asterisk2a + algo   44

(9682) Algorithm Killed the Video Star | Fallen Titans #5 - YouTube
watch time
evergreen content - content that can be enjoyed beyond date of release.
YouTube  algo  algorithm  Social  Media 
july 2018 by asterisk2a
Facebook’s new algorithm change is what makes publishers so afraid of Facebook - Recode
Today, Facebook announced that it’s tweaking its algorithm so that users see less stuff shared by publishers and brands and more stuff from friends and family. This isn’t a nightmare scenario for publishers, but it’s pretty grim; websites and news organizations are leaning more and more on Facebook for growing their audiences, and Facebook just weakened a key traffic driver for them. //&! I hesitate to make this analogy, but publishers relying on Facebook are starting to look a whole lot like drivers who keep trusting Uber to make their lives better. -
Facebook  profit  maximisation  profit  maximization  Newsfeed  algorithm  algo  algos  algorithms  Facebook  Instant  Articles  Social  Media  EULA  TOS  Platform  filter  bubble  filter  bubbles  Google  Search 
june 2016 by asterisk2a
Google demonstrates its power over the press by cowing German publishers | PandoDaily
[Google Traffic for all content publishers still huge despite rise of Social Media/Newsfeed, Twitter ] The publishers never really had a chance. Google doesn’t display advertisements on its News product, and no one forced them to allow the company to excerpt their stories. Indeed, Google pulled the excerpts from several large German newspapers in the beginning of October, making it clear that the company thinks publishers need the traffic driven by Google News more than Google needs the article snippets for which publishers are so desperate to be paid. Now those same publications have pulled their lawsuit because of Google’s “overwhelming market power.”
Google  business  model  journalism  journalismus  content  pageviews  Platform  YouTube  TOS  Twitter  Facebook  Google  Search  discovery  content  discovery  content  distribution  distribution  content  curation  paid  content  freemium  algorithm  algo  algorithms 
october 2014 by asterisk2a
News Roundtable: [...] deconstructing employment - YouTube
min 34 + "The article doesn't really examine productivity, it is examining wages." - Digital revolution has yet to fulfil its promise of productivity and better jobs ( +!+ - 'It's The Economist making a case for wealth redistribution!' +!+ How computers threaten the jobs of mid-skilled workers ( - 'few benefiters + we need substantial skill upgrading and change in education policy' +!+ Is A.I. the problem or the solution? - Automation, Robotics, mid-skilled jobs, routine jobs, lessons from Industrial Revolution, need investment in practical skills for the future, infrastructure investment, education policy, Universal Basic Income - so that no one is left behind
convenience  service  economy  Uber  HomeJoy  Lyft  Share  sharing  economy  Services  Industry  service  minimum  wage  mindestlohn  workforce  6-hour  work  day  4-day  work  week  leisure  time  Robert  Skidelsky  Google  Apple  Amazon  commoditization  commodity  business  Larry  Page  Future  of  Robotics  AI  algo  algorithm  algorithms  productivity  Mobile  Creative  Postmates  Mobile  Creatives  Washio  GrubHub  Big  Data  Why  Software  Is  Eating  the  World  Software  Is  Eating  World  middleman  self-employment  contractor  marketplace  efficiencies  marketplace  plurality  marketplace  inefficiencies  marketplace  labour  economics  labour  market  education  policy  Public  Year  of  Code  middle  class  squeezed  middle  class  underemployed  structural  unemployment  employment  unemployment  flat  globalization  globalisation  comparative  advantage  competitive  advantage  competitiveness  competitive  Germany  USA  UK  Europe  BRIC  MINT  added  value  self-driving  cars  transportation  transportation  protectionism  population  automation  social  capital  Non-Profit  GDP  happieness  happiness  index  freelance  freelancing  rat  race  differentiation  differentiate  social  entrepreneurship  entrepreneurship  technological  history  economic  history  history  Industrial  Revolution  Software  Revolution  computing  Gini  coefficient  living  wage  living 
october 2014 by asterisk2a
iPod Mastermind Tony Fadell On The Death Of The iPod: "You Can't Get Too Nostalgic" | Co.Design | business design
As for the future of music: It's not iPods, iPhones, or iPads. It's apps that read your mind. "Now that we all have access to all the music we could ever want, discoverability is the new Holy Grail," Fadell says. "Using machine learning and AI to figure out context, so that the celestial jukebox knows the perfect song for every occasion."
discovery  Signal  vs.  Noise  filter  bubble  filters  filter  curator  content  curation  curation  AI  algorithm  algorithms  algos  algo 
september 2014 by asterisk2a
Twitter’s Huge Mistake | TechCrunch
Twitter needs to grow and please shareholders ... shareholders don't care about users who boarded on during year 1 and 2 ....
Twitter  Facebook  Newsfeed  engagement  Signal  vs.  Noise  filter  filters  filter  bubble  audience  Wall  Street  algorithm  algos  algo  algorithms  differentiation  differentiate  user  experience 
september 2014 by asterisk2a
Algorithm tweaks don’t change the bottom line: Facebook is in charge of what you see — Tech News and Analysis
