series. This will be the first of five visits to the Bullring in 2020.
The schedule for the 22nd season of NLRA racing has been completed, and it features 17 events at eight area tracks. The season is set to begin on Devils Run weekend at the Devils Lake Speedway near Crary, ND, on June 1st.
The Northern Late Model Racing Association's 20th season of action will feature 17 big events during this anniversary season. In 1998, the Grand Forks, ND based racing series debuted with four races on its' initial slate of races, setting a foundation that the series continues to build off of today.
The 2017 season will begin on June 16th, as the series will co-headline events at the River Cities Speedway in Grand Forks with the World of Outlaws Sprint Car Series. Both series will make the 80 mile trip south to race together again at the Red River Valley Speedway in Fargo the following night.
First Date of 20th NLRA Season Announced
The first date of the Northern Late Model Racing Association's 20th season of racing has been announced. The series will head to the Greenbush Race Park in Greenbush, MN on June 24th, 2017.
The race would be the 25th for the series at the high banked three-tenths mile oval. The NLRA visited Greenbush twice in 2016. Cole Schill won his first NLRA series feature during the first event on June 18th. Brad Seng won the second visit on July 30th.
The Greenbush Race Park has been a regular stop on the NLRA tour. Greenbush was one of three tracks featured in the four race inaugural season for the tour in 1998. Tom Corcoran won the inaugural event at Greenbush that season.
Mike Spieker photo.
The NLRA has released its' 2016 series schedule. The series 19th season features 19 rounds, starting on Saturday night, June the 11th at the Jamestown Speedway in Jamestown, ND. The schedule also includes the return to the Red River Valley Speedway in West Fargo, ND on Friday night, June the 24th, and a second appearance in West Fargo on Sunday night, July the 17th alongside the Northern Outlaw Sprint Association. This is the first time the Upper Midwest's two premier racing series have met on the same night, and at the same track (away from River Cities) since June 10th, 2007, when Jeremy Keller and Jason Linnell were winners at the Nodak Speedway, in Minot, ND. It's also the fourth time in the history of the two series that they'll share the same dirt, the other two occurrences happened at the Norman County Raceway in 1998, and again in 2001.
2015 NLRA Schedule Released
Defending NLRA champion Brad Seng and the rest of the NLRA series regulars will embark on a 21 race schedule as the travelling series begins its' 18th season on Memorial Day weekend at the Viking Speedway in Alexandria, MN. To see the full schedule click here. Photo courtesy of Rick Rea.
NLRA - 2013 Northern Late Model Association Race Schedule
2013 NLRA Schedule
1. Sat. May 18th, 7pm, Devils Lake Speedway, Devils Lake, ND.
2. Sat. May 25th, 6pm, Viking Speedway, Alexandria, Mn.
3. Sun. May 26th, 6pm, Viking Speedway, Alexandria, Mn.
4. Weds. June 19th, 7pm, Norman County Raceway, Ada, Mn.


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P-51 "Skipper's Darlin' III" Men's Low Top Canvas Shoes - White
Size US5/EU38 US6/EU39 US7/EU40 US7.5/EU41 US8.5/EU42 US9.5/EU43 US10/EU44 US11/EU45 US12/EU46 US13/EU47 US14/EU48
US5/EU38 US6/EU39 US7/EU40 US7.5/EU41 US8.5/EU42 US9.5/EU43 US10/EU44 US11/EU45 US12/EU46 US13/EU47 US14/EU48
This design is based on the P-51 Mustang "Skipper's Darlin' III" as flown by Captain Andrew "Jug" Turner of the famous 332nd Fighter Group also known as the Tuskegee Airmen. Turner flew 69 missions while serving with and commanding the 100th Fighter squadron. Sadly, at only 27 years old he was later killed in an aircraft accident at Lockbourne Air Force Base, Ohio, when his Republic P-47 Thunderbolt collided with another. For his service he was awarded the Distinguished Flying Cross, Air Medal and the Congressional Gold Medal.
Please note that there can be subtle variations in color and minor movement during production that may cause a design element not to be in the exact position as it appears on screen. More details can be found on our FAQ page.


We may not know the official subtitle or the plot of American Horror Story Season 6 yet, but we certainly know the theme. After releasing a series of 11 cryptic teasers over the past two weeks that have only fanned the flames of speculation, FX has debuted a twelfth — and seemingly final — promo that ties it all together. Its caption reads: "Murder. Madness. Magic. Misfits. Mayhem… Mystery?" Each word in the sequence clearly corresponds to its respective season, meaning that Season 6 is all about the mystery. But the content of the promo itself may have offered us our first clue of what that mystery might entail: AHS Season 6 might tie all of the seasons together.
Ever since Ryan Murphy confirmed that each individual season of his anthology series were connected, viewers have been trying to formulate a theory for all it all fits together. So far, those connections have remained relatively minor — more Easter Eggs for fans than game-changing revelations — like Coven's Sister Mary Eunice showing up to collect Pepper from Elsa's Cabinet of Curiosities or Queenie checking into the Hotel Cortez. But those connections might move from the background to the forefront of the action if this latest promo is any indication.
A popular theory holds that Season 6 will function as a sequel to Season 1's Murder House, centering around a slightly grown-up version of the child born at the end of that season, Michael — aka the Antichrist. Murphy previously stated that Season 6 would involve children in some way, and one of the first teasers released featured a clawed hand clutching a creepy mobile, which seemed to jive with that theory.
But what if Murder House isn't the only chapter that Season 6 connects to? What if the reason the theme of the upcoming season is being kept so hush-hush is because it will reveal the grand unifying theory of American Horror Story? That certainly seems to be what the twelfth promo is implying, with images from one season feeding directly into the next, drawing a direct connection between each installment… all inexorably leading towards the mysterious sixth chapter.
What would a fully interconnected AHS universe even look like? Would it be revealed that the characters are living in some sort of Lost-esque purgatory? Are they existing in parallel dimensions? Are they traveling through the literal nine circles of hell as envisioned in Dante's Inferno? Or are the different seasons all just taking place in a world where everyone has multiple doppelgängers running around? It's hard to imagine — which could be why we haven't heard any details or seen any footage even though the season is premiering in just four short weeks.
If Season 6 is the season that ties everything together, could that signal the fact that the show is nearing its end? Is that why Murphy and FX are being so secretive about the upcoming batch of episodes? AHS wouldn't be the first show to air a surprise series finale this year; Penny Dreadful surprised its fanbase by announcing "The End" after its Season 3 finale back in June. And it's not like Murphy's plate is empty — in fact, it keeps getting more and more full. Aside from AHS, the mega-producer also has Scream Queens (about to begin its second season on FOX), American Crime Story (between seasons on FX), and Feud (a third upcoming anthology series for FX).
Can Murphy really keep running four shows simultaneously? Maybe — but if the mysterious sixth season turns out to be the last edition of American Horror Story, don't be too surprised to see it come to an end… just as long as he reveals how it's all connected first.