Facebook’s latest update to its ranking algorithm is supposedly designed to combat “clickbait” headlines in the content shared on the network — but all it does is reinforce how little we know about how Facebook decides what we see and don’t see
Google  Facebook  Google  Search  Newsfeed  Platform  algorithm  algos  algo  algorithms 
september 2014 by asterisk2a
Twitter knows if you’re male or female, which is only the beginning for targeted ads | PandoDaily
Gender is only the beginning. A company called Leadsift recently launched a new product that claims to analyze tweets to predict a user’s age, salary, and buying habits. “We extract over a hundred attributes by modeling on a user,” Leadsift CEO Tukan Das tells me. “Let’s say you check into an airport more than three times per month. We’ll automatically learn that you are a frequent flyer and a businessperson.”
Big  Data  analytics  algorithm  algos  algo  algorithms  Twitter  advertisement  targeting  advertisement  re-targeting  HTTP  cockie 
september 2014 by asterisk2a
News Feed FYI: Click-baiting | Hacker News
... fallacy on building your business on somebody else's proprietary, closed platform .... "Entrepreneurs" still doing it: "@jason: i've been pitched on 10+ @pinterest analytics tools; pass on investing for this reason." //
Facebook  Newsfeed  algorithm  algos  algo  algorithms  TOS  Platform  Google  Search  Twitter  Zynga  BuzzFeed  Social  Media  Clickbait  SEO  SEM  Start-Up  advice  Start-Up  lesson  Gmail  Signal  vs.  Noise  filter  bubble  filters  filter  click-baiting  copywriting  Listicle 
august 2014 by asterisk2a
Angst vor Amazons Übermacht | Kulturjournal | NDR - YouTube // books as cultural good. could non-mainstream authors and publishers/agencies survive in a marketplace where only mainstream sells and is promoted - via Amazon's recommendation engine (algo curation) !!??
Amazon  Germany  ebooks  ebook  self-publishing  publishing  2.0  Kindle  marketplace  oligopoly  oligopol  monopoly  ecommerce  diversity  culture  plurality  market  plurality  pluralism  mainstream  curation  content  curation  algos  algorithm  algorithms  algo  Kulturgut 
august 2014 by asterisk2a
Twitter Pollutes The Timeline | TechCrunch
The specific change in how your Twitter timeline operates allows for the company to inject additional content into your feed from other users you don’t follow. This is in addition to promoted tweet advertising content — you still get that thrust into your feed too. Yesterday the company added the following paragraph to a Help Center page which details exactly how far it’s moving the goal posts here: Additionally, when we identify a Tweet, an account to follow, or other content that’s popular or relevant, we may add it to your timeline. This means you will sometimes see Tweets from accounts you don’t follow. We select each Tweet using a variety of signals, including how popular it is and how people in your network are interacting with it. Our goal is to make your home timeline even more relevant and interesting. +++
Twitter  Facebook  Newsfeed  algorithm  algos  algo  algorithms  Signal  vs.  Noise  Timeline  Core  Product  Value  Proposition  utility  Wall  Street  shareholder  shareholder  user  experience  experience  customer  experience  shared  experience  mainstream 
august 2014 by asterisk2a
It feels like just yesterday my wife, two kids and I packed all our belongings,… In a Google+ post from Google head of search Amit Singhal, Google shares they have made “more than 890 improvements to Google Search last year alone.” In 2009, Google told us they made between 350 to 400 changes to search and in 2010, they said they made 550 improvements to search in the past year. Google’s Matt Cutts said in a video in 2010 they make one change per day to their core search algorithm. We also know Google tests hundreds of changes in a day but only some of them make the light of day. The 890 “improvements” Amit is talking about is search specific, but goes well beyond algorithms. It includes user interface changes, auto-complete, Google Now and much more.
Google  Search  Google  algorithm  algo  algorithms  a/b-testing  A/B  Testing 
august 2014 by asterisk2a
Facebook ads already know everything about you. This company wants to bring the same ad targeting to Twitter | PandoDaily
In any case, between the rise of more sophisticated ad targeting services like Leadsift, not to mention reports that Twitter may be experimenting with a Facebook-style algorithm, it’s beginning to feel like we’re exiting the golden age of social networks, when it was about conversations with other humans, and entering some strange corporatized new era, where the brands have taken over our favorite sites.
Twitter  Facebook  algorithm  algos  algo  Newsfeed  advertisement  re-targeting  advertisement  targeting 
august 2014 by asterisk2a
If Twitter implements a Facebook-style algorithm, you may not hear about the next Ferguson | PandoDaily
New York Times reported that Twitter CEO Dick Costolo was experimenting with Facebook-style algorithms designed to unearth the “best” content for users. The objective here is two-fold. For one, Twitter has a relatively steep learning curve compared to Facebook and other popular consumer web products. Getting the most out of Twitter can mean spending weeks or even months finding the best people to follow. It also takes some upkeep, finding new kids on the block to follow and unfollowing accounts that have worn out their welcome. With Wall Street unimpressed by Twitter’s user growth since going public, the company is desperately looking for ways to make the service more attractive to newcomers. The other reason? Advertising. Not only is Facebook good at predicting what news stories people will click on, it’s also learning how to leverage all the data it collects from “likes” and comments in order to better serve up advertisements.
differentiation  differentiate  Newsfeed  Twitter  Facebook  algorithm  algorithms  algo  filters  filter  bubble  filter  Wall  Street 
august 2014 by asterisk2a | Frank Schirrmacher - Emigration Of Thinking Because Of Algorithms.
... apart from teaching algo's, people have to be taught too - to think about the third factor that puts everything in question. algo's are about the absolute solution to problem x. thus we become blind to factor x, the third factor, the black swan (see GFC, we are not in a bubble, houseprices never reverted back to the mean). Narrative, doubt (zweifel), intuition - vs - algo's outcome. Without narrative, what world is that, where we just have results only? No narrative (linearity), no grammar. What world is that?
book  evolution  singularity  algorithm  algo  algorithms  Frank  Schirrmacher  technological  progress  ethical  machine  computer  science  degree  history  blackswan  GFC  Google  Facebook  filter  bubble  filters  filter  nassimtaleb  Nassim  Taleb  academia  academics  economic  history  debate  digital  economy  digital  world  unknown  unknowns  zweifel  intuition  narrative  doubt  Twitter  Pinterest  okcupid  Philosophy 
june 2014 by asterisk2a
Travis Kalanick of Uber - TWiST #180 - YouTube
MVP - minimal viable product, test of thesis; they rented a handful of cars with drivers in SF & build little app, the rest is history. make move to not have drivers but enable people to be drivers with income. Uber - elegance, design, ... this is now a brand, a status symbol. +++ on demand lifestyle, making magic happen via technology - employing STEM people. +++ could, because of supply liquidity, deliver, at premium, food to your door. +++ because of their technology, their platform, they either could licence out their problem solving platform (ie demand prediction - people just opening up the app - math is an operational cornerstone) to air transportation and or goods transportation. +++ Travis Kalanick at Startup School 2012 - >> multi-product company - for different budgets. Operations, Scaling - one problem that needed solving, a Playbook for expanding from one city to the next. Changing how u live, over months. not decades, today's age.
Uber  Travis  Kalanick  Start-Up  lesson  Start-Up  advice  entrepreneurship  entrepreneurial  entrepreneur  status  symbol  system  design  Product  systems  design  brand  Personal  brands  branding  on  demand  Supply  and  and  Supply  ondemand  on  demand  lifestyle  magic  technology  STEM  reputation  Silicon  Valley  multi-product  company  travel  traveling  transportation  public  transportation  Platform  lifestyle  western  lifestyle  instant  gratification  frictionless  friction  accelerated  life  marketplace  efficiencies  marketplace  plurality  marketplace  marketplace  inefficiencies  business  model  mobile  first  urbanisation  urban  planning  Operations  scaling  algorithm  algorithms  algo  dynamic  pricing  mathematics  complexity  marketing  Viral  Airbnb  Utility  utilities  21stcentury 
june 2014 by asterisk2a
On Google's new Search Algo Push/Update - Called Panda.
Lesson Learned. Don't build your business on other peoples platform. Even if it is search. Meaning if your business is primarily impressions/unique visitors coming in via search, or even Social Media (FB - newsfeed algo, Twitter - noise + search algo, Pinterest - search algo, Amazon - product search) ... then you have one more thing to worry about every day - because you can't fix it if they break it for you. +++
Google  search  engine  Platform  Open  Platform  Facebook  Twitter  Tumblr  Pinterest  YouTube  business  model  algorithm  algos  algorithms  algo  SEO  SEM  Social  Media  Newsfeed  Bing  Yahoo!  eBay  ecommerce  e-commerce  commodity  business  commoditization  Amazon  Don't  be  evil  communication  transparency  competitiveness  comparative  advantage  competitive  advantage  content  economy  marketing  Gary  Vaynerchuk  HuffingtonPost  Yelp!  Mahalo  Jason  Calacanis  jasoncalacanis  AltaVista  Vertical  Vertical  foursquare  interest  graph  graph  Google+  Listicle  Trending  Topics  Journalism  journalismus  BuzzFeed  Upworthy  Viral  Mashable  consumerist  zombie  consumer  Consumerism  consumer  user  user  experience  Start-Up  advice  Start-Up  lesson  TOS  Wordpress 
may 2014 by asterisk2a
TEDxNewWallStreet - Sean Gourley - High frequency trading and the new algorithmic ecosystem - YouTube
The speed of human strategic thinking is fundamentally limited by the biological hardware that makes up the brain. As humans we simply cannot operate on the millisecond time scale -- but algorithms can, and it is these algorithms that are now dominating the financial landscape. In this talk Sean Gourley examines this high frequency algorithmic ecosystem. An ecosystem, Gourley argues, that has evolved to the point where we as humans are no longer fully in control.
ecosystem  Artificial  intelligence  AI  algorithms  flashcrash  unintended  consequences  complexity  WallStreet  algo  HFT 
august 2012 by asterisk2a
Broken Market Chronicles: Algos Gone Autosell Wild - Video Explanation Of What Happened | ZeroHedge
Algos (automated trading strategies, via quantitative analysis and computing power) did disrupt the Equity markets again, substantially.

__ 1 day later:

What Does It Cost When Your Algo Goes Haywire?

$440 mln, in the case of Knight Capital, the giant market-making firm.

The company has essentially put itself up for sale after yesterday’s major technical snafu…
Knight  Capital  market  maker  HFT  SEC  WallStreet  algo 
august 2012 by asterisk2a
Arnuk Says High-Frequency Trading Fuels Volatility (Audio) - Nov 15, 2011

Sal Arnuk, a partner at Themis Trading LLC, says the structure of today's markets is "a fragmented mess," and that the "outsized nature and growth of ETFs" is causing problems. Arnuk talks with Bloomberg's Ken Prewitt and Barry Ritholtz, chief executive officer at FusionIQ, on Bloomberg Radio's "Bloomberg Surveillance." Ritholtz is sitting in for Tom Keene.

- 15 exchanges, 40 dark pools
- 80% of volume by 2% of participants on exchanges
HFT  algo  trading 
november 2011 by asterisk2a
Nanex White Paper: High Frequency Trading Is Insatiable - Its Hidden Costs | ZeroHedge
Extra capacity is vital for times of market stress from surprise news events or shocks to the system. The lack of capacity during these times will quickly lead to a drop in liquidity as traders pull out from lack of clear pricing information. This was a major cause of the flash crash.

We understand that market makers and HFT need to adjust their quotes to fast changing market conditions. But 10,000 times per second per symbol, or more, in an inactive stock? Every quote has a non-zero cost: millions of computers and miles of network cables must process and transport each one, costing both time and energy. Sending quotes and then canceling them before they ever leave the exchange network is absurd.
HFT  algo  trading  flashcrash 
october 2011 by asterisk2a
Bold ambition meets harsh reality as HFT targets Asia - YouTube
Forced from the U.S. and Europe by the threat of new regulations, HFT players are targeting Asia but the region has its own pitfalls.
HFT  algo  trading  Asia  2011 
august 2011 by asterisk2a
Time to take stock - |
A situation where high frequency trading is over two thirds of the transactions on the NYSE and about the same in the stock markets of the UK and Europe. Likewise they are over half the action in foreign exchange markets and they are rapidly becoming dominant in the futures market. Andrew Haldane from the Bank of England is arguing against allowing high frequency trading — algorithms chasing algorithms chasing algorithms — from being allowed to proliferate pointing at volatility as the problem:
Speed increases the risk of feasts and famines in market liquidity. HFT [high-frequency traders] contribute to the feast through lower bid-ask spreads. But they also contribute to the famine if their liquidity provision is fickle in situations of stress.
Haldane noted that relative to gross domestic product, the equity market capitalisation of the US, Europe and Asia had not grown since 2000, suggesting that “the contribution of equity markets to economic growth … has been static”.
HFT  algo  trading  stockmarket  GDP  opinion 
july 2011 by asterisk2a
The "Fractal" Limit Order Buster: The Latest Market Manipulation Algo Gimmick | zero hedge
latest algo appears to be nothing more than a limit order-busting market manipulation device, whose sole purpose is to destabilize and generate volatility for the creator of the algo. Curiously, as Nanex indicates, the algo is not limited to Natgas but also appears to recur in other far more liquid instruments, such as the SPY, when a comparable fractal pattern was observed in broad daylight. As to how the algo itself profits from the price instability it generates: we are unsure. One could certainly trade the increased volatility through derivatives, by buying vol cheap in advance of such as limit order triggered waterfall, especially in very thin markets, and then selling the vol at the apex of a given move. Obviously, this is merely speculation. That said, we are dead certain Finra and the SEC are promptly pursuing the trader responsible for this glaring attempt at market manipulation in order to find out precisely how one profits from such fractal algorithms.
algo  HFT  trading  fraud  SEC  Finra 
june 2011 by asterisk2a
Warning signs on market liquidity risks | Journalist Profile |
HFT trading prompting bids to be pulled. As the SEC described it: “This sudden decline in both price and liquidity may be symptomatic of the notion that prices were moving so fast, fundamental buyers and cross-market arbitrageurs were either unable or unwilling to supply enough buy-side liquidity.” A perfect recipe for a price vacuum and severe downdraft
Subjecting traders to an LVaR gives rise to a multiplier effect. Tighter risk management leads to more restricted positions, hence longer expected selling times, implying higher risk over the expected selling period, which further tightens the risk management, and so on. This feedback between liquidity and risk management can help explain why liquidity can suddenly drop. We show that this ‘snowballing’ illiquidity can arise if volatility rises, or if more agents face reduced risk-bearing capacity— for instance, because of investor redemptions, losses, or increased risk aversion.
algos ETF HFT causing uneconomic market dislocations
HFT  flashcrash  liquidity  trading  financialmarkets  markets  ETF  algo 
may 2011 by asterisk2a
Refuting The SEC's Lies At The Core Of The "Flash Crash" Analysis | zero hedge
There were 6,438 trades totalling 75,000 contracts. We matched them by time, price and size to the 147,577 trades (844,513 contracts) in the CME time and sales data between 14:32 and 14:52 (they matched exactly).

The SEC report identified a Sell Algorithm selling 75,000 contracts as the cause of the flash crash. If the "Sell Algorithm" in the SEC report refers to the Waddell & Reed trades, then there is a problem. A big one. Looking at the trades in context with the other trades during that time, they appear insignificant. The W&R trades also do not occur near the ignition point (14:42:44.075) we identified earlier. Furthermore, the W&R trades are practically absent during the torrential sell-off that began at 14:44:20. The bulk of the W&R trades occurred after the market bottomed and was rocketing higher -- a point in time that the SEC report tells us the market was out of liquidity.

Something is very wrong here.
flashcrash  2010  may  SEC  madoff  fraud  stockmarket  HFT  algo  quantum  hedgefunds  liquidity 
october 2010 by asterisk2a

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